Weighted gene co-expression network analysis identified 7 modules of genes whose expression patterns were significantly correlated with SSRI exposure. Functional enrichment analysis of differentially expressed genes as well as network module genes repeatedly identified various terms associated with mitochondrial and neuronal structures, mitochondrial respiration, and neurodevelopmental processes. The enrichment of these terms indicates that toxic effects of SSRI exposure are likely caused by mitochondrial dysfunction and subsequent neurodevelopmental effects. To our knowledge, this is the first effort to study the tissue-specific transcriptomic effects of SSRIs in developing zebrafish, providing specific, high resolution molecular data regarding the sublethal effects of SSRI exposure.Understanding azo dye degrading enzymes and the encoding of their functional genes is crucial for the elucidation of their molecular mechanisms. In this study, a thermophilic strain capable of degrading azo dye was isolated from the soil near a textile dye manufacturing factory. Based on its morphological, physiological and biochemical properties, as well as 16S rRNA gene sequence analysis, the strain was identified as Anoxybacillus sp. PDR2. The decolorization ratios of 100-600 mg/L Direct Black G (DBG) by strain PDR2 reached 82.12-98.39% within 48 h of dyes. Genome analysis revealed that strain PDR2 contains a circular chromosome of 3791144 bp with a G + C content of 42.48%. The genetic basis of azo dye degradation by strain PDR2 and its capacity to adapt to harsh environments, were further elucidated through bioinformatics analysis. RNA-Seq and qRT-PCR technology confirmed that NAD(P)H-flavin reductase, 2Fe-2S ferredoxin and NAD(P)-dependent ethanol dehydrogenase genes expressed by strain PDR2, were the key genes involved in DBG degradation. The combination of genome and transcriptome analysis was utilized to explore the key genes of strain PDR2 involved in azo dye biodegradation, with these findings providing a valuable theoretical basis for the practical treatment of azo dye wastewater.Intraspecific difference in toxicity brings uncertainty to ecological risk assessment (ERA) and water quality criteria (WQC) of chemicals. Here, we compared intraspecies sensitivity to toxicants for Mesocyclops leuckarti of which toxicity data was obtained from published literatures, and zebrafish Danio rerio of which toxicity data was done in this study). Due to the internal concentration of chemicals not measured, simplified toxicokinetic-toxicodynamic (TK-TD) models were used, and we investigated whether TK-TD parameters estimated by Bayesian method might represent the differences in sensitivity between life-stages of 2 species. The results demonstrated that the difference in TK-TD parameters (background mortality m0, no effect concentration NEC, the killing rate ks, and the dominant rate kd) could represent the toxicity difference between life-stages of individual species. The TK-TD model could predict toxicity in individual species (Cyprinus carpio L., Enchytraeus crypticus, Folsomia candida, Hyalella Azteca) exposed to different chemical concentrations and successfully extrapolate toxicity between different life stages of Mesocyclops leuckarti and Danio rerio by scaling several TK-TD parameters. The modified TK-TD model on the extrapolation toxicity of chemicals between life stages for species could be useful for the ERA and for deriving and revising WQC for chemicals.Glacier studies as of late have ruffled many eyeballs, exploring this frigid ecology to understand the impact of climate change. Mapquesting the glaciers led to the discovery of concealed world of "psychrophiles" harboring in it. In the present study, the antibiotic resistance genes (ARGs) and heavy metal resistance genes (MRGs) were evaluated through both the culture-dependent and culture-independent methods. Samples were collected from two different glaciers, i.e., debris-covered glacier (Changme Khangpu) and debris-free glacier (Changme Khang). Functional metagenomics of both the glacier samples, provided evidence of presence of resistant genes against various antibiotic groups. Bacitracin resistant gene (bacA) was the predominant ARG in both the glaciers. MRGs in both the glacier samples were diversified as the genes detected were resistant against various heavy metals such as arsenic, tungsten, mercury, zinc, chromium, copper, cobalt, and iron. Unique MRGs identified from Changme Khangpu glacier were resistant to copper (cutA, cutE, cutC, cutF, cueR, copC, and copB) and chromium (yelf, ruvB, nfsA, chrR, and chrA) whereas, from Changme Khang glacier they showed resistance against cobalt (mgtA, dmef, corD, corC, corB, and cnrA), and iron (yefD, yefC, yefB, and yefA) heavy metals. ARGs aligned maximum identity with Gram-negative psychrotolerant bacteria. The cultured bacterial isolates showed tolerance to high concentrations of tested heavy metal solutions. Interestingly, some of the antibiotic resistant bacterial isolates also showed tolerance towards the higher concentrations of heavy metals. Thus, an introspection of the hypothesis of co-occurrence and/co-selection of ARGs and MRGs in such environments has been highlighted here.The available evidence on the indoor air quality of operating rooms (ORs) in the Low- and Middle-income Countries (LMICs) is very scarce. https://www.selleckchem.com/products/esi-09.html Moreover, there is no study on the comparing the concentration of indoor air pollutants in different ORs. Therefore, this study aimed to measure and compare the benzene, toluene, ethylbenzene and xylene (BTEX) concentrations in the air of different ORs in hospitals of Sabzevar, Iran. Moreover, carcinogenic and non-carcinogenic risk of exposure to these pollutants were assessed using Monte Carlo simulations technique. This cross-sectional study was based on volatile organic compounds (VOCs) passive sampling of eight ORs including General surgery, Curettage, Eye surgery, Neurosurgery, Orthopedic, Laparoscopic, Cesarean and Ear, nose, throat (ENT) in two monthly campaigns from November 2019 to February 2020. One-way ANOVA and Post-hoc analyses were used to compare the concentration of BTEX compounds in different ORs. The overall mean (standard deviation (SD)) of benzene, toluene, ethylbenzene, xylene and total BTEX concentrations were 10.