Clinical profile and serological correlation with haemolysis in DAT-positive autoimmune haemolytic anaemia patients in Bangladesh.

Discerning the type of autoimmune haemolytic anaemia (AIHA) is crucial for transfusion support and initiation of treatment. This study aimed to establish the clinical profile and serological character of red cell autoantibodies and to investigate the relationship with haemolysis in AIHA patients who were direct antiglobulin test (DAT)-positive. A total of 59 DAT-positive AIHA patients were included in this study. Clinical, laboratory and serological findings were evaluated to find the gradation of haemolysis and to investigate its correlation with age, sex, type of autoantibody and level of autoantibody. Study findings revealed that most patients (89.8%) had haemolysis, wherein moderate haemolysis (67.8%) was predominant. Weakness, palpitations, fever, pallor, tachycardia and splenomegaly were common among patients with severe and moderate haemolysis. The majority (66.1%) had an associated disorder. Warm autoantibody was the most common, followed by cold and mixed cases. The severity of haemolysis correlated strongly with the strength of the DAT reaction (Cramer V 0.636, p<0.001). These findings may be useful to clinicians while determining a treatment plan. The direct relationship between severity of haemolysis and strength of DAT needs further exploration in a large population to establish whether it can be used as a tool to formulate a treatment plan when assessing AIHA patients in low resourced countries.

A comprehensive dataset for sentiment and emotion classification from Bangladesh e-commerce reviews.

In the rapidly evolving domain of e-commerce, analyzing customer feedback through reviews is crucial, particularly for understanding and enhancing consumer experience in the Bangladeshi market. Our comprehensive dataset, derived from two Bangladeshi e-commerce platforms, Daraz and Pickaboo, features a diverse collection of reviews in both Bengali and English, covering a broad range of products. These reviews are not only rich in linguistic variety but also encapsulate a spectrum of emotions, some even conveyed through emojis, offering a deep dive into consumer sentiment. Expert annotators have meticulously examined and categorized each review, classifying emotions into five distinct types - Happiness, Sadness, Fear, Anger, and Love - and sentiments into Positive (Happiness, Love) and Negative (Sadness, Anger, Fear) categories. This level of detailed annotation enables precise assessments of customer emotions and preferences, which are essential for evaluating and improving existing product offerings. Moreover, the insights gleaned from this dataset are invaluable for guiding future product development and uncovering new opportunities in the dynamic Bangladeshi market. Ultimately, this dataset not only serves as a significant resource for sentiment analysis using natural language processing (NLP) techniques but also contributes valuable insights into the unique consumer behavior patterns in Bangladesh, enriching the NLP community's understanding of diverse market dynamics.

ArsenicSkinImageBD: A comprehensive image dataset to classify affected and healthy skin of arsenic-affected people.

Compared to other popular research domains, dermatology got less attention among machine learning researchers. One of the main concerns for this problem is an inadequate dataset since collecting samples from the human body is very sensitive. In recent years, arsenic has emerged as a significant issue for dermatologists. Arsenic is a highly toxic substance found in the earth's crust whose small amounts can be very injurious to the human body. People who are exposed to arsenic for a long time through water and food can get cancer and skin lesions. With a view to contributing to this aspect, this dataset has been organized with the help of which the researchers can understand the impact of this contamination and design a solution using artificial intelligence. To the best of our knowledge, this is the first standard, easy-to-use, and open dataset of arsenic diseases. The images were collected from four places in Bangladesh, under the Department of Public Health Engineering, Chapainawabganj, where they are working on arsenic contamination. The dataset has 8892 skin images, with half of them showing people with arsenic effects and the other half showing mixed skin images that are not affected by arsenic. This makes the dataset useful for treating people with arsenic-related conditions. Eventually, this dataset can attract the attention of not only the machine learning researchers, but also scientists, doctors, and other professionals in the associated research field.

Comprehensive dataset of annotated rice panicle image from Bangladesh.

Bangladesh's economy is primarily driven by the agriculture sector. Rice is one of the staple food of Bangladesh. The count of panicles per unit area serves as a widely used indicator for estimating rice yield, facilitating breeding efforts, and conducting phenotypic analysis. By calculating the number of panicles within a given area, researchers and farmers can assess crop density, plant health, and prospective production. The conventional method of estimating rice yields in Bangladesh is time-consuming, inaccurate, and inefficient. To address the challenge of detecting rice panicles, this article provides a comprehensive dataset of annotated rice panicle images from Bangladesh. Data collection was done by a drone equipped with a 4 K resolution camera, and it took place on April 25, 2023, in Bonkhoria Gazipur, Bangladesh. During the day, the drone captured the rice field from various heights and perspectives. After employing various image processing techniques for curation and annotation, the dataset was generated using images extracted from drone video clips, which were then annotated with information regarding rice panicles. The dataset is the largest publicly accessible collection of rice panicle images from Bangladesh, consisting of 2193 original images and 5701 augmented images.

Knowledge, attitude, and practice of university students towards monkeypox in Bangladesh.

The recent outbreak of viral zoonotic disease-monkeypox-caused by the monkeypox virus, has infected many people worldwide. This study aims to explore the knowledge, attitudes, and practices (KAP) concerning monkeypox among university students in Bangladesh. Data were collected using purposive snowball sampling from 887 university students through an online survey using Google Form. The participants were mostly in their twenties (M = 22.33 [SD 2.01] years), and they spent, on average, 2.59 [SD 1.91] hours/day on electronic and social media. The participants generally showed moderate knowledge (39.5%), low attitude (25.1%), and moderate practice (48.6%) toward monkeypox, with 47.6% having had a moderate KAP score. Findings further showed that personal attributes of university students, i.e., age, sex, year of schooling, residence, living status, geographical distribution, e.g., division, were statistically and significantly associated with knowledge, attitudes, and practices regarding monkeypox and overall KAP score. It is also apparent that health status, susceptibility to monkeypox, and exposure to social media were the most common factors significantly associated with knowledge, attitudes, and practices regarding monkeypox and overall KAP score. The current study's findings underscore the need for developing appropriate information, education, and communication (IEC) materials and their dissemination, which could play an important role in reducing the risk of monkeypox and similar other infectious diseases, particularly among students in Bangladesh.

Qualitative assessment of programmatic constraints in delivery of effective interventions for improving maternal nutrition in Bangladesh.

Introduction: Maternal undernutrition is highly prevalent in most of the developing countries. Prevalence of both extremes of maternal malnutrition (undernutrition and overweight/obesity) are common in those countries. For Bangladesh, the scenario is not different. The Government of Bangladesh recognises maternal nutrition as a public health priority and addresses the issue in its policies and programmes. We identified and analysed the existing maternal nutrition programmes and determined the bottlenecks in implementing the programmes in Bangladesh using qualitative approach. Methods: We followed a qualitative research approach and conducted 25 key informant interviews with the programme managers and policymakers, 10 in-depth interviews with the service providers and six focus group discussions with the pregnant women to identify the constraints of programme implementation. We analysed data using thematic and inductive approaches of qualitative research methods. Results: We have found that successful implementation of maternal nutrition intervention was being hampered by both the demand and supply side issues. On the demand side, major constraints were financial inability of the families to avail maternal nutrition-related services, ignorance of the family members and cultural barriers of using maternal nutrition-related services. Lack of priority and heavy workload of the service providers, lack of human resources, poor monitoring system, lack of medicine to supply and incoordination have been identified as major supply-side constraints in providing maternal nutrition-related interventions in Bangladesh. Conclusion: Both supply side and demand side issues are responsible for the existing bottlenecks in implementing maternal nutrition-related programmes in Bangladesh. Findings of this study will help the policymakers to learn about the programmatic constraints regarding maternal nutrition services in Bangladesh.

Stool specimen for diagnosis of pulmonary tuberculosis in adults: a systematic review.

OBJECTIVE: To assess the diagnostic accuracy of stool specimens to diagnose pulmonary tuberculosis (PTB) in adults. DESIGN: Systematic review. DATA SOURCES: MEDLINE (Ovid), Embase (Ovid), Web of Science and the Cochrane database were searched from inception to 9 March 2023-10 March 2023 using a comprehensive search strategy; reference lists of selected articles and relevant review articles were manually searched. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Studies in English reporting diagnostic performance of stool specimens against respiratory specimens using mycobacterial culture or smear microscopy or Xpert assay to diagnose PTB in adults were eligible for this systematic review. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened the retrieved citations and extracted data. The risk of bias and applicability of results were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Narrative data synthesis was performed. RESULTS: A total of 1658 citations were screened, and 28 full-text articles were assessed. Nine studies met the inclusion criteria. The reported sensitivity and specificity of stool culture varied between 21.4% and 63.9%, and 61.5% and 100%, respectively. In stool smear microscopy, sensitivities and specificities ranged from 12.1% to 53.9%, and from 79.5% to 100%, respectively. The reported sensitivities of PCR assays, including Xpert assays, ranged from 69.7% to 100%, with specificities ranging from 69.8% to 100%. Most of the studies had a low risk of bias and a low applicability concern in all domains. CONCLUSION: This systematic review could not conclude on the diagnostic accuracy of stool specimens for PTB diagnosis in adults. Further studies are required to evaluate the accuracy of stool specimens in adults to enable meta-analyses in updates of this review as well as other systematic reviews. PROSPERO REGISTRATION NUMBER: CRD42021245203.

Immunogenic multi-epitope-based vaccine development to combat cyclosporiasis of immunocompromised patients applying computational biology method.

Cyclospora cayetanensis infections, also known as cyclosporiasis, persist to be the prevalent emerging protozoan parasite and an opportunist that causes digestive illness in immunocompromised individuals. In contrast, this causal agent can affect people of all ages, with children and foreigners being the most susceptible populations. For most immunocompetent patients, the disease is self-limiting; in extreme circumstances, this illness can manifest as severe or persistent diarrhea as well as colonize on secondary digestive organs leading to death. According to recent reports, worldwide 3.55% of people are infected by this pathogen, with Asia and Africa being more prevalent. For the treatment, trimethoprim-sulfamethoxazole is the only licensed drug and does not appear to work as well in some patient populations. Therefore, the much more effective strategy to avoid this illness is immunization through the vaccine. This present study uses immunoinformatics for identifying a computational multi-epitope-based peptide vaccine candidate for Cyclospora cayetanensis. Following the review of the literature, a highly efficient, secure, and vaccine complex based on multi-epitopes was designed by utilizing the identified proteins. These selected proteins were then used to predict non-toxic and antigenic HTL-epitopes, B-cell-epitopes, and CTL-epitopes. Ultimately, both a few linkers and an adjuvant were combined to create a vaccine candidate with superior immunological epitopes. Then, to establish the vaccine-TLR complex binding constancy, the TLR receptor and vaccine candidates were placed into the FireDock, PatchDock, and ClusPro servers for molecular docking and iMODS server for molecular-dynamic simulation. Finally, this selected vaccine construct was cloned into Escherichia coli strain-K12; thus, the constructed vaccines against Cyclospora cayetanensiscould improve the host immune response and can be produced experimentally.

Occupational exposure to livestock and risk of tuberculosis and brucellosis: A systematic review and meta-analysis.

Occupational diseases are caused by zoonotic pathogens, which spread to humans through various types and intensities of human-livestock contact at work. In the present era, human brucellosis and tuberculosis remain the predominant occupational diseases throughout the world. However, the actual percentage of reported cases that are acquired from various livestock-related occupational groups is not well known. Therefore, we carried out a systematic review and meta-analysis of previous scatter studies mentioned the occurrence of human brucellosis and tuberculosis. From 2000 to 2021, a computer search of PubMed, Science Direct, Google Scholar, BioMed and Scopus was conducted and finally we found 71 studies (brucellosis = 54, tuberculosis = 17), which were included in this meta-analysis to calculate the aggregate prevalence using the random effects model. Moreover, I 2 statistic, Cochran's Q statistic heterogeneity and subgroup analysis were also performed. The analysis of the data showed that among the various livestock-related occupational groups, the global pooled prevalence of tuberculosis was 19% (95% CI: 09-30), which was higher than brucellosis 14% (95% CI: 10-18). In addition, North America and Africa were reported as the continents of the maximum prevalence rate of 25% (95% CI: -08-58) and 16% (95% CI: 11-21) for tuberculosis and brucellosis than the other continents. Afterwards, the individual's occupation was broken down into the following four groups: farm worker, livestock owner, livestock connected person and abattoir worker. The significant association was found between slaughterhouse workers and brucellosis prevalence (20%; 95% CI: 13-27) as well as the livestock owners and tuberculosis prevalence (28%; 95% CI: 06-50). Likely, a maximum prevalence of tuberculosis was documented among workers ages 20 to 49 years, and of brucellosis among those between the ages of 20 and 25, which suggests that age also had a role. Therefore, it is concluded that the livestock-related occupational groups were found to be at an increased risk of adverse zoonotic disease outcomes. Future studies could be focused on specific occupational group that are in high risk of disease transmission to minimize the effect of these two hazardous pathogens.

Exploratory Algorithm of a Multi-epitope-based Subunit Vaccine Candidate Against Cryptosporidium hominis: Reverse Vaccinology-Based Immunoinformatic Approach.

Cryptosporidiosis is the leading protozoan-induced cause of diarrheal illness in children, and it has been linked to childhood mortality, malnutrition, cognitive development, with retardation of growth. Cryptosporidium hominis, the anthroponotically transmitted species within the Cryptosporidium genus, contributes significantly to the global burden of infection, accounting for the majority of clinical cases in numerous nations, as well as its emergence in the last decade is largely due to detections obtained through noteworthy epidemiologic research. Nevertheless, there is no vaccine available, and the only licensed medication, nitazoxanide, has been demonstrated to have efficacy limitations in a number of patient groups recognized to be at high risk of complications. Therefore, current study delineates the computational vaccine design for Cryptosporidium hominis , the notable pathogen for enteric diarrhea. Firstly, a comprehensive literature search was conducted to identify six proteins based on their toxigenicity, allergenicity, antigenicity, and prediction of transmembrane helices to make up a multi-epitope-based subunit vaccine. Following that, antigenic non-toxic HTL epitope, CTL epitope with B cell epitope were predicted from the selected proteins and construct a vaccine candidate with adding an adjuvant and some linkers with immunologically superior epitopes. Afterwards, the constructed vaccine candidates and TLR2 receptor were put into the ClusPro server for molecular dynamic simulation to know the binding stability of the vaccine-TLR2 complex. Following that, Escherichia coli strain K12 was used as a cloning host for the chosen vaccine construct via the JCat server. As a result of the findings, it was resolute that the proposed chimeric peptide vaccine could improve the immune response to Cryptosporidium hominis.

Insight into the first multi-epitope-based peptide subunit vaccine against avian influenza A virus (H5N6): An immunoinformatics approach.

The rampant spread of highly pathogenic avian influenza A (H5N6) virus has drawn additional concerns along with ongoing Covid-19 pandemic. Due to its migration-related diffusion, the situation is deteriorating. Without an existing effective therapy and vaccines, it will be baffling to take control measures. In this regard, we propose a revers vaccinology approach for prediction and design of a multi-epitope peptide based vaccine. The induction of humoral and cell-mediated immunity seems to be the paramount concern for a peptide vaccine candidate; thus, antigenic B and T cell epitopes were screened from the surface, membrane and envelope proteins of the avian influenza A (H5N6) virus, and passed through several immunological filters to determine the best possible one. Following that, the selected antigenic with immunogenic epitopes and adjuvant were linked to finalize the multi-epitope-based peptide vaccine by appropriate linkers. For the prediction of an effective binding, molecular docking was carried out between the vaccine and immunological receptors (TLR8). Strong binding affinity and good docking scores clarified the stringency of the vaccines. Furthermore, molecular dynamics simulation was performed within the highest binding affinity complex to observe the stability, and minimize the designed vaccine's high mobility region to order to increase its stability. Then, Codon optimization and other physicochemical properties were performed to reveal that the vaccine would be suitable for a higher expression at cloning level and satisfactory thermostability condition. In conclusion, predicting the overall in silico assessment, we anticipated that our designed vaccine would be a plausible prevention against avian influenza A (H5N6) virus.

Global prevalence of zoonotic pathogens from pigeon birds: A systematic review and meta-analysis.

Pigeons have been considered the most preferred companion for human civilizations since prehistoric times. Despite the fact that pigeons offer the most palatable and nutritious food and provide pleasure to humans, they can pose a health risk because of carrying infectious and zoonotic organisms. Moreover, the scanty of systematic reports on the occurrence of zoonotic pathogens in pigeon makes the situations worst. Hence, the current study conducted a systematic review and meta-analysis to evaluate the global prevalence of zoonotic pathogens among the pigeon population from existing segregated literatures. Four internationally recognized databases including Google Scholar, Scopus, PubMed, and Science Direct were used to search the published studies from January 2000 to October 2021. Analyzing the total 18,589 samples, mean prevalence estimates of pigeon pathogens worldwide were found to be 17% (95% CI:13-21) whereas serological and molecular prevalence were reported as 18% (95% CI:12-23) and 17% (95% CI:10-23). Meanwhile, virus, bacteria, and protozoal pathogens were found to be 21% (10-32%), 17% (12-23%), and 14% (10-19%), respectively. Moreover, continent wise analysis of all zoonotic pigeon pathogens has revealed the highest prevalence rate in Asia 20% (95% CI: 14-26%), followed by Europe 16% (95% CI: 08-24%), Africa 16% (95% CI: 07-24%), and America (North and South) 10% (95% CI: 03-17%). Furthermore, the highest number of studies were reported from Iran showed the prevalence rate of 20%, China 13%, Bangladesh 37%, and Poland 15%. Therefore, this prevalence of data would be helpful to the policymakers to develop appropriate intervention strategies to prevent and control diseases in their respective locations.

Seawater fungi-derived compound screening to identify novel small molecules against dengue virus NS5 methyltransferase and NS2B/NS3 protease.

Dengue fever is a virus spread by mosquitoes that has no effective treatment or vaccination. Several dengue cases combined with the current COVID-19 pandemic, exacerbates this problem. Two proteins, NS5 methyltransferase and NS2B/NS3 primary protease complexes, are crucial for dengue viral replication and are the target sites for antiviral development. Thus, this study screened published literature and identified 162 marine fungus-derived compounds with active bioavailability. Following Lipinski's rules and antiviral property prediction, 41 compounds were selected for docking with NS5 methyltransferase and NS2B/NS3 protease (PDB ID: 6IZZ and 2FOM) to evaluate compounds that could stop the action of dengue viral protein complexes. To find the best candidates, computational ADME, toxicity, and drug target prediction were performed to estimate the potential of the multi-targeting fungal-derived natural compounds. Analyzing the result from 41 compounds, Chevalone E (-13.5 kcal/mol), Sterolic acid (-10.3 kcal/mol) showed higher binding energy against dengue NS2B/NS3 protease; meanwhile, Chevalone E (-12.0 kcal/mol), Brevione K (-7.4 kcal/mol), had greater binding affinity against NS5 methyltransferase. Consequently, this study suggests that Chevalone E is an effective inhibitor of NS5 methyltransferase and NS2B/NS3 protease. Ligand-based virtual screening from DrugBank was utilized to predict biologically active small compounds against dengue virus NS2B/NS3 major protease and NS5 methyltransferase. Both licensed medications, estramustine (DB01196) and quinestrol (DB04575), were found to be similar to Chevalone E, with prediction scores of 0.818 and 0.856, respectively. In addition, cholic acid (DB02659), acitretin (DB00459), and mupirocin (DB00410) are similar to Sterolic acid, zidovudine (DB00495), imipenem (DB01598), and nadolol (DB01203) are similar to Brocazine A, and budesonide (DB01222) and colchicine (DB01394) are related to Brevione K. These findings suggest that these could be feasible dengue virus treatment options, meaning that more research is needed.

Inhibitory Potentiality of Secondary Metabolites Extracted from Marine Fungus Target on Avian Influenza Virus-A Subtype H5N8 (Neuraminidase) and H5N1 (Nucleoprotein): A Rational Virtual Screening.

Highly contagious avian influenza virus' (AIV) subtypes, including H5N1 and H5N8 are considered as serious threats for poultry industry. Despite its severity, treatment and mitigation attempts are fall into baffling. Though a few approved anti-influenza medications are available, the M2 channel blockers amantadine and rimantadine, as well as the neuraminidase inhibitor oseltamivir are being less effective due to widespread drug resistance. To cope up with these circumstances, scientists have found nucleoprotein as a novice drug targeting site for H5N1. Hence, the current study used a rational screening method to find the best candidates for nucleoprotein inhibitors of H5N1 subtype and neuraminidase inhibitors for H5N8 subtype against pathogenic AIV. Finding the best candidates, molecular docking method and computational pharmacokinetics and pharmacology was developed to estimate the potential of the multi-targeting fungal-derived natural compounds for the development of drug. Chevalone E compound was found as the best inhibitor for both nucleoprotein and neuraminidase of H5N1 and H5N8 subtypes respectively, whereas, Brevione F and Brocazine-A for nucleoprotein with Penilactone-A and Aspergifuranone for neuraminidase. In case of drug prediction, the study recommends Estramustine and Iloprost against both nucleoprotein and neuraminidase. Besides these, Butorphanol, Desvenlafaxine, Zidovudine and Nadolol are the best drug candidates for nucleoprotein inhibitors, meanwhile, Sitaxentan, Ergoloid mesylate, Capecitabine and Fenoterol act as speculated candidates against neuraminidase.

Prevalence and predictors of pornography exposure during the third wave of the COVID-19 pandemic: A web-based cross-sectional study on students in Bangladesh.

Background: Pornography exposure, particularly among students, in Bangladesh, has increased in the twenty-first century. However, pornography exposure during the COVID-19 pandemic, when people were compelled to "stay at home" and relied extensively on the internet for all forms of activities, including academia, socializing, and communication, has remained unexplored. The present study aimed to assess the prevalence of pornography exposure among students during the third wave of the COVID-19 pandemic and to determine the associated predictors. Methods: A web-based cross-sectional study was carried out among students with certain specifications, i.e., current students at high school/college/university with access to the internet and valid social media accounts. By administering a semi-structured e-questionnaire using Google Forms, a total of 646 valid responses were retained for this study. The data were analyzed in two phases by Pearson's Chi-square and multiple logistic regression model, using IBM SPSS Statistics, version 25. The results were expressed as an adjusted odds ratio (AOR) with a 95% confidence interval (95% CI). Results: The findings suggest that 75.9% of students were exposed to pornography during the third wave of the COVID-19 pandemic and preferred to watch the amateur/professional genre of pornography. Pornography exposure was significantly associated with age and relationship status, as students aged 22-24 years (95% CI: 1.01-2.41; p = 0.045) and over 25 years (95% CI: 1.61-10.03; p = 0.003) were more likely to watch pornography, while married students and those in relationships (95% CI: 1.24-3.49; p = 0.006) also watched pornography during the pandemic. In contrast, students who were living alone (95% CI: 0.38-0.92; p = 0.021), were living in the Khulna division (95% CI: 0.16-0.52; p < 0.001) or had a negative attitude toward pornography (95% CI: 0.94-0.99; p = 0.002) were less likely to be exposed to pornography. Conclusion: Pornography exposure was higher among students in Bangladesh during the COVID-19 pandemic, and religiosity and disapproving attitudes toward pornography negatively influenced the pornography exposure. For a better understanding of the complex dynamics of socio-demographic issues with pornography exposure among students, extensive research is required for policymakers to devise appropriate strategies and interventions to ensure healthy and safe sex life for the younger population.

A systematic review and meta-analysis on prevalence and epidemiological risk factors of zoonotic Fascioliasis infection among the ruminants in Bangladesh.

The parasitic Fascioliasis is a zoonotic and economically significant disease for livestock and humans, creating public health concerns around the world, including in Bangladesh. Populations of Bangladesh are more vulnerable to this parasitic infestation for their intimate interactions. To tackles the adverse effects on humans from food animals, it is exigency to know the exact prevalence and associated risk factors of zoonotic Fascioliasis among ruminants. Therefore, the aim of this systematic review and meta-analysis was to determine the authentic knowledge of potential risk factors and prevalence among livestock populations. Four globally recognized databases, including Web of Science, Scopus, PubMed, and Google Scholar, along with local databases, were used to search the related studies since 2000. A total of 38 studies were selected for the meta-analysis, and the pooled prevalence of Fascioliasis was found at 20% (95 % CI: 15-25). A subgroup analysis was also performed for: species, age, sex, study duration, and sample size. The prevalence rate was found highest in cattle and sheep at 21% (95 % CI: 15-27), female individuals at 26% (95 % CI: 16-35), aged animals at 26% (95 % CI: 15-36), and rainy season at 25% (95 % CI: 16-34). This is the first systematic review and meta-analysis in Bangladesh that offers a comprehensive picture of the prevalence of Fascioliasis in ruminants and possible risk factors. Thus, this study will assist the government, policymakers, and veterinarians in implementing effective control measures by providing more detailed information about outbreak patterns.

Multi-epitope based subunit vaccine construction against Banna virus targeting on two outer proteins (VP4 and VP9): A computational approach.

Recently, RNA viruses have gained a mammoth concern for causing various outbreaks, and due to pandemics, they are acquiring additional attention throughout the world. An emerging RNA as well as vector-borne Banna Virus (BAV) is a human pathogen resulting in encephalitis, fever, headache, muscle aches, and severe coma. Besides human, pathogenic BAV was also detected from pigs, cattle, ticks, midges, and mosquitoes in Indonesia, China, and Vietnam. Due to high mutation tendency and dearth of a species barrier, this virus will consider as a significant threat in the near future throughout the planet, particularly in Africa. Despite of severe human case fatalities in several countries, there are no specific therapeutics, available vaccines, and other preventive measures against BAV. Thus, to find out the effective therapeutics and preventive strategies are crying exigency. In the present study, a unique multi-epitope-based peptide vaccine candidate is constructed using bioinformatics' tools that efficiently instigate immune cells for generating BAV antibodies. The potential vaccine candidates were developed using both T and B -cell epitopes. UniprotKB database was used to retrieve of two outer proteins (VP9 and VP4), and homologous sequences of BAV taxid: 7763, 649,604, 77,763, and 8453 were searched by NCBI BLAST. These serotypes are the most closely associated with the disease. Then combining the best-selected epitopes in various combinations with different adjuvants, three distinct vaccine candidates were formed. The validity tests were performed for the screened vaccine candidate regarding stability, allergenicity, and antigenicity parameters. Moreover, molecular dynamic simulations of the selected vaccine with TLR-8 immune receptor confirmed the stability of the binding pose and showed a significant response to immune cells. Thus, the results established that the designed chimeric peptide vaccine could enhance the immune response against BAV.

Changing trends in nutritional status of adolescent females: a cross-sectional study from urban and rural Bangladesh.

OBJECTIVES: Malnutrition remains a major problem among adolescents worldwide, but the types of nutritional problem impacting this group are changing significantly. This study aims to describe and analyse the trends in nutritional status and related epidemiological characteristics of 10 to 19 years old adolescent girls over time (2001 to 2018) in Bangladesh. METHODS: We extracted data from the Diarrhoeal Disease- Surveillance System of the International Centre for Diarrhoeal Disease Research Bangladesh. We performed χ2 test for trend to test for statistical significance of the changing trends of undernutrition and overnutrition among the study participants. Multivariable logistic regression model was fit to measure the strength of association, reported as adjusted OR (aOR) and corresponding 95% CIs. RESULTS: A total of 1224 and 628 adolescent females attended urban and rural treatment facilities, respectively, between 2001 and 2018. The proportion of stunting and thinness decreased substantially, whereas overweight has been observed to increase (1.7% to 7.4%, p<0.001) over the study period. Factors independently associated with stunting were illiteracy (aOR 2.39, 95% CI (1.68 to 3.39), p<0.001), monthly family income of less than US$100 (aOR 1.54, 95% CI (1.25 to 1.9), p<0.001) and family belonging to poorest wealth quintile (aOR 1.45, 95% CI (1.13 to 1.87), p=0.004). Younger participants (aOR 2.69, 95% CI (2.10 to 3.45), p<0.001), rural participants (aOR 1.71 95% CI (1.23 to 2.38), p<0.001), longer hospital stay (aOR 1.52, 95% CI (1.16 to 1.98), p=0.002) and monthly family income less than US$100 (aOR 1.44, 95% CI (1.09 to 1.89), p=0.009) were significantly associated with thinness. Conversely, overweight/obesity was associated with monthly family income more than US$100, duration of diarrhoea and rural participants. CONCLUSION: Undernutrition in adolescent girls has decreased with time, but the burden of overweight has increased. Higher literacy and better wealth status were found to be associated with the improved nutritional status of the participants.

Mother's dietary diversity and association with stunting among children <2 years old in a low socio-economic environment: A case-control study in an urban care setting in Dhaka, Bangladesh.

Mothers are often responsible for preparing nutritious foods in their households. However, the quality of mother's diets is often neglected, which may affect both mother's and child's nutrition. Because no single food contains all necessary nutrients, diversity in dietary sources is needed to ensure a quality diet. We aimed to study the association between mother's dietary diversity and stunting in children <2 years attending Dhaka Hospital of icddr,b, a diarrhoeal disease hospital in Dhaka, Bangladesh. A case-control study (n = 296) was conducted from November 2016 to February 2017. Data were collected from mothers of stunted children <2 years (length-for-age z score [LAZ] < -2) as "cases" and nonstunted (LAZ ≥ -1) children <2 years as "controls." Mothers were asked to recall consumption of 10 defined food groups 24 hr prior to the interview as per Guidelines for Minimum Dietary Diversity for Women. Among the mothers of cases, 58% consumed <5 food groups during the last 24 hr, compared with 45% in control mothers (P = 0.03). Children whose mothers consumed <5 food groups were 1.7 times more likely to be stunted than children whose mothers consumed ≥5 food groups (P = 0.04). Intake of food groups such as pulses, dairy, eggs, and vitamin A rich fruit was higher in control mothers. Proportion of mother's illiteracy, short stature, monthly family income