Background: Nipah virus (NiV) infection, often fatal in humans, is primarily transmitted in Bangladesh through the consumption of date palm sap contaminated by Pteropus bats. Person-to-person transmission is also common and increases the concern of large outbreaks. This study aimed to characterize the molecular epidemiology, phylogenetic relationship, and the evolution of the nucleocapsid gene (N gene) of NiV. Methods: We conducted molecular detection, genetic characterization, and Bayesian time-scale evolution analyses of NiV using pooled Pteropid bat roost urine samples from an outbreak area in 2012 and archived RNA samples from NiV case patients identified during 2012-2018 in Bangladesh. Results: NiV-RNA was detected in 19% (38/456) of bat roost urine samples and among them; nine N gene sequences were recovered. We also retrieved sequences from 53% (21 out of 39) of archived RNA samples from patients. Phylogenetic analysis revealed that all Bangladeshi strains belonged to NiV-BD genotype and had an evolutionary rate of 4.64 Â 10 À4 substitutions/site/year. The analyses suggested that the strains of NiV-BD genotype diverged during 1995 and formed two sublineages. Conclusion: This analysis provides further evidence that the NiV strains of the Malaysian and Bangladesh genotypes diverged recently and continue to evolve. More extensive surveillance of NiV in bats and human will be helpful to explore strain diversity and virulence potential to infect humans through direct or person-to-person virus transmission.

DiabCare Bangladesh 2008 evaluated the current status of diabetes care in Bangladesh as a continuation of similar cross-sectional study conducted previously in 1998. The current study recruited 1952 patients from general hospitals, diabetes clinics and referral clinics to study current scenario of diabetes management from 01 March 2009 to 31 March 2009. We report the results of type 2 diabetic population who constituted 95.3% (n=1860). Results showed deteriorating glycaemic control with mean HbA1c of 8.6±2.0% with only 23.1% of the patients achieving American Diabetes Association (ADA) target of <7%. 896 (47.0%) patients were hypertensive and 850 (94.9%) were on antihypertensive medication. 70.8% of patients had LDL levels >2.6 mmol/L; 43.8% had triglycerides >2.2 mmol/L; 44.1% had HDL<1 mmol/L despite 48% of the patients being on lipid lowering agents. Microvascular, macrovascular and severe late complications were reported in 39.2%, 9.9% and 12.1% patients respectively. The rates of diabetic complications were cataract 12.9%, microalbuminuria 15.7%, neuropathy symptoms 31.7%, leg amputation 1.2% and history of angina pectoris was 6.6%. Quality of life evaluation showed that about half of patients have poor quality of life. Also, there was poor adherence to diet, exercise and self testing of blood glucose. In conclusion, majority of the patients were still not satisfactorily controlled. There is an urgent need for effective remedial measures to increase adherence to practice guidelines and to educate both patients and healthcare personnel on importance of achieving clinical targets for metabolic control.

In this study, mechanisms of plasmid-mediated sulfamethoxazole resistances in the clinical strains of multi-drug resistant (MDR) Shigella flexneri 2a were elucidated for the first time in Bangladesh. From 2006 to 2011, a total of 200 S. flexneri 2a strains were randomly selected from the stock of the Enteric and Food Microbiology Laboratory of icddr,b. Antimicrobial susceptibility of the strains showed 73%, 98%, 93%, 58%, 98%, 64% and 4% resistance to trimethoprim-sulfamethoxazole, nalidixic acid, ampicillin, erythromycin, tetracycline, ciprofloxacin and ceftriaxone respectively. Plasmid profiling revealed heterogeneous patterns and interestingly, all the trimethoprim-sulfamethoxazole resistant (SXTR) strains yielded a distinct 4.3 MDa plasmid compared to that of the trimethoprim-sulfamethoxazole susceptible (SXTS) strains. Curing of this 4.3 MDa plasmid resulted in the susceptibility to sulfamethoxazole alone suggesting the involvement of this plasmid in the resistance of sulfamethoxazole. Moreover, PCR analysis showed the presence of sul2 gene in SXTR strains which is absent in SXTS strains as well as in the 4.3 MDa plasmid-cured derivatives, confirming the involvement of sul2 in the resistance of sulfamethoxazole. Furthermore, pulsed-field gel electrophoresis (PFGE) analysis revealed that both the SXTR and SXTS strains were clonal. This study will significantly contributes to the knowledge on acquired drug resistance of the mostly prevalent S. flexneri 2a and further warrants continuous monitoring of the prevalence and correlation of this resistance determinants amongst the clinical isolates of Shigella and other enteric pathogens around the world to provide effective clinical management of the disease.

Brain dynamics are highly complex and yet hold the key to understanding brain function and dysfunction. The dynamics captured by resting-state functional magnetic resonance imaging data are noisy, high-dimensional, and not readily interpretable. The typical approach of reducing this data to low-dimensional features and focusing on the most predictive features comes with strong assumptions and can miss essential aspects of the underlying dynamics. In contrast, introspection of discriminatively trained deep learning models may uncover disorder-relevant elements of the signal at the level of individual time points and spatial locations. Yet, the difficulty of reliable training on high-dimensional low sample size datasets and the unclear relevance of the resulting predictive markers prevent the widespread use of deep learning in functional neuroimaging. In this work, we introduce a deep learning framework to learn from high-dimensional dynamical data while maintaining stable, ecologically valid interpretations. Results successfully demonstrate that the proposed framework enables learning the dynamics of resting-state fMRI directly from small data and capturing compact, stable interpretations of features predictive of function and dysfunction.

Child open defecation is common in low-income countries and can lead to fecal exposure in the domestic environment. We assessed associations between child feces management practices vs. measures of contamination and child diarrhea among households with children <5 years in rural Bangladesh. We visited 360 households quarterly and recorded caregiver-reported diarrhea prevalence, and defecation and feces disposal practices for children <5 years. We examined caregiver and child hands for visible dirt and enumerated E . coli in child and caregiver hand rinse and stored drinking water samples. Safe child defecation (in latrine/potty) and safe feces disposal (in latrine) was reported by 21% and 23% of households, respectively. Controlling for potential confounders, households reporting unsafe child defecation had higher E . coli prevalence on child hands (prevalence ratio [PR] = 1.12, 1.04–1.20) and in stored water (PR = 1.12,1.03–1.21). Similarly, households reporting unsafe feces disposal had higher E . coli prevalence on child hands (PR = 1.11, 1.02–1.21) and in stored water (PR = 1.10, 1.03–1.18). Effects on E . coli levels were similar. Children in households with unsafe defecation and feces disposal had higher diarrhea prevalence but the associations were not statistically significant. Our findings suggest that unsafe child feces management may present a source of fecal exposure for young children.

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We studied the restriction endonuclease cleavage patterns of rRNA genes (ribotypes) of 72 clinical isolates of Shigellaflexneri representing eight serotypes to determine whether ribotyping could be used to distinguish S. flexneri strains and to compare the discriminating ability of the method with that of serotyping. By using a cloned Escherichia coli rRNA operon as the probe, Southern blot hybridization of restriction endonucleasedigested total DNA was carried out. Ribotyping of the isolates with each of the five restriction endonucleases

Nipah virus (NiV) is an emerging zoonotic virus causing outbreaks of encephalitis and respiratory illnesses in humans, with high mortality. NiV is considered endemic in Bangladesh and Southeast Asia. There are no licensed vaccines against NiV. This study aimed at predicting a dual-antigen multi-epitope subunit chimeric vaccine against surface-glycoproteins G and F of NiV. Targeted proteins were subjected to immunoinformatics analyses to predict antigenic B-cell and T-cell epitopes. The proposed vaccine designs were implemented based on the conservancy, population coverage, molecular docking, immune simulations, codon adaptation, secondary mRNA structure, and in-silico cloning. Total 40 T and B-cell epitopes were found to be conserved, antigenic (vaxijen-value > 0.4), non-toxic, non-allergenic, and human non-homologous. Of 12 hypothetical vaccines, two (NiV_BGD_V1 and NiV_BGD_V2) were strongly immunogenic, non-allergenic, and structurally stable. The proposed vaccine candidates show a negative Z-score (− 6.32 and − 6.67) and 83.6% and 89.3% of most rama-favored regions. The molecular docking confirmed the highest affinity of NiV_BGD_V1 and NiV_BGD_V2 with TLR-4 (ΔG = − 30.7) and TLR8 (ΔG = − 20.6), respectively. The vaccine constructs demonstrated increased levels of immunoglobulins and cytokines in humans and could be expressed properly using an adenoviral-based pAdTrack-CMV expression vector. However, more experimental investigations and clinical trials are needed to validate its efficacy and safety.