Mixed metals exposure and cognitive function in Bangladeshi adolescents.

BACKGROUND: Over 57 million people in Bangladesh have been chronically exposed to arsenic-contaminated drinking water. They also face environmental exposure to elevated levels of cadmium (Cd), manganese (Mn), and lead (Pb), all of which have been previously observed in environmental and biological samples for this population. These metals have been linked to adverse neurocognitive outcomes in adults and children, though their effects on adolescents are not yet fully characterized. Additionally, previous studies have linked selenium (Se) to protective effects against the toxicity of these other metals. OBJECTIVES: To examine the associations between mixed metals exposure and cognitive function in Bangladeshi adolescents. METHODS: The Metals, Arsenic, & Nutrition in Adolescents study (MANAs) is a cross-sectional study of 572 Bangladeshi adolescents aged 14-16 years, whose parents were enrolled in the Health Effects of Arsenic Longitudinal Study (HEALS). Biosamples were collected from these adolescents for measurement of whole blood metalloid/metal levels of As, Cd, Mn, Pb, and Se. Participants also completed an abbreviated version of The Cambridge Neuropsychological Test Automated Battery (CANTAB), a cognitive function test designed to measure performance across several aspects of executive function. Linear regression was used to examine associations for each metal while controlling for the other metals. Bayesian Kernel Machine Regression (BKMR) assessed the overall mixture effect in addition to confirming the effects of individual metal components observed via linear regression. RESULTS: Linear regression revealed negative associations for Spatial Working Memory and both As and Mn (As B=-2.40, Mn B=-5.31, p < 0.05). We also observed negative associations between Cd and Spatial Recognition Memory (B=-2.77, p < 0.05), and Pb and Delayed Match to Sample, a measure of visual recognition and memory (B=-3.67, p < 0.05). Finally, we saw a positive association for Se and Spatial Span Length (B=0.92, p < 0.05). BKMR results were largely consistent with the regression analysis, showing meaningful associations for individual metals and CANTAB subtests, but no overall mixture effect. Via BKMR, we observed negative associations between Pb and Delayed Match to Sample, and Cd and Spatial Recognition Memory; this analysis also showed positive associations for Se and the Planning, Reaction Time, and Spatial Span subtests. BKMR posterior inclusion probability consistently reported that Se, the only component of the mixture to show a positive association with cognition, was the most important member of the mixture. CONCLUSIONS: Overall, we found Se to be positively associated with cognition, while Mn and As were linked to poorer working memory, and Cd and Pb were associated with poorer visual recognition and memory. Our observations are consistent with previous reports on the effects of these metal exposures in adults and children. Our findings also suggest agreement between linear regression and BKMR methods for analyzing metal mixture exposures. Additional studies are needed to evaluate the impact of mixed metals exposure on adverse health and poorer cognition later in life for those exposed during adolescence. Findings also suggest that metal exposure mitigation efforts aimed at adolescents might influence lifelong cognitive outcomes in regions where environmental exposure to metals is endemic.

Furthering climate-smart farming with the introduction of floating agriculture in Bangladeshi wetlands: Successes and limitations of an innovation transfer.

Although floating farming, a climate-smart practice, is a response to climate change challenges facing agriculture in wetland areas, the adoption of floating agriculture in Bangladesh wetland areas (also known as Haor) is slow. The purpose of our study was to identify the factors that motivate and barriers that inhibit the adoption of floating agriculture in the Haor region in Bangladesh's Kishoreganj district. To achieve our purpose, we used Roger's five-stage innovation-decision theory. We collected data from a sample of 120 Haor rural farmers using a quantitative questionnaire answered via a personal interview. We used a binary logistic regression to identify the factors that predict farmers' motivational actions in adopting floating agriculture. In addition, we rank ordered the data to identify the obstacles that prohibit farmers from implementing floating agriculture. The results demonstrate that education, training related to floating agriculture, credit received, communication behavior, trialability and observability, and complexity in practicing floating agriculture motivate farmers to adopt floating agriculture. The results also show that climatic factors (e.g., high waves and excessive rainfall, aquatic plant scarcity) and non-climatic factors (e.g., inadequate demonstration plots, conflict, and political power abuse) inhibit adoption of floating agriculture. Our study provides suggestions for increasing farmers' adoption of floating agriculture in wetland areas.

Nutrition, one-carbon metabolism and arsenic methylation in Bangladeshi adolescents.

BACKGROUND: Over 57 million people in Bangladesh are chronically exposed to arsenic-contaminated drinking water. Ingested inorganic arsenic (InAs) undergoes hepatic methylation generating monomethyl- (MMAs) and dimethyl- (DMAs) arsenic species in a process that facilitates urinary As (uAs) elimination. One-carbon metabolism (OCM), a biochemical pathway that is influenced by folate and vitamin B12, facilitates the methylation of As. OCM also supports nucleotide and amino acid synthesis, particularly during periods of rapid growth such as adolescence. While folate supplementation increases As methylation and lowers blood As (bAs) in adults, little data is available for adolescents. OBJECTIVES: To examine the associations between OCM-related micronutrients and As methylation in Bangladeshi adolescents chronically exposed to As-contaminated drinking water. METHODS: We conducted a cross-sectional study of 679 Bangladeshi adolescents, including 320 boys and 359 girls aged 14-16 years. Nutritional status was assessed by red blood cell (RBC) folate, plasma folate, plasma B12 and homocysteine (Hcys). Arsenic-related outcomes included blood arsenic (bAs), urinary arsenic (uAs), and urinary arsenic metabolites expressed as a percentage of total urinary As: %InAs, %MMAs, %DMAs. RESULTS: Boys had significantly lower B12, higher Hcys, higher bAs, higher uAs, higher %MMAs, and a trend toward lower RBC folate compared to girls. Therefore, regression analyses controlling for water As and BMI were sex stratified. Among girls, RBC folate was inversely associated with bAs, plasma B12 was inversely associated with uAs, and plasma Hcys was inversely associated with %MMA. Among boys, plasma folate was inversely associated with %InAs and positively associated with %DMA, RBC folate was inversely associated with %InAs and positively associated with %MMA, while Hcys was positively associated with %InAs. CONCLUSIONS: These findings suggest that associations between OCM nutritional status, bAs, and distribution of As metabolites in adolescents are similar to previously reported observations in adults and in children. The As methylation findings are statistically significant among boys but not among girls; this may be related to estrogen which more strongly influences OCM in females. The inverse association between Hcys and %MMA in girls is somewhat unexpected given that Hcys is known to be an indicator of impaired OCM and low folate/B12 in adults. Overall, these results indicate that the associations between OCM-related micronutrients and arsenic methylation in adolescents are generally similar to prior findings in adults, though these associations may differ by sex. Additionally, these findings suggest that more investigation into the role of Hcys in adolescent physiology is needed, perhaps particularly for girls. Additional studies are needed to evaluate the impact of OCM and As methylation on As-related adverse health outcomes (such as cancer and cardiovascular disease) in people exposed to As during adolescence.

Sand Barriers around Latrine Pits Reduce Fecal Bacterial Leaching into Shallow Groundwater: A Randomized Controlled Trial in Coastal Bangladesh.

We evaluated the effectiveness of a sand barrier around latrine pits in reducing fecal indicator bacteria (FIB) leaching into shallow groundwater. We constructed 68 new offset single pit pour flush latrines in the Galachipa subdistrict of coastal Bangladesh. We randomly assigned 34 latrines to include a 50 cm thick sand barrier under and around the pit and 34 received no sand barrier. Four monitoring wells were constructed around each pit to collect water samples at baseline and subsequent nine follow-up visits over 24 months. Samples were tested using the IDEXX Colilert method to enumerate E. coli and thermotolerant coliforms most probable number (MPN). We determined the difference in mean log10MPN FIB counts/100 mL in monitoring well samples between latrines with and without a sand barrier using multilevel linear models and reported cluster robust standard error. The sand barrier latrine monitoring well samples had 0.38 mean log10MPN fewer E. coli (95% CI: 0.16, 0.59; p = 0.001) and 0.38 mean log10MPN fewer thermotolerant coliforms (95% CI: 0.14, 0.62; p = 0.002), compared to latrines without sand barriers, a reduction of 27% E. coli and 24% thermotolerant coliforms mean counts. A sand barrier can modestly reduce the risk presented by pit leaching.

Early life and adolescent arsenic exposure from drinking water and blood pressure in adolescence.

OBJECTIVES: Evidence of the association between inorganic arsenic (As) exposure, especially early-life exposure, and blood pressure (BP) in adolescence is limited. We examined the association of As exposure during early childhood, childhood, and adolescence with BP in adolescence. METHODS: We conducted a cross-sectional study of 726 adolescents aged 14-17 (mean 14.75) years whose mothers were participants in the Bangladesh Health Effects of Arsenic Longitudinal Study (HEALS). Adolescents' BP was measured at the time of their recruitment between December 2012 and December 2016. We considered maternal urinary As (UAs), repeatedly measured during childhood, as proxy measures of early childhood (<5 years old, A1) and childhood (5-12 years old, A2) exposure. Adolescents' current UAs was collected at the time of recruitment (14-17 years of age, A3). RESULTS: Every doubling of UAs at A3 and maternal UAs at A1 was positively associated with a difference of 0.7-mmHg (95% confidence interval [CI]: 0.1, 1.3) and a 0.7-mmHg (95% CI: 0.05, 1.4) in SBP, respectively. These associations were stronger in adolescents with a BMI above the median (17.7 kg/m2) than those with a BMI below the median (P for interaction = 0.03 and 0.03, respectively). There was no significant association between any of the exposure measures and DBP. The Weighted Quantile Sum (WQS) regression confirmed that adolescents' UAs at A3 and maternal UAs at A1 contributed the most to the overall effect of As exposure at three life stages on SBP. Mixture analyses using Bayesian Kernel Machine Regression identified UAs at A3 as a significant contributor to SBP and DBP independent of other concurrent blood levels of cadmium, lead, manganese, and selenium. CONCLUSION: Our findings suggest an association of current exposure and early childhood exposure to As with higher BP in adolescents, which may be exacerbated by higher BMI at adolescence.

The impact of multiple stenosis and aneurysms on arterial diseases: A cardiovascular study.

The comparative effect of serial stenosis and aneurysms arteries on blood flow is examined to identify atherosclerotic diseases. The finite element approach has been used to solve the continuity, momentum, and Oldroyd-B partial differential equations to analyze the blood flow. Newtonian and non-Newtonian both cases are taken for the viscoelastic response of blood. In this study, the impact of multiple stenotic and aneurysmal arteries on blood flow have been studied to determine the severity of atherosclerosis diseases through the analysis of blood behavior. The novel aspect of the study is its assessment of the severity of atherosclerotic disorders for the occurrence of serial stenosis and aneurysm simultaneously in the blood vessel wall in each of the four cases. The maximum abnormal arterial blood flow effect is found for the presence of serial stenoses compared to aneurysms which refers to the severity of atherosclerosis. At the hub of stenosis, the blood velocity magnitude and wall shear stress (WSS) are higher, whereas the arterial wall normal gradient values are lower. For all cases, the contrary results are observed at the hub of the aneurysmal model. The blood flow has been affected significantly by the increases in Reynolds number for both models. The influence of stenotic and aneurysmal arteries on blood flow is graphically illustrated in terms of the velocity profile, pressure distribution, and WSS. Medical experts may use this study's findings to assess the severity of cardiovascular diseases.

ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application.

Chronic kidney diseases (CKDs) are a significant public health issue with potential for severe complications such as hypertension, anemia, and renal failure. Timely diagnosis is crucial for effective management. Leveraging machine learning within healthcare offers promising advancements in predictive diagnostics. In this paper, we developed a machine learning-based kidney diseases prediction (ML-CKDP) model with dual objectives: to enhance dataset preprocessing for CKD classification and to develop a web-based application for CKD prediction. The proposed model involves a comprehensive data preprocessing protocol, converting categorical variables to numerical values, imputing missing data, and normalizing via Min-Max scaling. Feature selection is executed using a variety of techniques including Correlation, Chi-Square, Variance Threshold, Recursive Feature Elimination, Sequential Forward Selection, Lasso Regression, and Ridge Regression to refine the datasets. The model employs seven classifiers: Random Forest (RF), AdaBoost (AdaB), Gradient Boosting (GB), XgBoost (XgB), Naive Bayes (NB), Support Vector Machine (SVM), and Decision Tree (DT), to predict CKDs. The effectiveness of the models is assessed by measuring their accuracy, analyzing confusion matrix statistics, and calculating the Area Under the Curve (AUC) specifically for the classification of positive cases. Random Forest (RF) and AdaBoost (AdaB) achieve a 100% accuracy rate, evident across various validation methods including data splits of 70:30, 80:20, and K-Fold set to 10 and 15. RF and AdaB consistently reach perfect AUC scores of 100% across multiple datasets, under different splitting ratios. Moreover, Naive Bayes (NB) stands out for its efficiency, recording the lowest training and testing times across all datasets and split ratios. Additionally, we present a real-time web-based application to operationalize the model, enhancing accessibility for healthcare practitioners and stakeholders. Web app link: https://rajib-research-kedney-diseases-prediction.onrender.com/.

4mC-CGRU: Identification of N4-Methylcytosine (4mC) sites using convolution gated recurrent unit in Rosaceae genome.

An epigenetic modification is DNA N4-methylcytosine (4mC) that affects several biological functions without altering the DNA nucleotides, including DNA conformation, cell development, replication, stability, and DNA structural changes. To prevent restriction enzyme from damaging self-DNA, 4mC performs a critical role in restriction-modification functions. Existing studies mainly focused on finding hand-crafted features to identify 4mC locations, but these methods are inefficient due to high time consuming and high costs. In our research work, we propose a 4mC-CGRU which is a deep learning-based computational model with a standard encoding method to identify the 4mC sites from DNA sequences that learned autonomous feature selection in the Rosaceae genome, particularly in Rosa chinensis (R. chinensis) and Fragaria vesca (F. vesca). The proposed model consists of a convolutional neural network (CNN) and a gated recurrent unit network (GRU)-based model for identifying 4mC sites from Fragaria vesca and Rosa chinensis in the genomes. The CNN model extracts useful features from the datasets and the GRU classifies the DNA sequences. Thus, our approach can automatically extract important features to detect relative sites from DNA sequence. The performance analysis shows that the proposed model consistently outperforms over the state-of-the-art works in detecting 4mC sites.

A Grid Search-Based Multilayer Dynamic Ensemble System to Identify DNA N4-Methylcytosine Using Deep Learning Approach.

DNA (Deoxyribonucleic Acid) N4-methylcytosine (4mC), a kind of epigenetic modification of DNA, is important for modifying gene functions, such as protein interactions, conformation, and stability in DNA, as well as for the control of gene expression throughout cell development and genomic imprinting. This simply plays a crucial role in the restriction-modification system. To further understand the function and regulation mechanism of 4mC, it is essential to precisely locate the 4mC site and detect its chromosomal distribution. This research aims to design an efficient and high-throughput discriminative intelligent computational system using the natural language processing method "word2vec" and a multi-configured 1D convolution neural network (1D CNN) to predict 4mC sites. In this article, we propose a grid search-based multi-layer dynamic ensemble system (GS-MLDS) that can enhance existing knowledge of each level. Each layer uses a grid search-based weight searching approach to find the optimal accuracy while minimizing computation time and additional layers. We have used eight publicly available benchmark datasets collected from different sources to test the proposed model's efficiency. Accuracy results in test operations were obtained as follows: 0.978, 0.954, 0.944, 0.961, 0.950, 0.973, 0.948, 0.952, 0.961, and 0.980. The proposed model has also been compared to 16 distinct models, indicating that it can accurately predict 4mC.

A cross-sectional study of water arsenic exposure and intellectual function in adolescence in Araihazar, Bangladesh.

BACKGROUND: Exposure to inorganic arsenic (As) from drinking water is associated with modest deficits in intellectual function in young children; it is unclear whether deficits occur during adolescence, when key brain functions are more fully developed. OBJECTIVES: We sought to determine the degree to which As exposure is associated with adolescent intelligence, and the contributory roles of lead, cadmium, manganese and selenium. METHODS: We recruited a cross-section of 726 14-16 year olds (mean age = 14.8 years) whose mothers are participants in the Bangladesh Health Effects of Arsenic Longitudinal Study (HEALS), and whose household well water As levels, which varied widely, were well characterized. Using a culturally modified version of the WISC-IV, we examined raw Full Scale scores, and Verbal Comprehension, Perceptual Reasoning, Working Memory and Processing Speed Indices. Blood levels of As (BAs), Mn, Pb, Cd and Se were assessed at the time of the visit, as was creatinine-adjusted urinary As (UAs/Cr). RESULTS: Linear regression analyses revealed that BAs was significantly negatively associated with all WISC-IV scores except for Perceptual Reasoning. With UAs/Cr as the exposure variable, we observed significantly negative associations for all WISC-IV scores. Except for Se, blood levels of other metals, were also associated with lower WISC-IV scores. Controlling for covariates, doubling BAs, or UAs/Cr, was associated with a mean decrement (95% CI) of 3.3 (1.1, 5.5), or 3.0 (1.2, 4.5) points, respectively, in raw Full scale scores with a sample mean of 177.6 (SD = 36.8). Confirmatory analyses using Bayesian Kernel Machine Regression, which identifies important mixture members, supported these findings; the primary contributor of the mixture was BAs, followed by BCd. CONCLUSIONS: Our data indicate that the adverse consequences of As exposure on neurodevelopment observed in other cross-sectional studies of younger children are also apparent during adolescence. They also implicate Cd as a neurotoxic element that deserves more attention.

Child Intelligence and Reductions in Water Arsenic and Manganese: A Two-Year Follow-up Study in Bangladesh.

BACKGROUND: Arsenic (As) exposure from drinking water is associated with modest intellectual deficits in childhood. It is not known whether reducing exposure is associated with improved intelligence. OBJECTIVE: We aimed to determine whether reducing As exposure is associated with improved child intellectual outcomes. METHODS: Three hundred three 10-year-old children drinking from household wells with a wide range of As concentrations were enrolled at baseline. In the subsequent year, deep community wells, low in As, were installed in villages of children whose original wells had high water As (WAs ≥ 50 µg/L). For 296 children, intelligence was assessed by WISC-IV (Wechsler Intelligence Scale for Children, 4th ed.), with a version modified for the study population, at baseline and approximately 2 years later; analyses considered standardized scores for both Full Scale IQ and Verbal Comprehension, Perceptual Reasoning, Working Memory, and Processing Speed Indices. Creatinine-adjusted urinary arsenic (UAs/Cr), blood As (BAs), and blood manganese (BMn) were assessed at both times. RESULTS: UAs/Cr concentrations declined significantly by follow-up for both the high (≥ 50 µg/L) and low (< 50 µg/L) WAs subgroups. At baseline, adjusting for maternal age and intelligence, plasma ferritin, head circumference, home environment quality, school grade, and BMn, UAs/Cr was significantly negatively associated with Full Scale IQ, and with all Index scores (except Processing Speed). After adjustment for baseline Working Memory scores and school grade, each 100-µg/g reduction in UAs/Cr from baseline to follow-up was associated with a 0.91 point increase in Working Memory (95% CI: 0.14, 1.67). The change in UAs/Cr across follow-up was not significantly associated with changes in Full Scale IQ or Index scores. CONCLUSIONS: Installation of deep, low-As community wells lowered UAs, BAs, and BMn. A greater decrease in UAs/Cr was associated with greater improvements in Working Memory scores, but not with a greater improvement in Full Scale IQ. CITATION: Wasserman GA, Liu X, Parvez F, Factor-Litvak P, Kline J, Siddique AB, Shahriar H, Uddin MN, van Geen A, Mey JL, Balac O, Graziano JH. 2016. Child intelligence and reductions in water arsenic and manganese: a two-year follow-up study in Bangladesh. Environ Health Perspect 124:1114-1120; http://dx.doi.org/10.1289/ehp.1509974.

The effect of antisense to NF-κB in an albumin microsphere formulation on the progression of left-ventricular remodeling associated with chronic volume overload in rats.

BACKGROUND: Increased NF-κB levels play a crucial role in the pathophysiology of heart failure and are known to cause ventricular remodeling. Antisense therapy can be used for blocking the expression of NF-κB and subsequently avoiding heart failure. However, as with most biotechnology products, molecular instability and overall cost are often the major issues and concerns limiting the advancement of most antisense drugs to the market. Therefore, a cost-efficient biodegradable sustained release particle drug delivery system to transport and target NF-kB antisense to its intended site of action would be ideal. PURPOSE: To evaluate the in vivo performance of a sustained release spray-dried albumin microsphere formulation for effective delivery and treatment of left ventricular remodeling with antisense to NF-κB. METHODS: Albumin-based microspheres encapsulating antisense to NF-kB were prepared by spray drying and studied in a rat model to treat congestive heart failure. RESULTS: The NF-κB activation and TNF-α release seen in treated animals were significantly lower than control animals. Ventricular remodeling was controlled in animals with antisense-treated AV fistulas as ΔV0-25 and ΔV0 were significantly lower compared to animals with untreated AV fistulas. CONCLUSION: This treatment was successful in curbing ventricular remodeling by suppressing NF-κB activation.