Duodenal transcriptomics demonstrates signatures of tissue inflammation and immune cell infiltration in children with environmental enteric dysfunction across global centers.

BACKGROUND: Environmental enteric dysfunction (EED) is an inflammatory condition of the small intestine that is prevalent in children residing in low- and middle-income countries. EED is accompanied by profound histopathologic changes in the small bowel, loss of absorptive capacity, increased intestinal permeability, increased microbial translocation, and nutrient loss. OBJECTIVES: We sought to identify dysregulated genes and pathways that might underlie pediatric EED. METHODS: RNA-sequencing libraries were generated from endoscopically obtained duodenal tissue from undernourished children with EED from 3 prospective cohorts of children with EED. The EED transcriptome was defined in comparison to North American children without EED. Weighted gene coexpression network analysis (WGCNA) was tested for gene modules associated with EED and its histologic features. RESULTS: The 1784 upregulated genes in EED were highly enriched for immune and inflammatory processes, including IL-17 and JAK-STAT signaling, and cytokine-cytokine receptor interactions. The 1388 downregulated genes included genes corresponding to xenobiotic metabolism, detoxification, and antioxidant capacities. A gene coexpression module enriched for antimicrobial responses and chemokine activity was significantly associated with villous blunting, goblet cell depletion, and overall histologic severity of EED. CONCLUSIONS: The transcriptome signatures of EED include specific innate and adaptive immune responses that are consistently elevated across study centers, coupled with reduced detoxification and antioxidant capacities. These data may have implications for targeted interventions to improve EED outcomes.

Biomarker relationships with small bowel histopathology among malnourished children with environmental enteric dysfunction in a multicountry cohort study.

BACKGROUND: Validated biomarkers could catalyze environmental enteric dysfunction (EED) research. OBJECTIVES: Leveraging an EED histology scoring system, this multicountry analysis examined biomarker associations with duodenal histology features among children with EED. We also examined differences in 2-h compared with 1-h urine collections in the lactulose rhamnose (LR) dual sugar test. METHODS: Three cohorts of undernourished children unresponsive to nutrition intervention underwent esophagogastroduodenoscopy and duodenal biopsies. Histopathology scores were compared to fecal calprotectin (CAL), myeloperoxidase (MPO), neopterin (NEO), and urinary LR ratio and lactulose percentage recovery. Log-transformed biomarkers were used in linear regressions adjusted for age, center, and sample collection-biopsy time interval in multivariable models. RESULTS: Data on >1 biomarker were available for 120 Bangladeshi (CAL, MPO, NEO, and LR), 63 Pakistani (MPO, NEO, and LR), and 63 Zambian children (CAL). Median age at endoscopy was similar (19 mo) across centers. Median sample collection prior to endoscopy was consistent with each center's study design: 2 wk in Bangladesh (urine and stool) and Zambia (stool), and 6 (urine) and 11 (stool) mo in Pakistan. In multivariable models, intraepithelial lymphocytes were associated with CAL (exponentiated [exp.] coefficient: 1.19; 95% confidence interval [CI]: 1, 1.41), intramucosal Brunner's glands with MPO (exp. coefficient: 1.33; 95% CI: 1.05, 1.69) and NEO (exp. coefficient: 1.37; 95% CI: 1.1, 1.7), and chronic inflammation with NEO (exp. coefficient: 1.61; 95% CI: 1.17, 2.17). Intraepithelial lymphocytes were associated with lactulose % recovery (exp. coefficient: 1.22; 95% CI: 1.05, 1.41). LR recovery was substantially lower in 1-h collections than in 2-h collections. CONCLUSIONS: Four commonly used markers of enteric dysfunction were associated with specific histologic features. One-hour urine collection may be insufficient to reflect small bowel permeability in LR testing. While acknowledging the challenges with obtaining relevant tissue, these findings form the basis for further EED biomarker validation research.

Machine Learning-Assisted Mixed Quantum-Classical Dynamics without Explicit Nonadiabatic Coupling: Application to the Photodissociation of Peroxynitric Acid.

We have devised a hybrid quantum-classical scheme utilizing machine-learned potential energy surfaces (PES), which circumvents the need for explicit computation of nonadiabatic coupling elements. The quantities necessary to account for the nonadiabatic effects are directly obtained from the PESs. The simulation of dynamics is based on the fewest-switches surface-hopping method. We applied this scheme to model the photodissociation of both N-O and O-O bonds in a conformer of peroxynitric acid (HO2NO2). Adiabatic PES data for the six lowest states of this molecule were computed at the CASSCF level for various nuclear configurations. These served as the training data for the machine-learning models for the PESs. The dynamics simulation was initiated on the lowest optically bright singlet excited state (S4) and propagated along the two Jacobi coordinates J→1 and J→2 while accounting for the nonadiabatic effects through transitions between PESs. Our analysis revealed that there is a very high chance of dissociation of the N-O bond leading to the HO2 and NO2 fragments.

Development of machine learning models predicting mortality using routinely collected observational health data from 0-59 months old children admitted to an intensive care unit in Bangladesh: critical role of biochemistry and haematology data.

INTRODUCTION: Treatment in the intensive care unit (ICU) generates complex data where machine learning (ML) modelling could be beneficial. Using routine hospital data, we evaluated the ability of multiple ML models to predict inpatient mortality in a paediatric population in a low/middle-income country. METHOD: We retrospectively analysed hospital record data from 0-59 months old children admitted to the ICU of Dhaka hospital of International Centre for Diarrhoeal Disease Research, Bangladesh. Five commonly used ML models- logistic regression, least absolute shrinkage and selection operator, elastic net, gradient boosting trees (GBT) and random forest (RF), were evaluated using the area under the receiver operating characteristic curve (AUROC). Top predictors were selected using RF mean decrease Gini scores as the feature importance values. RESULTS: Data from 5669 children was used and was reduced to 3505 patients (10% death, 90% survived) following missing data removal. The mean patient age was 10.8 months (SD=10.5). The top performing models based on the validation performance measured by mean 10-fold cross-validation AUROC on the training data set were RF and GBT. Hyperparameters were selected using cross-validation and then tested in an unseen test set. The models developed used demographic, anthropometric, clinical, biochemistry and haematological data for mortality prediction. We found RF consistently outperformed GBT and predicted the mortality with AUROC of ≥0.87 in the test set when three or more laboratory measurements were included. However, after the inclusion of a fourth laboratory measurement, very minor predictive gains (AUROC 0.87 vs 0.88) resulted. The best predictors were the biochemistry and haematological measurements, with the top predictors being total CO2, potassium, creatinine and total calcium. CONCLUSIONS: Mortality in children admitted to ICU can be predicted with high accuracy using RF ML models in a real-life data set using multiple laboratory measurements with the most important features primarily coming from patient biochemistry and haematology.

High protein intake on later outcomes in preterm children: a systematic review and meta-analysis.

BACKGROUND: Appropriate protein intake is crucial for growth and development in children born preterm. We assessed the effects of high (HP) versus low protein (LP) intake on neurodevelopment, growth, and biochemical anomalies in these children. METHODS: Randomised and quasi-randomised trials providing protein to children born preterm (<37 completed weeks of gestation) were searched following PRISMA guideline in three databases and four registers (PROSPERO registration CRD42022325659). Random-effects model was used for assessing the effects of HP (≥3.5 g/kg/d) vs. LP (<3.5 g/kg/d). RESULTS: Data from forty-four studies (n = 5338) showed HP might slightly reduce the chance of survival without neurodisability at ≥12 months (four studies, 1109 children, relative risk [RR] 0.95 [95% CI 0.90, 1.01]; P = 0.13; low certainty evidence) and might increase risk of cognitive impairment at toddler age (two studies; 436 children; RR 1.36 [0.89, 2.09]; P = 0.16; low certainty evidence). At discharge or 36 weeks, HP intake might result in higher weight and greater head circumference z-scores. HP intake probably increased the risk of hypophosphatemia, hypercalcemia, refeeding syndrome and high blood urea, but reduced risk of hyperglycaemia. CONCLUSIONS: HP intake for children born preterm may be harmful for neonatal metabolism and later neurodisability and has few short-term benefits for growth. IMPACT STATEMENT: Planned high protein intake after birth for infants born preterm might be harmful for survival, neurodisability and metabolism during infancy and did not improve growth after the neonatal period. Protein intake ≥3.5 g/kg/d should not be recommended for children born preterm.

Environmental risk analysis of a Ramsar site: a case study of east Kolkata wetlands with PSR framework.

The East Kolkata Wetlands (EKWT), designated as a Ramsar Site for its crucial role in sewage water purification, agriculture and pisciculture, faces escalating environmental threats due to rapid urbanisation. Employing the pressure-state-response (PSR) framework and Environmental Risk Assessment (ERA), this study spans three decades to elucidate the evolving dynamics of EKWT. Using Landsat TM and OLI images from 1991, 2001, 2011 and 2021, the research identifies key parameters within the PSR framework. Principal component analysis generates environmental risk maps, revealing a 46% increase in urbanisation, leading to reduced vegetation cover and altered land surface conditions. The spatial analysis, utilizing Getis-Ord Gi* statistics, pinpoints risk hotspots and coldspots in the EKWT region. Correlation analysis underscores a robust relationship between urbanisation, climatic response and environmental risk. Decadal ERA exposes a noteworthy surge in high-risk areas, indicating a deteriorating trend. Quantitative assessments pinpoint environmental risk hotspots, emphasizing the imperative for targeted conservation measures. The study establishes a direct correlation between environmental risk and air quality, underscoring the broader implications of EKWT's degradation. While acknowledging the East Kolkata administration's efforts, the research recognises its limitations and advocates a holistic, multidisciplinary approach for future investigations. Recommendations encompass the establishment of effective institutions, real-time monitoring, public engagement and robust anti-pollution measures. In offering quantitative insights, this study provides an evidence-based foundation for conservation strategies and sustainable management practices essential to safeguard the East Kolkata Wetlands.

Prognostic accuracy of early warning scores for predicting serious illness and in-hospital mortality in patients with COVID-19.

A simple bedside triage tool is essential to stratify COVID-19 patients in the emergency department (ED). This study aimed to identify an early warning score (EWS) that could best predict the clinical outcomes in COVID-19 patients. Data were obtained from medical records of 219 laboratory-confirmed COVID-19 positive patients. We calculated 13 EWSs based on the admission characteristics of the patients. Receiver operating characteristic (ROC) curve analysis was used to assess the performance of the scores in predicting serious illness and in-hospital mortality. The median patient age was 51 (38, 60) years, and 25 (11.4%) patients died. Among patients admitted with mild to moderate illness (n = 175), 61 (34.9%) developed serious illness. Modified National Early Warning Score (m-NEWS) (AUROC 0.766; 95% CI: 0.693, 0.839) and Rapid Emergency Medicine Score (REMS) (AUROC 0.890; 95% CI: 0.818, 0.962) demonstrated the highest AUROC point estimates in predicting serious illness and in-hospital mortality, respectively. Both m-NEWS and REMS demonstrated good accuracy in predicting both the outcomes. However, no significant difference was found between m-NEWS (p = 0.983) and REMS (p = 0.428) as well as some other EWSs regarding the AUROCs in predicting serious illness and in-hospital mortality. We propose m-NEWS could be used as a triage score to identify COVID-19 patients at risk of disease progression and death especially in resource-poor settings because it has been explicitly developed for risk stratification of COVID-19 patients in some countries like China and Italy. However, this tool needs to be validated by further large-scale prospective studies.

Prevotella copri and microbiota members mediate the beneficial effects of a therapeutic food for malnutrition.

Microbiota-directed complementary food (MDCF) formulations have been designed to repair the gut communities of malnourished children. A randomized controlled trial demonstrated that one formulation, MDCF-2, improved weight gain in malnourished Bangladeshi children compared to a more calorically dense standard nutritional intervention. Metagenome-assembled genomes from study participants revealed a correlation between ponderal growth and expression of MDCF-2 glycan utilization pathways by Prevotella copri strains. To test this correlation, here we use gnotobiotic mice colonized with defined consortia of age- and ponderal growth-associated gut bacterial strains, with or without P. copri isolates closely matching the metagenome-assembled genomes. Combining gut metagenomics and metatranscriptomics with host single-nucleus RNA sequencing and gut metabolomic analyses, we identify a key role of P. copri in metabolizing MDCF-2 glycans and uncover its interactions with other microbes including Bifidobacterium infantis. P. copri-containing consortia mediated weight gain and modulated energy metabolism within intestinal epithelial cells. Our results reveal structure-function relationships between MDCF-2 and members of the gut microbiota of malnourished children with potential implications for future therapies.

Small Intestine Bacterial Overgrowth is associated with increased Campylobacter and epithelial injury in duodenal biopsies of Bangladeshi children.

Small intestine bacterial overgrowth (SIBO) has been associated with enteric inflammation, linear growth stunting, and neurodevelopmental delays in children from low-income countries. Little is known about the histologic changes or epithelial adherent microbiota associated with SIBO. We sought to describe these relationships in a cohort of impoverished Bangladeshi children. Undernourished 12-18-month-old children underwent both glucose hydrogen breath testing for SIBO and duodenoscopy with biopsy. Biopsy samples were subject to both histological scoring and 16s rRNA sequencing. 118 children were enrolled with 16s sequencing data available on 53. Of 11 histological features, we found that SIBO was associated with one, enterocyte injury in the second part of the duodenum (R = 0.21, p = 0.02). SIBO was also associated with a significant increase in Campylobacter by 16s rRNA analysis (Log 2-fold change of 4.43; adjusted p = 1.9 x 10-6). These findings support the growing body of literature showing an association between SIBO and enteric inflammation and enterocyte injury and further delineate the subgroup of children with environmental enteric dysfunction who have SIBO. Further, they show a novel association between SIBO and Campylobacter. Mechanistic work is needed to understand the relationship between SIBO, enterocyte injury, and Campylobacter.

Prediction of maximum scour depth at clear water conditions: Multivariate and robust comparative analysis between empirical equations and machine learning approaches using extensive reference metadata.

Flow obstructed by bridge piers can increase sediment transport leading to local scour. This local scour poses a risk to the stability of bridge structures, which could lead to structural failures. There are two main approaches for evaluating the scour depth (ds) of bridge piers. The first is based on understanding hydraulic phenomena and developing relationships with properties affecting scour. The second uses data-driven soft computing models that lack physical interpretations but rely on algorithms to predict outcomes. Methods are chosen by researchers based on their goals and resources. This study aims to create innovative ensemble frameworks comprising support vector machine for regression (SVMR), random forest regression (RFR), and reduced error pruning tree (REPTree) as base learners, alongside bagging regression tree (BRT) and stochastic gradient boosting (SGB) as meta learners. These ensembles were developed to analyse maximum scour depths (dsm) in clear water conditions, utilizing 35 literature's experimental data published in last 63 years. The performance of each machine learning (ML) approach was assessed using statistical performance indicators. The proposed model was also compared with top six empirical equations with strong predictive ability. Results show that among these empirical equations, the equation from Nandi and Das (2023) performs best. Performance evaluation considering training, testing, and the entire dataset, SGB (REPTree), BRT(SVMR-PUK), and SGB (REPTree) exhibited the highest performance, securing the top rank among all ML models and empirical equations. Sensitivity analysis identified sediment gradation and flow intensity as the most influential variables for predicting dsm during both training and testing phases, respectively.

Coastal groundwater quality prediction using objective-weighted WQI and machine learning approach.

The water quality index (WQI) is a globally accepted guideline to indicate the water quality standard of any groundwater resource. Water levels in existing groundwater sources are declining in several coastal zones. Therefore, for monitoring water quality and improving water management, the prediction and identification of groundwater status by an effective technique with higher accuracy is urgently needed. Therefore, this research aims to find an effective model for WQI prediction by comparing entropy and critic weight-based WQI (ENW-WQI and CRITIC-WQI) with multi-layer perceptron artificial neural network (MLP-ANN) technique and also to identify contaminated zones using GIS. Initially, 1000 water sampling datasets with concentrations of several water quality parameters of different coastal blocks of eastern India during 2018 to 2022 are considered for the estimation of ENW-WQI and CRITIC-WQI. It shows 65% and 67% of the samples are excellent to good for drinking. ENW-WQI and CRITIC-WQI-based MLP-ANN models have been established considering different data portioning and hidden neuron numbers. Input variables and appropriate dataset partitioning with hidden neurons for models obtained from correlation and trial-error analysis. Spatial distribution maps are also produced for calculated WQIs using inverse distance weighted interpolation approaches. Three fitting models are obtained: ENW-WQI-MLP-ANN, CRITIC-WQI-MLP-ANN-I and CRITIC-WQI-MLP-ANN-II. CRITIC-WQI-MLP-ANN-II model (data ratio 85:15, network structure 6-12-1, R2 = 0.986, NSE = 0.98, and error rate 0.49%) provides the best accuracy in WQI prediction. The GIS-based WQI maps record several areas related to drinking water quality. The results of this research can help in planning the provision of safe drinking water in the future.

Prevalence and factors associated with undernutrition and overnutrition among ever-married adolescent girls in Bangladesh: an analysis of national surveys from 2004 to 2017.

Nutritional impairment during adolescence may result in adverse physical and reproductive health outcomes. We investigated the prevalence and determined the factors associated with underweight and overweight/obesity among ever-married adolescent girls in Bangladesh. We used Bangladesh Demographic and Health Surveys data conducted in 2004, 2007, 2011, 2014, and 2017. A total of 7040 ever-married adolescent girls aged 15-19 years were included in this analysis. Prevalence of underweight (body mass index [BMI]<18.5 kg/m2) significantly decreased from 39.53% (95% CI = 36.71, 42.43) to 23.62% (95% CI = 21.35, 26.05) during 2004-2017 (p < 0.001). However, prevalence of overweight/obesity (BMI ≥ 23 kg/m2) significantly increased from 5.9% (95% CI = 4.67, 7.43) to 22.71% (95% CI = 20.39, 25.20) during the same period (p < 0.001). The girls with higher age (OR = 0.94, 95% CI = 0.90, 0.99, p = 0.023), higher level of education (OR = 0.60, 95% CI = 0.43, 0.83, p = 0.002), and richest wealth quintile (OR = 0.78, 95% CI = 0.62, 0.98, p = 0.035) had significantly lower risk of being underweight. Adolescent girls having more than one child (OR = 1.41, 95% CI = 1.15, 1.73, p = 0.001) were more likely to be underweight. Elderly adolescents with better economic status were more at risk of being overweight/obese (OR = 2.57, 95% CI = 1.86, 3.55, p < 0.001). Girls married to skilled/unskilled workers (OR = 0.58, 95% CI = 0.44, 0.77, p < 0.001) and persons involved in small businesses (OR = 0.66, 95% CI = 0.49, 0.89, p = 0.007) had lower risk of having a high BMI. Using contraceptive (OR = 0.8, 95% CI = 0.69, 0.94, p = 0.006) was negatively associated with overweight/obese. Although prevalence of undernutrition among ever-married adolescent girls is declining, the proportion of being overweight/obese is increasing in Bangladesh warranting effective strategies to improve adolescent nutrition.

Bioactive glycans in a microbiome-directed food for children with malnutrition.

Evidence is accumulating that perturbed postnatal development of the gut microbiome contributes to childhood malnutrition1-4. Here we analyse biospecimens from a randomized, controlled trial of a microbiome-directed complementary food (MDCF-2) that produced superior rates of weight gain compared with a calorically more dense conventional ready-to-use supplementary food in 12-18-month-old Bangladeshi children with moderate acute malnutrition4. We reconstructed 1,000 bacterial genomes (metagenome-assembled genomes (MAGs)) from the faecal microbiomes of trial participants, identified 75 MAGs of which the abundances were positively associated with ponderal growth (change in weight-for-length Z score (WLZ)), characterized changes in MAG gene expression as a function of treatment type and WLZ response, and quantified carbohydrate structures in MDCF-2 and faeces. The results reveal that two Prevotella copri MAGs that are positively associated with WLZ are the principal contributors to MDCF-2-induced expression of metabolic pathways involved in utilizing the component glycans of MDCF-2. The predicted specificities of carbohydrate-active enzymes expressed by their polysaccharide-utilization loci are correlated with (1) the in vitro growth of Bangladeshi P. copri strains, possessing varying degrees of polysaccharide-utilization loci and genomic conservation with these MAGs, in defined medium containing different purified glycans representative of those in MDCF-2, and (2) the levels of faecal carbohydrate structures in the trial participants. These associations suggest that identifying bioactive glycan structures in MDCFs metabolized by growth-associated bacterial taxa will help to guide recommendations about their use in children with acute malnutrition and enable the development of additional formulations.

Nutritional status and dietary diversity of pregnant and nonpregnant reproductive-age Rohingya women.

There are no data on the nutritional status and dietary diversity of the pregnant and nonpregnant reproductive-age Rohingya women who have recently shifted to the Bhasan Char Relocation Camp located on an island in the Bay of Bengal. A cross-sectional survey was conducted in November-December, 2021 to assess the nutritional status and evaluate the dietary diversity of two vulnerable groups of the forcibly displaced Rohingya population: nonpregnant reproductive-age women and pregnant mothers. Multivariable logistic regression was applied to identify the factors associated with nutritional impairments. Overall, 7.6% of the nonpregnant reproductive-age women were underweight (Body Mass Index [BMI] < 18.5 kg/m2), and nearly one-third of them had a BMI ≥ 25 kg/m2. However, 26.7% of the pregnant mothers were undernourished (BMI < 20.0 kg/m2) and almost one-fourth of them were either overweight or obese (BMI ≥ 25.0 kg/m2). The prevalence of thinness (Mid Upper Arm Circumference [MUAC] < 23 cm) was 34.5% among pregnant mothers, and 10.1% of them were severely thin (MUAC < 21 cm). The mean (±SD) of the Women's Dietary Diversity Score (WDDS) was 3.3 (±1.1) for nonpregnant reproductive-age women and 3.7 (±1.3) for pregnant mothers enrolled in this study. Overall, 63.8% of the nonpregnant women of childbearing age and 46% of the pregnant mothers had a low WDDS (WDDS < 4). The WDDS was found to be protective against thinness among nonpregnant reproductive-age women (AOR = 0.61; 95% CI = 0.37, 0.93; p-value = .03) and low BMI in pregnant mothers (AOR = 0.71; 95% CI = 0.55, 0.91; p-value = .01). The results of this survey will assist in early recognition of the nutritional demands, and act as a guide to planning nutrition-based programs among Rohingya reproductive-age women relocated to the Bhasan Char Island.

MLR index-based principal component analysis to investigate and monitor probable sources of groundwater pollution and quality in coastal areas: a case study in East India.

Identifying groundwater contamination sources and supervising groundwater quality conditions are urgently needed to protect the groundwater resources of coastal areas like Contai of India, as communities here are heavily relying on groundwater which deteriorates progressively. So current research aims to address in detail about origins and influencing factors of groundwater contamination, status, and monitoring water quality by employing extremely useful leading technologies like principal component and factor analyses (PCA/FA), groundwater quality index (GWQI), and multiple linear regression (MLR) that helps to simplify complicated works instead of the conventional methods. Eight groundwater quality parameters were evaluated here, such as pH, TH (total hardness), Tur (turbidity), EC (electrical conductivity), TDS (total dissolved solids), Mn (manganese), Fe (iron), and Cl (chloride) for 38 sites. Three principal components with ~ 81% of the total variance were extracted from the PCA/FA analysis. The origin of maximum loadings of each factor is identified as a result of saline water, disintegration and leaching process, organic or else biogenic activities, and lithogenic or otherwise non-lithogenic links through percolating water. GWQI results show that ~ 87% of the samples fall into the good category and ~ 13% of the samples fall into the poor to very poor category. A model consisting of Tur, Fe, EC, Mn, TH, and Cl as independent parameters is more feasible and is proposed to predict GWQI obtained from MLR analysis. This MLR model also suggests that turbidity with the highest beta coefficient (0.820) is a key contributor relative to the entire groundwater class in this affected area. The findings relating to this research may support the designer and officials in monitoring and protecting coastal groundwater resources like selected areas.

Polycyclic aromatic hydrocarbon (PAH) remediation during vermicomposting and composting: Mechanistic insights through PAH-budgeting.

Knowledge on the mechanism of earthworm-induced removal of polycyclic aromatic hydrocarbons (PAH) in vermicomposting systems and interaction with nutrient mineralization and microbial growth is scarce in literature. Moreover, the PAH accumulation capacity of Eudrilus eugeniae has not been studied. This research, therefore, investigates the apportionment dynamics of 13 PAH compounds in aerobic composting and vermicomposting (Eisenia fetida and E. eugeniae) systems using novel budget equations. The PAH removal efficiency of vermicomposting was significantly higher (2-threefold) than composting with concurrent microbial augmentation (p < 0.01). However, the 4-6 ring compounds reduced more significantly (30-50%) than the 3-ring PAHs (p < 0.01), and E. eugeniae was an equally competitive PAH-accumulator compared to E. fetida. The budget equations revealed that although the bioaccumulation capabilities of earthworms were retarded due to PAH exposure, earthworms facilitated PAH-immobilization in decomposed feedstock. A marked increase in bacterial, fungal, and actinomycetes proliferation in PAH-spiked vermibeds with parallel removal of the PAHs indicated that earthworm-induced microbial enrichment plays a vital role in PAH detoxification during vermicomposting. Correlation analyses strongly implied that earthworm-driven mineralization-humification balancing and microbial enrichment could be the critical mechanism of PAH remediation under vermicomposting.

Prevotella copri-related effects of a therapeutic food for malnutrition.

Preclinical and clinical studies are providing evidence that the healthy growth of infants and children reflects, in part, healthy development of their gut microbiomes1-5. This process of microbial community assembly and functional maturation is perturbed in children with acute malnutrition. Gnotobiotic animals, colonized with microbial communities from children with severe and moderate acute malnutrition, have been used to develop microbiome-directed complementary food (MDCF) formulations for repairing the microbiomes of these children during the weaning period5. Bangladeshi children with moderate acute malnutrition (MAM) participating in a previously reported 3-month-long randomized controlled clinical study of one such formulation, MDCF-2, exhibited significantly improved weight gain compared to a commonly used nutritional intervention despite the lower caloric density of the MDCF6. Characterizing the 'metagenome assembled genomes' (MAGs) of bacterial strains present in the microbiomes of study participants revealed a significant correlation between accelerated ponderal growth and the expression by two Prevotella copri MAGs of metabolic pathways involved in processing of MDCF-2 glycans1. To provide a direct test of these relationships, we have now performed 'reverse translation' experiments using a gnotobiotic mouse model of mother-to-offspring microbiome transmission. Mice were colonized with defined consortia of age- and ponderal growth-associated gut bacterial strains cultured from Bangladeshi infants/children in the study population, with or without P. copri isolates resembling the MAGs. By combining analyses of microbial community assembly, gene expression and processing of glycan constituents of MDCF-2 with single nucleus RNA-Seq and mass spectrometric analyses of the intestine, we establish a principal role for P. copri in mediating metabolism of MDCF-2 glycans, characterize its interactions with other consortium members including Bifidobacterium longum subsp. infantis, and demonstrate the effects of P. copri-containing consortia in mediating weight gain and modulating the activities of metabolic pathways involved in lipid, amino acid, carbohydrate plus other facets of energy metabolism within epithelial cells positioned at different locations in intestinal crypts and villi. Together, the results provide insights into structure/function relationships between MDCF-2 and members of the gut communities of malnourished children; they also have implications for developing future prebiotic, probiotic and/or synbiotic therapeutics for microbiome restoration in children with already manifest malnutrition, or who are at risk for this pervasive health challenge.

Bioactive glycans in a microbiome-directed food for malnourished children.

Evidence is accumulating that perturbed postnatal development of the gut microbiome contributes to childhood malnutrition1-4. Designing effective microbiome-directed therapeutic foods to repair these perturbations requires knowledge about how food components interact with the microbiome to alter its expressed functions. Here we use biospecimens from a randomized, controlled trial of a microbiome-directed complementary food prototype (MDCF-2) that produced superior rates of weight gain compared to a conventional ready-to-use supplementary food (RUSF) in 12-18-month-old Bangladeshi children with moderate acute malnutrition (MAM)4. We reconstructed 1000 bacterial genomes (metagenome-assembled genomes, MAGs) present in their fecal microbiomes, identified 75 whose abundances were positively associated with weight gain (change in weight-for-length Z score, WLZ), characterized gene expression changes in these MAGs as a function of treatment type and WLZ response, and used mass spectrometry to quantify carbohydrate structures in MDCF-2 and feces. The results reveal treatment-induced changes in expression of carbohydrate metabolic pathways in WLZ-associated MAGs. Comparing participants consuming MDCF-2 versus RUSF, and MDCF-2-treated children in the upper versus lower quartiles of WLZ responses revealed that two Prevotella copri MAGs positively associated with WLZ were principal contributors to MDCF-2-induced expression of metabolic pathways involved in utilization of its component glycans. Moreover, the predicted specificities of carbohydrate active enzymes expressed by polysaccharide utilization loci (PULs) in these two MAGs correlate with the (i) in vitro growth of Bangladeshi P. copri strains, possessing differing degrees of PUL and overall genomic content similarity to these MAGs, cultured in defined medium containing different purified glycans representative of those in MDCF-2, and (ii) levels of carbohydrate structures identified in feces from clinical trial participants. In the accompanying paper5, we use a gnotobiotic mouse model colonized with age- and WLZ-associated bacterial taxa cultured from this study population, and fed diets resembling those consumed by study participants, to directly test the relationship between P. copri, MDCF-2 glycan metabolism, host ponderal growth responses, and intestinal gene expression and metabolism. The ability to identify bioactive glycan structures in MDCFs that are metabolized by growth-associated bacterial taxa will help guide recommendations about use of this MDCF for children with acute malnutrition representing different geographic locales and ages, as well as enable development of bioequivalent, or more efficacious, formulations composed of culturally acceptable and affordable ingredients.

Success of health cell approach in improving knowledge, attitude and practice related to COVID-19: difference-in-differences analyses of a community-based quasi-experimental trial.

OBJECTIVES: There remain hesitations and miscommunication regarding appropriate public health behaviours and conceptions related to COVID-19. We tested the effectiveness of the community-based health cell approach in improving knowledge, attitude and practice (KAP) related to COVID-19. SETTING: Households of the Bauniabadh slum area in Mirpur, Dhaka, Bangladesh. PARTICIPANTS: Household heads (HHs) and homemakers (HMs) of intervention (n=211) and comparison households (n=209). INTERVENTIONS: Behaviour change communication delivered at the community level in a quasi-experimental manner through small-scale community meetings and home visits. OUTCOME VARIABLES AND METHODS: The outcomes of interest were before-after mean and per cent changes in KAP scores. Data were collected from HHs and HMs before and after the intervention and difference-in-differences (DID) analysis technique was applied. RESULTS: We found statistically significant (p<0.05) before-after differences in the responses to the KAP questions made by the intervention groups. The DID models estimated the improvements in COVID-19-related KAP of HHs by 16.58 (95% CI: 14.05, 19.12), 20.92 (95% CI: 18.17, 23.67) and 28.45 (95% CI: 23.84, 33.07) per cent points, respectively. The DID estimates of KAP in HMs were 17.8 (95% CI: 15.09, 20.51), 22.33 (95% CI: 19.47, 25.19) and 28.06 (95% CI: 23.18, 32.93) per cent points, respectively. Overall, 20.91 (95% CI: 18.87, 22.94) and 21.81 (95% CI: 19.68, 23.94) per cent points of improvement were observed among HHs and HMs, respectively. The DID estimates of before-after mean changes in different KAP domains ranged from 2.24 to 2.68 units and the overall changes in KAP scores among HHs and HMs were 7.11 (95% CI: 6.42, 7.8) and 7.42 (95% CI: 6.69, 8.14) units. CONCLUSION: Scientifically valid information disseminated at the community level using the health cell approach could bring positive changes in KAP related to COVID-19.

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.