Environmentally relevant exposure to cotinine induces neurobehavioral toxicity in zebrafish (Danio rerio): A study using neurobehavioral and metabolomic approaches.

As an important psychoactive substance, cotinine is ubiquitous in aquatic environment and poses a threat to aquatic organisms. However, the mechanism of its adverse health impacts remains unclear. We evaluated the effects of cotinine exposure at environmentally relevant concentrations on the development and locomotor behavior of zebrafish (Danio rerio) larvae using neurotransmitters and whole endogenous metabolism. Mild developmental toxicity and significant neurobehavior disorder, such as spontaneous movement (1-1000 µg/L), 48 hpf tactile response (50, 100, and 1000 µg/L), and 144 hpf swimming speed (1, 10, 100, 500, and 1000 µg/L), were observed in zebrafish. Exposure to cotinine led to significant alterations in 11 neurotransmitters, including homogentisic acid, serotonin, glutamic acid and aspartic acid, etc. 298 metabolites were identified and two pathways - linoleic acid metabolism and taurine and hypotaurine metabolism - were delineated. In addition, amino acid neurotransmitters were significantly correlated with metabolites such as arachidonic acid as well as its derivatives, steroidal compounds, and amino acids. Serotonin demonstrates a noteworthy correlation with 31 out of 40 differentially expressed neurotransmitters, encompassing lipids, amino acids, and other compounds. These novel findings contribute to a comprehensive understanding of the ecological risks associated with cotinine contamination in surface waters.

Identification of key factors affecting neonicotinoid residues in crops and risk of dietary exposure.

Neonicotinoids, widely used on farmland, are ubiquitous in food; however, their distribution among various crops and associated exposure risks at the provincial level in China remain unclear. We collected 19 types of crop samples (fruits, vegetables, and tea) from farmland in nine prefectural cities in Zhejiang Province, China. We analyzed nine commonly used neonicotinoids in the edible portions of these crops. A notable detection rate (42.1 %-82.9 %) and high residual neonicotinoid concentrations (278 ± 357 ng/g) were observed. Tea exhibited the highest residue, followed by fruits, and vegetables showed the lowest (P < 0.05). Neonicotinoid ratios in crops to soil (R_C/S) and soil to water (R_S/W) were defined to discern insecticide distribution across different environments. Increased water solubility leads to increased migration of neonicotinoids (R_S/W) from agricultural soils to water through runoff, thereby increasing the relative contribution of nitenpyram and dinotefuran in water. In comparison with other studied compounds, all crops demonstrated the strongest soil uptake of thiamethoxam, denoted by the highest R_C/S value. Elevated R_C/S values in tea, pickled cabbage, and celery suggest increased susceptibility of these crops to neonicotinoid absorption from the soil (P < 0.05). Estimated dietary intake for teenagers, adults and elders was 8.9 ± 0.5, 8.9 ± 0.6, and 8.8 ± 0.3 µg/kg/d, respectively, below the reference dose (57 µg/kg/d). Teenagers, compared to adults and elders, exhibited significantly higher neonicotinoid exposure through fruit consumption, emphasizing the need for increased attention to neonicotinoid exposure among vulnerable populations.

Autophagy-related tumor subtypes associated with significant gene expression profiles and immune cell infiltration signatures to reveal the prognosis of non-small cell lung cancer.

Autophagy plays an important role in non-small cell lung cancer (NSCLC). We aimed to establish novel autophagy-related tumor subtypes to distinguish the prognosis of NSCLC. In this study, gene expression profiles, mutation data and clinical information obtained from the Cancer Genome Atlas. Kaplan Meier-plotter could evaluate prognostic value of autophagy-related genes. Consensus clustering revealed autophagy-related tumor subtypes. Gene expression profiles, mutation data and immune infiltration signatures were identified, oncogenic pathways and gene-drug interactions were performed according to the clusters. Finally, a total of 23 prognostic genes were screened and consensus clustering analysis divided the NSCLC into 2 clusters. The mutation signature showed that 6 genes are special. Immune infiltration signatures showed that higher fraction of immune cells was associated with cluster 1. The oncogenic pathways and gene-drug interactions also showed different patterns. In conclusion, autophagy-related tumor subtypes have different prognosis. Understanding the subtypes of NSCLC are helpful to accurately identify the NSCLC and personalized treatment.

Metabonomic and transcriptomic modulations of HepG2 cells induced by the CuO-catalyzed formation of disinfection byproducts from biofilm extracellular polymeric substances in copper pipes.

Cupric oxide (CuO) is able to catalyze the reactions among disinfectant, extracellular polymeric substances (EPS) and bromide (Br-) in copper pipes, which may deteriorate the water quality. This study aimed to investigate the metabonomic and transcriptomic modulations of HepG2 cells caused by the CuO-catalyzed formation of disinfection byproducts (DBPs) from EPS. The presence of CuO favored the substitution reactions of chlorine and bromine with EPS, inducing a higher content of total organic halogen (TOX). In addition, DBPs were shifted from chlorinated species to brominated species. A total of 182 differential metabolites (DMs) and 437 differentially expressed genes (DEGs) were identified, which were jointly involved in 38 KEGG pathways. Topology analysis indicates that glycerophospholipid and purine metabolism were disturbed most obviously. During glycerophospholipid metabolism, the differential expression of genes GPATs, AGPATs, LPINs and DGKs impacted the conversion of glycerol-3-phosphate to 2-diacyl-sn-glycerol, which further affected the conversion among phosphatidylcholine, phosphatidylserine and phosphocholines. During purine metabolism, it was mainly the differential expression of genes POLRs, RPAs, RPBs, RPCs, ENTPDs and CDs that impacted the transformation of RNA into guanine-, xanthosine-, inosine- and adenosine monophosphate, which were further successively transformed into their corresponding nucleosides and purines. The study provides an omics perspective to assess the potential adverse effects of overall DBPs formed in copper pipes on human.

Identification of a Five Autophagy Subtype-Related Gene Expression Pattern for Improving the Prognosis of Lung Adenocarcinoma.

Background: Autophagy plays an important role in lung adenocarcinoma (LUAD). In this study, we aimed to explore the autophagy-related gene (ARG) expression pattern and to identify promising autophagy-related biomarkers to improve the prognosis of LUAD. Methods: The gene expression profiles and clinical information of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA), and validation cohort information was extracted from the Gene Expression Omnibus database. The Human Autophagy Database (HADb) was used to extract ARGs. Gene expression data were analyzed using the limma package and visualized using the ggplot2 package as well as the pheatmap package in R software. Functional enrichment analysis was also performed for the differentially expressed ARGs (DEARGs). Then, consensus clustering revealed autophagy-related tumor subtypes, and differentially expressed genes (DEGs) were screened according to the subtypes. Next, the univariate Cox and multivariate Cox regression analyses were used to identify independent prognostic ARGs. After overlapping DEGs and the independent prognostic ARGs, the predictive risk model was established and validated. Correlation analyses between ARGs and clinicopathological variables were also explored. Finally, the TIMER and TISIDB databases were used to further explore the correlation analysis between immune cell infiltration levels and the risk score as well as clinicopathological variables in the predictive risk model. Results: A total of 222 genes from the HADb were identified as ARGs, and 28 of the 222 genes were pooled as DEARGs. The most significant GO term was autophagy (p = 3.05E-07), and KEGG analysis results indicated that 28 DEARGs were significantly enriched in the ErbB signaling pathway (p < 0.001). Then, consensus clustering analysis divided the LUAD into two clusters, and a total of 168 DEGs were identified according to cluster subtypes. Then univariate and multivariate Cox regression analyses were used to identify 12 genes that could serve as independent prognostic indicators. After overlapping 168 DEGs and 12 genes, 10 genes (ATG4A, BAK1, CAPNS1, CCR2, CTSD, EIF2AK3, ITGB1, MBTPS2, SPHK1, ST13) were selected for the further exploration of the prognostic pattern. Survival analysis results indicated that this risk model identified the prognosis (p = 4.379E-10). Combined with the correlation analysis results between ARGs and clinicopathological variables, five ARGs were screened as prognostic genes. Among them, SPHK1 expression levels were positively correlated with CD4+ T cells and dendritic cell infiltration levels. Conclusions: In this study, we constructed a predictive risk model and identified a five autophagy subtype-related gene expression pattern to improve the prognosis of LUAD. Understanding the subtypes of LUAD is helpful to accurately characterize the LUAD and develop personalized treatment.

Formation of carbonaceous and nitrogenous iodinated disinfection byproducts from biofilm extracellular polymeric substances by the oxidation of iodide-containing waters with lead dioxide.

Lead dioxide (PbO2) is an important form of lead mineral scales in drinking water pipes. Iodide (I-) widely presents in source waters and can be thermodynamically oxidized by PbO2 to the reactive iodine species (I2/HOI). Biofilm extracellular polymeric substances (EPS) are nonnegligible precursors of disinfection byproducts (DBPs). The aim was to study the oxidation of I- by PbO2 and formation of iodinated DBPs (I-DBPs) from EPS. At a high molar ratio of PbO2 to I- (> 100), the observed rate constants of I- oxidation decreased as pH increased from 6.0 to 9.0 with an H+ dependence of 0.79, and the rate constant (k) was 1.6 × 1011 M-2.79 s-1. Most of formed I2/HOI (> 92%) was transformed to organic iodine in the presence of EPS. EPS had a lower formation potential (FP) of carbonaceous I-DBPs (C-IDBPs), while a higher that of nitrogenous I-DBPs (N-IDBPs) than HA, resulting in a higher Chinese Hamster Ovary cell cytotoxicity. Generally, the formation of I-DBPs decreased with the increase of pH due to the reduction of surface positive charge and electrochemical driving force. PbO2 dose and I- concentration also had a significant effect on the I-DBPs formation. EPS proteins had a higher FP of both C- and N-IDBPs than polysaccharides on account of more electrophilic sites and higher nitrogen content. In proteins, aspartic acid was the main contributor to triiodomethane and iodoacetic acids formation, whereas aspartic acid, asparagine and tyrosine were the major precursors of diiodoacetonitrile and diiodoacetamide. The study helps to improve the control strategy of I-DBPs when biofilm outbreaks in lead-containing water pipes.

Clinical characteristics of COVID-19 and its comparison with influenza pneumonia.

OBJECTIVES: To recognise clinical features of COVID-19 pneumonia and its differences from influenza pneumonia. METHODS: 246 patients were enrolled into COVID-19 cohort and 120 patients into influenza cohort. All data were collected and analysed retrospectively. The variables under focus included demographic, epidemiological, clinical, laboratory and imaging characteristics of COVID-19 pneumonia and comparison were made with influenza pneumonia. RESULTS: The COVID-19 cohort included 53.25% female and 46.75% male. Their main symptom was fever; while 28.05% of patients had only initially fever; 21.54% of them remained feverless. After excluding prior kidney diseases, some patients showed abnormal urinalysis (32.11%), elevated blood creatinine (15.04%) and blood urea nitrogen (19.11%). Typical CT features included ground glass opacity, consolidation and band opacity, which could present as characteristic 'bat wing sign'. Our data showed that male, aged 65 or above, smoking, with comorbidities including diabetes, cardiovascular and kidney diseases, would experience more severe COVID-19 pneumonia. In comparison, COVID-19 cohort showed significantly higher incidence of clustering; the influenza cohort showed higher rate of fever. Both cohorts showed reduced lymphocyte numbers; however, 6 influenza patients showed lymphocytes increased, which was statistical significant compared with COVID-19 cohort. Also, influenza cohort displayed higher white blood cell counts and PCT values. CONCLUSION: There is no significant gender difference in the incidence of COVID-19 pneumonia. It predominantly affects the lung as well as the kidney. Age, smoking and comorbidities could contribute to disease severity. Although COVID-19 is more infectious, the rate of secondary bacterial infection is lower than influenza.