Establishing human microbial observatory programs in low- and middle-income countries.

Studies of the human microbiome are progressing rapidly but have largely focused on populations living in high-income countries. With increasing evidence that the microbiome contributes to the pathogenesis of diseases that affect infants, children, and adults in low- and middle-income countries (LMICs), and with profound and rapid ongoing changes occurring in our lifestyles and biosphere, understanding the origins of and developing microbiome-directed therapeutics for treating a number of global health challenges requires the development of programs for studying human microbial ecology in LMICs. Here, we discuss how the establishment of long-term human microbial observatory programs in selected LMICs could provide one timely approach.

Identification of Lytic Phages Against Multidrug-Resistant Klebsiella pneumoniae: Illuminating Hope on Antimicrobial-Resistance.

Background: Lytic phages have been considered as a solution to mitigate the emergence of multidrug-resistant bacteria. Nevertheless, finding phages capable of targeting a broad host-range remains a significant challenge. Materials and Methods: Our study introduces two lytic phages isolated from hospital effluent, which are active against extended-spectrum cephalosporin-resistant Klebsiella pneumoniae. Results: Overnight coculture with host, two purified phage lysates yielded around 3.0 × 107 PFU/mL with an average 0.8 ± 0.2 mm diameter of clear, round, and non-halo plaques in both instances. The genomes of iPHaGe-KPN-11i (177,603 bp, 273 coding sequences [CDS]) and iPHaGe-KPN-12i (178,179 bp, 275 CDS) belong to the Pseudotevenvirus genus. Both phages have at least 120 genes with known functions, including 1 endolysin and 2 tRNAs, and are capable of lysing at least 12 distinct bacterial species in vitro. Conclusions: Most phages are host-specific, whereas our phages can kill multiple bacterial species, enabling their potential use for a broad range of hosts.

Circulating dengue virus serotypes, demographics, and epidemiology in the 2023 dengue outbreak in Chittagong, Bangladesh.

Dengue is a serious epidemic for Bangladesh affecting thousands of lives. This study aimed to identify and determine the prevalence of the circulating variants of dengue virus (DENV) and their association with demographics and clinical manifestations among the dengue-infected patients. A total of 711 participants with NS1 antigen positivity were enrolled, followed by viral RNA extraction from the collected blood samples and a multiplex real-time reverse transcription-polymerase chain reaction (RT-PCR) assay to determine the dengue virus serotypes. Of 711 dengue-infected patients, 503 (70.7%) were male. Among different age groups, most of the patients were 21-30 years old (n = 255, 35.9%). The DENV2 (n = 483, 67.9%) serotype was more prevalent than the DENV3 (n = 144, 20.3%) and DENV1 (n = 84, 11.8%). The duration of fever was highest in the DENV-1 patients (4.79 ± 1.84 days) in contrast to DENV-3 (4.48 ± 1.68 days) and DENV-2 (4.33 ± 1.45 days) (P = 0.039). Importantly, five highly populated areas were identified as dengue hotspots in Chittagong metropolitan city. Our results provide crucial insights into the patterns of dengue virus transmission and severity among southern Bangladeshi population, thereby aiding in the development of targeted public health interventions and management strategies to combat future outbreaks.

Understanding dengue outbreaks in Rajshahi district, Bangladesh: A comprehensive case study.

Background and aims: The 2023 dengue outbreak in Bangladesh marked an unprecedented increase in fatalities, particularly in Dhaka, and demonstrated extensive prevalence nationwide, including Rajshahi district. Dengue fever remains a significant public health challenge in Southeast Asia, with complex epidemiological patterns. Previous research has mainly focused on den serotypes in Dhaka. Therefore, this study aims to identify serotypes in the Rajshahi district under endemic conditions. Methods: Blood samples from suspected dengue patients were collected at Rajshahi Medical College Hospital. Initial rapid detection of dengue-positive cases was performed using (Nonstructural Protein 1 L) NS1, (Immunoglobulin G) IgG, and (Immunoglobulin M) IgM tests. Upon confirmation of dengue positivity, viral RNA was extracted for molecular testing. The dengue serotype was identified using real-time reverse transcription-polymerase chain reaction (rRT-PCR). Results: The study revealed that 93.3 % of the patient were infected with (Dengue virus type 2) DENV2 and rest 6.7 % of the patient were (Dengue virus type 3) DENV3 among 30 dengue positive patients. Demographic observations show the distribution of dengue over nine upazilas. In Paba upazila, we found two DENV3 alongside DENV2. Conclusion: The study concludes that the 2023 dengue outbreak in Rajshahi district, Bangladesh, predominantly involved the DENV2 serotype. Geospatial analysis underscores the importance of understanding regional distribution patterns to enhance targeted interventions against dengue fever in endemic areas.

Effects of household concrete floors on maternal and child health - the CRADLE trial: a randomised controlled trial protocol.

Introduction: Early life soil-transmitted helminth infection and diarrhea are associated with growth faltering, anemia, impaired child development, and mortality. Exposure to fecally contaminated soil inside the home may be a key contributor to enteric infections, and a large fraction of rural homes in low-income countries have soil floors. The objective of this study is to measure the effect of installing concrete floors in homes with soil floors on child soil-transmitted helminth infection and other maternal and child health outcomes in rural Bangladesh. Methods and analysis: The Cement-based flooRs AnD chiLd hEalth (CRADLE) trial is an individually randomised trial in Sirajganj and Tangail districts, Bangladesh. Households with a pregnant woman, a soil floor, walls that are not made of mud will be eligible, and no plan to relocate for 3 years. We will randomise 800 households to intervention or control (1:1) within geographic blocks of 10 households to account for strong geographic clustering of enteric infection. Laboratory staff and data analysts will be blinded; participants will be unblinded. We will install concrete floors when the birth cohort is in utero and measure outcomes at child ages 3, 6, 12, 18, and 24 months. The primary outcome is prevalence of any soil-transmitted helminth infection (Ascaris lumbricoides, Necator americanus, or Trichuris trichiura) detected by qPCR at 6, 12, 18, or 24 months follow-up in the birth cohort. Secondary outcomes include household floor and child hand contamination with E. coli, extended-spectrum beta-lactamase producing E. coli, and soil-transmitted helminth DNA; child diarrhea, growth, and cognitive development; and maternal stress and depression. Ethics and dissemination: Study protocols have been approved by institutional review boards at Stanford University and the International Centre for Diarrheal Disease Research, Bangladesh (icddr,b). We will report findings on ClinicalTrials.gov, in peer-reviewed publications, and in stakeholder workshops in Bangladesh. Trial registration number: NCT05372068, pre-results.

Antimicrobial Susceptibility and Genomic Profiles of Multidrug-Resistant Staphylococcus aureus from Nasopharynx of Asymptomatic Children in Dhaka, Bangladesh.

Children carrying Staphylococcus aureus in their nasopharynx are at a higher risk of contracting systemic infection. Due to lack of sufficient information regarding such carriage, this study was conducted to explore the prevalence, antibiotic susceptibility, and genomic profiles of S. aureus isolated from nasopharyngeal samples of 163 randomly selected asymptomatic Bangladeshi children aged from 5-<15 years. Antibiotic susceptibility pattern and genomic analysis of the samples were conducted using standard microbiological methods and genomic tools. The carriage was confirmed in 44 (27%) children who were mostly well nourished without respiratory symptoms in the last 3 months. Higher carriage was observed among the younger age group (5-<10 years) who completed vaccines for pneumonia (p = 0.002) and influenza (p = 0.004). Among the isolates, 84.1% were multidrug-resistant and 47.5% (n = 40) were methicillin-resistant S. aureus (MRSA). All the isolates (100%) were resistant to cefixime with higher resistance to ampicillin (95.5%) and penicillin (90.9%). Among the three investigated isolates, two were ST80 (ID-1 and ID-52) and one was a novel strain (ID-19) with the presence of aph-Stph, blaI, blaZ, dha1, fosB, lmrS, mepA, norA, and tet38 genes. The current research demonstrates a high incidence of multidrug-resistant S. aureus and reports the first instance of ST80 in asymptomatic children in Bangladesh.

Comprehensive Analysis of SARS-CoV-2 Dynamics in Bangladesh: Infection Trends and Variants (2020-2023).

The first case of COVID-19 was detected in Bangladesh on 8 March 2020. Since then, the Government of Bangladesh (GoB) has implemented various measures to limit the transmission of COVID-19, including widespread testing facilities across the nation through a laboratory network for COVID-19 molecular testing. This study aimed to analyze the dynamics of SARS-CoV-2 in Bangladesh by conducting COVID-19 testing and genomic surveillance of the virus variants throughout the pandemic. Nasopharyngeal swabs were collected from authorized GoB collection centers between April 2020 and June 2023. The viral RNA was extracted and subjected to real-time PCR analysis in icddr,b's Virology laboratory. A subset of positive samples underwent whole-genome sequencing to track the evolutionary footprint of SARS-CoV-2 variants. We tested 149,270 suspected COVID-19 cases from Dhaka (n = 81,782) and other districts (n = 67,488). Of these, 63% were male. The highest positivity rate, 27%, was found in the >60 years age group, followed by 26%, 51-60 years, 25% in 41-50 years, and the lowest, 9% in under five children. Notably, the sequencing of 2742 SARS-CoV-2 genomes displayed a pattern of globally circulating variants, Alpha, Beta, Delta, and Omicron, successively replacing each other over time and causing peaks of COVID-19 infection. Regarding the risk of SARS-CoV-2 infection, it was observed that the positivity rate increased with age compared to the under-5 age group in 2020 and 2021. However, these trends did not remain consistent in 2022, where older age groups, particularly those over 60, had a lower positivity rate compared to other age groups due to vaccination. The study findings generated data on the real-time circulation of different SARS-CoV-2 variants and the upsurge of COVID-19 cases in Bangladesh, which impacted identifying hotspots and restricting the virus from further transmission. Even though there is currently a low circulation of SARS-CoV-2 in Bangladesh, similar approaches of genomic surveillance remain essential for monitoring the emergence of new SARS-CoV-2 variants or other potential pathogens that could lead to future pandemics.

Incidence of Hospitalization due to Influenza-Associated Severe Acute Respiratory Infection During 2010-2019 in Bangladesh.

BACKGROUND: Global influenza-associated acute respiratory infections contribute to 3-5 million severe illnesses requiring hospitalization annually, with 90% of hospitalizations occurring among children < 5 years in developing countries. In Bangladesh, the inadequate availability of nationally representative, robust estimates of influenza-associated hospitalizations limits allocation of resources for prevention and control measures. METHODS: This study used data from the hospital-based influenza surveillance (HBIS) system in Bangladesh from 2010 to 2019 and healthcare utilization surveys to determine hospital utilization patterns in the catchment area. We estimated annual influenza-associated hospitalization numbers and rates for all age groups in Bangladesh using WHO methods, adjusted for a 6-day-a-week enrollment schedule, selective testing of specimens from children under five, and healthcare-seeking behavior, based on the proportion of symptomatic community participants seeking healthcare within the past week. We then estimated national hospitalization rates by multiplying age-specific hospitalization rates with the corresponding annual national census population. RESULTS: Annual influenza-associated hospitalization rates per 100,000 population for all ages ranged from 31 (95% CI: 27-36) in 2011 to 139 (95% CI: 130-149) in 2019. Children < 5 years old had the highest rates of influenza-associated hospitalization, ranging from 114 (95% CI: 90-138) in 2011 to 529 (95% CI: 481-578) in 2019, followed by adults aged ≥ 65 years with rates ranging from 46 (95% CI: 34-57) in 2012 to 252 (95% CI: 213-292) in 2019. The national hospitalization estimates for all ages during 2010-2019 ranged from 47,891 to 236,380 per year. CONCLUSIONS: The impact of influenza-associated hospitalizations in Bangladesh may be considerable, particularly for young children and older adults. Targeted interventions, such as influenza vaccination for these age groups, should be prioritized and evaluated.

Post-discharge mortality among patients hospitalised with severe acute respiratory infection, Bangladesh, 2012-2019: a prospective observational study.

Background: Enhancing outcomes post-hospitalisation requires an understanding of predictive factors for adverse events. This study aimed to estimate post-discharge mortality rates among patients with severe acute respiratory infection (SARI) in Bangladesh, identify associated factors, and document reported causes of death. Methods: From January 2012 to December 2019, we conducted follow-up calls to patients or their families 30 days after discharge to assess the status of patients with SARI. Proportions of deaths within 30 days of discharge were estimated, and a comparative analysis of demographics, clinical characteristics, and influenza illness between decedents and survivors was performed using multivariable Cox regression models. Findings: Among 23,360 patients with SARI (median age: 20 years, IQR: 1.5-48, 65% male), 351 (1.5%) died during hospitalisation. Of 23,009 patients alive at discharge, 20,044 (87%) were followed, with 633 (3.2%) deaths within 30 days of discharge. In children (<18 years), difficulty breathing (adjusted hazard ratio [aHR] 1.8; 95% CI 1.1-3.0), longer hospital stay (aHR 1.1; 95% CI 1.1-1.1), and heart diseases (aHR 8.5; 95% CI 3.2-23.1) were associated with higher post-discharge death risk. Among adults (≥18 years), difficulty breathing (aHR 2.3; 95% CI 1.7-3.0), chronic obstructive pulmonary disease (aHR 1.7; 95% CI 1.4-2.2), and intensive care unit admission (aHR 5.2; 95% CI 1.9-14.0) were linked to elevated post-discharge death risk. Influenza virus was detected in 13% (46/351) of in-hospital SARI deaths and 10% (65/633) of post-discharge SARI deaths. Interpretation: Nearly one in twenty patients with SARI died during hospitalisation or within 1 month of discharge, with two-thirds of deaths occurring post-discharge. Seasonal influenza vaccination is recommended to mitigate influenza-associated mortality. To enhance post-discharge outcomes, hospitals should consider developing safe-discharge algorithms, reinforcing post-discharge care plans, and establishing outpatient monitoring for recently discharged patients. Funding: Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA [U01GH002259].

Safety and effectiveness of a recombinant hepatitis E vaccine in women of childbearing age in rural Bangladesh: a phase 4, double-blind, cluster-randomised, controlled trial.

BACKGROUND: Hepatitis E virus (HEV) leads to high mortality in pregnant women in low-income countries. We aimed to evaluate the safety of a HEV vaccine and its effectiveness in preventing hepatitis E during pregnancy. METHODS: In this phase 4, double-blind, cluster-randomised trial, 67 villages in Matlab, Bangladesh, were randomised 1:1 to receive HEV239 (a recombinant HEV vaccine) or a control vaccine (Hepa-B, a hepatitis B vaccine), using block randomisation with random number tables and blocks of size eight, stratified by cluster population size. Eligible non-pregnant women (aged 16-39 years) were vaccinated intramuscularly on day 0, at 1 month, and at 6 months, and followed up for 2 years after the last immunisation. The primary endpoint was hepatitis E in the pregnant, per-protocol population (those who received all three doses within 2 days of the scheduled dates), while safety was a secondary endpoint, assessed in the intention-to-treat (ITT) population (participants who received at least one dose). Solicited adverse events were recorded for the first 7 days after each dose, and unsolicited events until 2 years after a participant's final dose. Pregnancy-related safety outcomes were assessed in the pregnant ITT population. This study is registered with ClinicalTrials.gov (NCT02759991). FINDINGS: Between Oct 2, 2017, and Feb 28, 2019, 19 460 participants were enrolled and received either HEV239 (9478 [48·7%] participants, 33 clusters) or Hepa-B (9982 [51·3%] participants, 34 clusters), of whom 17 937 (92·2%) participants received three doses and 17 613 (90·5%) were vaccinated according to protocol (8524 [48·4%] in the HEV239 group and 9089 [51·6%] in the control group). No pregnant participants were confirmed to have hepatitis E in either treatment group. HEV239 showed a mild safety profile, similar to Hepa-B, with no difference in the proportion of solicited adverse events between groups and no severe solicited events. Pain was the most common local symptom (1215 [12·8%] HEV239 recipients and 1218 [12·2%] Hepa-B recipients) and fever the most common systemic symptom (141 [1·5%] HEV239 recipients and 145 [1·5%] Hepa-B recipients). None of the serious adverse events or deaths were vaccine related. Among pregnant participants, the HEV239 group had a higher risk of miscarriage (136 [5·7%] of 2407 pregnant participants) compared with the control group (102 [3·9%] of 2604; adjusted odds ratio 1·54 [95% CI 1·15-2·08]). INTERPRETATION: The effectiveness of HEV239 in pregnant women remains uncertain. HEV239 was safe and well tolerated in non-pregnant women, but findings regarding miscarriage warrant further investigation. FUNDING: Research Council of Norway; Innovax.

Dataset of air pollutants (PM2.5, PM10, CO) concentrations in the export processing area of Dhaka, Bangladesh.

This study presents a valuable dataset on air quality in the densely populated Dhaka Export Processing Zone (DEPZ) of Bangladesh. It included a dataset of Particulate Matter (PM2.5, PM10) and CO concentrations with Air Quality Index (AQI) values. PM data was collected 24h, and CO data was collected 8h monthly from 2019 to 2023 using respirable dust sampler APS-113NL for PM2.5, APS-113BL for PM10, and LUTRON AQ9901SD Air Quality Monitor Data Logger used to measure CO concentration data. Data sampling locations are selected based on population density, and employment data for DEPZ is also included, highlighting a potential rise in population density. This article also forecasted pollutant concentrations, AQI values, and health hazards associated with air pollutants using the Auto Regressive Moving Average (ARIMA) model. The performance of the ARIMA model was also measured using root mean squared error (RMSE) and mean absolute error (MAE). However, this can be used to raise awareness among the public about the health hazards associated with air pollution and encourage them to take measures to reduce their exposure to air pollutants. In addition, this data can be instrumental for researchers and policymakers to assess air pollution risks, develop control strategies, and improve air quality in the DEPZ.

Emergence of the novel sixth Candida auris Clade VI in Bangladesh.

Candida auris, initially identified in 2009, has rapidly become a critical concern due to its antifungal resistance and significant mortality rates in healthcare-associated outbreaks. To date, whole-genome sequencing (WGS) has identified five unique clades of C. auris, with some strains displaying resistance to all primary antifungal drug classes. In this study, we presented the first WGS analysis of C. auris from Bangladesh, describing its origins, transmission dynamics, and antifungal susceptibility testing (AFST) profile. Ten C. auris isolates collected from hospital settings in Bangladesh were initially identified by CHROMagar Candida Plus, followed by VITEK2 system, and later sequenced using Illumina NextSeq 550 system. Reference-based phylogenetic analysis and variant calling pipelines were used to classify the isolates in different clades. All isolates aligned ~90% with the Clade I C. auris B11205 reference genome. Of the 10 isolates, 8 were clustered with Clade I isolates, highlighting a South Asian lineage prevalent in Bangladesh. Remarkably, the remaining two isolates formed a distinct cluster, exhibiting >42,447 single-nucleotide polymorphism differences compared to their closest Clade IV counterparts. This significant variation corroborates the emergence of a sixth clade (Clade VI) of C. auris in Bangladesh, with potential for international transmission. AFST results showed that 80% of the C. auris isolates were resistant to fluconazole and voriconazole, whereas Clade VI isolates were susceptible to azoles, echinocandins, and pyrimidine analogue. Genomic sequencing revealed ERG11_Y132F mutation conferring azole resistance while FCY1_S70R mutation found inconsequential in describing 5-flucytosine resistance. Our study underscores the pressing need for comprehensive genomic surveillance in Bangladesh to better understand the emergence, transmission dynamics, and resistance profiles of C. auris infections. Unveiling the discovery of a sixth clade (Clade VI) accentuates the indispensable role of advanced sequencing methodologies.IMPORTANCECandida auris is a nosocomial fungal pathogen that is commonly misidentified as other Candida species. Since its emergence in 2009, this multidrug-resistant fungus has become one of the five urgent antimicrobial threats by 2019. Whole-genome sequencing (WGS) has proven to be the most accurate identification technique of C. auris which also played a crucial role in the initial discovery of this pathogen. WGS analysis of C. auris has revealed five distinct clades where isolates of each clade differ among themselves based on pathogenicity, colonization, infection mechanism, as well as other phenotypic characteristics. In Bangladesh, C. auris was first reported in 2019 from clinical samples of a large hospital in Dhaka city. To understand the origin, transmission dynamics, and antifungal-resistance profile of C. auris isolates circulating in Bangladesh, we conducted a WGS-based surveillance study on two of the largest hospital settings in Dhaka, Bangladesh.

Application of extreme learning machine (ELM) forecasting model on CO2 emission dataset of a natural gas-fired power plant in Dhaka, Bangladesh.

Understanding and predicting CO2 emissions from individual power plants is crucial for developing effective mitigation strategies. This study analyzes and forecasts CO2 emissions from an engine-based natural gas-fired power plant in Dhaka Export Processing Zone (DEPZ), Bangladesh. This study also presents a rich dataset and ELM-based prediction model for a natural gas-fired plant in Bangladesh. Utilizing a rich dataset of Electricity generation and Gas Consumption, CO2 emissions in tons are estimated based on the measured energy use, and the ELM models were trained on CO2 emissions data from January 2015 to December 2022 and used to forecast CO2 emissions until December 2026. This study aims to improve the understanding and prediction of CO2 emissions from natural gas-fired power plants. While the specific operational strategy of the studied plant is not available, the provided data can serve as a valuable baseline or benchmark for comparison with similar facilities and the development of future research on optimizing operations and CO2 mitigation strategies. The Extreme Learning Machine (ELM) modeling method was employed due to its efficiency and accuracy in prediction. The ELM models achieved performance metrics Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Scaled Error (MASE), values respectively 3494.46 (<5000), 2013.42 (<2500), and 0.93 close to 1, which falls within the acceptable range. Although natural gas is a cleaner alternative, emission reduction remains essential. This data-driven approach using a Bangladeshi case study provides a replicable framework for optimizing plant operations and measuring and forecasting CO2 emissions from similar facilities, contributing to global climate change.

Rotavirus trends and distribution of genotypes before and during COVID-19 pandemic era: Bangladesh, 2017-2021.

Rotavirus gastroenteritis is accountable for an estimated 128 500 deaths among children younger than 5 years worldwide, and the majority occur in low-income countries. Although the clinical trials of rotavirus vaccines in Bangladesh revealed a significant reduction of severe rotavirus disease by around 50%, the vaccines are not yet included in the routine immunization program. The present study was designed to provide data on rotavirus diarrhea with clinical profiles and genotypes before (2017-2019) and during the COVID-19 pandemic period (2020-2021). Fecal samples were collected from 2% of the diarrheal patients at icddr,b Dhaka hospital of all ages between January 2017 and December 2021 and were tested for VP6 rotavirus antigen using ELISA. The clinical manifestations such as fever, duration of diarrhea and hospitalization, number of stools, and dehydration and so on were collected from the surveillance database (n = 3127). Of the positive samples, 10% were randomly selected for genotyping using Sanger sequencing method. A total of 12 705 fecal samples were screened for rotavirus A antigen by enzyme immunoassay. Overall, 3369 (27%) were rotavirus antigen-positive, of whom children <2 years had the highest prevalence (88.6%). The risk of rotavirus A infection was 4.2 times higher in winter than in summer. Overall, G3P[8] was the most prominent genotype (45.3%), followed by G1P[8] (32.1%), G9P[8] (6.8%), and G2P[4] (6.1%). The other unusual combinations, such as G1P[4], G1P[6], G2P[6], G3P[4], G3P[6], and G9P[6], were also present. Genetic analysis on Bangladeshi strains revealed that the selection pressure (dN/dS) was estimated as <1. The number of hospital visits showed a 37% drop during the COVID-19 pandemic relative to the years before the pandemic. Conversely, there was a notable increase in the rate of rotavirus positivity during the pandemic (34%, p < 0.00) compared to the period before COVID-19 (23%). Among the various clinical symptoms, only the occurrence of watery stool significantly increased during the pandemic. The G2P[4] strain showed a sudden rise (19%) in 2020, which then declined in 2021. In the same year, G1P[8] was more prevalent than G3P[8] (40% vs. 38%, respectively). The remaining genotypes were negligible and did not exhibit much fluctuation. This study reveals that the rotavirus burden remained high during the COVID-19 prepandemic and pandemic in Bangladesh. Considering the lack of antigenic variations between the circulating and vaccine-targeted strains, integrating the vaccine into the national immunization program could reduce the prevalence of the disease, the number of hospitalizations, and the severity of cases.

Innovative Machine Learning Strategies for Early Detection and Prevention of Pregnancy Loss: The Vitamin D Connection and Gestational Health.

Early pregnancy loss (EPL) is a prevalent health concern with significant implications globally for gestational health. This research leverages machine learning to enhance the prediction of EPL and to differentiate between typical pregnancies and those at elevated risk during the initial trimester. We employed different machine learning methodologies, from conventional models to more advanced ones such as deep learning and multilayer perceptron models. Results from both classical and advanced machine learning models were evaluated using confusion matrices, cross-validation techniques, and analysis of feature significance to obtain correct decisions among algorithmic strategies on early pregnancy loss and the vitamin D serum connection in gestational health. The results demonstrated that machine learning is a powerful tool for accurately predicting EPL, with advanced models such as deep learning and multilayer perceptron outperforming classical ones. Linear discriminant analysis and quadratic discriminant analysis algorithms were shown to have 98 % accuracy in predicting pregnancy loss outcomes. Key determinants of EPL were identified, including levels of maternal serum vitamin D. In addition, prior pregnancy outcomes and maternal age are crucial factors in gestational health. This study's findings highlight the potential of machine learning in enhancing predictions related to EPL that can contribute to improved gestational health outcomes for mothers and infants.

Emergence of SARS-CoV-2 Omicron sub-lineage JN.1 in Bangladesh.

We report complete genome sequences of 14 severe acute respiratory syndrome coronavirus 2 Omicron sub-lineage JN.1 obtained from Bangladeshi individuals between 19 December 2023 and 21 January 2024. All sequence data were generated by Oxford Nanopore Sequencing Technology using the amplicon sequencing approach developed by the ARTIC network.

Coding-complete genomes of 18 SARS-CoV-2 Omicron JN.1, JN.1.4, and JN.1.11 sub-lineages in Bangladesh.

We report 18 coding-complete genome sequences of emerging SARS-CoV-2 Omicron sub-lineages JN.1, JN.1.4, and JN.1.11 from Bangladesh. Nasopharyngeal swab samples were obtained from individuals with COVID-19 symptoms between December 2023 and January 2024. Whole genome sequencing was performed following the ARTIC Network-based protocol using Oxford Nanopore Technology.

Standardised quantitative assays for anti-SARS-CoV-2 immune response used in vaccine clinical trials by the CEPI Centralized Laboratory Network: a qualification analysis.

BACKGROUND: Accurate quantitation of immune markers is crucial for ensuring reliable assessment of vaccine efficacy against infectious diseases. This study was designed to confirm standardised performance of SARS-CoV-2 assays used to evaluate COVID-19 vaccine candidates at the initial seven laboratories (in North America, Europe, and Asia) of the Coalition for Epidemic Preparedness Innovations (CEPI) Centralized Laboratory Network (CLN). METHODS: Three ELISAs (pre-spike protein, receptor binding domain, and nucleocapsid), a microneutralisation assay (MNA), a pseudotyped virus-based neutralisation assay (PNA), and an IFN-γ T-cell ELISpot assay were developed, validated or qualified, and transferred to participating laboratories. Immune responses were measured in ELISA laboratory units (ELU) for ELISA, 50% neuralisation dilution (ND50) for MNA, 50% neutralisation titre (NT50) for PNA, and spot-forming units for the ELISpot assay. Replicate assay results of well characterised panels and controls of blood samples from individuals with or without SARS-CoV-2 infection were evaluated by geometric mean ratios, standard deviation, linear regression, and Spearman correlation analysis for consistency, accuracy, and linearity of quantitative measurements across all laboratories. FINDINGS: High reproducibility of results across all laboratories was demonstrated, with interlaboratory precision of 4·1-7·7% coefficient of variation for all three ELISAs, 3·8-19·5% for PNA, and 17·1-24·1% for MNA, over a linear range of 11-30 760 ELU per mL for the three ELISAs, 14-7876 NT50 per mL for PNA, and 21-25 587 ND50 per mL for MNA. The MNA was also adapted for detection of neutralising antibodies against the major SARS-CoV-2 variants of concern. The results of PNA and MNA (r=0·864) and of ELISA and PNA (r=0·928) were highly correlated. The IFN-γ ELISpot interlaboratory variability was 15·9-49·9% coefficient of variation. Sensitivity and specificity were close to 100% for all assays. INTERPRETATION: The CEPI CLN provides accurate quantitation of anti-SARS-CoV-2 immune response across laboratories to allow direct comparisons of different vaccine formulations in different geographical areas. Lessons learned from this programme will serve as a model for faster responses to future pandemic threats and roll-out of effective vaccines. FUNDING: CEPI.

Detection of Rotavirus in Respiratory Specimens From Bangladeshi Children Aged <2 Years Hospitalized for Acute Gastroenteritis.

To examine the potential for respiratory transmission of rotavirus, we systematically assessed if rotavirus RNA is detectable by real-time quantitative reverse transcription-polymerase chain reaction from nasal and oropharyngeal swab specimens of Bangladeshi children with acute rotavirus gastroenteritis. Forehead swabs were collected to assess skin contamination. Among 399 children aged <2 years hospitalized for gastroenteritis during peak rotavirus season, rotavirus RNA was detected in stool, oral, nasal and forehead swab specimens of 354 (89%). A subset was genotyped; genotype was concordant within a child's specimen set and several different genotypes were detected across children. These findings support possible respiratory transmission of rotavirus and warrant further investigation.

Complete genome sequence of Escherichia phage iGC_PHA_EC001.

Antimicrobial resistance (AMR) in bacteria poses a global health emergency due to limited treatment options. Here, we report a lytic bacteriophage belonging to Stephanstirmvirinae family against an AMR Escherichia coli (ST2089). Escherichia phage iGC_PHA_EC001 is of genus Phapecoctavirus and 148,445 bp in length, encoding 269 predicted protein-coding sequences and 10 tRNAs. The phage encodes two lytic proteins containing phage_lysozyme (PF00959.22) and cell wall hydrolase_2 (PF07486.15) as catalytic domains, respectively.