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BackgroundUnited States data protection laws vary depending on the data type and its context. Data projects involving social determinants of health often concern different data protection laws, making them difficult to navigate. ObjectiveWe systematically aggregated and assessed useful online resources to help navigate the data-sharing landscape. MethodsWe included publicly available resources that discussed legal data-sharing issues with some health relevance and published between 2010 and 2019. We conducted an iterative search with a common string pattern using a general-purpose search engine that targeted 24 different sectors identified by Data Across Sectors for Health. We scored each online resource for its depth of legal and data-sharing discussions and value for addressing legal barriers. ResultsOut of 3710 total search hits, 2721 unique URLs were reviewed for scope, 322 received full-text review, and 154 were selected for final coding. Legal agreements, consent, and agency guidance were the most widely covered legal topics, with HIPAA (The Health Insurance Portability and Accountability Act), Family Educational Rights and Privacy Act (FERPA), Title 42 of the Code of Federal Regulations Part 2 being the top 3 federal laws discussed. Clinical health care was the most prominent sector with a mention in 73 resources. ConclusionsThis is the first systematic study of publicly available resources on legal data-sharing issues. We found existing gaps where resources covering certain laws or applications may be needed. The volume of resources we found is an indicator that real and perceived legal issues are a substantial barrier to efforts in leveraging data from different sectors to promote health.

Abstract Purpose Propensity score matching is vital in epidemiological studies using observational data, yet its estimates relies on correct model-specification. This study assesses supervised deep learning models and unsupervised autoencoders for propensity score estimation, comparing them with traditional methods for bias and variance accuracy in treatment effect estimations. Methods Utilizing a plasmode simulation based on the Right Heart Catheterization dataset, under a variety of settings, we evaluated (1) a supervised deep learning architecture and (2) an unsupervised autoencoder, alongside two traditional methods: logistic regression and a spline-based method in estimating propensity scores for matching. Performance metrics included bias, standard errors, and coverage probability. The analysis was also extended to real-world data, with estimates compared to those obtained via a double robust approach. Results The analysis revealed that supervised deep learning models outperformed unsupervised autoencoders in variance estimation while maintaining comparable levels of bias. These results were supported by analyses of real-world data, where the supervised model’s estimates closely matched those derived from conventional methods. Additionally, deep learning models performed well compared to traditional methods in settings where exposure was rare. Conclusion Supervised deep learning models hold promise in refining propensity score estimations in epidemiological research, offering nuanced confounder adjustment, especially in complex datasets. We endorse integrating supervised deep learning into epidemiological research and share reproducible codes for widespread use and methodological transparency.

Awareness of electronic waste (e-waste) improves safety practices among workers, thereby reducing health risks associated with pollutants. Investigating the awareness and safe practices among these workers could help identify areas for improvement, a task not yet undertaken in Bangladesh. Consequently, this study aimed to examine the awareness, safety measures, and associated factors among e-waste workers in the country. In this cross-sectional study, 236 workers from an e-waste recycling facility located near Dhaka were interviewed using a semi-structured questionnaire from August to September 2022. Eight questions captured information on socio-demographics and work factors, 24 questions on e-waste awareness, and 11 questions on safety practices. Total awareness and safety scores were calculated and categorized as “good” and “poor” based on a cut-off point of 80% of the total score. Bivariate and regression analyses were done to determine associated factors. Only 25% of workers had good e-waste awareness; major knowledge gaps were regarding minimization, health hazards, and environmental impact. Good awareness was significantly associated with female gender, higher education, income, smoking, experience ⩾5 years, and training. About 58% followed good safety practices, but the use of boots and helmets was inadequate. Good safety practices were significantly associated with higher education, income, smoking, experience, training, and overtime work. On multivariable analysis, those with higher education had 12 times (95% CI 4.83-32.81) and 6 times (95% CI 2.94-12.81) higher odds of good awareness and practices, respectively. Trained workers had 3.6 times (95% CI 1.67-7.52) higher odds of good practices. There was a significant correlation between awareness and practices (r = .70, P

Bioherbicides might be used to manage weeds as opposed to synthetic chemical herbicides, reducing environmental risks and advancing sustainable agriculture in the meantime. Bioherbicides employ different mechanisms of action to control weeds. Microbial bioherbicides may infect and damage weed plants, disrupt their growth, or produce compounds inhibiting weed development. Plant-derived bioherbicides often target specific biochemical processes crucial for weed survival. It can be applied through conventional spraying equipment, seed treatments, or soil incorporation. Bioherbicide development faces several challenges. One major hurdle is the complex diversity of weed species across different regions, requiring tailored bioherbicide solutions. The regulatory approvals for bioherbicides can be lengthy and costly, hindering widespread adoption. Scaling up production processes and ensuring product stability also pose challenges. By reducing reliance on chemical herbicides, bioherbicides can mitigate environmental pollution, protect non-target organisms, and promote sustainable agricultural practices. The development of locally adapted bioherbicides and strategic collaborations between researchers, industries, and policymakers could further enhance their prospects in a particular country. In addition, the knowledge gaps need to be addressed prior to adopting bioherbicides in agriculture. These review intended to explore the existing state of knowledge about the categories of bioherbicides, their formulation procedure, application approaches and mode of action to control weed. The bioherbicides that are currently on the market, their effects on weed physiology, and possible factors affecting their efficacy are all included in this review. Moreover, this review offers a perspective on existing challenges and future opportunities for adopting the bioherbicides in sustainable and eco-friendly agriculture.

This study presents the development of multifunctional protective clothing for disabled individuals using PBAT/PLA biopolymeric-based electrospun nanofibrous membranes. The fabric consists of a superhydrophobic electrospun nanofibrous cloth reinforced with silica nanoparticles. The resulting nanofiber membranes were characterized using FE-SEM, a CA goniometer, breathability and hydrostatic pressure resistance tests, UV–vis spectroscopy, thermal infrared photography, tensile tests, and nanoindentation. The results demonstrated the integration of superhydrophobicity, breathability, and mechanical improvements in the protective clothing. The nanofibrous porous structure of the fabric allowed breathability, while the silica nanoparticles acted as an effective infrared reflector to keep the wearer cool on hot days. The fabric’s multifunctional properties make it suitable for various products, such as outdoor clothing and accessories for individuals with disabilities. This study highlights the importance of selecting appropriate textiles for protective clothing and the challenges faced by disabled individuals in terms of mobility, eating, and dressing. The innovative and purposeful design of this multifunctional protective clothing aimed to enrich the lives of individuals with disabilities.

The majority of congenital heart defects (CHDs) are thought to result from the interaction between multiple genetic, epigenetic, environmental, and lifestyle factors. Epigenetic mechanisms are attractive targets in the study of complex diseases because they may be altered by environmental factors and dietary interventions. We conducted a population based, case-control study of genome-wide maternal DNA methylation to determine if alterations in gene-specific methylation were associated with CHDs. Using the Illumina Infinium Human Methylation27 BeadChip, we assessed maternal gene-specific methylation in over 27,000 CpG sites from DNA isolated from peripheral blood lymphocytes. Our study sample included 180 mothers with non-syndromic CHD-affected pregnancies (cases) and 187 mothers with unaffected pregnancies (controls). Using a multi-factorial statistical model, we observed differential methylation between cases and controls at multiple CpG sites, although no CpG site reached the most stringent level of genome-wide statistical significance. The majority of differentially methylated CpG sites were hypermethylated in cases and located within CpG islands. Gene Set Enrichment Analysis (GSEA) revealed that the genes of interest were enriched in multiple biological processes involved in fetal development. Associations with canonical pathways previously shown to be involved in fetal organogenesis were also observed. We present preliminary evidence that alterations in maternal DNA methylation may be associated with CHDs. Our results suggest that further studies involving maternal epigenetic patterns and CHDs are warranted. Multiple candidate processes and pathways for future study have been identified.

The contemporary Assamese plays have developed as a result of numerous interwoven influences and channels. And it is clear that western influences were what shaped the Assamese plays into their perfection. After independence, Assamese writers of prose, poetry, and theatre, produced works that were on pace with the period. It demonstrated identical compositional experimentation and sociological analysis. The Assamese plays exhibit a strong western heritage from playwrights like Ibsen, Shaw, Beckett, and other absurd dramatists. A few dramatists, like Dr. Arun Sarma, Ratna Ojha, and Himendrakumar Borthakur made reflections of works of Lonesco and Beckett and despite the fact the impact of absurd dramas was not very common. In this article, the researcher investigated the works of the most renowned and esteemed Assamese playwright, Dr. Arun Sarma (1964), to emphasize the distinguishing components and similarities of Shri Nibaran Bhattacharya and Aahaar with those of absurd dramatic tropes. The researcher discovered, using the comparative technique of analysis, that, despite frequent assertions to the contrary, Aahaar has much in common with the absurdist movement, whereas Shri Nibaran Bhattacharya cannot be regarded as a fully-fledged absurd drama.

IntroductionRice is an important crop that is considered a staple meal for 2.7 billion people worldwide. Therefore, the demand for it will increase with the increase of population. Environmental constraints always pose a serious threat to crop production, including rice. Drought is one of the most important challenges that limits the production of high-yielding cultivars in arid and rainfed areas. Global warming has also become a factor in limiting rice production in rain-dependent areas. Therefore, researchers are looking for a way to stabilize rice production in arid regions. In this study, informative markers related to the desired agronomic traits were identified in 59 rice genotypes using microsatellite marking system.Materials and methodsIn order to evaluate the tolerance of rice genotypes to drought stress and to identify tolerant and sensitive genotypes, 59 genotypes received from the National Rice Research Institute and the International Rice Research Institute in a randomized complete block design with three replications in two separate conditions, without Stress (flood) and drought stress were performed in a research farm located in Aliabad Katoul city in 2013. In both conditions (normal and drought stress), the genotypes were planted in five rows of 25 × 25 cm in rows one meter long. Thirty days after planting in the nursery, healthy and strong seedlings were transferred to the main land. The required agronomic operations were carried out equally during the growth and development period of the plants under stress and normal conditions and only in terms of irrigation of the experimental field in both flood and stress environments, until the tillering stage of the cultivars were equally flooded. Then, to create stress, irrigation was done from 40 days after transplanting (maximum tillering stage) to the end of the growing season at 25-day intervals. Phenotypic values of grain yield and 1000-grain weight were measured under two conditions according to standard guidelines for evaluation of traits in rice. In order to investigate the relationship between agronomic traits and microsatellite markers with 59 rice genotypes out of 36 microsatellite molecular markers were performed in the Plant Breeding and Genetics Laboratory of Gonbad Kavous University, Faculty of Agriculture and Natural Resources. Young leaves of 21-day-old seedlings were extracted in four-leaf stage using CTAB method. Touchdown PCR reaction was studied and evaluated randomly using 36 microsatellite primers for 3 markers from each chromosome. To separate PCR products, 6% polyacrylamide gel electrophoresis was used and to reveal the banding pattern, silver nitrate staining method was used. The content of polymorphic information was calculated. The relationship between molecular data and traits of studied rice genotypes was investigated using multiple regression. Thus, each quantitative trait was considered as a dependent variable and microsatellite markers were considered as independent variables.Results and discussionThe average content of polymorphic corrections (PIC) was estimated to be 0.58, which showed RM 5647 with 0.81 the highest and RM 6022 with 0.32 the lowest polymorphism (PIC). The results of stepwise regression analysis showed that a total of 90 markers for normal conditions and 69 markers for drought stress conditions for morphological traits were identified. Under normal conditions, the number of spikes and the number of days to flowering with 9 markers and under drought stress, the weight of the cluster with 9 markers showed the most positive markers. The most explanation for variation in normal conditions is related to the total number of grains (0.83) by gene loci RM6324-E, RM5652-E, RM5761-D, RM6179-F, RM549-B, RM462-B, RM7420-D Explained. In drought stress conditions, the most explanation for variation related to panicle weight (0.70) by gene loci RM519-D, RM7545-A, RM6179-E, RM7118-G, RM3525-B, RM5761-B, RM38-C, RM7091-A, RM5647-B explained.ConclusionThe results showed that some markers are associated with more than one trait, which indicates that these traits are very closely related to each other or may be influenced by multi-effect genes. To understand this, it is necessary to develop transgressive generations and linkage.

To estimate COVID-19 infections and deaths in healthcare workers (HCWs) from a global perspective during the early phases of the pandemic. Systematic review. Two parallel searches of academic bibliographic databases and grey literature were undertaken until 8 May 2020. Governments were also contacted for further information where possible. There were no restrictions on language, information sources used, publication status and types of sources of evidence. The AACODS checklist or the National Institutes of Health study quality assessment tools were used to appraise each source of evidence. Publication characteristics, country-specific data points, COVID-19-specific data, demographics of affected HCWs and public health measures employed. A total of 152 888 infections and 1413 deaths were reported. Infections were mainly in women (71.6%, n=14 058) and nurses (38.6%, n=10 706), but deaths were mainly in men (70.8%, n=550) and doctors (51.4%, n=525). Limited data suggested that general practitioners and mental health nurses were the highest risk specialities for deaths. There were 37.2 deaths reported per 100 infections for HCWs aged over 70 years. Europe had the highest absolute numbers of reported infections (119 628) and deaths (712), but the Eastern Mediterranean region had the highest number of reported deaths per 100 infections (5.7). COVID-19 infections and deaths among HCWs follow that of the general population around the world. The reasons for gender and specialty differences require further exploration, as do the low rates reported in Africa and India. Although physicians working in certain specialities may be considered high risk due to exposure to oronasal secretions, the risk to other specialities must not be underestimated. Elderly HCWs may require assigning to less risky settings such as telemedicine or administrative positions. Our pragmatic approach provides general trends, and highlights the need for universal guidelines for testing and reporting of infections in HCWs.

Abstract Background Phytochemicals or secondary metabolites are low molecular weight organic compounds with little function in plant growth and development. Nevertheless, the metabolite diversity govern not only the phenetics of an organism but may also inform the evolutionary pattern and adaptation of green plants to the changing environment. Plant chemoinformatics analyzes the chemical system of natural products using computational tools and robust mathematical algorithms. It has been a powerful approach for species-level differentiation and is widely employed for species classifications and reinforcement of previous classifications. Results This study attempts to classify Angiosperms using plant sulfur-containing compound (SCC) or sulphated compound information. The SCC dataset of 692 plant species were collected from the comprehensive species-metabolite relationship family (KNApSAck) database. The structural similarity score of metabolite pairs under all possible combinations (plant species-metabolite) were determined and metabolite pairs with a Tanimoto coefficient value > 0.85 were selected for clustering using machine learning algorithm. Metabolite clustering showed association between the similar structural metabolite clusters and metabolite content among the plant species. Phylogenetic tree construction of Angiosperms displayed three major clades, of which, clade 1 and clade 2 represented the eudicots only, and clade 3, a mixture of both eudicots and monocots. The SCC-based construction of Angiosperm phylogeny is a subset of the existing monocot-dicot classification. The majority of eudicots present in clade 1 and 2 were represented by glucosinolate compounds. These clades with SCC may have been a mixture of ancestral species whilst the combinatorial presence of monocot-dicot in clade 3 suggests sulphated-chemical structure diversification in the event of adaptation during evolutionary change. Conclusions Sulphated chemoinformatics informs classification of Angiosperms via machine learning technique.

Budd-Chiari syndrome (BCS) is the clinical spectrum presenting with hepatic venous outflow obstruction from the hepatic veins to the junction of the inferior vena cava (IVC) and the right atrium. This syndrome is rare in infants and children, which leads to misdiagnoses or delayed diagnoses. Clinical presentations may be non-specific. A high index of suspicion and imaging findings may help in early diagnosis of this condition. We report a rare case of BCS in a 6-week-old male infant who presented with jaundice and gradual abdominal distension. He was successfully treated with rivaroxaban.

IntroductionAdherence to cancer prevention recommendations can greatly reduce colorectal cancer risk. This study explored patterns and determinants of adherence to these recommendations by participants (n = 26 074) at baseline in a cohort study in British Columbia, Canada. MethodsAdherence to five colorectal cancer primary prevention behaviours derived from Canadian Cancer Society/World Cancer Research Fund recommendations (nonsmoking, body mass index (BMI), physical activity, alcohol consumption and fruit and vegetable consumption) was measured, and a composite score constructed based on their sum. The definition of secondary prevention adherence was based on the Canadian Task Force on Preventive Health Care recommendations for colorectal cancer screening. ResultsAdherence to primary prevention guidelines ranged from 94.8% (nonsmoking) to 44.2% (healthy BMI). Median composite score was 4. Higher composite scores were associated with being female, being married and with a higher educational attainment. Colorectal cancer screening adherence was 62.4%. Older age, chronic conditions, a recent medical examination and higher income were associated with greater odds of adherence to screening. ConclusionAdherence to some colorectal cancer prevention behaviours was high, consistent with findings that British Columbia has low rates of many risky health behaviours. However, there was a clustering of poorer adherence to prevention behaviours with each other and with other risk factors. Screening adherence was high but varied with some sociodemographic and health factors. Future work should evaluate targeted interventions to improve adherence among those in the lowest socioeconomic status and health groups. A better understanding is also needed of the barriers to access and engagement with colorectal cancer screening that persist even in the Canadian public health care system.

IntroductionL’adhésion aux recommandations en matière de prévention du cancer peut grandement réduire le risque de cancer colorectal. Cette étude porte sur les tendances et les déterminants de l’adhésion à ces recommandations par les participants (n = 26 074) au début d’une étude de cohorte en Colombie‑Britannique (Canada). MéthodologieNous avons mesuré l’adhésion à cinq comportements de prévention primaire du cancer colorectal tirés des recommandations émises par la Société canadienne du cancer et le Fonds mondial de recherche contre le cancer (absence de tabagisme, indice de masse corporelle (IMC), activité physique, consommation d’alcool et consommation de fruits et légumes) et nous avons établi un score composite reposant sur la somme des mesures. La définition de l’adhésion aux comportements de prévention secondaire est fondée sur les recommandations du Groupe d’étude canadien sur les soins de santé préventifs pour le dépistage du cancer colorectal. RésultatsL’adhésion aux lignes directrices en matière de prévention primaire variait entre 94,8 % (absence de tabagisme) à 44,2 % (IMC santé). Le score composite médian était de 4. Les scores composites supérieurs ont été associés au fait d’être une femme, d’être marié(e) et d’avoir un niveau de scolarité plus élevé. Le taux d’adhésion au dépistage du cancer colorectal était de 62,4 %. Un âge avancé, la présence de maladies chroniques, le fait d’avoir subi un examen médical récemment et le fait de faire partie d’un ménage à revenu élevé étaient associés à une probabilité accrue d’adhésion au dépistage. ConclusionL’adhésion à certains comportements de prévention du cancer colorectal s’est révélée élevée, ce qui concorde avec les constatations selon lesquelles la Colombie-Britannique affiche des taux faibles pour de nombreux comportements risqués pour la santé. Cependant, on a constaté une agglomération de plus faible adhésion aux comportements de prévention les uns avec les autres et en présence d’autres facteurs de risque. L’adhésion au dépistage s’est révélée élevée, mais varie en fonction de certains facteurs sociodémographiques et sanitaires. Les travaux futurs devraient porter sur des interventions ciblées visant à améliorer l’adhésion des individus faisant partie des groupes dont le statut socioéconomique et l’état de santé sont les plus précaires. Il faut également mieux comprendre les obstacles à l’accès et à la participation au dépistage du cancer colorectal, qui persistent même au sein du système de santé public canadien.

Abstract Background Two-stage least square [2SLS] and two-stage residual inclusion [2SRI] are popularly used instrumental variable (IV) methods to address medication nonadherence in pragmatic trials with point treatment settings. These methods require assumptions, e.g., exclusion restriction, although they are known to handle unmeasured confounding. The newer IV-method, nonparametric causal bound [NPCB], showed promise in reducing uncertainty compared to usual IV-methods. The inverse probability-weighted per-protocol [IP-weighted PP] method is useful in the same setting but requires different assumptions, e.g., no unmeasured confounding. Although all of these methods are aimed to address the same nonadherence problem, comprehensive simulations to compare performances of them are absent in the literature. Methods We performed extensive simulations to compare the performances of the above methods in addressing nonadherence when: (1) exclusion restriction satisfied and no unmeasured confounding, (2) exclusion restriction is met but unmeasured confounding present, and (3) exclusion restriction is violated. Our simulations varied parameters such as, levels of adherence rates, unmeasured confounding, and exclusion restriction violations. Risk differences were estimated, and we compared performances in terms of bias, standard error (SE), mean squared error (MSE), and 95% confidence interval coverage probability. Results For setting (1), 2SLS and 2SRI have small bias and nominal coverage. IP-weighted PP outperforms these IV-methods in terms of smaller MSE but produces high MSE when nonadherence is very high. For setting (2), IP-weighted-PP generally performs poorly compared to 2SLS and 2SRI in term of bias, and both-stages adjusted IV-methods improve precision than naive IV-methods. For setting (3), IV-methods perform worst in all scenarios, and IP-weighted-PP produces unbiased estimates and small MSE when confounders are adjusted. NPCB produces larger uncertainty bound width in almost all scenarios. We also analyze a two-arm trial to estimate vitamin-A supplementation effect on childhood mortality after addressing nonadherence. Conclusions Understanding finite sample characteristics of these methods will guide future researchers in determining suitable analysis strategies. Since assumptions are different and often untestable for IP-weighted PP and IV methods, we suggest analyzing data using both IP-weighted PP and IV approaches in search of a robust conclusion.

Background Hepatitis A is the most common cause of acute viral hepatitis, with a typical simple, self-limiting course. But it is not free from complications. Atypical presentations, such as in the form of prolonged cholestasis, ascites, pleural effusion, relapsing hepatitis, or fulminant hepatic failure, pose challenges to disease management. Knowledge about varying presentations and identification of factors associated with atypical presentations will help to early diagnosis of atypical courses of disease. Objective To describe various atypical clinical presentations, biochemical findings of hepatitis A infection, and possible related factors. Methods Ninety-five children aged 1 to 18 years, diagnosed with hepatitis A infection, and admitted to the Department of Pediatric Gastroenterology & Nutrition, BSMMU, Dhaka, Bangladesh from January 2015 to May 2018 were studied retrospectively. Results Atypical presentations were manifested in 19 (20%) out of 95 children with hepatitis A virus (HAV) infection. The mean age of atypical patients [6.32 (SD 3.45) years] was significantly lower than that of typical patients [8.22 (SD 3.58) years] (P=0.0041). The most common atypical manifestation was ascites (11/19), followed by hepatic encephalopathy (9/19), acute liver failure (719), thrombocytopenia (2/19), pleural effusion (2/19), and cholestasis (1; 1.1%). Children with atypical features had significantly higher international normalized ratio (INR) and serum bilirubin, as well as lower hemoglobin level than the typical group. Children of atypical group had significantly higher number of organomegaly and coagulopathy. Conclusion Ascites, hepatic encephalopathy, acute liver failure, thrombocytopenia, pleural effusion, and prolonged cholestasis were common forms of atypical presentation. Younger age, organomegaly, higher bilirubin level, prolonged PT, and decreased hemoglobin level could be predictive of an atypical presentation of HAV in children.

Abstract Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is associated with unique changes in mitochondrial metabolism, including elevated respiration rates and morphological alterations. We examined electron transport chain (ETC) complex activity in fibroblasts derived from 18 children with ASD as well as mitochondrial morphology measurements in fibroblasts derived from the ASD participants and four typically developing controls. In ASD participants, symptoms severity was measured by the Social Responsiveness Scale and Aberrant Behavior Checklist. Mixed-model regression demonstrated that alterations in mitochondrial morphology were associated with both ETC Complex I+III and IV activity as well as the difference between ETC Complex I+III and IV activity. The subgroup of ASD participants with relative elevation in Complex IV activity demonstrated more typical mitochondrial morphology and milder ASD related symptoms. This study is limited by sample size given the invasive nature of obtaining fibroblasts from children. Furthermore, since mitochondrial function is heterogenous across tissues, the result may be specific to fibroblast respiration. Previous studies have separately described elevated ETC Complex IV activity and changes in mitochondrial morphology in cells derived from children with ASD but this is the first study to link these two findings in mitochondrial metabolism. The association between a difference in ETC complex I+III and IV activity and normal morphology suggests that mitochondrial in individuals with ASD may require ETC uncoupling to function optimally. Further studies should assess the molecular mechanisms behind these unique metabolic changes. Trial registration: Protocols used in this study were registered in clinicaltrials.gov as NCT02000284 and NCT02003170.

Background and objectivesLittle is known of the potential sex and age differences in the MS prodrome. We investigated sex and age differences in healthcare utilization during the MS prodrome.MethodsThis was a population-based matched cohort study linking administrative and clinical data from British Columbia, Canada (population = 5 million). MS cases in the 5 years preceding a first demyelinating event (“administrative cohort;” n = 6,863) or MS symptom onset (“clinical cohort;” n = 966) were compared to age-, sex- and geographically-matched controls (n = 31,865/4,534). Negative binomial and modified Poisson models were used to compare the rates of physician visits and hospitalizations per international classification of diseases chapter, and prescriptions filled per drug class, between MS cases and controls across sex and age-groups (< 30, 30–49, ≥50 years).ResultsIn the administrative cohort, males with MS had a higher relative rate for genitourinary-related visits (males: adjusted Rate Ratio (aRR) = 1.65, females: aRR = 1.19, likelihood ratio test P = 0.02) and antivertigo prescriptions (males: aRR = 4.72, females: aRR = 3.01 P < 0.01). Injury and infection-related hospitalizations were relatively more frequent for ≥50-year-olds (injuries < 30/30–49/≥50: aRR = 1.16/1.39/2.12, P < 0.01; infections 30–49/≥50: aRR = 1.43/2.72, P = 0.03), while sensory-related visits and cardiovascular prescriptions were relatively more common in younger persons (sensory 30–49/≥50: aRR = 1.67/1.45, P = 0.03; cardiovascular < 30/30–49/≥50: aRR = 1.56/1.39/1.18, P < 0.01). General practitioner visits were relatively more frequent in males (males: aRR = 1.63, females: aRR = 1.40, P < 0.01) and ≥50-year-olds (< 30/≥50: aRR = 1.32/1.55, P = 0.02), while differences in ophthalmologist visits were disproportionally larger among younger persons, < 50-years-old (< 30/30–49/≥50: aRR = 2.25/2.20/1.55, P < 0.01). None of the sex and age-related differences in the smaller clinical cohort reached significance (P ≥ 0.05).DiscussionSex and age-specific differences in healthcare use were observed in the 5 years before MS onset. Findings demonstrate fundamental heterogeneity in the MS prodromal presentation.

ABSTRACT SARS-CoV-2 anti-spike antibody concentrations and angiotensin converting enzyme-2 (ACE-2) inhibition have been used as surrogates to live viral neutralizing antibody titers; however, validity among vaccinated individuals is unclear. We tested the correlation of these measures among vaccinated participants, and examined subgroups based on duration since vaccination and vaccine dosing intervals. We analyzed 120 samples from two-dose mRNA vaccinees without previous COVID-19. We calculated Spearman correlation coefficients between wild-type viral neutralizing antibody titers and: anti-spike (total and IgG), anti-receptor-binding-domain (RBD), and anti-N-terminal-domain (NTD) antibodies; and ACE-2 binding by RBD. We performed three secondary analyses, dichotomizing samples by the first vaccination-to-blood collection interval, second vaccination-to-blood collection interval, and by the vaccine dosing interval (all groups divided by the median), and compared correlation coefficients (Fisher’s Z test). Of 120 participants, 63 (53%) were women, 91 (76%) and 29 (24%) received BNT162b2 and mRNA-1273 vaccines, respectively. Overall, live viral neutralization was correlated with anti-spike total antibody (correlation coefficient = 0.80), anti-spike IgG (0.63), anti-RBD IgG (0.62), anti-NTD IgG (0.64), and RBD ACE2 binding (0.65). Samples with long (>158 days) first vaccination-to-blood collection and long (>71 days) second vaccination-to-blood collection intervals demonstrated higher correlation coefficients, compared with short groups. When comparing cases divided by short (≤39 days) versus long vaccine dosing intervals, only correlation with RBD-ACE-2 binding inhibition was higher in the long group. Among COVID-negative mRNA vaccinees, anti-spike antibody and ACE-2 inhibition concentrations are correlated with live viral neutralizing antibody titers. Correlation was stronger among samples collected at later durations from vaccination. IMPORTANCE Live viral neutralizing antibody titers are an accepted measure of immunity; however, testing procedures are labor-intensive. COVID-19 antibody and angiotensin converting enzyme-2 (ACE-2) levels have been used as surrogates to live viral neutralizing antibody titers; however, validity among vaccinated individuals is unclear. Using samples from 120 two-dose mRNA vaccinees without previous COVID-19, we found that live viral neutralization was correlated with COVID-19 antibody and ACE2 binding levels. When grouping samples by the time interval between vaccination and sample blood collection, samples collected over 158 days after the first vaccine and over 71 days from the second vaccine demonstrated stronger correlation between live viral neutralization titers and both antibody and ACE2 levels, in comparison to those collected earlier.

Abstract Background Phosphate (Pi) deficiency severely affects crop growth and productivity, including wheat, therefore it is necessary to develop cultivars with enhanced Pi-deficiency tolerance. However, the underlying mechanism of Pi-deficiency tolerance in wheat is still elusive. Two contrasting wheat cultivars, low-Pi tolerant Kenong199 (KN199) and low-Pi sensitive Chinese Spring (CS) were used to reveal adaptations in response to Pi deficiency at the morphological, physiological, metabolic, and molecular levels. Results KN199 was more tolerant to Pi deficiency than CS with significantly increased root biomass and R/S ratio. Root traits, the total root length, total root surface area, and total root volume, were remarkably enhanced by Pi deficiency in KN199. The shoot total P and soluble Pi concentrations of KN199 were significantly higher than those of CS, but not in roots. In KN199, high Pi level in shoots is a higher priority than that in roots under Pi deficiency. It was probably due to differentially regulation in the miR399-mediated signaling network between the shoots of the two cultivars. The Pi deficiency-induced root architecture adaptation in KN199 was attributed to the regulation of the hormone-mediated signaling (ethylene, gibberellin, and jasmonates). The expression of genes associated with root development and Pi uptake was enhanced in KN199. Some primary metabolites (amino acids and organic acids) were significantly accumulated in roots of KN199 under Pi deficiency. Conclusions The low-Pi tolerant wheat cultivar KN199 possessed greater morphological and primary metabolic adaptations in roots than CS under Pi deficiency. The adaption and the underlying molecular mechanisms in wheat provide a better understanding of the Pi-deficiency tolerance and the strategies for improving Pi efficiency in wheat.

Abstract Background Hepatitis C virus (HCV) causes life-threatening chronic infections. Implementation of novel, economical or widely available screening tools can help detect unidentified cases and facilitate their linkage to care. We investigated the relationship between chronic HCV infection and a potential complete blood count biomarker (the monocyte-to-platelet ratio) in the United States. Methods The analytic dataset was selected from cycle years 2009–2016 of the National Health and Nutrition Examination Survey. Complete case data- with no missingness- was available for n = 5281 observations, one-hundred and twenty-two (n = 122) of which were exposed to chronic HCV. The primary analysis used survey-weighted logistic regression to model the effect of chronic HCV on the monocyte-to-platelet ratio adjusting for demographic and biological confounders in a causal inference framework. Missing data and propensity score methods were respectively performed as a secondary and sensitivity analysis. Results In the analytic dataset, outcome data was available for n = 5281 (n = 64,245,530 in the weighted sample) observations of which n = 122 (n = 1,067,882 in the weighted sample) tested nucleic acid positive for HCV. Those exposed to chronic HCV infection in the United States have 3.10 times the odds of a high monocyte-to-platelet ratio than those not exposed (OR = 3.10, [95% CI: 1.55–6.18]). Conclusion A relationship exists between chronic HCV infection and the monocyte-to-platelet ratio in the general population of the United States. Reversing the direction of this association to predict chronic HCV infection from complete blood counts, could provide an economically feasible and universal screening tool, which would help link patients with care.

The SARS-CoV-2 belongs to the coronavirus family, which also includes common endemic coronaviruses (HCoVs). We hypothesized that immunity to HCoVs would be associated with stronger immunogenicity from SARS-CoV-2 vaccines. The study included samples from the COSRIP observational cohort study of adult paramedics in Canada. Participants provided blood samples, questionnaire data, and results of COVID-19 testing. Samples were tested for anti-spike IgG against SARS-CoV-2, HCoV-229E, HCoV-HKU1, HCoV-NL63, and HCoV-OC43 antigens. We first compared samples from vaccinated and unvaccinated participants, to determine which HCoV antibodies were affected by vaccination. We created scatter plots and performed correlation analysis to estimate the extent of the linear relationship between HCoVs and SARS-CoV-2 anti-spike antibodies. Further, using adjusted log-log multiple regression, we modeled the association between each strain of HCoV and SARS-CoV-2 antibodies. Of 1510 participants (mean age of 39 years), 94 (6.2%) had a history of COVID-19. There were significant differences between vaccinated and unvaccinated participant in anti-spike antibodies to HCoV-HKU1, and HCoV-OC43; however, levels for HCoV-229E and HCoV-NL63 were similar (suggesting that vaccination did not affect these baseline values). Among vaccinated individuals without prior COVID-19 infection, SARS-COV-2 anti-spike IgG demonstrated a weak positive relationship between both HCoV-229E (r = 0.11) and HCoV-NL63 (r = 0.12). From the adjusted log-log multiple regression model, higher HCoV-229E and HCoV-NL63 anti-spike IgG antibodies were associated with increased SARS-COV-2 anti-spike IgG antibodies. Vaccination appears to result in measurable increases in HCoV-HKU1, and HCoV-OC43 IgG levels. Anti-HCoV-229E and HCoV-NL63 antibodies were unaffected by vaccination, and higher levels were associated with significantly higher COVID-19 vaccine-induced SARS-COV-2 antibodies.

Abstract Background The 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD) and meta-regression methods to assess the evidence supporting the WHO recommendations and whether they needed any refinements. Methods Access to IPD from three trials was granted through ClinicalStudyDataRequest.com (CSDR). Seven modelling approaches were applied and compared: 1) Unadjusted AgD network meta-analysis (NMA) – the original analysis; 2) AgD-NMA with meta-regression; 3) Two-stage IPD-AgD NMA; 4) Unadjusted one-stage IPD-AgD NMA; 5) One-stage IPD-AgD NMA with meta-regression (one-stage approach); 6) Two-stage IPD-AgD NMA with empirical-priors (empirical-priors approach); 7) Hierarchical meta-regression IPD-AgD NMA (HMR approach). The first two were the models used previously. Models were compared with respect to effect estimates, changes in the effect estimates, coefficient estimates, DIC and model fit, rankings and between-study heterogeneity. Results IPD were available for 2160 patients, representing 6.5% of the evidence base and 3 of 24 edges. The aspect of the model affected by the choice of modeling appeared to differ across outcomes. HMR consistently generated larger intervals, often with credible intervals (CrI) containing the null value. Discontinuations due to adverse events and viral suppression at 96 weeks were the only two outcomes for which the unadjusted AgD NMA would not be selected. For the first, the selected model shifted the principal comparison of interest from an odds ratio of 0.28 (95% CrI: 10.17, 0.44) to 0.37 (95% CrI: 0.23, 0.58). Throughout all outcomes, the regression estimates differed substantially between AgD and IPD methods, with the latter being more often larger in magnitude and statistically significant. Conclusions Overall, the use of IPD often impacted the coefficient estimates, but not sufficiently as to necessitate altering the final recommendations of the 2018 WHO Guidelines. Future work should examine the features of a network where adjustments will have an impact, such as how much IPD is required in a given size of network.

Supply and demand management of Hirmand water resources is one of the most important problems facing by policy makers and they will not be able to manage this sector properly without specifying the future prospects of the Hirmand Area. The main objective of the research is to determine the priority of future allocation of water resources in the Hirmand Area by using dynamic optimization models in different climatic conditions in agricultural, household, public and environmental sectors. The method of this research is based on the applied scientific method. The required statistics and information are obtained by the library method. In this research, the water demand functions in the agricultural, household, public and environmental sectors as well as the water supply function are achieved initially in different climatic conditions and then the general objective function for determining the allocation priority is estimated by using EVIEWS and GAMS soft wares. The results showed that in different conditions for agricultural sector, water demand is inversely related to water price, therefore under drought, wet and normal conditions, if the water price increases by one percent, the product will have a negative value decrease by 4.4%, 88% and 1.006% respectively. Moreover, since in this model the demand function for water is only a function of the price, the return to the scale is decreasing and Iso Quant Curve in the agricultural sector has a negative technical substitution rate in all aquatic conditions. In household demand, the results showed that with increase in water price, consumption decreases and rise of price is a necessary condition for reducing consumption, but is not sufficient. The average consumption based on the current trend is 12.42 M3 per month for each household. The reaction in the amount of demand change versus the change in the number of stormy days is positive and equal to 0.39. The results of the study for determination of water allocation indicate that if the next year is drought, priority of allocating for household sector will be (44%) - agriculture (41%) - Public (10%) and environmental (5%). In normal year, allocation priority will be (41%) household - (37%) agriculture - (14%) environmental and public sector (8%). While in rainy year, the allocation of priority has recorded for agriculture (43%) - domestic (39%) - environmental (15%) and public (7%). At the end some strategic policies based on research findings are suggested.

Background and Aim: Nowadays, toxic chemical contaminants in food are a major food safety problem in Bangladesh. Among toxic food contaminants, formalin is used to preserve fruit, vegetables, and fish, where urea is used for the whitening of rice and puffed rice. The purpose of this study was to determine the biochemical and histopathological effects on the liver of young and adult pigeons after exposure to formalin and urea contaminated feed. Materials and Methods: A total of 15 young and 15 adult pigeons were divided into control group, formaldehyde exposed group (2.5 mL formalin/kg feed), and urea exposed (1 g/kg feed) group. Each group consisted of five pigeons. After the experimentation procedures, the blood samples were collected for biochemical study, and the liver tissue was collected for histomorphological study. The statistical analysis was performed using the Student's t-test, and p

Abstract Background The use of individual patient data (IPD) in network meta-analyses (NMA) is rapidly growing. This study aimed to determine, through simulations, the impact of select factors on the validity and precision of NMA estimates when combining IPD and aggregate data (AgD) relative to using AgD only. Methods Three analysis strategies were compared via simulations: 1) AgD NMA without adjustments (AgD-NMA); 2) AgD NMA with meta-regression (AgD-NMA-MR); and 3) IPD-AgD NMA with meta-regression (IPD-NMA). We compared 108 parameter permutations: number of network nodes (3, 5 or 10); proportion of treatment comparisons informed by IPD (low, medium or high); equal size trials (2-armed with 200 patients per arm) or larger IPD trials (500 patients per arm); sparse or well-populated networks; and type of effect-modification (none, constant across treatment comparisons, or exchangeable). Data were generated over 200 simulations for each combination of parameters, each using linear regression with Normal distributions. To assess model performance and estimate validity, the mean squared error (MSE) and bias of treatment-effect and covariate estimates were collected. Standard errors (SE) and percentiles were used to compare estimate precision. Results Overall, IPD-NMA performed best in terms of validity and precision. The median MSE was lower in the IPD-NMA in 88 of 108 scenarios (similar results otherwise). On average, the IPD-NMA median MSE was 0.54 times the median using AgD-NMA-MR. Similarly, the SEs of the IPD-NMA treatment-effect estimates were 1/5 the size of AgD-NMA-MR SEs. The magnitude of superior validity and precision of using IPD-NMA varied across scenarios and was associated with the amount of IPD. Using IPD in small or sparse networks consistently led to improved validity and precision; however, in large/dense networks IPD tended to have negligible impact if too few IPD were included. Similar results also apply to the meta-regression coefficient estimates. Conclusions Our simulation study suggests that the use of IPD in NMA will considerably improve the validity and precision of estimates of treatment effect and regression coefficients in the most NMA IPD data-scenarios. However, IPD may not add meaningful validity and precision to NMAs of large and dense treatment networks when negligible IPD are used.

Formaldehyde (FA), a ubiquitous environmental pollutant, has long been suspected to possess reproductive toxicity. Here, we investigated the histopathological alteration of male gonads following exposure to FA-contaminated feed (40% aqueous solution of FA; 2.5 ml formalin/kg feed) in pigeons for 15 days. The mean body weights were not changed significantly in FA-contaminated feed exposed pigeons compared with control pigeons. The hemoglobin concentration was significantly decreased and serum enzyme aspartate transaminase (AST) was significantly increased in FA-exposed pigeons in comparison with control pigeons. Histologically, the structural components of the testes are the seminiferous tubules and interstitial tissues, which are surrounded by a connective tissue capsule. In control pigeons, the size and shape of seminiferous tubules were normal with a regular arrangement of spermatogenic cells. In FA-exposed pigeons, the testicular capsule was thickened and degeneration of spermatogenic cells in the seminiferous tubules was observed. The number of spermatogenic cells was significantly decreased in the seminiferous tubules of FA-exposed pigeons in comparison with control pigeons, indicating that the low exposure of FA affects the spermatogenic cells populations in male birds. The present results suggested that FA might cause infertility in birds. [ J Adv Biotechnol Exp Ther 2020; 3(3.000): 152-157]

From a sustainability standpoint, TiO2 semiconductor photocatalyst has a lot of potential in water purification. However, due to TiO2's high band gap and rapid recombination rate of electron/hole (e−/h+) pairs, visible light exposure is not practicable. To overcome these limitations, this study investigated the effects of phosphorous (P) doping and multi-walled carbon nanotubes (MWCNTs) insertion in the TiO2 matrix. The thin films form of the photocatalyst was focused on to avoid the challenges associated with the usage of powder form photocatalyst. Thin films of TiO2, TiO2/MWCNTs and phosphorous (P)-doped TiO2/MWCNTs composites have been satisfactorily prepared on glass substrates by a newly developed facile sol-gel drop coating (SGDC) method. Characterization of the prepared samples for morphology, structure, and other properties was done by using Field Emission Scanning Electron Microscopy (FESEM), Fourier Transform Infrared Spectroscopy (FTIR), X-ray diffraction (XRD), and Ultraviolet–Visible (UV–Vis) absorption spectroscopy. The XRD pattern of all thin films exhibited an anatase phase of the TiO2 crystal lattice, and calculation of lattice parameters revealed a fair match of lattice values of P-doped TiO2/MWCNTs thin films with the standard value of the same. The photocatalytic activity was estimated by the degradation of methylene blue (MB) dye in water under visible light exposure. The efficiency percentage of the as synthesized P-doped TiO2/MWCNTs thin films was more than doubled when compared to pure TiO2 and MWCNTs-TiO2. The enhancement of photocatalytic activity of P-doped TiO2/MWCNTs thin films is due to the photo-induced electron absorption effect by MWCNTs and the electron trap effect by P, a non-metal within the TiO2 matrix. Additionally, P doping within TiO2 also lowers the band gap, which in turn helps to exhibit pronounced photo-catalytic activity in the visible light region. A first-order kinetics model fitted the experimental photodegradation data well. The findings of the study suggest that P-doped TiO2/MWCNTs composite thin films prepared by the SGDC method can be widely applied in waste water treatment using visible light exposure.

ABSTRACT SARS-CoV-2 seroprevalence studies may be complicated by vaccination efforts. It is important to characterize the ability of serology methods to correctly distinguish prior infection from postvaccination seroreactivity. We report the performance of the Meso Scale Discovery (MSD) V-PLEX COVID-19 Coronavirus Panel 2 IgG assay. Using serum samples from a prospective cohort of paramedics, we calculated the performance of the V-PLEX nucleocapsid (“N”) assay to classify prior SARS-CoV-2 infections, defined as a (i) history of a positive SARS-CoV-2 PCR test or (ii) positive serology results using the Roche Elecsys total nucleocapsid anti-SARS-Cov-2 assay. We calculated sensitivity and specificity at the optimal threshold (defined by the highest Youden index). We compared subgroups based on vaccination status, and between models that excluded prior infections 3 to 12 months before sample collection. Of 1119 participants, 914 (81.7%) were vaccinated and 60 (5.4%) had evidence of a preceding SARS-CoV-2 infection. Overall and within vaccinated and unvaccinated subgroups, the optimal thresholds were 828 AU/mL, 827 AU/mL, and 1324 AU/mL; with sensitivities of 0.95 (95% CI: 0.94 to 0.96), 0.95 (0.94 to 0.96), 0.94 (0.92 to 0.96) and specificities of 0.88 (0.86 to 0.90), 0.87 (0.85 to 0.89), and 0.94 (0.89 to 0.98), respectively. N-assay specificity was significantly better in unvaccinated (versus vaccinated) individuals (P = 0.005). Overall optimal thresholds based on the AUC values were higher for samples from unvaccinated participants, especially when examining infections within the preceding 9 months (5855 versus 1704 AU/mL). Overall, V-PLEX nucleocapsid assay cutoff values were higher among unvaccinated individuals. Specificity was also significantly higher among unvaccinated individuals. Different thresholds were required to achieve optimal test performance, especially for detecting SARS-CoV-2 infections within the preceding 9 months. IMPORTANCE Among a cohort of adult paramedics in Canada, we investigated the performance of nucleocapsid (N) antibody detection (measured with a V-PLEX assay) to identify previous COVID-19 infections and compared differences among vaccinated and unvaccinated. Our data indicate that vaccinated and unvaccinated groups require different thresholds to achieve optimal test performance, especially for detecting COVID-19 within the preceding 9 months. Overall, specificity was significantly higher among unvaccinated, compared to vaccinated individuals.

Social media plays an important role among the masses and students all over the world. Here, in this study, the main aim is to explore the role of social media among the undergraduate college-goers of Assam in learning English. The study covers the available social media platforms, such as WhatsApp, Facebook, Twitter, Instagram, YouTube, Messenger, and IMO. For this purpose, the researchers imply a qualitative approach along with a survey method, which includes a questionnaire on the web. It has four parts, namely access to ICT tools, competency to use social media, elements influencing the use of social media, and the perceptions of the English language when they use social media. It is distributed to the undergraduate students in the form of Google Forms through WhatsApp. The findings indicated that the students learn new things and gather new knowledge using social media. According to the result, social media plays an important role, and it helps them improve all their skills in the English language. Hence, the learners may be encouraged to engage themselves to use social media in English to master it and improve their proficiency.

Over 60% of the global productions of industrial enzymes are proteolytic enzymes in which about 35% are alkaline proteases. The current microbial sources are unable to reach industrial demands of alkaline protease which led scientists to search new sources with enhanced enzyme activity. Therefore, we applied UV irradiation to develop a Pseudomonas aeruginosa mutant as a new source of enhanced protease activity, followed by cultural and nutritional optimization. The mutagenesis was carried out by exposing parent strains to UV radiation (30w, 2537 Å) at 25 ºC with a different time interval. The protease activity was estimated as relative protease activity and standard protease assay (OD660). Among all, mutant strain P. aeruginosaM25 (PA-M25) exhibited 75.47% increased protease activity over the parent strain in submerged fermentation. It showed 612.84±2.50 U/ml of alkaline protease production compared to 349.26±2.57 U/ml by wild-type strain (significant at P≤0.005). Besides, the effects of nutritional factors on the protease production by PA-M25 were also studied. We found the optimal alkaline protease production in the medium (adjusted to pH 9.0) supplemented with 1% (w/v) glucose as carbon source, 0.5% (w/v) casein as nitrogen source and 2% (w/v) NaCl when incubated at 35 ºC for 48 h without agitation. We believe that the mutant PA-M25 could be a potential candidate to meet the growing protease demands. However, further assessments regarding the characterization of the protease enzyme, as well as the industrial fitness of the mutant, are warranted. [ J Adv Biotechnol Exp Ther 2020; 3(2.000): 135-142]

Abstract In veneer-drying facilities, controllers face many challenges to maintain desired parameters in the final product based on customer’s needs. The major challenge is setting process parameters to control the temperature and humidity within the various sections in the drying machine to obtain the desired properties of the final product. The regression tree approach can be used to simplify the complex relationship among process and product variables for identifying critical factors for drying veneer and achieving the desired range of veneer temperature. In this study, we investigated veneer-drying conditions and the short-term effect of climatic variables on veneer temperature. We have shown a three-step process to develop an optimal regression tree for veneer temperature. From the developed optimal tree, we are able to identify the most important threshold points of predictor space and adjustment for the climatic variables on the temperature of veneer sheets. The findings of this study were further investigated in an industrial setting and the desired veneer temperatures were attained for the final product. This application shows that we can follow the path of the optimal tree to pinpoint the most desired veneer temperature outcome. The developed optimal tree is relatively easy to use and interpret to estimate the average response of veneer temperature.