Search results for “model”

High-Throughput Complex Disease Modeling for Ethical Drug Discovery: Clinical Relevance of a NAM Platform for Cancer Biomarker Development

The development of tumor biomarkers derived from blood, or its components, has become pivotal in advancing early cancer diagnosis. Malignant transformations induce cancer-specific alterations in the transcriptome, proteome, and secretome of tumor cells. Recent studies highlighted similar alterations in peripheral blood mononuclear cells (PBMCs) in cancer patients, which appear to mirror the state of transformation in tumor cells. These findings suggest an intercellular communication–driven mechanism rather than a systemic inflammatory response and, in addition to current ctDNA-based liquid biopsy biomarkers, point to a novel, simple, and highly robust approach for the early detection of cancer. Using this phenomenon to advance PBMC-based biomarker development, it will be essential to achieve 3D in vitro tumor models that reproduce a highly physiological tumor microenvironment (TME). Likewise, more enhanced 3D ex vivo models are required to enable the replication of cell-to-cell and organ-to-organ communication. These systems will guide the self-organization of mixed microenvironments derived from different tissues and enable them to accurately reproduce the molecular connections underlying these alterations. In this study, an innovative new modular 3D co-culturing approach was used to expose PBMCs to lung tumoroids, under physiologically relevant conditions. Changes in DNA fragmentation of PBMCs in the presence of lung cancer were quantified and used as a biomarker. To validate the predictiveness of this biomarker, our results were compared with clinical data from a clinical evaluation study. Similar to the clinical trial observations, PBMCs, when exposed to lung tumoroids, showed a significantly lower level of DNA fragmentation (37%). This modular 3D co-culturing model showed a predictiveness of the clinical data of > 90%, demonstrating its power to monitoring cell-to-cell communication effects and support the development of blood-based biomarkers.

A New Model of Body Composition: Concept and Design Features of the DBA-Model

Indices, based on data such as height and weight in general and in particularly the body mass index (BMI), are often used to assess overweight. However, there is limited capacity to differentiate the amount of fat mass between individuals. This review refers to an anthropometric model called Dahlmann-Body-Analysis (DBA), which uses simple anthropometric parameters to define a Reference Weight (Ref-Wt). It is based on hand circumference as a proxy for the skeletal frame and, in addition, the circumference of the abdomen as a proxy for central obesity. Processed through a network of algorithms, the DBA model enabled to differentiate the Difference Weight – that means the difference between the Actual Weight and the Reference Weight – into fat mass and skeletal muscle mass. The DBA-model resembles the 2-component model of Albert R. Behnke, which he considered as a living functional construct including essential fat. The DBA-model matches with Behnke`s 2-component model insofar, as the essential fat is replaced by a physiological amount of fat tissue. The review summarizes studies to compare DBA-derived data with Metropolitan Life Insurance tables, evaluates DBA-derived fat tissue mass with bioelectrical impedance analysis (BIA) derived results and analyses the meaning of the DBA model in clinical settings to uncover the underlying mechanisms of metabolic syndrome (MetS) pathogenesis with increasing amounts of fat mass. The model offers the opportunity to calculate changes in fat or muscle tissue in an absolute (kg) or relative (%) amount on individuals. The data suggest that the DBA-model has satisfactory prediction qualities for use as a practical tool in public health care.

Diabetic Mouse Delayed Wound Model Following Treatment with the NerveStim™ Neuropathy System

Delayed wound healing in diabetes is characterized by impaired angiogenesis, persistent inflammation, extracellular matrix dysregulation, and peripheral neuropathy. A preclinical study was conducted using a diabetic mouse delayed wound model to evaluate the surrounding tissue of a wound, (its periwound) and its tissue responses following treatment with the NerveStim™ Neuropathy System, a combination topical gel and neuromuscular electrical stimulation platform. Periwound tissue was harvested at Day 14 and analyzed using NanoString gene expression profiling. Treated animals demonstrated visibly increased periwound tissue thickness compared to untreated controls. Differential expression analysis identified 76 significantly upregulated and 17 downregulated genes. Upregulated pathways included angiogenesis (Vegfa, Fgf2, Pdgfb, Nos3), neurotrophic signaling (Ngf, Bdnf, Scn9a, Trpv1), macrophage polarization (Arg1, Mrc1, Il10), and extracellular matrix remodeling (Col1a1, Col3a1, Mmp9, Timp1). Downregulation of select pro-inflammatory mediators (Nos2, Mif) was observed. These coordinated transcriptional changes are consistent with activation of reparative immune, neurovascular, and matrix remodeling pathways in diabetic periwound tissue.

Mathematical Modelling of Typhoid Fever Transmission Dynamics and Intervention Impact in Harare, Zimbabwe (2018–2020)

Background Typhoid fever remains a significant public health issue in Harare City, Zimbabwe, exacerbated by recurrent outbreaks between 2018 and 2020. Key challenges, including inadequate water supply and sanitation infrastructure, high population density, and limited healthcare access, have intensified the disease burden. Understanding the key transmission drivers and assessing the impact of various interventions are essential for informing policy and health strategies. Objectives This study aimed to: 1: To predict future trends in typhoid fever cases Harare City typhoid hot areas. 2: To develop a mathematical model to simulate the spread of typhoid fever incidence under different intervention scenarios and recommend evidence-based strategies for reducing the disease burden in Harare City. Methods A dynamic compartmental SIR-based model, adapted from the Pitzer Vaccine Effectiveness (VE) framework, was employed to simulate disease transmission. This model accounted for both short-cycle (human-to-human) and long-cycle (environmental) transmission pathways. Data from Harare City (2018–2020) were used for model calibration and forecasting, and sensitivity analysis was performed to assess the impact of different intervention levels. Findings The model identified inadequate sanitation, contaminated water sources, and low health- seeking behaviors as primary drivers of typhoid transmission. In the absence of interventions, the model projected a sustained high rate of transmission. However, treatment and WASH interventions could reduce the disease burden by 50–60%, while combined strategies incorporating vaccination and education led to an 80% reduction in cases. Sensitivity analysis indicated that treatment and WASH interventions were particularly impactful at moderate coverage levels. Conclusion Mathematical modeling effectively demonstrated the multifactorial drivers of typhoid fever transmission in Harare. Integrated interventions that combine WASH, vaccination, treatment, and education present the most promising approach for long-term control of the disease. The findings offer a solid, data-driven foundation for public health decision-making and resource allocation.

The Energy–Matter–Behavioral Model of Mental Health Hygiene: A Systems-Based Framework for Sustainable Well-Being

The Energy–Matter–Behavioral (EMB) model offers a systems-based lens for understanding and maintaining mental health hygiene. This framework integrates stress reduction, biological resilience, and behavioral reinforcement into a coherent triad, addressing not only symptoms but underlying energetic and material dynamics. By aligning practices such as exercise, meditation, social connection, sleep, and diet with EMB principles, this model presents a transdisciplinary, evidence-informed approach to mental health in an overstimulated world.

Existential Therapy and the Contextual Model: Unified by Presence, Flexibility, and Meaning-Making

This article offers a literature review and theoretical synthesis and application of existential therapy and the contextual model. It reviews the contextual factors that may be predictive of positive therapy outcomes in general, identifies distinct types of existential therapy, highlights core commonalities in these existential branches, and explores how the main aims of the existential therapy approach may be foundational in facilitating improved mental health treatment outcomes and well-being. The author asserts that presence-both intrapersonal and interpersonal are at the heart of the contextual factors, along with flexibility, and meaning-making. This assertion has implications for therapist education, development, training, and supervision.

Learning and Memory in an Animal Model of Longevity: The Ames Dwarf Mice

The Ames dwarf mice have a recessive mutation of the PROP-1 gene that produces hereditary dwarfism. The abnormality is responsible for an anterior-pituitary deficiency that results in a substantial reduction of growth hormone, thyroid-stimulating hormone, and prolactin. These mice are smaller in size than their normal siblings but live approximately twice as long. The normal siblings do not have the mutation, and therefore still have the typical levels of the three hormones. The purpose of the present research was to determine if the reduced hormones in the Ames dwarf mice affected their ability to learn and delayed the age-related loss of memory. In general, the hypotheses proposed indicate that there will be no significant differences on the tasks in regards to the genotype or the age of the mice. These hypotheses would support previous research and suggest a delay in the age-related loss of memory and the ability to learn in the Ames dwarf mice. Learning was assessed using a matching-to-sample procedure, while memory was evaluated using a modified radial-arm procedure. Generally, the age of the animals had little to do with their performance on any of the tasks. Taken together, the overall results showed no significant differences in accuracy between any of the groups of mice or a behavioral decline as the mice age. The present results are consistent with the theory of a delayed age-related behavioral decline in the Ames dwarf mice.

A New Model of Body Composition Detects Association Between Severe Obesity and Increase in Skeletal Muscle Mass

Obesity is associated with functional limitations in muscle performance. The true effect of obesity on skeletal muscle mass, including any interactions with aging effects, remains to be elucidated. The present study investigated the impact of obesity on the stimulation of muscle growth, based on a new model of body composition. A dataset of 44 men and 64 women was analysed. Body weight (Wt), body height (Ht), hand circumference (HdC) and waist circumference (WC) were measured. Processed by the Dahlmann-Body-Analysis (DBA) system, a new model of body composition, the increase of skeletal muscle mass (ΔSMM) compared to the individual reference weight was calculated. Muscle mass data derived by the DBA model are compared with DXA-derived predictive equations of studies representing different countries and ethnicities estimating the appendicular skeletal muscle mass. Means of these groups are tested by ANOVA. Age ranged from 18 to 72 years. All subjects had a BMI ≥ 29.7 (kg/m²). The mean values of ΔSMM as an estimate of muscle mass gain calculated by the DBA-system were 11.8 ±3.6 kg for men and 8.9 ±2.6 kg for women, respectively, demonstrating a linear, significantly rising relationship with BMI (ß > 0, p<0.001). The study population did not show a decrease in muscle mass with age in either men or women up to an age of 65 years. The results suggest that the present model has satisfactory prediction qualities to detect an increase in skeletal muscle mass associated with a growing burden of body fat.

Loneliness and Bedtime Procrastination: Exploring a Model of Interconnectedness Among Young Adults in Germany

Background/Aim This study aimed to examine the relationship between loneliness and bedtime procrastination in young adults in Germany, offering critical insights into the development and maintenance of both conditions. Specifically, it sought to test a new model that connects these two psychological constructs. Materials and Methods A quantitative online survey was conducted with 500 young adults (Mage = 23.3, 83.6% female). Loneliness was assessed using the UCLA Loneliness Scale, while bedtime procrastination was measured using the Bedtime Procrastination Scale. Results The results show a significant positive correlation between loneliness and bedtime procrastination in young adults. Sleep quality was also found to significantly correlate positively with loneliness as well as with bedtime procrastination. Conclusion The findings provide a crucial framework for understanding the relationship between the two psychological constructs of loneliness and bedtime procrastination. Implications for possible future interventions are discussed.

Ultrasound Guided Pericardial Effusion Training Model for Neonates

This methods article presents a neonatal pericardial effusion training model using ultrasound. It details materials, construction, and training objectives to support procedural competence.

Parents and Siblings as Role Models in Dealing With Digital Screen Media. Findings from A Media Fasting Intervention

Parents' and siblings’ role model motivation and function could play an important role in positively influencing both their own media behavior and that of family members. To investigate whether parents and siblings consciously take on this role model function, their intentions were being evaluated with a standardized questionnaire before a 6-week media fasting intervention. 135 pairs of parents and 178 pairs of children were included. A major component of the parents' media fasting intention to media fast was to be a role model for their children. This was particularly related to the idea that media fasting has something cleansing about it, as well as the hope of becoming more attentive and calm as a family. These parents seem to want to strengthen family cohesion and climate and protect their children from excessive media consumption. Children who want to be role models for their parents also intend to have a positive influence within the family and want to be role models for their siblings. Regression analyses revealed several predictors of the parents' intent for role model function: the hope of becoming more attentive and calm as a family, the view that media fasting has something cleansing about it, and the perception that it is good for one's children to use less digital screen media, and, inversely, age (R2 =.35). The best predictors of the corresponding intention among the children were the desire to be a role model for their siblings, for the family to do more together again and, as for the parents, a younger age (R2=.57). The intentions of both groups are different, but the possibility of using less media is perceived as sensible. The role model function appears to be a relevant motivating and influencing factor regarding the conscious use of digital screen media and regulation of screen time. This should be taken into account when developing interventions.

Ontogenes in Drosophila Melanogaster and a Model of Speciation

A new type of mutations-dominant lethals with a facultative manifestation -were discovered in D. melanogaster in 2000. These mutations were named conditional mutations. Under restrictive genetic conditions, the mutations manifest themselves as dominant lethals, whereas dominant lethality disappears under permissive conditions, displaying a set of other manifestations. The genes responsible for the emergence of conditional mutations were named ontogenes. The experiments with mutations in ontogenes have revealed the following processes: (1) genome editing in germline cells; (2) induction of high mutagenesis rates in germline cells of the mutants for ontogenes; (3) zygotic selection; (4) isolation of mutants; and (5) alterations in the lethality of mutants with time. The specific features in the manifestation of ontogenes together with the listed processes formed the background for construction of the model of speciation named the regeneration model. The event of speciation is represented as the regeneration of the working state of a genetic system disturbed by the emergence of a mutation in an ontogene. According to the model, it is ontogenes that are in charge of speciation and, eventually, the structure of living matter in the form of individual species. The significance of Mendelian protein-coding genes and Darwinian selection of the fittest according to these genes are doubtless but not paramount.

Evaluating the Effectiveness of Quality Improvement Strategies in Mid-Level Private Healthcare Facilities of Lagos State: A Donabedian Model-Based Approach

Background This study evaluates the effectiveness of quality improvement (QI) strategies in mid-level private healthcare facilities in Lagos State, with a focus on the structural components, healthcare processes, and healthcare outcomes. Employing the Donabedian model, the research aims to comprehensively assess and enhance healthcare service quality in these facilities. Methods A before-and-after study design was employed, involving a baseline assessment of 321 health facilities and endline assessment of 239 healthcare facilities, and a subsequent 10 - 12-month quality improvement intervention. Data were collected using facility assessments, client exit interviews, and interviews with key stakeholders. The analysis included a before and after analysis of the structural components, healthcare processes, and healthcare outcomes. Results The study demonstrates positive outcomes in mid-level private healthcare facilities in Lagos State following quality improvement (QI) interventions. Structural components, including, improved equipment availability, and enhanced compliance with standards, showcased significant improvements. Renovations and heightened registration compliance further underscored commitment to regulatory standards. Challenges in service availability, particularly in family planning and laboratory services, were identified. Importantly, the implementation of a QI scoring system revealed an overall positive impact, with the average score rising from 69% to 74%, signifying enhanced quality across diverse priority areas. Implications These findings highlight the success of QI interventions in transforming healthcare processes and structural components. Despite notable progress, persistent challenges in specific services call for targeted interventions. The substantial increase in patient satisfaction and overall QI scores underscores the transformative potential of sustained efforts and tailored interventions in mid-level private healthcare facilities in Lagos State. Conclusions This research comprehensively evaluates the effectiveness of quality improvement strategies implemented in mid-level private healthcare facilities in Lagos State, Nigeria, utilizing the Donabedian Model as a guiding framework. The findings provide valuable insights for policy recommendations, with the aim of aligning healthcare services with the Donabedian model to ensure the provision of high-quality care in mid-level private healthcare facilities in Lagos State. This study contributes to the ongoing efforts to improve healthcare quality in Lagos State. Contribution to Knowledge The research provides empirical insights into the effectiveness of quality improvement strategies in mid-level private healthcare facilities, particularly within the context of Lagos State, Nigeria. It highlights the significance of addressing structural components, optimizing healthcare processes, and monitoring healthcare outcomes to enhance the quality of care provided, aligning with the Donabedian model. These findings offer a valuable basis for policy recommendations and further research efforts aimed at improving healthcare quality in similar settings.

Enzyme Immobilization on Polypropylene Film: A Role Model for Biocatalytic Polymer Membranes?

Polymer electrolyte membrane (PEM) technologies hold promise for sustainable energy solutions, yet pinhole-related challenges persist. Our research introduces a novel biohybrid approach to self-healing, enhancing multiple healing cycles with minimal membrane disruption. Initial steps involve immobilizing enzymes on a polymeric membrane. This study establishes the immobilization process and analytical framework through enzyme immobilization on polypropylene. Applicability and stability are investigated, laying groundwork for potential Nafion™ applications and advancing climate neutral energy. Qualitative analysis employs colorimetric p-NPA assay on polypropylene-immobilized lipase from Candida rugosa (CRL) and Lipase B from Candida antarctica (CALB). Both enzymes hold their temperature optimum at 50°C which is increased by 10°C via immobilization. Diisopropylcarbodiimide (DIC) is optimal for immobilization. Synchronous enzyme and DIC addition is advantageous. After 8 reuse cycles, immobilized enzymes retain 54.3% residual activity. Immobilizates exposed to PEM fuel cell conditions show better stability due to covalent immobilization than free CRL. Yet, declines occur under stressors like 60 °C and concentrated alcohol. Immobilizates remain resilient at pH 3 and under oxidizing as well as reducing conditions constituted by varied gas atmospheres. Considering PEM fuel cells' operational range, in-depth investigations across conditions are vital. Future studies target long-term PEM fuel cell lifespans, focusing on extremophilic enzymes or modifications for high-temperature stability. Subsequently, the transferability of the immobilization method to Nafion™ shall be deliberated based on the outcomes.

Osteoarthritis and Depression Update: 2023-Can the Stress and Coping Model Help?

Background Osteoarthritis and depression are both key barriers to healthy aging and greatly heighten the risk for many negative health issues that seriously impact life quality. When combined what are the implications? Aim This mini review examines 2023 data pertaining to osteoarthritis and depression and older adults and a possible theoretical framework of stress that may direct our approaches in the future. Methods and Procedures Articles published between January 1 and August 15 2023 that addressed the current topic of interest and that were extracted from PUBMED, PubMed Central, Science Direct, and Google Scholar were carefully read and their key points arepresented in narrative form. Results As in the past, very few tangible theory-based prospective analyses that employ valid measures of depression and examine any association of any form of osteoarthritis longitudinally and in a consistent manner prevail. Several reports use the same or similar large cohort to draw upon, and find various degrees of clinical implications, but this may not embrace the need for more inclusivity, sampling strategies, control and diversity issues, as well as embracing the role of cognitions positive and negative. Conclusion Without efforts to develop sound research designs of diverse and carefully differentiated osteoarthritis substantive samples it is impossible to delineate the origin or implications of the osteoarthritis-depression linkage reported currently or arrive at a deep understanding of its relevance, to life quality and public health costs. What is needed to protect against or minimize either or both these clinically related disabling correlates in the aged population warrants timely study.

A General Approach to Modeling Covid-19

The present work shows that it is possible to analytically solve a general model to explain the transmission dynamics of SARS-CoV-2. First, the within-host model is described, and later a between-host model, where the coupling between them is the viral load of SARS-CoV-2. The within-host model describes the equations involved in the life cycle of SARS-CoV-2, and also the immune response; while that the between-Host model analyzes the dynamics of virus spread from the original source of contagion associated with bats, subsequently transmitted to a host, and then reaching the reservoir (Huanan Seafood Wholesale Market in Wuhan ), until finally infecting the human population.

Baroreflex Sensitivity, Cardiac and Kidney Remodeling and Deterioration in Vasoactive Substances Content in Blood in Experimental Model of Renovascular Hypertension. Action of Natural Flavone, Luteolin

This study aimed to analyze pharmacological actions of phenolic compound luteolin on the renal and cardiac hypertrophy, blood pressure (BP), baroreflex sensitivity (BRS), levels of epoxyeicosatrienoic acids (EETs), prostaglandin E-2 (PGE-2) and endothelin-1 (E1) in plasma in the 2 kidney - 1 clip (2K-1C) model of renovascular hypertension (RVH). All animals, were randomized into 2 groups: control (normal) I - sham-operated, II- RVH male Wistar rats, which after 4 weeks of surgical intervention secondly randomized to control II group, treated 0.1% dimethyl sulphoxide (DMSO) and main group - with luteolin in 15 DMSO, 3 mg/kg body weight, intraperitonially, during 2 weeks. ET-1, EETs and PGE2 levels investigated in carotid artery blood plasma and analyzed using ELISA kits. All data statistically analyzed using the SPSS-10.0 program. In RVH rats BP increased by 32%, cardiac and right kidney hypertrophy and reduction in parasympathetic component of BRS by 40% and sympathetic by 39%. The plasma level of total trans-EETs and PGE2 in RVH rats decreased by 44% and 50% respectively, while the level of ET-1 increased by 67%. Two weeks treatment with luteolin lowered BP, improved parasympathetic, without marked changes in sympathetic component of BRS. Deremodeling of cardiac and renal hypertrophy under prolonged treatment with luteolin accompanied with increasing in the level of EETs by 44%, PGE-2 by 50% and markedly reducing of plasma content of ET-1 (by 60%). Inhibition of EET hydrolase using low doses of luteolin provides beneficial cardio and renoprotective action in experimental model of RVH.

Time Series Analysis and Prediction of COVID-19 pandemic using Dynamic Harmonic Regression Models

Rapidly spreading Covid-19 virus and its variants, especially in metropoli- tan areas around the world, became a major health public concern. The tendency of Covid-19 pandemic and statistical modelling represent an urgent challenge in the United States for which there are few solutions. In this paper, we demonstrate com- bining Fourier terms for capturing seasonality with ARIMA errors and other dynamics in the data. Therefore, we have analyzed 156 weeks COVID-19 dataset on national level using Dynamic Harmonic Regression model, including simulation analysis and ac- curacy improvement from 2020 to 2023. Most importantly, we provide a new advanced pathways which may serve as targets for developing new solutions and approaches.

Seasonal ARIMA model for Covid-19 pandemic Prediction in the United States

The COVID-19 pandemic has had a profound impact on global health and economies. The pandemic continues to spread and accurate forecasting of its spread is essential for the effective management of healthcare systems and the development of effective policies. The development of forecasting models for COVID-19 has become increasingly important as the pandemic continues to evolve. In this paper, we will summarize the Covid-19 pandemic in the United States state by state. And then, we utilize the temporal data of coronavirus spread from January 18, 2020 to January 29, 2023. Finally, we model the evolution of the COVID-19 outbreak and perform prediction using ARIMA and time series forecasting models on some selected states.

Experimental Study by the Plan Composite Centered Method, Modeling and Optimization of Hydrogen Production by Alkaline Electrolysis

A planned experimental study on the production of green hydrogen by alkaline electrolysis is carried out by the Plan Composite Centered (PCC) method. The parameters studied are the concentration of the electrolyte, the distance between electrodes, the height of the electrodes, the total supply voltage of the electrolyser, temperature, and the electrolyte type. The results show that the effect of concentration, height, voltage and temperature are positive. However, the effect of the distance between the electrodes is negative. Electrolysis with potassium hydroxide (KOH) is more efficient than with sodium hydroxide (NaOH). The second-order interactions are weak, except for the voltage-temperature interaction which is significant. The results of the experimental study conducted in this work are in agreement with previous studies. Two a polynomial modeling (with KOH and with NaOH) suitable for predicting the flow of hydrogen produced are presented. Three optimizations of ascending constraints on the operating parameters to have a maximum hydrogen production and with a minimum of electrical energy and a minimum of concentration consumed are carried out.

Visualization of Myocardial Damage Based on Surface Heart Model

The visual presentation of the results of the analysis of cardio graphic information is an important element of the diagnostic process. The article discusses the issues of visualization of the state of the heart, notes the importance of a visual representation of the processes of the functioning of the heart for diagnosis. The Delaunay triangulation is considered and it is proved that on its basis it is possible to approximate an arbitrarily complex surface. An algorithm for constructing a surface model of the heart based on Delaunay triangulation has been developed. The issues of texture generation are covered in detail. The texture is a convenient tool for displaying the state ofthe heart, as it allows you to visually show the place of possible damage on the surface of the heart.

Specified model of the work environment in a public university in central Mexico

The work environment, in its most general conception, alludes to biased expectations of risks and benefits around a function and in relation to the performance of a working group, but in its factorial structure, dimensions have been found that explain a moderate percentage of the variance of the construct. In this sense, the objective of this paper is to specify a model for the study of the work climate, considering the institutionalism and human capital of a public university. An exploratory study was carried out with an intentional sample of 125 administrative personnel. From a structural model it was found that the relationship climate factor explained the highest percentage of the variance (21%) and it was the reflective dimension of the construct (0.524). The inclusion of the task climate is recommended due to its link with the leadership and the collaborative climate.

Histo-Morphological Effect of The Small, Large Intestines and Stomach of Animal Models Treated With Aqueous Extract of Abelmoschus Esculentus

This study investigates the effect of Aqueous extract of abelmoschus esculentus on the microanatomy of the small, large intestine and stomach and the body weight of Wister rats. Twenty-one adults male wistar rats weighing between 100-120 grams were assigned into three groups consisting of seven rats each; Group A (control), Group B (low dose), and Group C (high dose). The rats in the control group were fed with fed with feed and water only while the rats in groups B and C were treated with 0.1mg/kg body weight and 3.0mg/kg body weight of abelmoschus esculentus respectively for 14 days. At the end of administration, the final weights of all rats were recorded before sacrifice using cervical dislocation and the small, large intestine and the stomach were harvested, processed and stained using H&E stain. The results were revealed as significant (p<0.05) increased in the mean body weight compared with the weight in the control groups and experimental groups. The treated animal groups revealed increased cellularity, focal metaplasia of the mucosal cells with villous disruption in the small intestine and dysplasia of the mucosal with loss of epithelial shape in large intestine. The stomach histology showed gastric pits with goblet cells smooth muscles layer and surface epithelium in the control group. Sections from the low dose treated group showed deep epithelical gastric pit areas with marked depletion of pits and goblet cells while the high dose treated group revealed dysplasia of gastric pits, goblet cells and smooth muscles appear mildly eroded.

Modeling of the Deposition of Low-Density Lipoprotein Particles inside an Ideal Geometry of the Heart Coronary Arteries

In this study, flow hemodynamic parameters and settling of LDL particles in healthy ideal and ideal with stenosis coronary artery have been studied using the Open FOAM software. Not only the effect of movement of the vessel on particles depositions have been studied, but also both non-Newtonian and Newtonian behaviors of blood have been investigated. The particle's motion and deposition have been simulated. It has resulted that only in small vessels, non-Newtonian behavior of blood can be seen and in bigger vessels, there is no remarkable difference between two Newtonian and non-Newtonian models. Vessel movement has no important effects on entered shear stress on its wall, but the alteration in flow lines causes a 70% increment in particles depositions on a vessel with stenosis. This shear stress has no considerable changes with inlet velocity alteration, but it has intensive dependence on geometry in the vessel with stenosis (13 times more oscillation in stenosis location than a healthy vessel).

Analysis of Covid-19 Using A Modified SEIR Model To Understand The Cases Registered in Singapore, Spain, And Venezuela

This work proposes a modification of a compartmental-type model based on the Susceptible-Exposed-Infected-Recovered (SEIR) scheme to describe the dynamics of contagion by Covid-19 in any part of the world, including also the numerical and analytical calculation of the mantissa and the resolution of a partial differential equation system. As an example, the different incidents that occurred in Singapore, Spain and Venezuela are analyzed to demonstrate the usefulness of the methodology developed in this work that can be seamlessly extended to other regions.

Ameliorative Potential of Chlorogenic Acid on Rotenone-Induced Neurotoxicity in Drosophila Melanogaster Model

Chlorogenic acid (CA), abundantly found in green coffee beans, is a phenolic compound with antioxidant and anti-inflammatory properties amongst others. Exposure to rotenone, a natural pesticide, induces Parkinsonism (a type of neurodegeneration) through the induction of mitochondria dysfunction and oxidative stress. Phytochemicals with antioxidant properties may be promising in attenuating this condition. In this research, the ameliorative role of CA on rotenone-induced toxicity in Drosophila melanogaster was evaluated. Drosophila melanogaster (Harwich strain, 1- 3 days old) was used. 6 groups of five vials each with 50 flies/vial were exposed to CA (0; control (2% ethanol), 7.5, 15, 30, 45 and 60 mg/kg diet) for 28 days in the longevity analysis. A 28-day survival assay was carried out with rotenone (0, 250 and 500 μM). CA (30 mg/kg diet) was selected to evaluate its ameliorative potential on rotenone. For the study, the flies were divided into four groups of five vials each and exposed to CA and rotenone; Group A- control (2% ethanol), Group B- CA only, Group C- rotenone only and Group D- CA (30 mg/kg diet)+ rotenone (500 μM)for 7 days. Thereafter, the homogenate was evaluated for oxidative stress status, rate of emergence, negative geotaxis and acetyl cholinesterase activity. CA (30 mg/kg diet) extended the lifespan of flies by 21.4%. Also, CA ameliorated rotenone-induced perturbation in catalase, glutathione-S-transferase and acetyl cholinesterase activities, total thiol and glutathione levels, and behavioral deficit (p < 0.05). CA may have ameliorative effect against rotenone-induced toxicity and Parkinsonism.

By Design: Aligning Structure with Values to Impact Outcomes in a Public Utility Model

The lived experiences of thousands of health care providers demonstrates an inconguence in values while giving us a tremendous amount of information - if we listen. At every level behaviors are compromised in a structure when the values of the providers are not aligned with the system. Over time, statistics as well as disease become so normalized that the status quo dominates perceptions and inhibits action. The United States will continue to have mediocre to poor outcomes unless the ethical foundation of the system is fundamentally altered to profit on wellness. “You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.” Buckminster Fuller 1

A Model-Based Estimation of Annual Long-Term Care Costs in Germany Following Post-Operative Cognitive Dysfunction (POCD) in Elderly Patients

Acute post-operative delirium (POD) and long-term post-operative cognitive dysfunction (POCD) are frequent and associated with increased mortality, dependency on care giving and institutionalization rates. The POCD-related cost burden on the German long-term care insurance provides an indication for the savings potential from risk-adapted treatment schemes. Comprehensive estimates have not been assessed or published so far. A model-based cost-analysis was designed to estimate POCD-related costs in the long-term care insurance. Comprehensive analysis of inpatient operations and procedures (OPS-codes) served as the base for case number calculations, which were then used as input to the actual cost model. POCD-incidence rates were obtained from the BioCog study. Various sensitivity analyses were performed to assess uncertainty of the model results. Total POCD related annual costs in the German long-term care insurance account for approximately 1.6 billion EUR according to the base case of our analysis. Total annual costs for all POCD cases depend on surgery numbers, incidence rates, other assumptions, and uncertain input parameters. The financial burden to the long-term care insurance is substantial, even in a conservative scenario of the cost model. Variability of results stems from uncertain assumptions, POCD-incidence rates and from uncertain patient numbers who are undergoing surgery and are therefore at risk to develop POCD.

Mathematical Modeling of Covid-19

Background The novel coronavirus (COVID-19) suddenly appeared in Wuhan, Hubei since December 2019, and quickly swept across China, then the whole world. Today, after more than 100 days of fighting against the virus, China's epidemic has been effectively controlled, but when we looking at the entire world, the novel coronavirus has rampaged globally, especially in the United States and many European countries. This paper mainly studies the impact of COVID-19 outbreaks at Hubei Province and the United States, fits the given data and predicts future trends. Methods Based on the theoretical basis of traditional differential equations and SIR infectious disease model1, and combined with the actual situation to improve the model. Hubei Province is modeled in different time periods, and the effects of birth rate and natural mortality on the model are analyzed. Since the birth rate and natural mortality in the United States in recent years cannot be found, the epidemic situation in the United States can only be analyzed based on the absence of births and natural deaths. Finally, we used Netlogo2 to establish a closed environment (Small World), and combined with known data to conduct simulation experiments on COVID-19 infection. Findings Through the analysis of given data through the SIR model, it is found that before the Chinese government has taken comprehensive measures to cure patients (before 10 February), the number of patients in Hubei Province will reach the peak at the end of February, and will gradually decline thereafter, and on 20 March, the epidemic will be effectively controlled in the future, which coincides with the fact that Wuhan closed the last mobile cabin hospital on 10 March. On the other hand, after the Chinese government tried its best to cure the patients (after 21 February), the number of patients continued to decline over time and will reach 0 in mid-April, which is also consistent with the actual data. According to the factors of birth and natural death, the sensitivity analysis of the above model found that when the epidemic situation is at its peak, it has little effect on the curve, but when the epidemic situation gradually flattens, it still has a certain effect on the trend of the curve. Finally, looking at the situation in the United States, due to the high transmission rate, the number of patients in the United States continues to rise and is expected to reach its maximum in mid-June. We also use Netlogo to simulate the environment in which the virus spread, and find that the general trend of the curves is also consistent with the actual curves. Interpretation The Chinese government has taken various measures to deal with the novel coronavirus pneumonia, including the establishment of two temporary hospitals and dozens of sheltered hospitals, the temporary transformation of university dormitories into isolation rooms345, the closure of Wuhan, the ban on the movement of people and so on. These measures have helped to reduce the spread of the virus and greatly increased the patient's cure rate. But the US government ’s actions are not as effective as China’s, not only because the government ’s actions are inappropriate and untimely, and the people’s opposition to isolation has not subsided. As a result, the virus has spread widely in the United States. More than one million people have been infected with the virus, and tens of thousands of people have died from COVID-196.

Models and data Analysis of the Outbreak Risk of COVID-19

With the spread of the new coronavirus around the world, governments of various countries have begun to use the mathematical modeling method to construct some virus transmission models assessing the risks of spatial spread of the new coronavirus COVID-19, while carrying out epidemic prevention work, and then calculate the inflection point for better prevention and control of epidemic transmission. This work analyzes the spread of the new coronavirus in China, Italy, Germany, Spain, and France, and explores the quantitative relationship between the growth rate of the number of new coronavirus infections and time. In investigating the dynamics of a disease such as COVID-19, its mathematical representation can be constructed at many levels of details, guided by the questions the model tries to help answer. Mathematical sophistication may have to yield to a more pragmatic approach closer to the ability to make predictions that inform public health policies. Background In December 2019 , the first Chinese patients with pneumonia of unknown cause is China admitted to hospital in Wuhan, Hubei Jinyintan , since then, COVID-19 in the rapid expansion of China Wuhan, Hubei, in a few months time, COVID-19 is Soon it spread to a total of 34 provincial-level administrative regions in China and neighboring countries, and Hubei Province immediately became the hardest hit by the new coronavirus. In an emergency situation, we strive to establish an accurate infectious disease retardation growth model to predict the development and propagation of COVID-19, and on this basis, make some short-term effective predictions. The construction of this model has Relevant departments are helpful for the prevention and monitoring of the new coronavirus, and also strive for more time for the clinical trials of Chinese researchers and the research on vaccines against the virus to eliminate the new corona virus as soon as possible. Methods According to the original data change law, Establish a Logistic growth model, we collect and compare and integrate the spread of COVID-19 in China, Italy, France, Spain and Germany, record the virus transmission trend among people in each country and the protest measures of relevant government departments. Findings Based on the analysis results of the Logistic model model, the Logistic model has a good fitting effect on the actual cumulative number of confirmed cases, which can bring a better effect to the prediction of the epidemic situation and the prevention and control of the epidemic situation. Interpretation In the early stage of the epidemic, due to inadequate anti-epidemic measures in various countries, the epidemic situation in various countries spread rapidly. However, with the gradual understanding of COVI D -19, the epidemic situation began to be gradually controlled, thereby retarding growth

Post Covid-19 Doctor-Patient Relationship Model. Creation of Social Connection Contexts With Physical Distancing

The coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 1 has produced a significant change in the way general medicine is conducted. This shift has been remarkably quick towards telecare. The form of the clinical interview has changed, and with it communication and the doctor-patient relationship; Before COVID-19, all communication techniques and doctor-patient relationship, which were considered tried and true to establish a good relationship with patients, involved physical proximity 2. Now in many European countries and in the United States face-to-face consultations have been reduced to 10-20%, with most contacts now being provided remotely using symptom checkers, electronic messaging, and phone or video consultations 3.

A Predictive Tobacco Control Mass Media Programming Model to Achieve Best Buys in Low –and Middle-Income Country Settings

Background Evidence based message design and efficient dissemination of messages are critical to the success of tobacco control mass media campaigns. Although evidence to measure effectiveness of messages is emerging within low -and middle-income country (LMIC) settings, evidence-based approaches for mass media message dissemination is currently lacking due to challenges in accurate assessment of gross rating points (GRPs) for efficient delivery of campaign messages. Approaches to more accurately predict optimal campaign impact are required to achieve best-buys in resource constrained settings Method A case study approach compared findings from two national tobacco control mass media campaigns implemented in Bangladesh. Stage one reviewed protocols to assess the efficacy of message designs. Second stage analysis involved a review of the mass media campaign recall findings from cross-sectional, post-intervention surveys. Last, a post assessment of GRPs for both campaigns was conducted to support the development of an algorithm to better predict campaign impact at the greatest cost-efficiencies. Results Message mean pre-test scores identified that the Baby Alive campaign scored approximately 20% lower than mean pre-test scores of messages for the Graphic Health Warning campaign. Media dissemination for the Baby Alive campaign was also relatively low at 165GRPs achieving 16.8% prompted recall while the Graphic Health Warning campaign delivered 292GRPs to achieve 47.0% prompted recall. The analytic-predictive model identified that for messages with high pre-test scores an increase of only 1.5GRPs was required to the existing media plan to potentially achieve an additional percentage point of recall. Discussion Given the weaknesses in GRP calculations in LMIC settings, analysis of multiple metrics should be considered to achieve best buys for tobacco control mass media campaigns. Based on optimal message mean pre-test scores of 90%+ and delivery of 292GRPs, which achieved 47% campaign recall, optimal recall of 70% could be predicted with a media plan delivering 342GRPs. More analytical-predictive mass media programming models need to be developed in other LMIC settings examining multiple campaign findings to confirm if this algorithm can provide better returns on investment with efforts directed toward delivering interventions that are supported by a strong evidence base.

Assessment of Body Size by Structural Equation Model Using Anthropometric Traits of Fishermen Community: A Methodological Approach

Objectives Aim of the study was to develop a ‘composite body size score’ (CBSS) using anthropometric traits to estimate body size and to assess the nutritional status of each study individual on the basis of CBSS. Materials and Methods Data on seventeen anthropometric traits were collected from 710 individuals (Male, Female) from fishermen community inhabiting coastal villages of West Bengal, India. For estimating body sizes, Structural Equation Model (SEM) was constructed with Path Analysis (PA). Later, second order Confirmatory Factor Analysis (CFA) was applied on SEM to determine CBSS. It was hypothesized in the models that CBSS is composed with three sets of latent variables viz., linear, circular and skinfold, constructed from anthropometric traits. Applying new derived optimal cut off points of CBSS was used to determine lean, normal and robust body sizes. Individuals with negative values of CBSS were categorised as lean body size,. Positive values of CBSS were categorised into two categories- normal and robust body size. Results On the basis of CBSS, result showed that 50.6%, 48.8% and 0.6% of the individuals were categorised under lean, normal and robust body size respectively. Females showed relatively higher percent of lean body size i.e. under nutrition (73.8%) compared to males (26.2%). Conclusion The hypothesized model estimate more accurate composite body size score, based on anthropometric traits. All the traits are highly significant on the model. The lean body size category can be use in predicting ‘Undernutrition’.

Controlling the Covid-19 Pandemic without Killing the Economy: About Data Driven Decision Making with a Data Model Assessing Local Transmission Risk

Context In the face of further waves of the COVID-19 pandemic it becomes essential to find a balance between protective actions to guard public health and restrictive measures which can collapse our economy. Background As a basis for public health decisions, officials still rely on metrics which were helpful in the beginning of the pandemic but are now not precise enough for a focused and targeted approach to keep the spread of the infection under control. This can lead to public mistrust, “pandemic tiredness”, and can cause unnecessary damage to the economy without having the desired protective effect on public health. Methods This article discusses various metrics, their advantages and caveats, and it provides suggestions for use in a more targeted and risk-based approach, as an alternative to the current “general lock-down” practice. It suggests the notion of including a concept of “risk contacts per area” to better describe the possibility of virus transmission than currently published metrics do. The article also suggests specific analyses of real-world data for identification of populations at risk for severe courses of COVID-19 to allow more targeted protective actions. Discussion Data currently used to describe the COVID-19 pandemic lack important parameters like population density and local likelihood of potentially infectious contacts. The currently often used “all or nothing” approach of shut-down orders needs to be replaced by more sophisticated tactics considering individual local exposure risks and need to be balanced towards metrics on economic short term and long-term impact. In addition, smart analyses of real-world data may contribute to effective protection of individuals at risk.

Social Network Analysis of Integrated Medical Services for Hypertension – Using District Hospitals of Shanghai as a Model

Objective To examine the current linkage between different medical services for hypertension patients for enhanced integration among medical service systems. Methods A total of 18 hospitals and community medical centers from a district of Shanghai were enrolled for social network analysis which covered emergency visits and hospitalization records of 171,177 outpatients with hypertension. Stata software was used for data preprocessing and UCINET software was used for network analysis of medical service providers to quantify and visualize the network tightness and the "main role" of information delivery of the medical institution network in the area. Results The service network of hypertension consultation institutions in the region is closely connected as a whole, but the level of diagnosis and treatment of medical services in various communities varies widely, and the degree of association with higher-level medical institutions is not uniform. Conclusion Based on the limited tightness of various medical service providers, it is necessary to implement the responsibilities of individual medical institutions at different levels and pay more attention to improving the service capabilities of primary medical institutions for enhanced integrating medical services in future.

The Interaction Model of Concentrated Solar Radiation with Materials

The paper analyzes approaches to modeling the processes of interaction of concentrated solar radiation with materials. The experimental results obtained on the synthesis of materials from a melt in a solar furnace are presented. The features of the interaction of concentrated solar radiation with materials are analyzed. The mechanisms are described and a model for the interaction of concentrated solar radiation with materials is created. A feasibility study is proposed for the technology of glass-based glass materials obtained on the Big Solar Furnace.

Genetic-Mathematical Modelling of the Populations Interaction

The solution of a genetic-mathematical problem of interaction of the human population cells and virus population to a problem of pandemic COVID-19 is submitted. The mathematical model based on the Hardy - Weinberg law consisting of two interdependent differential equations is used. The equations reflect time dynamics of the human cells and virus populations during their interaction. Solutions of the differential equations are found and results of these solutions are analyzed. The estimation of duration pandemic is received at use of parameters of the human liver cells and a flu virus.

Determining the Efficiency of Fuzzy Logic EOQ Inventory Model with Varying Demand in Comparison with Lagrangian and Kuhn-Tucker Method Through Sensitivity Analysis

This paper considers an EOQ inventory model with varying demand and holding costs. It suggests minimizing the total cost in a fuzzy related environment. The optimal policy for the nonlinear problem is determined by both Lagrangian and Kuhn-tucker methods and compared with varying price-dependent coefficient. All the input parameters related to inventory are fuzzified by using trapezoidal numbers. In the end, a numerical example discussed with sensitivity analysis is done to justify the solution procedure. This paper primarily focuses on the aspect of Economic Order Quantity (EOQ) for variable demand using Lagrangian, Kuhn-Tucker and fuzzy logic analysis. Comparative analysis of there methods are evaluated in this paper and the results showed the efficiency of fuzzy logic over the conventional methods. Here in this research trapezoidal fuzzy numbers are incorporated to study the price dependent coefficients with variable demand and unit purchase cost over variable demand. The results are very close to the crisp output. Sensitivity analysis also done to validate the model.

Biomedical Infophysical Models of Filtering Ghost Airflows by Wearing Masks and Maintaining Social Distancing to Prevent COVID-19 and Reopen All Systems after Shutdowns (Lockdowns)

The COVID-19 pandemic has killed more than 400 thousand and infected more than 7 million people in the whole world as of 06/10/2020. Many open systems, such as educations, transportations, entertainments, sports or foods, have been completely or partially locked down in many regions of the world to prevent COVID-19 spreading. Therefore, how to reopen all of the open systems after the shutdown has become a world urgent issue. Evidences of COIVD-19 have showed: person-to-person transmission occurs among close contacts; virus droplets (or aerosols) play an important role in the transmission; people can prevent COVID-19 by measures of mask-wearing or maintaining social distancing. However, how these measures work to prevent COVID-19 is still not clear in a perspective of biomedical Infophysics. In this study, (1) we think the transmission of infection can be accomplished by real or virtual person; (2) we define a virtual person as ghost airflow, a term we coin to describe virus droplets (or aerosols) that are initially generated by human carriers and remain in the air to be transmitted. These ghost airflows are as dangerous as the real virus carriers particularly in enclosed (confined) environments; (3) we propose biomedical infophysical models (BMIPM) of filtering the ghost airflows by mask-wearing and maintaining social distancing, to help people to understand the filtering mechanisms and willingly follow the guidelines of preventing covid-19, and therefore to successfully reopen all of the open systems after the shutdowns (lockdowns) and (or) to avoid the shutdowns (lockdowns) in future epidemics or pandemics. Significantly, we compare the prevention efficiencies of COVID-19 between people who are accustomed and not accustomed to masks based on the published WHO, CDC or NHC pandemic data. The compared results support our models in this investigation. Coronaviruses easily survive and have high toxicity, in dirty, wet and cold environments, and the air pollution is linked with higher COVID-19 death rates. The dingy environments and air-conditioning, freezing systems sufficiently provide such necessary dirty, wet and cold conditions and polluted airflows to exacerbate the mortality rate of COVID-19. Therefore, we strongly suggest: to use air conditioners as less as possible, to turn the wind levels as low as possible and to clean (disinfecting) the air-conditioning systems (filters and channels) and environments as frequent as possible.

Artificial Neural Network Model for Rainfall Data Analysis During 2004-2017 in Tamil Nadu, India – Prevailing Pattern Evaluation on Climate Change

This research paper focuses on rainfall variations in Tamil Nadu, India using Wavelet, Linear regression and Artificial Neural Networks model from 2004 to 2017. As the rainfall is the key factor in understanding climate change, the seasonal datasets from 2004-2017 of Tamil Nadu state has been taken for study. The salient feature of this study is the application of Neural Networks and wavelet analysis. It reveals that the rainfall variations are ambiguous that it does not maintain a constant pattern. Wavelet coefficients of multiresolution spectrogram reveals that the intensity of rainfall in each year. Linear regression model divulge the pattern of rainfall followed in every season and the results show that except winter season all other season suffers deficient rainfall. The deficiency of rainfall may be due to different parameters like ElNino or LaNina pattern or global warming. Results showed that all seasons except winter does not maintain consistency in the rainfall variability. Winter season provides the positive slope values of 4.7 and 0.6 for January and February respectively. Moreover Artificial Neural Networks training provides prominent results of Regression value 0.98 which is comparably high with other seasons taken for study.

Structural Equation Modeling to Detect Predictors of CD4 Cell Count Change due to Long Term Antiretroviral Therapy Administered to HIV-Positive Adults at Felege Hiwot Teaching and Specialized Hospital, Bahir Dar, Ethiopia

Background The relationship between predictors and the variable of interest was estimated using a structural equation model which is used to predict latent variables. The main advantage of the SEM is the ability to estimate the direct and indirect pathways of the effect of the primary independent variable on the outcome, given sufficient sample sizes. Despite not directly modeling the mediated pathways, GLMMs excluding mediating variables performed well with respect to power, bias and coverage probability in modeling the total effect of the primary independent variables on the outcome. In longitudinal studies, data are collected from subjects at several time points. The main purpose of longitudinal analysis is to detecting the trends or trajectories of the variables of interest. Methods A longitudinal study was conducted on 792 adults living with HIV/AIDS who commenced HAART. Structural equation modeling was used to construct a model to detecting predictors of CD4 cell count change. The procedure was illustrated by applying it to longitudinal health-related quality-of-life data on HIV/AIDS patients, collected from September 2008 to August 2012 monthly for the first six months and quarterly for remaining study period. Results The result of current investigation indicates that CD4 cell count change was highly influenced by certain socio-demographic and clinical variables. Out of all the participants, 141 (82%) have been considered 100% adherent to antiretroviral therapy. Structural equation modeling has confirmed the direct effect that personality (decision-making and tolerance of frustration) has on motives to behave, or act accordingly, which was in turn directly related to medication adherence behaviors. In addition, these behaviors have had a direct and significant effect on viral load, as well as an indirect effect on CD4 cell count. The final model demonstrates the congruence between theory and data (x2/df. = 1.480, goodness of fit index = 0.97, adjusted goodness of fit index = 0.94, comparative fit index = 0.98, root mean square error of approximation = 0.05), accounting for 55.7% of the variance. Conclusions The results of this study support our theoretical model as a conceptual framework for the prediction of medication adherence behaviors in persons living with HIV/AIDS. Implications for designing, implementing, and evaluating intervention programs based on the model are to be discussed.

Pharmacodynamic Modeling of Sunscreens: New Efficacy Evaluation, Risks of Sunburn and Melanoma and Very Low to Very High Sun Protection Factor

Pharmacodynamic modeling of sunscreens was performed using a new concept of Skin UV Index (SUI) on the exposed skin as a parameter to evaluate the potential effectiveness of sunscreens against sun damage. The SUI predicts the UV heat intensity on the skin surface in terms of the solar UV Index at the time of the study and is calculated by solar UV Index/sunscreen’s SPF. SUI numbers for sunscreen with SPF ranging from 2 to 100 under a solar UV Index of 10 was used for illustration. Based on guidelines from WHO, Australia and New Zealand, sunscreens yielding SUI < 3 are assumed to be effective against sun damage such as sunburn and melanoma. Based on the above assumption, sunscreens with SPF > 4 were found to be effective when sunscreens were evenly applied at 2 mg/cm2. Review of numerous studies suggests that missing applications may represent a major, seemingly unavoidable, SPF-independent factor causing unintended sunburns for sunbathers in the US and other countries with a temperate climate. This might in turn become a major factor for causing exponential increase in melanoma incidence rates observed in the last few decades. For example, in an SPF 30 sunscreen study all 25 participants suffered unintended sunburns after one week of sunbathing. Also, a mean missing application of 20% of the total exposed area and a mean missing of about 50% of the time were reported in two separate studies. Simulations were also performed with under-applications of 50% and 75%. The present simulations may provide a rationale of why routine use of a low SPF 8 sunscreen was reported to be effective against melanoma in a 2018 Australian study. Based on model simulations it is proposed that in the US, SPF 8 sunscreen and SPF 2 to 6 sunscreen may be adequate for routine, unintentional use for sun-sensitive populations and non-sun-sensitive populations, respectively.

RETRACTED: Monte Carlo Approach To Genotype By Environment Interaction Models

This article has been retracted on 10 February 2021. VIEW THE RETRACTION NOTICE (https://doi.org/10.14302/issn.2643-2811.jmbr-25-5847) Understanding the implication of Genotype-by-Environment (GXE) interaction structure is an important consideration in plant breeding programs. Traditional statistical analyses of yield trials provide little or no insight into the particular pattern or structure of the GXE interaction. In this study, efforts were made to solve these problems under different level of data occurrence. We employed the simulation process of Monte Carlo in generating since use of a real-life data may pose a serious difficulty. In this paper, we simulated for two data Types of Balance and Unbalance designs with different Levels of generations (3X3, 7X7, 10X10, and 3X7, 7X3, 7X10, 10X7 , , respectively). We therefore check the performance of GXE interaction on four different models (AMMI, FW, GGE and Mixed model), and also their stability and adaptability. The findings revealed that, when the assumption was maintained, AMMI outperformed Finlay-Wilkinson model, GGE Biplot model and Mixed model.

Retraction Note: Monte Carlo Approach To Genotype By Environment Interaction Models

Mathematical Modeling and Epidemic Prediction of COVID-19 and its Significance to Epidemic Prevention and Control Measures

Background Since receiving unexplained pneumonia patients at the Jinyintan Hospital in Wuhan, China in December 2019, the new coronavirus (COVID-19) has rapidly spread in Wuhan, China and spread to the entire China and some neighboring countries. We establish the dynamics model of infectious diseases and time series model to predict the trend and short-term prediction of the transmission of COVID-19, which will be conducive to the intervention and prevention of COVID-19 by departments at all levels in mainland China and buy more time for clinical trials. Methods Based on the transmission mechanism of COVID-19 in the population and the implemented prevention and control measures, we establish the dynamic models of the six chambers, and establish the time series models based on different mathematical formulas according to the variation law of the original data. Findings The results based on time series analysis and kinetic model analysis show that the cumulative diagnosis of pneumonia of COVID-19 in mainland China can reach 36,343 after one week (February 8, 2020), and the number of basic regenerations can reach 4.01. The cumulative number of confirmed diagnoses will reach a peak of 87,701 on March 15, 2020; the number of basic regenerations in Wuhan will reach 4.3, and the cumulative number of confirmed cases in Wuhan will reach peak at 76,982 on March 20. Whether in Mainland China or Wuhan, both the infection rate and the basic regeneration number of COVID-19 continue to decline, and the results of the sensitivity analysis show that the time it takes for a suspected population to be diagnosed as a confirmed population can have a significant impact on the peak size and duration of the cumulative number of diagnoses. Increased mortality leads to additional cases of pneumonia, while increased cure rates are not sensitive to the cumulative number of confirmed cases. Interpretation Chinese governments at various levels have intervened in many ways to control the epidemic. According to the results of the model analysis, we believe that the emergency intervention measures adopted in the early stage of the epidemic, such as blocking Wuhan, restricting the flow of people in Hubei province, and increasing the support to Wuhan, had a crucial restraining effect on the original spread of the epidemic. It is a very effective prevention and treatment method to continue to increase investment in various medical resources to ensure that suspected patients can be diagnosed and treated in a timely manner. Based on the results of the sensitivity analysis, we believe that enhanced treatment of the bodies of deceased patients can be effective in ensuring that the bodies themselves and the process do not result in additional viral infections, and once the pneumonia patients with the COVID-19 are cured, the antibodies left in their bodies may prevent them from reinfection COVID-19 for a longer period of time.

Effect of the Biofield Energy Treated Proprietary Test Formulation for Sleep Biomarkers in the Unpredictable Chronic Stress (UCS) Animal Model 

Sleep biomarkers in brain such as melatonin, BDNF (Brain-derived neurotrophic factor), PGD2 (Prostaglandin D2), leptin, orexin-A, and acetylcholine were evaluated in the unpredictable chronic stress (UCS) rodent model in the presence of Consciousness Energy Healing Treated (the Trivedi Effect®) novel test formulation in male Sprague Dawley (SD) rats using ELISA assay. The test formulation was consisted of minerals (Zn, Fe, Cu, Se, Ca, Mg), vitamins (C, E, B6, B12, D3), β-carotene, ginseng, and cannabidiol isolate. The test formulation constituents were divided into two parts, one part of each ingredient was distinct as the untreated test formulation, while the other portion of the test formulation and a group of animals received Biofield Energy Healing Treatment by a renowned Biofield Energy Healer, Mr. Mahendra Kumar Trivedi. The level of melatonin in groups viz. G5 (Biofield Energy Treated Test formulation) and G7 (15-days pre-treatment of Biofield Energy Treated Test formulation) was significantly increased by 17.6% (p≤0.01) and 16%, respectively as compared with the disease control group (G2). Brain-derived neurotrophic factor (BDNF) level in brain was increased by 5.2% in G7 group as compared with the G4. Prostaglandins D2 (PGD2) level was significantly (p≤0.001) increased by 12.7%, 18.1%, 23.7%, and 30.7% in the G6, G7, G8 (15 days pre-treatment of Biofield Energy Treated Test formulation to the Biofield Energy Treatment per se rats), and G9 (untreated test formulation to the Biofield Energy Treatment per se to the rats) groups, respectively as compared with the G2. The level of leptin after Biofield Energy Treatment and with the test formulation was altered. However, orexin-A level was significantly decreased by 37.1% (p≤0.05), 32.6%, 40.5% (p≤0.05), 44.4% (p≤0.05), and 28.2% in the G5, G6, G7, G8, and G9 groups respectively, as compared with the G2. Similarly, acetylcholine (Ach) level was significantly (p≤0.001) decreased by 42.5%, 49.2%, 40.1%, 47.9%, and 45% in the G5, G6, G7, G8, and G9 groups, respectively as compared with the G2. Overall, the results showed the significant slowdown the stress-related disease progression and its complications/symptoms in the preventive in the Biofield Energy Treatment group per se and/or Biofield Energy Treated Test formulation groups (viz. G6, G7, G8, and G9) comparatively with the disease group. The Trivedi Effect® showed increased level of melatonin and decreased levels of insomnia related brain biomarkers which might be helpful to induce better sleep in human.

Nitrogen Leaching Loss Estimation from Paddy Soil in the Taihu Lake Region of China by a Newly Developed Simple Model

Nitrogen leaching as a direct pathway of N loss from agricultural land can negatively affect groundwater and surface water quality. However, a simple and efficient method for nitrogen leaching loss estimation is still inefficient. In this study, an exponential model was developed using the experimental data from a two-year field experiment conducted in the Taihu Lake region of China to simulate the N leaching from the paddy soil. The results showed the leached N was in the range of 5.66 to 8.45 kg N/ha during the whole rice season, which was accounted for 1.7%-2.1% of the applied N. A good agreement between the measured and model predicted results for N leaching loss was observed, suggesting the validity of the established model. The model was further validated with the data of other studies in other regions. The results demonstrated this model is able to simulate the N leaching loss accurately and can provide a beneficial tool for users to predict N leaching loss in paddy soil.

Spectroscopic and Foliar pH Model for Yield Prediction in a Symbiotic Corn Production 

The agronomic management of symbiotic (S) inoculations, by means of bio-fertilizers (BF), is aimed at inducing modifications of the plant rhizosphere and thereafter of the phenotype and yield of the crop. It is here shown that the yield response of maize to a symbiotic treatment may be correlated to six easy-to-calculate indicator variables on the basis of the raw foliar pH, NIR-Spectroscopy of leaves, and the NIRS of hay litter-bags from soils. It has been confirmed, in a set of thirteen pairwise comparisons of Symbiotic (S) soil inoculated by BF vs. Control (non-inoculated soil; C), that the inoculation on average acidified the leaves by -3.7% pH units (P<0.0001). The responses in yield ranged from +25.2% to -9.2% (av.ge +3.5%; P = 0.03), but with average null responses in two centers and a significant response (+11%) in a third center. NIR-Tomoscopy scans (No. 574) were also performed on the leaves, and in addition, hay-litter-bags that had previously been buried in fields were dug up after two months, and 431 NIR- scans were acquired. The effect-size on the yield was expressed as the logarithm of the response ratio, i.e. the mean of the inoculated Symbiotic treatment divided by the mean of the non-inoculated Control for each pairwise comparison. A multiple regression model was developed to predict the symbiotic response to the treatment using six independent variables, including the squared litter-bag fingerprints, and an R2adj. level of 0.78 (P=0.01) was reached, with a standard error of ±4%. Validation in one external maize field, with a positive response to bio-fertilizers, demonstrates the juxtaposition of the estimated and accomplished yield. In a second experiment, with 40 pairwise comparisons, the two tested maize varieties did not respond to five types of bio-fertilizer, and the negative results were predicted at 84% (P 0.0012). The soil biota is a key factor for the application of appropriate microbial inoculants in the field, but the genotype/genotype interactions between the microbial strain (s) and the crop cultivar (s) require prior screening to obtain the desired results.

Evaluation of Anti-Aging Activity of the Biofield Energy Treated Novel Test Formulation Using SIRT1 and Telomerase Activity in in Vitro Model

Telomerase and SIRT1 (member of the sirtuin protein family) along with the lifestyle and diet are the major determinants of aging and its associated diseases such as cancer and cardiovascular disorders. The study objective was to investigate the effect of Consciousness Energy Healing based novel test formulation in pre-adipocytes (3T3-L1) and human peripheral blood mononuclear cells (PBMCs) for anti-aging activity using SIRT1 and telomerase assay. The test formulation was divided into two parts. One portion was denoted as the untreated test item without any Biofield Energy Treatment, while the other portion was defined as the Biofield Energy Healing Treatment, which received the Biofield Energy Healing Treatment by a renowned Biofield Energy Healer, Mahendra Kumar Trivedi. The cell viability using MTT assay showed that the cell viability of 3T3-L1 and PBMCs cells was more than 70% indicating a safe and nontoxic profile. The experimental data in PBMCs cells showed that the Biofield Energy Treated Test formulation showed a significant improved telomerase activity by 39.25%, 20.86%, and 17.95% at concentrations 0.01, 5, and 100 µg/mL, respectively as compared with the untreated test formulation group. These results indicate that the Biofield Energy Healing Treatment would be the significant approach to prevent aging-related disorders such as decline cardiovascular diseases, osteoporosis, dementia, osteoarthritis, Alzheimer’s, hypertension, cancer, Parkinson's Disease, Chronic Obstructive Pulmonary Disease (COPD), Stress, Asthma, cataract, age-related macular degeneration (AMD), hearing loss and metabolic disorders.

Genetic-Mathematical Modelling of Mutational Processes in a Population

Processes of genetic-mathematical modeling of a population development are considered. A basic distinction in the mathematical description of a family tree and a population is shown. In a family tree alternation of generations has discrete character. In a population there is a continuous alternation of generations. The method of the differential equations is applied for the description of a population. It is shown that mutational process in a population can be described with use of a Green’s function. For radiating influence on a population the universal evolutionary law is found.

Enhanced Healing and Bone re-Modelling by Low-Level Laser Therapy for Rapid Pain Control in Pediatric Fractures

Objective The current clinical case series assess the clinical outcome of the use of low-level laser in the treatment of painful pediatric fractures not solidly consolidated and re-modelled after casting for a standard of 4-6 weeks Materials and Methods The patient cohort consisted of 17 consecutive unselected patients in pediatric age group with delayed fracture consolidation and/or undesirable angulation despite casting for a standard period of 4-6 weeks in whom the parents refused any surgical intervention and/or bone grafting options. All subjects were referred from other medical centers after inadequate healing of the fracture ends upon repeating the x ray after the cast was off at the 4-6 weeks mark. Low-level laser therapy (LLLT) on alternate days for 8weeks in upper limb fracture cases, and 12 weeks in lower limb fracture cases were administered with a view of enhancing bone healing and/or re-modelling since both previous clinical and basic science studies on LLLT showed a stimulatory effect on fracture healing. Results All patients had solid union, mean time for union for upper and lower limb fractures were 6 and 10 weeks respectively. The calculated p value is statistically significant at p < 0.05. No patient defaulted follow up. All parents were satisfied with the clinical and radiological result of the LLLT treatment. Conclusion LLLT was found not only to enhance bone healing potential but in fact improved bone re-modelling when used in the proper wavelength and energy density in pediatric upper and lower limbs fractures, thereby also rapidly resolve the intolerable pain in paediatric fracture population

Chest Wall Prostheses for Pectus Excavatum and Poland Syndrome Using 3D-Printed Models: Technique and Outcomes After 25 Years' Experience

Background: Chest wall deformities may be managed with skeletal manipulation, which risks life-threatening complications. Custom-made prostheses are a less invasive surgical option, manufactured from silicone elastomer using 3D computed tomographic reconstruction and 3D-printed thoracic models. Methods: All patients undergoing custom-made implants between January 2010 and March 2017 were identified from the prosthetic department records. A retrospective review of the clinical records was performed. Mean follow up period was 1.8 years. A comparison was made with our earlier results from 1995 to 2009. Results: Twenty-six patients underwent insertion of custom-made implants for chest wall deformity. Pectus excavatum was present in 50% (n=13), and Poland syndrome 42% (n=11). All 11 female patients underwent 3D reconstruction and 3D printed models, and 3 of 15 males. Four underwent simultaneous bilateral breast augmentation, and three had staged breast augmentation. Seroma occurred in 27% (n=7), and hypertrophic scar in 12% (n=3). The reoperation rate was 23% (n=6), including autologous fat graft in two patients. Surgical suction drains were used in 42% (n=11) patients, of whom 36% (n=4) developed seroma, compared with 17% (n=2) of those without drains (p=0.08). Conclusions: Custom-made prostheses are an effective and safe option for patients with chest wall deformities. The majority have a short postoperative inpatient stay (81%) and are satisfied with the outcome (77%). Seroma was the commonest complication (27%), and drains did not reduce seroma risk. Single dose intravenous antibiotic prophylaxis is adequate. A minority of patients opt for further aesthetic procedures.

Retinal and Cortical Contributions to Excessive V1 Neuron Firing Rate Variability in Schizophrenia: A Computational Modeling Analysis

Excessive variability in behavioral performance and neuronal activation is a common finding in studies of schizophrenia. Recent evidence suggests that this may be due to an imbalance in the ratio of excitation to inhibition in brain function, or E/I imbalance. We used computational modeling of visual system activity to determine whether different potential causes of E/I imbalance would generate effects resembling those reported in schizophrenia. Three major findings emerged. First, reductions in retinal and lateral geniculate nucleus signaling initially led to increases in firing rate variability within the context of reduced V1 activation; however, with prolonged adaptation to weakened sensory signaling, compensatory hyper-activation in V1 neurons occurred, but variability was no longer increased. Second, direct increases in V1 excitation, or decreases in inhibition, led to the highest levels of initial activation but not variability; however, with prolonged inhibitory adaptation to increased excitation, overall activity was no longer elevated, but an increase in firing rate variability was observed. Third, the greatest fluctuation in firing rate variability, in response to the same stimulus across increasing contrast levels, was observed with reductions in sensory signaling, but only immediately after model perturbations; with prolonged adaption, the largest fluctuations were associated with increased excitation or reduced inhibition within V1. Implication of these findings are that schizophrenia-related increases in neuronal response variability may arise from at least two sources: 1) weakened sensory signaling and its associated low signal-to-noise ratio; and 2) compensatory but incomplete inhibitory responses to continuous increases in cortical excitation.

Modeling of Talent Acquisition for Organizational Development

In this work, we try to explain the concept of human talent with the help of some equations and models, which are not generated by any one previously. Here we also trying to explain ‘human talent is not resources it’s itself one of the great sources to find out all possible resources’. Because we cannot predict human talent directly, to judge it, we should have to adapt some methods for talent acquisition, which we explained with the help of models and equations. How human talent is one of the great source, if we want to know it, we have to observe human behavior, wits and intelligence strictly by working simultaneously with them. In this work our conclusion is ‘human talent natural and dynamic in nature’ and can be easily diverted to perform any task. Where as machine and technology has programmed memory, logics i.e. artificial intelligence (AI), and hence in result talent is fixed and constant in nature and only able to do repetitive and fixed task and also for proper handling and utilization of machines and technology need arises of human talent. In last only want to mentioned work is very useful in all HRM and OB practices.

Modeling of Dynamic/Situational Leadership for Effective Entrepreneurship Development

In this article we try to pay attention of readers, researchers and management executives how one can adapting situational leadership in another words dynamic leadership and enhance organization performance for goal attainment with high motivational leverages for effective team building and teamwork. We developed two models and explained how we should have to improve leadership qualities to lead business efficiently.

Insight into Management Issues modeling for Perfect Business Simulation

In this paper, I try to focus on widely growing field of Management Science; and that, “Modeling of Management Issues “. Now days Business Simulation techniques are used to earn more profit from Business and this is only issues control future course of actions properly. By using models we can predict & control future course of action & situation. Modeling is not a new subject. It’s oldest technique, but widely used in Physical Sciences, like Chemistry, Physics, Electronics, Engineering field, But it’s again become vital after some time in Life Sciences, like Botany, Zoology, Bio-Chemistry, Bio-Tech and Medical field problem modeling and now in current world it’s also become very vital in Information Technology and Management subjects. Here one question is always arise, why such a modeling is needed, and where and when needed, and answer of this simple question is, considering some simple problems like ‘ to find out the width of a river (But your are not allowed to cross it), find out the temperature (but you are not allowed to use thermometer), means try to find out any Quantity or parameter/variable without existence or entity of that, and if virtual situation satisfied by using modeling technique, we implement that virtual model for actual situation. In last I want to conclude modeling is the heart of any branch of Education, weather its science, Arts, Commerce, Medical, Information Technology, Engineering or Management and in summaries form I want to say this paper is nothing but one of the theoretical model, which is for modeling of Management issues for perfect Business Simulation.

A Multilevel Hazards Model for Child Mortality In Nigeria

Many researchers have devoted considerable attention to the impact of individual-level factors on child mortality, but little is known about how family and community characteristics affect health of children. Trend in child mortality as well as its determinants, has long been the subject of academic and policy debates. In spite of this, the problem of child mortality remains as daunting as ever. In fact, advancement in medical sciences and the upsurge in information and telecommunication technology equipment have not significantly reduced child mortality in the country, unlike in the West. The Multilevel proportional hazards model for data that are hierarchically clustered at three levels was applied to the study of covariates of child mortality in Nigeria. This study merges two parallel developments of statistical tools for data analysis: statistical methods known as hazard models that are used for analyzing event-duration data and statistical methods for analyzing hierarchically clustered data known as multilevel models. These developments have rarely been integrated in research practice and the formalization and estimation of models for hierarchically clustered survival data remain largely uncharted. The model was estimated using the Newton-Raphsons numerical search approach. The model accounts for hierarchical clustering with three random effects or frailty effects. We assume that the random effects are independent and follow the Exponential and Weibull distribution. The results indicate that bio-demographic factors are more important in infancy while socioeconomic factors and household and environmental conditions have a greater effect in childhood. Furthermore, there is significant variation in child mortality risks even after controlling for measured determinants of mortality. Also, factors that fall under family and community level are more significant indicating that child survival is most controlled or determined by family and community factors and variables at the child level is not weighty. This suggests that there may exits unobserved or unobservable factors related to mortality.

Flame Propagation Model and Combustion Phenomena: Observations, Characteristics, Investigations, Technical Indicators, and Mechanisms

Critical conditions are usually obtained for ignition in a self-heating solid system consisting of two components generating heat independently, one component being inexhaustible and the other exhaustible by either simple first order or autocatalytic reaction. Ignition depends upon whether the exhaustible component can cause a temperature rise in excess of the upper stationary, but unstable, value possible for the inexhaustible component reacting alone. The system provides a theoretical model for some commonly occurring examples of self-heating and ignition in porous solids containing oxidisable oils. It is shown that: (a) the ignition criterion of the model, which involves a nonarbitrary critical temperature increase, has a high degree of physical reality; (b) the model is, in principle, capable of predicting ignition from primary kinetic and thermal data; (c) it is likely to be possible often to make a reliable prediction of critical size for self-ignition in a two-component system at ordinary atmospheric temperatures by a simple extrapolation from small-scale ignition data, obtained at higher temperatures, in the same way as for ignition due to a single reaction. Examination of both adiabatic and non-adiabatic flame theories showed that a 'steady state' exists only under the special condition that a heat sink exists at the initial temperature. For the general case of freely propagating, non-adiabatic flames only a quasi-steady state can be achieved.

Reproductive Performance and Factors Influencing Fetal Outcome: A Practical Guide to Experiments on Lung Development in A Nitro Fen-Induced Rat Model for Congenital Diaphragmatic Hernia

Our study aims to help researchers calculate resources based on a rat breeding colony for experiments on fetal lung development. The Wistar rat is commonly used in experimental research. In the context of fetal lung studies, the nitrofen rat is a model for pulmonary hypoplasia and congenital diaphragmatic hernia. Data needed to calculate resources for new experiments are not easily available. We prospectively acquired data on the reproductive performance and fetal outcome of 314 consecutive virgin Wistar dams in our fetal lung research breeding colony. We define the impact of breeding conditions on rat fertility and evaluate different methods to diagnose early rat gestation. Effects of nitrofen exposure as well as fetal surgery in terms of prenatal mortality and gross anatomical parameters of lung development are quantified in nitrofen-exposed and -unexposed fetuses from embryonic day 19 to 21 in 12h intervals. A reduced mating interval (1h) provides a great degree of experimental control with feasible pregnancy rates and a large litter size. Nitrofen exposure, as well as fetal surgery, depict high fetal survival rates. Fetal lung findings were very reproducible and could allow for reduction of animals utilized within experimental groups.

Modelling Development in Plant Anatomy

Four rules for good anatomical modeling of plants are explored. First, the cell is the reference source for modelling at any level. Second, developmental signaling occurs between few cells, about 12. Third, rules of are algorithmic and not simply physical forces as proposed by Thompson. Finally, it is desirable to proposed a likely alternative model that can be discounted. The main value of modelling is selecting data for modelling rather than the by a biased investigator.

Post Abortion Contraception Model: A Comprehensive Package for Improving Safe Abortion Care in Developing Countries

Background: Despite liberal abortion laws and wide availability of contraceptives in Ghana, declining Post Abortion Contraception remains a public health challenge due to early unplanned pregnancies and recurrent abortions. The development of this model was therefore to address challenges of low contraception following induced abortion in health facilities within the capital city of Ghana. Method: The development of this model was an outcome of a nested study title: ‘decision making for induced abortion in Accra metropolis, Ghana’ in 2014. This model was piloted for four years using Marie Stopes, Ipas and Ghana Health Service trained abortion providers with family planning skills in one hundred purposively selected health facilities comprising 90 private and 10 Non-Governmental Organization mandated by law to provide safe abortion care services in the capital city of Ghana. The model mainly focused on contraceptive products, pricing, placement, promotion and people. Results: There was an increase (90% average) in Post Abortion Contraception across the selected facilities following the intervention using the model. Conclusion: The study concludes that an integration of products, pricing, placement, promotion and people with options counselling prior to an induced abortion are key considerations for an improved post abortion contraception uptake in developing countries.

Acute and Chronic Wound Fluid Inversely Influence Wound Healing in an in-Vitro 3D Wound Model

If a wound progressively heals or the healing process is impaired is basically influenced by the surrounding milieu. This is reflected by the wound fluid. Its specific composition triggers the migration, proliferation and differentiation of dermal and epidermal cells which so far was not sufficiently examined in 2D cell culture models. The influence of the different wound entities was analyzed on a newly implemented three dimensional in-vitro model, which improved the transferability to the in-vivo situation. The influence of pooled wound fluids from patients suffering from acute or chronic wounds were investigated within a time period of 10 days after wound application. Histological and immunohistochemical analyses were performed addressing the impact of AWF and CWF on regeneration, such as cell proliferation, fibroblast activity and cell migration. AWF slightly stimulated fibroblast migration while CWF inhibited their activation and migration. The CXCR4- immunopositive population was continuously decreased compared to the control and AWF treatment. The expression of FAP was enhanced under AWF and medium. In keratinocytes CWF massively stimulated cell proliferation initiating on day six after injury. The presence of 10% CWF inhibited fibroblast activation and migration and induced the degradation of the collagen matrix. Keratinocytes were stimulated to proliferate, resulting in healing inhibiting hyperplasia. Transferred to human wounds, no effective wound closure would be achieved because of the de-regulation of pro-proliferative and migration-stimulating factors and a degraded extracellular matrix. This newly implemented 3D study model represents a novel appropriate in-vitro system for studying healing mechanisms and potential therapeutic applications.

A Model for Identifying Actionable Findings on Computed Tomography in Crohn’s Disease Patients in the Emergency Department

Patients with inflammatory bowel disease (IBD) frequently visit the emergency department (ED). The use of cputed tomography (CT) scans in this population has drastically increased in recent years and may confer an increased risk of malignancy. Records were obtained for IBD patients aged 18 or older who visited our institutional ED with a gastrointestinal chief complaint and who had a CT scan ordered by an ED physician. A predictive model for identifying a clinically actionable finding (CAF) on CT scan was created using logistic regression carried out on a predetermined set of variables. Data were available on 156 Crohn’s disease (CD) patients contributing 350 visits and 63 ulcerative colitis (UC) patients contributing 114 total visits. CAF was identified at 108/350 (30.9%) of visits in CD patients and 33/114 (29.0%) of visits in UC patients. History of CAF (OR 11.6, CI 4.54-29.6) and a platelet count above 400,000/mL (OR 3.42, CI 1.56-7.50) were the strongest predictors of CAF. History of psychiatric illness (OR 0.67, CI 0.35-1.29) and diarrhea (OR .043, CI 0.23-0.83) were associated with a lower likelihood of CAF. A prediction model was created that was able to detect 94.4% of CAF cases while correctly predicting CAF non-cases 35% of the time. This model holds promise as a tool to reduce imaging in this population.

A Role for in Vitro Disease Models in the Landscape of Preclinical Cardiotoxicity and Safety Testing

Drug-induced cardiotoxicity is one of the predominant reasons for drug attrition and withdrawals. This is of critical concern when potentially cardiotoxic drugs are administered to individuals with inherited arrhythmogenic cardiac diseases or with metabolic diseases such as obesity and diabetes, which are key risk factors for cardiovascular diseases. Pathophysiological alteration prevalent under such conditions can alter or exacerbate cardiotoxic responses. The growing incidence of obesity, diabetes and metabolic syndrome subject a significant percentage of the population to drug treatments, thereby augmenting their risk for drug-induced cardiovascular toxicity. Hence, screening for drug-induced cardiotoxicity early in the preclinical stages of drug development, by using appropriate human disease models, can be effective in ensuring safety in clinical trials and preventing late stage and post-marketing drug withdrawals owing to cardiotoxicity. The advent of human pluripotent stem cells (hPSC) and induced pluripotent stem cell (iPSC)-derived cardiomyocytes are revolutionizing safety/toxicity screening in human cells by providing relevant human-specific, renewable model systems to explore human drug toxicity. The ability to generate patient-specific iPSCs that can model cardiac diseases, now offers a valuable option that can further improve drug safety assessments and enable a more accurate prediction of toxicity that occurs in the representative population that are prescribed the drugs. Use of appropriate disease models will not only provide cost savings by decreasing potential drug attrition and withdrawals, seen with many drugs, but will also be a promising option to advance precision medicine

Analyzing Students’ Opinions about their Learning Environments and Study Approaches with Bayesian Modeling

Our own long term experiences as clinical teachers among undergraduate medical students have generated the interest to investigate the plausible connection between students’ study orientation and their learning experiences in small groups.The objective of the study was to assess the hypothesis whether learning in small groups may contribute to study motivation. Participants were 52 undergraduate medical students (10-12 in each group) in the primary health care course between 1st and 5th year during the spring term 2012. The questionnaires used were the Inventory of General studies (IGSO) for study orientation and IQ questionnaire for group learning. The data were analyzed by Bayesian network modeling. In this study, the application used was the Bayminer (www.BayMiner.com) non-linear visualization modeling software. Positive atmosphere in a small group increases study motivation and commitment and predicts mutual trust and gives space to new ideas, where contradictive views can raise interesting discussions. Based on Bayesian modeling it seems that the experience of motivational problems in the present studies may be an indicator of study alienation and connected with the perception of small group dysfunctionality.

Transiently Raised IOP Equivalent to That Experienced During Ocular Surgery Causes Moderate Inflammation but does not Affect Retinal Function or Result in Retinal Ganglion Cell Loss in An Animal Model

Purpose: High intraocular pressure (IOP) is known to result in retinal ganglion cell (RGC) loss, both with chronically raised intraocular pressure (such as with glaucoma) and with acute raises in pressure (due to injury or acute angle closure). Because IOP is often raised during ocular surgery, the purpose of this study was to evaluate the effect of transient moderate IOP on retinal function, RGC survival and the expression of Connexin 43 (Cx43) and glial fibrillary acidic protein (GFAP), ubiquitously expressed central nervous system (CNS) proteins that are known to be elevated during the retinal inflammatory response to injury. Materials and Methods: Wistar rats were exposed to transient IOP at 40 mmHg for 5 or 30 minutes, and 60 mmHg for 5 minutes (via cannulation of the anterior chamber with a saline reservoir raised to a height corresponding to the desired IOP), mimicking potential IOP rises during surgery such as DSAEK and some laser procedures (LASIK and femtosecond laser cataract surgery). Separate groups of animals had IOP maintained at 10 mmHg for 5 or 30 minutes as cannulation controls, or 120 mmHg for 60 minutes as positive controls. Changes in the optic nerve and retina were assessed immunohistochemically for GFAP and Cx43 expression. Retinal function was assessed using electroretinography (ERG) recorded at baseline and 14 days after the IOP rise and compared with RGC counts. Results: Results showed that there was a differential GFAP labelling pattern observed in the anterior optic nerve in the 40 mmHg 30 minute and 60 mmHg 5 minute groups 4 hours after manipulation. Gap junction protein Cx43 was minimally up-regulated in the retina in the short-term. There was, however, minimal long-term effect on retinal function and no RGC loss. Conclusions: n conclusion, elevations of IOP that are short in duration such as those occurring during surgical procedures, do not cause significant changes long-term in retinal function or RGC survival. Key Messages: Cx43 and GFAP are known to be elevated during the retinal inflammatory response to injury. No previous study has explored the effect of moderate and relatively short increases in IOP on the initial inflammatory response. We observed a mild glial inflammatory response in the anterior optic nerve, but only a minimal up-regulation of Cx43. However, transient and moderate IOP rises did not induce long term disruption to RGC function or number as measured by electrophysiology and RGC counts, respectively. This is applicable to clinical practice, as it means the IOP elevations that occur during some surgical procedures are unlikely to be causing long term damage in retinal function or RGC survival.

Biopsychosocial Path Model of Self-Management and Quality of Life in Patients with type 2 Diabetes

Objectives: The present study investigated biopsychosocial predictors (HbA1c, self-efficacy, and social support) of self-management and health-related quality of life among patients with type 2 diabetes. Methods: 160 adults referred to the Iranian Diabetes Society participated in this study. Participants completed General Self-Efficacy Scale, Perceived Social Support, Diabetic Self-care Behaviors scale, and D-39 (diabetics’ quality of life). Results: Data were analyzed with SPSS-19 and Lisrel 8.8, utilizing statistical path analysis. Results revealed significant positive correlations between self-efficacy and social support subscales, self-care and health-related quality of life. Also, HbA1c had not correlation with HRQOL. The final path model fitted well and showed that direct self-care paths with (β = 0.24) and indirect social support with (β = 0.32) had the most effects on health-related quality of life. Conclusions: The results confirmed the theoretical model and scientific evidence for providing psychological solution to promote quality of life in patients with type 2 Diabetes.

Dietary Advice on Prescription (DAP). A Pedagogical Model for Better Dietary Habits Tested in a Two-Year Randomized Clinical Trial. 

There Is A Gap Between What We Know And What We Do, Such As Knowing What We Should Eat And What We Actually Eat, A So-Called “Attitude/Behavior Gap”. It Is Not Necessary To Go From A Change In Attitude To A Change In Behavior. It Is Possible To Do The Opposite; In Other Words, It Is Possible To Go From A Change In Behavior To A Change In Attitude. The Objective Of This Paper Is To Describe And Explain The Concept Of Dietary Advice On Prescription (DAP) And Present The Reasons And Evidences For The DAP Messages. Dietary Advice On Prescription (DAP) Starts With Discussing Behaviors Related To Dietary Habits And Then Goes From Behaviors Towards Attitudes. DAP Is A Theory-Based Pedagogical Model That Deals With Behaviors Related To Why, How And When We Eat, Rather Then What We Eat. The DAP Model Is A Method That Quickly Leads The Client Onto A Track That Yields Autonomy, Respects The Client’s Integrity, Gives Confirmation, Emphasizes The Delight And Pleasure Of Eating, Stimulates Discussions And Gives The Client The Initiative In These Discussions. In A Clinical Situation, The Counsellor Lays Out The DAP Postcards On A Table And The Client Picks One Card (Or Several) That Feels Relevant And Interesting For The Client To Discuss. Together They Make An Agenda For The Discussion Such As, For Instance, In What Order To Discuss The DAP Postcards. The Counsellor Asks In An Open Manner With A Motivational Interview (MI) Spirit Why The Client Has Chosen The Particular Card(S). The Client Explains, Elaborates, Turns And Twist About The Choices He/She Has Made. The Results Of The First Published Qualitative Study Of This Two-Year Randomized Controlled Trial Demonstrate That The Participants Found The Concept Valuable.

The Use of Predictive Markers for the Development of a Model to Predict Lowest Quartile Weight Loss following Roux-en-Y Gastric Bypass.

Introduction: The Roux-en-Y Gastric Bypass (RYGB) has been one of the most popular surgeries in the USA for years. While many models have been made to investigate the factors that affect weight loss, these factors are still highly debated. Objective: To create a model that predict performance of RYGB patients. Methods: 110 out of 344 patients who received a RYGB at a single institution between Jan 2010 and April 2014 were included in this study. Data was collected retrospectively. Patients were included if they had greater than 1 year follow up with at least three follow up points and could be modeled with r2>0.95. All patients were one year beyond surgery, while 40 were completely lost to follow up, 104 at 1 month, 138 at 3 months, 188 at 6 months, and 225 at one year. 9 patients were not included because they did not meet the criteria of the study. Patients were divided into quartiles based on percentage excess weight loss (%EWL) at one year. Multivariate analysis was performed to determine the significant factors that influence patients being in the first quartile of weight loss (17-60% %EWL). Results: Only males with a Body Mass Index (BMI) above 44 and females with a BMI above 64 were found to be predictive of patients being in the first quartile. Our model has Positive and Negative predictor values of 66% and 80% respectively with sensitivity and specificity of 29% and 95% respectively. Conclusions: An model to predict %EWL was created, only gender and pre-operative BMI were found to be significant factors. In general females have better outcomes with higher BMI’s than do males. This information should be discussed with patients when deciding a procedure. However, more studies are needed for validation of these results.

COLLAGE 360: A Model of Person-Centered Care to Promote Health Among Older Adults

This article describes COLLAGE 360, a person‑centered care model for older adults that integrates comprehensive assessment, goal‑setting, and coordinated community services. The approach seeks to promote health and function while reducing fragmentation across medical and social supports. Early implementation experience outlines feasibility and pathways to measure outcomes and scale within aging networks.

Biocompatible Scaffolds for Human-Induced Pluripotent Stem Cell Transplantation and Modeling Post-Stroke Recovery in Three-Dimensional Neural Cell Culture

Human-induced pluripotent stem cells (HiPSCs) demonstrate promise in their ability to differentiate into neural cells and ultimately replace the cell types and thereby brain tissue damaged by stroke. This may diminish cognitive impairment due to stroke. Prior to transplantation, an appropriate scaffold must be determined to allow for heightened accuracy by facilitating proper adhesion, differentiation, and proliferation, increasing the likelihood of success, as will be defined in this review, in vivo. This paper aims to provide a review of available biocompatible scaffolds and their efficacy, to provide insight for future research utilizing clinical trials to study stem cell therapy as a form of post-stroke recovery. A systematic review of scaffolds outlined in full-text, peer-reviewed articles with unique experimental data, available on PubMed, will be conducted to determine an ideal scaffold, based on article and scaffold selection criteria best suited for the transplantation of human-induced pluripotent stem cells.

Reasons for the Low Male Involvement in Routine Child Immunization in Hoima District Uganda using the Attitude, Social Influence and Self Efficacy Model

Millions of children continue to miss immunizations each year despite global increases in financing and advances in vaccine technology. Male involvement in routine child immunization activities could improve and sustain coverage but is rarely emphasized in immunization programs or research. This study identified factors associated with male involvement in routine child immunization using the attitude, social influence and self-efficacy model.A household cluster survey was conducted among 460 fathers aged 18 years or more, with children aged 10-23 months. A semi-structured interviewer-administered questionnaire was used to collect data. Prevalence Risk Ratios (PRRs) were used to measure associations with level of involvement using generalized linear models with Poisson family, log link and robust standard errors in STATA 12. Our findings show that half (51%, 236/460) of the respondents were aged 25-34 years; 36% (166/460) had completed eight or more years of formal education. Although90% (415/460) of the respondents were willing to be involved, only 29% (133/460) were highly involved in routine child immunization. Highly involved fathers had a positive attitude towards involvement in routine child immunization (adj. PRR 2.3, 95% CI 1.18 – 4.98) and were ≥45 years adjusted prevalence risk ratio (adj. PRR) 2.0, 95% confidence interval (CI) 1.15 - 3.76. Traders had a lower involvement compared to those engaged in other occupations (adj. PRR 0.55, 95% CI: 0.37 - 0.82). In conclusion, few fathers were involved in routine child immunization. Strategies to improve fathers’ positive attitude such as health education are needed to increase their involvement, specifically targeting younger fathers and traders.

A High Volume, User-Friendly Immunization Clinic in Vellore, India: A Model for Urban Hospitals

The Expanded Program on Immunization (EPI) in India delivers vaccines under its policy, through government hospitals, health centers and outreach clinics. However, the national average full immunization coverage is stagnating at about 70%. The days and times of clinics are not always convenient for mothers working at home or employed outside. Moreover, vaccines not under EPI, but recommended by the Indian Academy of Pediatrics (IAP), are unavailable there, forcing mothers to go to private sector immunization clinics to get them. Recognizing the local need for user-friendly immunization clinic, we designed one in the Department of Child Health. The impetus came from local demand by a civil society organization (Rotary Club of Vellore). Our immunization clinic is open every working day (8.30 am to 4.00 pm) offering both groups of vaccines. Its success is illustrated by the fact that over 7000 children per month receive immunization in this clinic. We describe its design and operation so that this model may be replicated in other urban hospitals with pediatric sections.

Early Glycine Supplementation Re-Establishes Adrenal Catecholamine Secretion in Hypothalamic Obesity Model in Rats but does not Affect Visceral Adiposity.

Obesity is a worldwide epidemic that features a multifactorial syndrome characterized by a chronic positive energetic unbalance. Neonatal administration of monosodium L-glutamate (MSG) causes lesion on the arcuate nucleus of hypothalamus that led to development of obesity in the adult life in rodents characterized by a notorious accumulation of catecholamine in the adrenal medulla. The amino acid glycine induces catecholamine secretion of adrenal medulla. Thus, the objective of our work was to evaluate the possible effects of glycine administration in the MSG-obesity model in rats and investigate its impact on adrenal catecholamine medulla homeostasis. Male Wistar rats received MSG solution (4mg/g body weight) subcutaneously in the cervical area for 5 days after delivery, controls received saline solution. Animals were also divided in two groups, in which one received tap water added with glycine (0.1g/Kg) after weaning on 21st day until 90 days of life.Biometrical variables, visceral fat pads weight, total content and basal secretion of adrenal cathecolamine were evaluated. Glycine increased Lee index of all tested groups and had no effect on visceral adiposity. However, glycine treatment completely reestablished catecholamine total content and basal secretion of MSG-obese group. In conclusion, although glycine treatment apparently completely reestablishes catecholamine secretion homeostasis it is not sufficient to significant directly reduce visceral adiposity in MSG obesity model in rats.

Laryngeal Tissue Engineering using Rabbit Adipose Derived Stem Cells in Fibrin: A Pre-Clinical Model

Vocal fold scarring is a clinical problem without reliable treatment. Tissue engineering of a vocal fold replacement is an exciting potential treatment for vocal fold scars that involve multiple layers of the vocal fold. Human adipose-derived stem cells (ASC) were previously used to produce a promising vocal fold cover layer replacement. However, relevant in vivo studies are needed before human application, and implanting the human cells in animal larynges would introduce significant risk and data confounding. We therefore report here the development of a construct based on rabbit ASC with the potential for use in pre-clinical implantation studies. Rabbit ASC were isolated and cultured in a three-dimensional fibrin matrix to create an implantable construct resembling the vocal fold mucosa. Key differences between the human cell and the rabbit cell models are highlighted.

Development of a Model-Based Noninvasive Glucose Monitoring Device for Non-Insulin Dependent People

Continuous-time glucose monitoring (CGM) effectively improves glucose control, as oppose to infrequent glucose measurements (i.e. using Lancet Meters), by providing frequent blood glucose concentration (BGC) to better associate this variation with changes in behavior. Currently, the most widely used CGM devices rely on a sensor that is inserted invasively under the skin. Because of the invasive nature and also the replacement cost of sensors, the primary users of current CGM devices are insulin dependent people (type 1 and some type 2 diabetics). Most non-insulin dependent diabetics use only lancet glucose measurements. The ultimate goal of this research is the development of CGM technology that overcomes these limitations (i.e. invasive sensors and their cost) in an effort to increase CGM applications among non-insulin dependent people. To meet this objective, this preliminary work has developed a methodology to mathematically infer BGC from measurements of non-invasive input variables which can be thought of as a “virtual” or “soft” sensor approach. In this work virtual sensors are developed and evaluated on 20 subjects using four BGC measurements per day and eight input variables representing meals, activity, stress, and clock time. Up to four weeks of data are collected for each subject. One evaluation consists of 3 days of training and up to 25 days of testing data. The second one consists of one week of training, one week of validation, and 2 weeks of testing data. The third one consists two weeks of training, one week of validation and one week of testing data. Model acceptability is determined on an individual basis based on the fitted correlation to CGM testing data. For 3 day, 1 week, and 2 weeks training studies, 35%, 55% and 65% of the subjects, respectively, met the Acceptability Criteria that we established based on the concept of usefulness.

The Risk Factors, Complications, Management Strategies and Predictors of Morbidity & Mortality Among Pediatric Patients Presenting with Severe Diarrhea at Muhimbili National Hospital’s Emergency Medicine Department

Background Acute diarrhea is the major cause of health public problem among paediatric patients in Tanzania. And in Low income countries (LICs), studies have shown, Acute watery Diarrhea (AWD) is the cause of morbidity and mortality which can be prevented by immediate identification and treatment of complications. Methods A prospective cohort study was done between December 2021 and April 2022 to determine the risks, complications, management strategies and predictors of mortality among paediatric patients ≤12 years of age with severe diarrhea. We excluded those who arrived in cardiac arrest at the Emergency Medicine Department (EMD) of Muhimbili National Hospital (MNH). Proportion was used to summarize the counts and frequency of participants who were at risk of complications and management strategies given and for predictors of outcomes. A Modified Poisson log linear model with a robust estimation test was used to test for significant associations between predictors and outcomes. Multivariate logistic regression was used to adjust for confounders. Results A total 6,570 paediatric patients presented to EMD during study period, and we recruited 144 (2.2%). The median age was 1 (IQR 0.7-2.0) years and most were male 86 (59.7%). Among the study participants with diarrhea, 120 (83.3%) had dehydration, acidosis 60 (42.3%), hypoglycemia 8 (5.6%), hypokalemia 76 (53.1%), and Acute renal failure 11 (7.6%). Those patients with complications received appropriate management, including IV crystalloid solution given to 131 (90.97%), and correction of acidosis 60 (42.3%), hypoglycemia correction with IV dextrose 10% 6 (4.2%), and hypokalemia and infections were corrected with IV potassium chloride 52 (36.1%) and IV antibiotic treatment 84 (58.3%) respectively. Conclusion Pediatric patients under 2 years of age are at high risk of severe diarrhea with dehydration as compared to other ages. Early referral and availability of point care tests are essential in early recognition of accompanied complications.

From Pelvis to Foot: A Functional Approach to Preventing Ankle Sprains in Athletes

Background Ankle sprains are among the most common injuries in sports, often characterized by high recurrence rates despite appropriate local treatment. Traditional approaches primarily focus on the injured joint, with limited attention to proximal biomechanical factors that may predispose athletes to injury. Objective To propose a functional, longitudinal kinetic chain model in which sacroiliac joint dysfunction may act as a predisposing factor for ankle sprain/strain injuries in athletes. Methods This paper presents a clinical hypothesis based on biomechanical reasoning and observational findings. The proposed model describes how sacroiliac joint dysfunction, particularly posterior innominate rotation (PI), may lead to pelvic obliquity and functional leg length discrepancy. These changes may induce compensatory femoral external rotation and foot toe-out, altering ground contact mechanics during gait and running. Results (Hypothesis) The altered alignment and loading pattern may increase the vertical impact force and modify the ground reaction vector on the functionally shorter limb, resulting in reduced mechanical stability at the ankle during heel strike or foot contact. Over time, this may increase susceptibility to inversion or eversion injuries, manifesting clinically as recurrent sprain/strain. Conclusion Ankle sprains in athletes may, in some cases, represent the distal expression of a proximal biomechanical imbalance. Incorporating assessment of the sacroiliac joint and the longitudinal kinetic chain into routine clinical evaluation may improve injury risk identification and contribute to more effective prevention strategies. Further research is needed to investigate this proposed relationship.

Activation of Transcription Factor EB Protects Against Proinflammatory Insults Through NF-κB Inhibition in Keratinocytes

Keratinocytes are pivotal in mediating cutaneous inflammation. Identifying anti-inflammatory factors within these cells holds promise for developing novel therapeutic strategies to manage skin inflammation. Transcription factor EB (TFEB) has recently emerged as a key regulator linking cellular energy metabolism to inflammatory processes, primarily through its influence on autophagy and NF-κB signaling. However, whether TFEB activation exerts anti-inflammatory effects in keratinocytes remains unclear. In vitro inflammation model was established in HaCat cells by incubation with proinflammatory mediators LPS and IL-1β. Cell viability and TFEB expression and phosphorylation were measured. The effect of TFEB activation by C1 and adenoviral TFEB overexpression on the expression of proinflammatory genes including COX-2, MCP-1 and IL-6 were detected. Also, IκBα protein level were determined. TFEB phosphorylation is increased while TFEB total protein expression is inhibited by treatment with LPS and IL-1β. Pharmacological activation of TFEB by compound C1 and TFEB overexpression suppressed the expression of COX-2, MCP-1 and TNF-α induced by LPS and IL-1β. TFEB overexpression increased basal IκBα expression and restored IκBα level under LPS treatment. TFEB knockdown reduced TFEB expression and lowered basal expression level of COX-2, MCP-1 and TNF-α. Our findings indicate that TFEB activation can mitigate inflammatory gene expression in keratinocytes triggered by LPS and IL-1β. This implicates TFEB as a significant novel modulator of cutaneous inflammation, highlighting its potential as a therapeutic target. Targeting TFEB could thus be a viable strategy for developing new treatments for chronic inflammatory skin conditions.

Interactions Between Natural Nuclear Reactors and Microbial Evolutionary Processes

The impact of ionizing radiation on genetic change is well established, yet the extent to which naturally occurring radiation fields have influenced evolutionary trajectories remains incompletely understood. This study examined correlations between microbial evolution and the radiation and geochemical environments associated with natural fission reactors, with emphasis on the Oklo–Bangombé system in present-day Gabon, Africa. The current paper compares plausible doserate regimes adjacent to reactor zones with published observations of radiationinduced phenotypes, geneexpression changes, and repair strategies in model organisms and complex biotas. This study further considers indirect mechanisms (e.g., water radiolysis, redox restructuring, tracemetal mobilization) by which natural reactors could have modulated ecological selection pressures over long timescales. The synthesis supports the plausibility of three interacting pathways: (i) increased mutation supply under low, chronic dose rates; (ii) selection in oxidantrich, redoxstratified niches; and (iii) metabolic subsidies (e.g., H₂) from radiolysis that support chemotrophic guilds. Although temporal–spatial associations exist between reactor activity and biological innovations preserved in Paleoproterozoic strata of Gabon, current evidence remains correlational rather than demonstrably causal. The study further outlines testable predictions and experimental designs capable of discriminating among these mechanisms.

A Decision Tree Ensemble Approach to Diabetes Prediction using the Framingham Heart Dataset, Exploring the Role of AI-Associated Interventions in Reducing Diabetes-Related Adverse Outcomes Between Men and Women

Objective Diabetes poses significant public health challenges, with many individuals remaining undiagnosed and at risk of complications. This study aimed to evaluate the performance of decision tree ensemble methods for predicting diabetes onset using the Framingham Heart Study Teaching Dataset and to explore sex-specific risk patterns relevant to AI-driven interventions. Methods We analyzed data from 11,627 participants, incorporating demographics, vital signs, smoking status, medication use, and laboratory measures. Random Forest classifiers were developed to predict diabetes incidence at approximately 6-year (Period 2) and 12-year (Period 3) follow-ups. Class imbalance was addressed using undersampling, oversampling, and the Synthetic Minority Over-sampling Technique (SMOTE). Results The models demonstrated robust performance, achieving an Area Under the Curve (AUC) of 0.856 in Period 2, and moderate predictive ability in Period 3 (AUC = 0.732 in males, 0.786 in females). Key predictors included glucose level, BMI, systolic blood pressure, age, and heart rate. Notably, differences emerged in predictive accuracy between men and women, suggesting potential sex-specific vulnerabilities that merit further study. Conclusion Machine learning approaches, particularly Random Forests, show promise for medium- and long-term diabetes risk prediction, supporting early identification and intervention efforts. Future work should focus on hyperparameter tuning and explainability techniques, such as SHapley Additive exPlanations (SHAP) values, to improve model precision, interpretability, and fairness. Equity-focused strategies remain critical to ensure AI-driven tools benefit diverse populations and do not exacerbate existing disparities in diabetes care.

How Intensive Short-Term Dynamic Psychotherapy Merges with Hypnotism and Solution- Focused Methods

Intensive Short-Term Dynamic Psychotherapy (ISTDP) has proven effective in over 120 outcome studies, particularly for anxiety, depression, and personality disorders. This conceptual paper proposes a theoretical integration of ISTDP with Solution- Focused Brief Therapy (SFBT) and clinical hypnosis. Each modality offers unique strengths—ISTDP enables rapid emotional processing, SFBT builds client resilience and solutions, and hypnosis enhances neuroplasticity and emotional receptivity. Drawing on existing empirical and neuroscientific literature, this paper synthesizes these modalities into a unified clinical framework. The integrated model emphasizes accelerated change through emotional access, strategic future orientation, and unconscious facilitation. Case examples illustrate the framework's practical applications across complex clinical presentations. The integration addresses gaps in single-modality treatments and provides a cost-effective, neurobiologically supported method of intervention. This article offers clinicians structured decision- making strategies and practical tools for real-time integration, while outlining future directions for empirical research.

Correlation of Fast Food Consumption and Overweight/Obesity among Undergraduate Students at the University of Hargeisa in Hargeisa, Somaliland

Background Fast food consumption is the major cause of obesity and overweight in worldwide affecting more than 2 billion people, especially developing countries and low income countries. It can lead to hyperinsulinemia and development of insulin resistance, high energy density, high glycemic index, and fatty acid composition of fast foods may increase the prevalence of obesity and cardiovascular risk factors Objectives The main aim of this study was, to assess fast food consumption and its association with overweight /obesity among undergraduate students of University Hargeisa, Somaliland, 2023. Methods The study was carried out from May 01 to July 20, 2023 at University of Hargeisa using an institutional based cross-sectional study design to among 260 students. The study participants were selected using a simple random sampling technique. A structured questionnaire was prepared based on review literatures and dig out from related studies. The anthropometric data was taken by data collectors to measure weight and height using a stadiometer. Data was entered and checked for errors using EPI-info version 7.1.5.0 and then, data were exported to statistical package for social sciences (SPSS) software version 21 and STATA software version 14 for data processing and analysis. Descriptive statistics such as; frequencies, means and proportion was used for present the findings. A variable with P-values of less than 0.25 in the binary logistic regression analysis was entered into a multivariable logistic regression analysis to identify the independent predictors of stunting. Finally, variable at P-value less than 0.05 in multivariable logistic regression analysis was considered as a statistically significant variable. Results In this study, the majority 235 (90.4%, CI: 86.5- 93.8) of the study participants were fast food consumers. The study revealed that, from the total study participants 46(17.7%),127(48.8%),84(32.3%), 3(1.2%) were underweight, normal, overweight and obese respectively. A chi-square test revealed that there was a significant (p-value=0.058) associations between BMI and fast food consumption among students of University of Hargeisa. On multi-variable logistic regression model educational level of the students (AOR = 12.45 (95% CI: 1.7, 14.6)) and frequency of fruit (AOR = 0.76, 95% CI (0.7, 0.8)) and vegetable consumptions (AOR = 0.51, 95% CI (0.47, 0.575)) were found to be significantly associated with fast food consumptions (p < 0.05). Conclusion In this study, of the total 90.4% number of fast food consumers. A chi-square test revealed that there was a significant (p-value=0.058) associations between BMI and fast food consumption among students of University of Hargeisa. Educational level of the students and frequency of fruit and vegetable consumptions were found to be significantly associated with fast food consumptions. Effort should be made to increase access to fast food-related information and counseling.

Exploring the Mechanism of Complex Lemon-Angelica Sinensis-Boswellia Essential Oil on Anxiety Disorders with Melasma Through Network Pharmacology and Experimental Validation

The incidence rate of melasma is notably high among patients with anxiety disorders. Aromatherapy primarily influences the physiological and psychological states of individuals through the inhalation or application of essential oils, thereby facilitating the treatment or alleviation of various conditions. This study aims to explore the action mechanism of complex lemon-angelica sinensis -boswellia essential oil (CEO) in treating anxiety disorders with melasma. We investigated the active ingredients, targets, and pathways of CEO in relation to anxiety and melasma using network pharmacology. We employed cell assays and conducted nebulized essential oil inhalation tests on CUMS mice to validate the intervention effects of CEO on anxiety. A total of 28 active components, including neryl acetate, 3-butenylphthalide and octyl acetate, and 26 cross-targets, such as ESR1, CCND1 and PIK3CA, were identified. GO and KEGG pathway analyses indicated that these cross-targets were primarily involved in endocrine regulation, cell proliferation, and apoptosis, specifically through PI3K/Akt signaling pathway and calcium signaling pathway. The experimental results demonstrated that CEO significantly reduced the secretion of NO, TNF-a and IL-6, as well as the mRNA expressions of ESR1, CCND1 and PIK3CA in cells compared to the inflammatory cell model. Furthermore, CEO notably decreased the forced swimming immobility time of mice and the levels of IL-1β, ESR1 and CCND1 in hippocampus when compared to model mice. These findings suggest that CEO may regulate ESR1, CCND1 and PIK3CA through its citral, 3-butylphthalate and neryl acetate, thereby influencing endocrine function, cell proliferation and apoptosis, inhibiting inflammation and anxiety-like behavior in CUMS-induced mice.

Efficacy of Neemraj and Beauvitech on Abundance and Distribution of Arthropod Pests in Soil and Hydroponically Grown Strawberry

Strawberry is a commercially important crop which has gained global significance in terms of production and consumption. The strawberry farmers have been faced with economic losses due to attack from arthropod and phytophagus pests. To overcome this challenge, management of pests is important with reduced impact on beneficial organisms and the environment. Use of non-chemical approaches as an alternative to insecticide driven management is highly gaining popularity. Identification of the non-chemical production for management of strawberry pest such as entomopathogenic fungi and botanicals is critical. The need for compatibility of entomopathogenic fungi in crop production techniques with other insecticides to enhance efficacy is required. The interaction between these control agents could be synergistic, additive or even antagonistic. Synergistic interactions usually lead to enhanced effectiveness of the microbial control agents while reducing the adverse effects of the pesticides in combination. In this review a description of the compatibility of entomopathogenic fungus Beauvaria bassiana and botanical neem in strawberry pest management is given. The experiment involved five treatments: Neemraj, Beauvitech, Neemraj and Beauvitech, Ampligo and control. These treatments were allocated in a completely Randomized design in two separate greenhouse setups one with soil and other with pumice. The treatments were replicated four times. The data was subjected to analysis of variance (ANOVA) using the general linear model (GLM) procedure of the statistical analysis system (SAS) program, version 9.1. Tukey’s (HSD) test at P≤ 0.05 was used to separate significant means. The combination of Neemraj and Beauvitech was most effective in the management of pests in both hydroponics and soil grown media. Pest populations were reduced significantly as follows; thrips, Frankliniella spp 2.1, red spider mites Tetranychus species 11.5, tarnished plant bug Lygus species 3.0, there was 0% cricket Gryllus species damage and 0 number strawberry weevil in hydroponics cultures while in soil culture pest mean populations were: thrips 5.6, spider mites Tetranychus species 18.2, strawberry weevil (Otiorhynchus species) 7.0, tarnished plant bug 3.0 and there was 13.8% cricket Gryllus species damage on strawberry plants.

Risk Factors and Control Strategies for Cattle Tick Infestations in Nigeria: Influence of Acaricide Application Methods, Hand-Picking Frequency, and Herd Mobility in Plateau State

Background Tick infestations severely impair cattle health and productivity in Nigeria through blood loss, hide damage, and transmission of tick-borne pathogens. Objective This study assessed key risk factors influencing tick infestation and evaluated control methods among Fulani pastoral herds in Plateau State. Methods A cross-sectional survey involving 250 cattle from ten herds was conducted across five Local Government Areas. Tick burden was analyzed against acaricide application methods (pour-on vs. hand-spray), hand-picking frequency, and herd mobility (sedentary vs. migratory). Data were collected via owner interviews and manual tick counts. Statistical analyses were performed using generalized linear models in R software. Results Cattle treated with pour-on acaricides had significantly lower tick burdens compared to those treated via hand-spray (P<0.05). Herds that practiced hand-picking five times weekly had fewer ticks than those hand-picking thrice weekly (P<0.01). Migratory herds recorded significantly lower infestations than sedentary herds (P<0.05). Conclusion Effective tick control requires the integration of optimized acaricide application, frequent manual removaland consideration of herd mobility patterns. Education, capacity building, and policy support are necessary to enhance adoption of effective tick control measures among pastoralists.

Perceived Physical Progress and Mental Improvement Among Midlife Women Practicing the 3D Movement Method: A Brief Report from a Cross-Sectional Survey

Background Mind–body exercises are frequently used to support well-being during the menopausal transition, but perceived physical and psychological outcomes associated with practices such as the 3D Movement Method have not been quantitatively assessed. Objective To examine associations between characteristics of the 3D Movement Method and women’s self-reported physical and mental improvement during the menopausal transition. Methods Cross-sectional survey data from 330 women aged ≥ 35 years were analyzed using general linear models. Perceived physical progress and mental improvement were each assessed using single-item, 15-point scales. Independent variables included practice frequency, duration of experience, explanation clarity, satisfaction, baseline health status (SF-36 Physical and Mental Component Summary scores), age, and menopausal status. Results The model for physical progress was significant, F(16, 144) = 6.26, p < .001, R² = .41. Greater practice frequency, longer experience, clearer instructional explanations, and higher satisfaction were each independently associated with higher perceived physical progress. The mental improvement model was also significant, F(16, 96) = 2.25, p = .008, R² = .27, identifying satisfaction as the sole significant predictor. Baseline health, age, and menopausal status did not predict outcomes in either model. Conclusions Perceived physical progress was shaped by structured engagement parameters consistent with deliberate-practice principles, whereas perceived mental improvement was primarily linked to subjective satisfaction, a pattern compatible with motivational accounts of engagement. The 3D Movement Method may support women’s health across the menopausal transition when designed to optimize clarity, engagement, and experiential quality.

Addressing an Overlooked Population: The Role of Discrimination and Violence in Depression Among South Asian Female College Students

South Asian female college students in the United States face mental health challenges shaped by intersecting experiences of discrimination and violence. This study examined how discrimination and violence contribute to depression in this population. An anonymous, cross-sectional, web-based survey (N=673) was distributed nationally through South Asian organizations, listservs, and social media. Validated measures assessed day-to-day discrimination, college-based discrimination, experiences of violence during college, and depression (PHQ-9). Bivariate analyses and multivariate linear regression examined associations, adjusting for sociodemographic factors. Over half of participants (51.1%) reported college-based discrimination, 66.1% reported experiencing violence during college, and 25.7% met the criteria for depression. In adjusted models, day-to-day discrimination (β=0.261, p<0.001) and college violence (β=0.207, p<0.001) were significant predictors of depression. Bisexual and questioning/unsure students also reported higher depression scores than heterosexual peers. Discrimination and violence are key social determinants of mental health among this population. Findings underscore the need for culturally responsive mental health services, intersectional campus policies, and evidence-based interventions to promote health equity among minority women in higher education.

Caregiver-Child Co-Rumination and Treatment Outcomes in a Randomized Clinical Trial of Rumination-Focused Cognitive-Behavioral Therapy

A number of developmental factors increase risk for adolescent rumination. This particular kind of repetitive negative thinking pattern often begins in the context of familial stressors and parental modeling. Though rumination can be effectively targeted with rumination-focused cognitive behavioral therapy (RF-CBT), it is unknown whether caregiver-child co-rumination (1) affects caregiver views of their child’s psychopathology, (2) or interferes with youth rumination- focused treatment. The present study uses data from a randomized clinical trial of RF-CBT to examine whether caregiver-child co-rumination, or caregivers’ own rumination patterns, are associated with bias in parental perception of their adolescent’s depression symptoms. We also examine if co-rumination scores at baseline moderate rumination scores for youth at treatment termination, and whether treatment effects dampen or decay more significantly post-treatment among youth with higher caregiver-child co-rumination. Youth (N = 76) were randomized to either 10-14 sessions of RF-CBT (n = 38) or treatment as usual (TAU; n = 38) and completed interviews and surveys at pre-treatment baseline, post-treatment, and 3-, 6-, 9-, and 12-month follow up. Results indicate that neither caregiver rumination nor co-rumination scores bias caregivers’ views of their child’s depression symptoms. In terms of reduction in child’s rumination scores, estimated treatment effects were larger for patients with higher baseline co- rumination scores, and there was no statistically significant difference in treatment effect decay over time in high versus low co-rumination groups. Results indicate co-rumination overall does not dampen the effect of RF-CBT, and those experiencing the highest levels of co-rumination may benefit most from treatment.  

The Brainstem Auditory Evoked Potential: A Reinterpretation of its Electrogenesis

Depending upon the species, the brainstem auditory evoked potential (BAEP) consists of four or five major high frequency components. According to longstanding doctrine, each wave represents the sequential activation of successively higher nuclei and tracts from the 8th (auditory) nerve to the midbrain (inferior colliculus). Although this conceptual framework has acquired the status of near dogma, surprisingly little evidence exists in support. In the present analysis, a new interpretation of the electrogenesis of the BAEP is proposed which is simpler although it retains skeletal elements of the older explanation. The revised model is mostly derived from two distinct sources. In the first, the timing of the BAEP waves is compared with that of cortical activity for a range of mammals including humans, monkeys, cats, rats and guinea pigs. It is demonstrated that for each of these, the conduction time of the acoustic signal to the cortex from the putative midbrain component (wave IV or V) is so unrealistically long that it implies that the entire waveform must arise in the peripheral pathways of the auditory system. In the second, a retrospective analysis is made of click repetition rates on the BAEP using extradural electrodes. It was shown that at high rates of stimulation (about 100/sec), the behavior of the waveform is almost totally at variance with the expectations of the conventional model. The essence of the revised conception is that all BAEP waves are just variations of the compound action potential of the 8th nerve, albeit generated or regenerated via separate routes and different methods. Such an explanation would thereby account for their near uniform sharp morphology as well as creating the impression of a composite neuronal response. More specifically, in the case of a four component BAEP, wave I is assumed to be generated by the normal air conduction route in an identical manner to the conventional explanation. In contrast, wave ll is assumed to be generated via bone conduction in the temporal skull thereby bypassing the transduction process in the middle ear. Wave lll is assumed to be generated by the first echo of the bone-conducted sound wave. Likewise, the second rebound within the temporal bone serves as the stimulation to evoke wave lV. As the energy of the auditory stimulus gradually dissipates, it may still continue to generate a train of lower amplitude potentials. It is concluded that the BAEP may contain little or no brainstem or midbrain activity and therefore the term BAEP may be a misnomer. A more appropriate epithet might therefore be the auditory nerve evoked potential or ANEP.

Global importance of supporting the krill to whale component of the pelagic food web associated with migrations following deep sea seamounts

The main diet of baleen whales is krill in the Arctic, Antarctic and during migrations in the Atlantic, Pacific and Indian Oceans. Hence, the aim of this paper is to quantify the global importance of the krill to baleen whale component of the pelagic food web and possible feedback loops. That was undertaken by comparing the results of Ecopath Models in the Antarctic and Arctic Oceans and to migration areas in the North Atlantic and Alaska, was well as the large Seamount area from the Antarctic and Arctic. Biological production transfer is the essential component of the prey to predator pelagic food web, which maintains the production of predators. The importance of sustaining global baleen whale migrations is to support ecosystem production by whale defecation contribution to nutrient recycling. It is important to sustain krill and fish abundance in whale migration feeding areas using ecosystem-based fishery management (EBFM) fishing rates. It was shown by the literature that migrations tended to followed deep-sea seamounts, and baleen whale defecation and nutrient cycling at seamounts led to the effects of nutrient upwelling by deep sea currents at seamounts. Hence, it is suggested seamounts be protected as important marine ecosystems. Therefore, those processes indicate sustaining krill and whale abundance is likely to support global marine ecosystem stability in open ocean migration areas.

Comparative Study of Deep Learning Techniques for Detecting Corn Plant Leaf Diseases Using Transfer Learning

Plant leaf diseases pose significant threats to crop yield and agricultural sustainability, making early and accurate detection crucial for effective disease management. In current years, deep neural network (DNN) techniques have shown remarkable potential in the field of image classification, including plant disease detection. The study aims to investigate the performance of two popular deep learning architectures, namely, VGG16 and InceptionResNetV2, for the detection of tomato plant leaf disease. The proposed methodology involves acquiring a diverse dataset comprising high-resolution images of healthy and diseased leaves from the target crops. Preprocessing techniques such as image augmentation and normalization are applied to enhance the generalization ability of the models and mitigate overfitting. Transfer learning is employed to initialize the deep learning architectures with weights pre-trained on large-scale image datasets to accelerate convergence and improve the models' performance in limited data scenarios. To evaluate performance of proposed networks various metrics such as validation and test accuracies, precision and recall, F1 score, and the area under the curve (AUC) are considered. From the investigations, the classification accuracy of the finest architectures is as follows: 99.8 percent for VGG16 and 99.4 percent for InceptionResNetV2 on Corn Leaves. The results suggest that the models developed during the investigation phase to identify the leaf disease were superior to any existing Deep Neural Networks (DNNs).

Intersecting Epidemics: Intimate Partner Violence, Stress, and Diabetes Among South Asian Women in the United States

South Asian women in the United States face disproportionate health challenges, including higher rates of intimate partner violence as well as higher rates of Type 2 diabetes and gestational diabetes compared to other racial and ethnic groups. This cross-sectional study examines the association between intimate partner violence (psychological, physical, and sexual) and the diagnosis of gestational diabetes and type 2 diabetes. A web-based survey recruited 2,634 South Asian women in the U.S., collecting data on socio-demographics, intimate partner violence experiences, stress levels, and diabetes diagnosis. Logistic regression models adjusted for significant sociodemographic factors revealed that women with a history of intimate partner violence were 5.82 significantly more likely to report a type 2 diabetes diagnosis and 3.91 more likely to report a gestational diabetes diagnosis. Furthermore, stress as measured by the perceived stress scale, was also higher among women with intimate partner violence, potentially moderating the relationship between intimate partner violence and adverse health outcomes through cortisol dysregulation. Despite high levels of educational attainment and employment, the prevalence of intimate partner violence was alarmingly high (66.7%), highlighting its pervasive impact on socioeconomic strata. These findings underscore the urgent need for culturally tailored interventions addressing intimate partner violence and its health consequences within South Asian communities. Further research is warranted to elucidate causal pathways and inform integrated public health strategies to mitigate disparities in chronic disease and intimate partner violence-related health outcomes.

Enduring Struggles and Protracted War: Hatred as a Multi-Faceted Construct

This paper examines the concept of conflict- and war-related hatred as a multifaceted construct. Drawing upon various theoretical frameworks, we hypothesized that hatred in the context of conflict and war would encompass five distinct dimensions: Groupthink (Contagious Hatred), Destructiveness, Exposure, Chronicity, and Extreme-Severe Affect. To empirically validate this conceptual framework, we conducted a second-order factor analysis using data from 709 questionnaire responses collected from citizens in the Gaza Strip. The findings revealed that the optimal model comprises three primary constructs: Contagious Hatred, Chronicity, and Extreme- Severe Affect. Based on these results, we argue that collective existential threats in contexts of protracted conflict and war amplify groupthink, foster a sense of chronicity, and evoke intense negative affect. These findings underscore the complexity of hatred as a psychological and social phenomenon in conflict zones.

The Role of Cerebral Hypercarbia in the Induction of the Near-Death Experience

The near-death experience (NDE) is an altered state of consciousness which arises when a person is critically ill or injured and possibly clinically dead. It should not be conflated with other mental events such as the deathbed vision or the fear or anticipation of death. Many believe that the NDE represents a genuine paranormal phenomenon providing a glimpse of an otherworldly existence and proof of an afterlife. Those who are skeptical of such a survivalist or supernatural interpretation have long pointed out that the core components of the NDE can be readily simulated with a variety of states, conditions and agents. In this conception, the NDE is reduced to no more or less than an extraordinarily complex hallucination. Since its rediscovery in the 1970s, multiple, often ingenious, attempts have been made to account for the NDE in such naturalistic or neuroscientific terms. None has so far proven completely satisfactory. One of the oldest, least considered but still promising is the CO2 theory which argues that a hypercarbic brain is a necessary precursor for the induction of a NDE. Supportive evidence that CO2 does play a pivotal role in the generation of the NDE can be gathered from diverse sources. These include: 1. measurement of blood gases; 2. Meduna’s now abandoned CO2 therapy; 3. analysis of the very limited number of pathophysiological conditions underlying the NDE; 4. recent discoveries of the role of 5-HT neurons in the central respiratory system. A model is proposed in which CO2 molecules are considered to be functionally equivalent to those of the classical hallucinogens (LSD, mescaline, psilocybin, dimethyltryptamine). These agents can mimic the phenomenology of the NDE with remarkable fidelity. What is still missing from any such explanation is the long-sought transduction mechanism which converts physical events into mental ones. This is a generic problem which confronts all attempts to explain the neurogenesis of mystical, psychedelic or visionary activity.

RBM45: Molecular, Cellular, and Evolutionary Biology

This article surveys RBM45 from molecular function and RNA binding to cellular roles and evolutionary conservation. It summarizes emerging links to neurobiology and disease, and highlights tools and models to probe RBM45 biology.

Effects of a Novelty Virtual Interactive Brain Atlas on Student Perception of Neuroanatomy

The instructional techniques in neuroanatomy laboratories continue to evolve to incorporate online interactive resources to improve student experience and outcomes. This study aims to design an “all in one”Virtual Interactive Brain Atlas (VIBA) that provides students with an educational resource that will improve their knowledge of neuroanatomy while in the brain lab and provide them with lab resources they can self-study and self-test. Coronal, midsagittal, whole brain, and horizontal brain slices were used to create detailed descriptions, interactive features, and quiz assessments to create VIBA. Upper level undergraduate and optometry students taking a neuroanatomy one-semester course were provided with VIBA for use during the semester. A paper survey was distributed after completing the course to determine student perception. No significant difference was indicated between the student groups regarding their self-reported understanding prior to the brain lab (p= 0.194) and after the brain lab (p= 0.308). There was a significant difference between the student populations when stating that they strongly agreed that the online brain atlas improved their understanding of neuroanatomy (p= 0.032) and that the VIBA tool was easy to navigate (p=0.048). There was a significant difference between the two student groups that strongly agreed that the online brain atlas quality was sufficient (p= 0.015). This online interactive brain atlas was created in a time-efficient manner from readily available models and was well received by experienced neuroanatomy faculty and students.

Mental Health Disparities Among LGBTQ+ Youth and The Strategies to Promote Their Well-Being

Introduction Compared to their heterosexual counterparts, cisgender LGBTQ+ youth are more likely to experience numerous mental health conditions, for instance, suicidal ideation, stress, and anxiety. This study aimed to explore mental health disparities among LGBTQ+ youth while identifying strategies to promote their well-being. Methodology Incorporating a systematic approach, studies were selected according to the predefined inclusion criteria, ensuring recentness and relevance. Five databases were systematically searched while the PRISMA flowchart was employed for illustrating the systematic selection process. The PEO framework directed the study selection. Thematic analysis was applied to identify themes that were related to the study aim. Results Five themes were emerged including policy changes and legal frameworks, contextual and cultural factors, family and social support, underlying factors of mental health, and healthcare services access. The synthesis of the literature uncovers the multifaceted relationship between cultural and contextual factors and policy changes, social and family support and healthcare services. The study also underlines the importance of implementing an intersectional minority stress model for comprehensively understanding mental health disparities among LGBTQ+ youth. Conclusion The results emphasize the importance of ongoing research in policy alterations, accessibility to healthcare, and creating supportive surroundings to tackle differences in mental health. Recognizing the complexity of these issues, this paper requires an in-depth examination that considers intersecting factors, promotes inclusivity, and involves long-term studies in providing mental health support to enhance the well-being of LGBTQ+ young individuals.

Exploring syntactic complexity and its relationship with writing quality in EFL argumentative essays

Despite a large number of studies examining syntactic features that are predictive of second language (L2) writing quality, assessed by human raters at the university level, few have systematically investigated this link using a large set of indices in the foreign language learning (EFL) classroom context. The current study sought to determine the extent to which a variety of syntactic complexity and sophistication indices are associated with and may predict writing quality by analyzing 30 argumentative essays written by undergraduate EFL students in an Ethiopian university classroom setting. To represent syntactic complexity as a multidimensional construct, we used conventional absolute measures, fine-grained clausal and phrasal indices, and newly proposed sophistication indices related to the use of verb argument constructions (VACs) indexed by TAASSC (Tool for the Automatic Analysis of Syntactic Sophistication and Complexity; 17. Essays were graded, and five separate predicted models of writing quality were created utilizing each complex feature index and all of the measures. Robust predictors of writing quality were identified at both syntactic complexity and sophistication dimensions. Regression analyses showed that the combined model including both fine-grained clausal complexity and VAC-based indices could account for 53.6% of the variance (the largest amount of variance in the study) in writing scores. The finding indicates that the inclusion of diversified adverbial modifiers and nonfinite clauses such as modal auxiliaries controlled by less frequent verbs were predictive of higher-quality writing. These findings shed light on some characteristics of L2 learners' writing growth and enable us to draw pedagogical implications for teaching and assessing writing in the Ethiopian EFL context.

Automated Grassweed Detection in Wheat Cropping System: Current Techniques and Future Scope

Wheat is a staple grain crop in the United States and around the world. Weed infestation, particularly grass weeds, poses significant challenges to wheat production, competing for resources and reducing grain yield and quality. Effective weed management practices, including early identification and targeted herbicide application are essential to avoid economic losses. Recent advancements in unmanned aerial vehicles (UAVs) and artificial intelligence (AI), offer promising solutions for early weed detection and management, improving efficiency and reducing negative environment impact. The integration of robotics and information technology has enabled the development of automated weed detection systems, reducing the reliance on manual scouting and intervention. Various sensors in conjunction with proximal and remote sensing techniques have the capability to capture detailed information about crop and weed characteristics. Additionally, multi-spectral and hyperspectral sensors have proven highly effective in weed vs crop detection, enabling early intervention and precise weed management. The data from various sensors consecutively processed with the help of machine learning and deep learning models (DL), notably Convolutional Neural Networks (CNNs) method have shown superior performance in handling large datasets, extracting intricate features, and achieving high accuracy in weed classification at various growth stages in numerous crops. However, the application of deep learning models in grass weed detection for wheat crops remains underexplored, presenting an opportunity for further research and innovation. In this review we underscore the potential of automated grass weed detection systems in enhancing weed management practices in wheat cropping systems. Future research should focus on refining existing techniques, comparing ML and DL models for accuracy and efficiency, and integrating UAV-based mapping with AI algorithms for proactive weed control strategies. By harnessing the power of AI and machine learning, automated weed detection holds the key to sustainable and efficient weed management in wheat cropping systems.