Arsenic, a global pollutant and a threshold-free primary carcinogen, can accumulate in rice. Previous studies have focused on arsenic poisoning in drinking water and the effects on gut microbes. The research on arseniasis through food, which involves the bio-transformation of arsenic, and the related changes in gut microbiome is insufficient. Mice were exposed from animal feed prepared with four arsenic species (iAsIII, iAsV, MMA, and DMA) at a dose of 30 mg/kg according to the arsenic species proportion in rice for 30 days and 60 days. The levels of total arsenic (tAs) and arsenic species in mice feces and urine samples were determined using ICP-MS and HPLC-ICP-MS, respectively. 16S rRNA and ITS gene sequencing were conducted on microbial DNA extracted from the feces samples. At 30 days and 60 days exposure, the tAs levels excreted from urine were 0.0092 and 0.0093 mg/day, and tAs levels in feces were 0.0441 and 0.0409 mg/day, respectively. We found significant differences in arsenic species distribution in urine and feces (p < 0.05). In urine, the predominant arsenic species were iAsIII (23% and 14%, respectively), DMA (55% and 70%, respectively), and uAs (unknown arsenic, 14% and 10%, respectively). In feces, the proportion of major arsenic species (iAsV, 26% and 21%; iAsIII, 16% and 15%; MMA, 14% and 14%; DMA, 19% and 19%; and uAs, 22% and 29%, respectively) were evenly distributed. Microbiological analysis (MRPP test, α- and β-diversities) showed that diversity of gut bacteria was significantly related to arsenic exposure through food, but diversity of gut fungi is less affected. Manhattan plot and LEfSe analysis showed that arsenic exposure significantly changes microbial taxa, which might be directly associated with arsenic metabolism and diseases mediated by arsenic exposure, such as Deltaproteobacteria, Polynucleobacter, Saccharomyces, Candida, Amanitaceae, and Fusarium. Network analysis was used to identify the changing hub taxa in feces along with arsenic exposure. Function predicting analysis indicated that arsenic exposure might also significantly increase differential metabolic pathways and would disturb carbohydrates, lipid, and amino acids metabolism of gut bacteria. The results demonstrate that subchronic arsenic exposure via food significantly changes the gut microbiome, and the toxicity of arsenic in food, especially in staples, should be comprehensively evaluated in terms of the disturbance of microbiome, and feces might be the main pathway through which arsenic from food exposure is excreted and bio-transformed, providing a new insight into the investigation of bio-detoxification for arseniasis.

Background. The prevalence of obesity and type 2 diabetes mellitus (T2DM) has become the most serious global public health issue. In recent years, there has been increasing attention to the role of long noncoding RNAs (lncRNAs) in the occurrence and development of obesity and T2DM. The aim of this work was to find new lncRNAs as potential predictive biomarkers or therapeutic targets for obesity and T2DM. Methods. In this study, we identified significant differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) between adipose tissue of individuals with obesity and T2DM and normal adipose tissue (absolute log2FC≥1 and FDR<0.05). Then, the lncRNA-miRNA interactions predicted by miRcode were further screened with a threshold of MIC>0.2. Simultaneously, the mRNA-miRNA interactions were explored by miRWalk 2.0. Finally, a ceRNA network consisting of lncRNAs, miRNAs, and mRNAs was established by integrating lncRNA-miRNA interactions and mRNA-miRNA interactions. Results. Upon comparing adipose tissue from individuals with obesity and T2DM and normal adipose tissues, 364 significant DEmRNAs, including 140 upregulated and 224 downregulated mRNAs, were identified in GSE104674; in addition, 231 significant DEmRNAs, including 146 upregulated and 85 downregulated mRNAs, were identified in GSE133099. GO and KEGG analyses have shown that downregulated DEmRNAs in GSE104674 and GSE133099 were associated with obesity- and T2DM-related biological pathways, such as lipid metabolism, AMPK signaling, and insulin resistance. Furthermore, 28 significant DElncRNAs, including 14 upregulated and 14 downregulated lncRNAs, were found. Based on the predicted lncRNA-miRNA and mRNA-miRNA relationships, we constructed a competitive endogenous RNA (ceRNA) network, including five lncRNAs, ten miRNAs, and 15 mRNAs. KEGG-GSEA analysis revealed that four lncRNAs (FLG-AS1, SNAI3-AS1, AC008147.0, and LINC02015) in the ceRNA network were related to the biological pathways of metabolic diseases. Conclusions. Through ceRNA network analysis, our study identified four new lncRNAs that may be used as potential biomarkers and therapeutic targets of obesity and T2DM, thus laying a foundation for future clinical studies.

Objective: We aimed to evaluate whether depression is associated with increased risk of dietary inflammatory index (DII) or energy-adjusted DII (E-DII) and whether the association is partly explained by insulin resistance (IR).Methods: Base on the National Health and Nutrition Examination Survey (NHANES) 2005–2018. Univariate analyses of continuous and categorical variables were performed using t-test, ANOVA, and χ² test, respectively. Logistic regression was used to analyze the relationship between DII or E-DII and depression in three different models. Mediation analysis was used to assess the potential mediation effects of homeostatic model assessment-IR (HOMA-IR).Results: A total of 70,190 participants were included, and the DII score was higher in the depressed group. DII score was related to all participant characteristics except age (p < 0.05). After being included in covariates (Model 3), participants in the highest quartile of DII score have increased odds of depression (OR: 1.82, 95% CI: 1.28–2.58) compared with those in the first quartile of DII score. And, a significant dose–response relationship was found (p-trend <0.05). No interaction between DII and HOMA-IR was observed in terms of the risk of depression, and HOMA-IR did not find to play a mediating role in the association between DII and depression. Similar results were obtained for the association between E-DII and depression.Conclusion: Our results suggest that a higher pro-inflammatory diet increases the risk of depression in U.S. adults, while there was no evidence of a multiplicative effect of DII or E-DII and HOMA-IR on disease risk, nor of a mediating effect of HOMA-IR.

With an estimated 425 million diabetic patients worldwide in 2019, type 2 diabetes (T2D) has reached a pandemic proportion and represents a major unmet medical need. A key determinant of the development and progression of T2D is pancreatic beta‐cell dysfunction, including the loss of cell mass, the impairment of insulin biosynthesis, and inadequate exocytosis. Recent studies have shown that transient receptor potential vanilloid 4 (TRPV4), a Ca²⁺‐permeable nonselective cation channel, is involved in beta‐cell replication, insulin production and secretion. TRPV4 agonists have insulinotropic activity in pancreatic beta‐cell lines, but the prolonged activation of TRPV4 leads to beta‐cell dysfunction and death. In addition, TRPV4 is involved in a wide variety of pathophysiological activities and has been reported to play an important role in diabetes‐related complications such as obesity, cardiovascular diseases, diabetic retinopathy, nephropathy, and neuropathy. In a rodent T2D model, Trpv4 agonists promote vasodilation and improve cardiovascular function, while Trpv4 antagonists reduce high‐fat diet‐induced obesity, insulin resistance, diabetic nephropathy, retinopathy, and neuropathy. These findings raise interest in using TRPV4 as a therapeutic target for T2D. In this review, we intend to summarize the latest findings regarding the role of TRPV4 in diabetes as well as diabetes‐related conditions and to evaluate its potential as a therapeutic target for diabetes and diabetes‐related diseases.

To understand the heavy metal pollution in agricultural soils along the East River basin and assess the pollution related health effect to local residents, interviews and archived data were obtained to identify the study sites affected by polluted tailing. Soil samples were collected and tested for heavy metal content and the Comprehensive Pollution Index (CPI). The degree of pollution of agricultural soils in the area was assessed using GIS-based Spatial distribution map of heavy metals and the trend of soil heavy metal risk. Two villages (Matian and Zhudui) near the East River were included in this study for health effect assessment. A total of 193 residents aged 15 or above from each village were tested for the present status of chronic diseases. Convenient sampling method was used to collect blood samples from 78 residents for heavy metal concentration. The contents of Pb, Cd, As, Zn, and Cu in the agricultural soils were all over the standards with a moderate to severe CPI. Among these metals, Cd was the highest followed by Pb, and Cu was the lowest. The contents of Pb, Cd, As, and Zn tend to be higher in soils closer to the river. The prevalence of chronic diseases was over 30%, which is significantly higher than the report from the national central region (23.15%). The average blood lead level (BLL) among children under 14 years is 7.42 μg/dL. Although the adults in Matian village had a significantly higher BLL (χ² = 8.70, p = 0.03) as compared to Zhudui village, there was no significant difference for the prevalence of chronic diseases between the two villages (χ² = 3.23, p = 0.09). The mean BLL of children and the proportion of children with BLL ≥ 10 µg/dL in this study are equivalent to the national average. The higher BLL concentration and prevalence of chronic diseases in adults might be due to their long-term exposure to heavy metal contamination environment and higher background level of heavy metals. Findings from this study will form the baseline information for local government to the development of effective approaches to control the heavy metal contamination and reduce the pollution related adverse health effect on local residents.