Nonmalignant Respiratory Effects of Chronic Arsenic Exposure from Drinking Water among Never-Smokers in Bangladesh

BACKGROUND: Arsenic from drinking water has been associated with malignant and nonmalignant respiratory illnesses. The association with nonmalignant respiratory illnesses has not been well established because the assessments of respiratory symptoms may be influenced by recall bias or interviewer bias because participants had visible skin lesions. OBJECTIVES: We examined the relationship of the serum level of Clara cell protein CC 16-a novel biomarker for respiratory illnesses-with well As, total urinary As, and urinary As methylation indices. METHODS: We conducted a cross-sectional study in nonsmoking individuals (n = 241) selected from a large cohort with a wide range of As exposure (0.1-761 mu g/L) from drinking water in Bangladesh. Total urinary As, urinary As metabolites, and serum CC16 were measured in urine and serum samples collected at baseline of the parent cohort study. RESULTS: We observed an inverse association between urinary As and serum CC 16 among persons with skin lesions (beta = -0. 13, p = 0.01). We also observed a positive association between secondary methylation index in urinary As and CC16 levels (beta = 0. 12,,P = 0.05) in the overall study population; the association was stronger among people without skin lesions (beta = 0. 18, p = 0.04), indicating that increased methylation capability may be protective against As-induced respiratory damage. In a subsample of study participants undergoing spirometric measures (n = 3 1), we observed inverse associations between urinary As and predictive FEV1 (forced expiratory volume measured in 1 sec) (r = -0.37; FEV1/forced vital capacity ratio and primary methylation index (r = -0.42, p = 0.01). CONCLUSIONS: The findings suggest that serum CC 16 may be a useful biomarker of epithelial lung damage in individuals with arsenical skin lesions. Also, we observed the deleterious respiratory effects of As exposure at concentrations lower than reported in earlier studies

Thyroid hormones and neurobehavioral functions among adolescents chronically exposed to groundwaterwith geogenic arsenic in Bangladesh

Groundwater, the major source of drinking water in Bengal Delta Plain, is contaminated with geogenic arsenic (As) enrichment affecting millions of people. Children exposed to tubewell water containing As may be associated with thyroid dysfunction, which in turn may impact neurodevelopmental outcomes. However, data to support such relationship is sparse. The purpose of this study was to examine if chronic water As (WAs) from Holocene alluvial aquifers in this region was associated with serum thyroid hormone (TH) and if TH biomarkers were related to neurobehavioral (NB) performance in a group of adolescents. A sample of 32 healthy adolescents were randomly drawn from a child cohort in the Health Effects of Arsenic Longitudinal Study (HEALS) in Araihazar, Bangladesh. Half of these participants were consistently exposed to low WAs (<10 μg/L) and the remaining half had high WAs exposure (≥10 μg/L) since birth. Measurements included serum total triiodothyronine (tT3), free thyroxine (fT4), thyrotropin (TSH) and thyroperoxidase antibodies (TPOAb); concurrent WAs and urinary arsenic (UAs); and adolescents' NB performance. WAs and UAs were positively and significantly correlated with TPOAb but were not correlated with TSH, tT3 and fT4. After accounting for covariates, both WAs and UAs demonstrated positive but non-significant relationships with TSH and TPOAb and negative but non-significant relationships with tT3 and fT4. TPOAb was significantly associated with reduced NB performance indicated by positive associations with latencies in simple reaction time (b = 82.58; p < 0.001) and symbol digit (b = 276.85; p = 0.005) tests. TSH was significantly and negatively associated with match-to-sample correct count (b = −0.95; p = 0.05). Overall, we did not observe significant associations between arsenic exposure and TH biomarkers although the relationships were in the expected directions. We observed TH biomarkers to be related to reduced NB performance as hypothesized. Our study indicated a possible mechanism of As-induced neurotoxicity, which requires further investigations for confirmatory findings

Characterization of the complete mitochondrial genome of Gangetic ailia, Ailia coila (Siluriformes: Ailiidae)

The first complete mitochondrial genome sequence of Ailia coila from Bangladesh was determined by the bioinformatic assembly of the next generation sequencing (NGS) reads. The constructed circular mitogenome for A. coila was 16,565 bp in length which harbored the canonical 13 protein-coding genes, 22 tRNAs, 2 rRNAs. Two non-coding regions, control region, D-loop (927 bp), and origin of light strand replication, OL (30 bp) were also well conserved in the mitogenome. Among the currently reported mitochondrial genomes in the order Siluriformes, A. coila was most closely related to Eutropiichthys vacha (AB919123) with 85.63% sequence identity

Identifying Insomnia From Social Media Posts: Psycholinguistic Analyses of User Tweets

BackgroundMany people suffer from insomnia, a sleep disorder characterized by difficulty falling and staying asleep during the night. As social media have become a ubiquitous platform to share users’ thoughts, opinions, activities, and preferences with their friends and acquaintances, the shared content across these platforms can be used to diagnose different health problems, including insomnia. Only a few recent studies have examined the prediction of insomnia from Twitter data, and we found research gaps in predicting insomnia from word usage patterns and correlations between users’ insomnia and their Big 5 personality traits as derived from social media interactions. ObjectiveThe purpose of this study is to build an insomnia prediction model from users’ psycholinguistic patterns, including the elements of word usage, semantics, and their Big 5 personality traits as derived from tweets. MethodsIn this paper, we exploited both psycholinguistic and personality traits derived from tweets to identify insomnia patients. First, we built psycholinguistic profiles of the users from their word choices and the semantic relationships between the words of their tweets. We then determined the relationship between a users’ personality traits and insomnia. Finally, we built a double-weighted ensemble classification model to predict insomnia from both psycholinguistic and personality traits as derived from user tweets. ResultsOur classification model showed strong prediction potential (78.8%) to predict insomnia from tweets. As insomniacs are generally ill-tempered and feel more stress and mental exhaustion, we observed significant correlations of certain word usage patterns among them. They tend to use negative words (eg, “no,” “not,” “never”). Some people frequently use swear words (eg, “damn,” “piss,” “fuck”) with strong temperament. They also use anxious (eg, “worried,” “fearful,” “nervous”) and sad (eg, “crying,” “grief,” “sad”) words in their tweets. We also found that the users with high neuroticism and conscientiousness scores for the Big 5 personality traits likely have strong correlations with insomnia. Additionally, we observed that users with high conscientiousness scores have strong correlations with insomnia patterns, while negative correlation between extraversion and insomnia was also found. ConclusionsOur model can help predict insomnia from users’ social media interactions. Thus, incorporating our model into a software system can help family members detect insomnia problems in individuals before they become worse. The software system can also help doctors to diagnose possible insomnia in patients

Changes in human peripheral blood mononuclear cell (HPBMC) populations and T-cell subsets associated with arsenic and polycyclic aromatic hydrocarbon exposures in a Bangladesh cohort

Exposures to environmental arsenic (As) and polycyclic aromatic hydrocarbons (PAH) have been shown to independently cause dysregulation of immune function. Little data exists on the associations between combined exposures to As and PAH with immunotoxicity in humans. In this work we examined associations between As and PAH exposures with lymphoid cell populations in human peripheral blood mononuclear cells (PBMC), as well as alterations in differentiation and activation of B and T cells. Two hundred men, participating in the Health Effects of Arsenic Longitudinal Study (HEALS) in Bangladesh, were selected for the present study based on their exposure to As from drinking water and their cigarette smoking status. Blood and urine samples were collected from study participants. We utilized multiparameter flow cytometry in PBMC to identify immune cells (B, T, monocytes, NK) as well as the T-helper (Th) cell subsets (Th1, Th2, Th17, and Tregs) following ex vivo activation. We did not find evidence of interactions between As and PAH exposures. However, individual exposures (As or PAH) were associated with changes to immune cell populations, including Th cell subsets. Arsenic exposure was associated with an increase in the percentage of Th cells, and dose dependent changes in monocytes, NKT cells and a monocyte subset. Within the Th cell subset we found that Arsenic exposure was also associated with a significant increase in the percentage of circulating proinflammatory Th17 cells. PAH exposure was associated with changes in T cells, monocytes and T memory (Tmem) cells and with changes in Th, Th1, Th2 and Th17 subsets all of which were non-monotonic (dose dependent). Alterations of immune cell populations caused by environmental exposures to As and PAH may result in adverse health outcomes, such as changes in systemic inflammation, immune suppression, or autoimmunity.</p

Changes in human peripheral blood mononuclear cell (HPBMC) populations and T-cell subsets associated with arsenic and polycyclic aromatic hydrocarbon exposures in a Bangladesh cohort.

Exposures to environmental arsenic (As) and polycyclic aromatic hydrocarbons (PAH) have been shown to independently cause dysregulation of immune function. Little data exists on the associations between combined exposures to As and PAH with immunotoxicity in humans. In this work we examined associations between As and PAH exposures with lymphoid cell populations in human peripheral blood mononuclear cells (PBMC), as well as alterations in differentiation and activation of B and T cells. Two hundred men, participating in the Health Effects of Arsenic Longitudinal Study (HEALS) in Bangladesh, were selected for the present study based on their exposure to As from drinking water and their cigarette smoking status. Blood and urine samples were collected from study participants. We utilized multiparameter flow cytometry in PBMC to identify immune cells (B, T, monocytes, NK) as well as the T-helper (Th) cell subsets (Th1, Th2, Th17, and Tregs) following ex vivo activation. We did not find evidence of interactions between As and PAH exposures. However, individual exposures (As or PAH) were associated with changes to immune cell populations, including Th cell subsets. Arsenic exposure was associated with an increase in the percentage of Th cells, and dose dependent changes in monocytes, NKT cells and a monocyte subset. Within the Th cell subset we found that Arsenic exposure was also associated with a significant increase in the percentage of circulating proinflammatory Th17 cells. PAH exposure was associated with changes in T cells, monocytes and T memory (Tmem) cells and with changes in Th, Th1, Th2 and Th17 subsets all of which were non-monotonic (dose dependent). Alterations of immune cell populations caused by environmental exposures to As and PAH may result in adverse health outcomes, such as changes in systemic inflammation, immune suppression, or autoimmunity