Metabolite profiles of live or dead carp (Cyprinus carpio) exposed to endosulfan sulfate using a targeted GC–MS analysis

Endosulfan sulfate is a major oxidized metabolite of endosulfan, which is a broad-spectrum chlorinated cyclodiene insecticide. In this study, GC–MS-based metabolic profiles of dead or live carp (Cyprinus carpio) exposed to endosulfan sulfate were investigated to elucidate the molecular toxicological effects of endosulfan sulfate on carp. Three different extraction methods were compared, and a 50% methanol solution was chosen as an efficient extraction method. Carp was exposed to endosulfan sulfate at a concentration of 8 ppb for 2 days. After exposure, the whole body of the fish was homogenized with liquid N2, extracted with the 50% methanol solution and dried before TMS derivatization for GC–MS analyses of the dead and live carp. A SIM (selected ion monitoring)-library of 373 metabolites was applied after GC–MS analysis to detect 146 metabolites in carp. Based on the one-way ANOVA results (P  1.5 or < 0.667), 30 metabolites were identified as biomarkers that were significantly different in the metabolic profiles among the control, dead and live carp. A metabolic pathway analysis using MetaboAnalyst 4.0 revealed that those biomarkers were important for the living or death response to endosulfan sulfate. The pathways indicated by the metabolic pathway analysis included starch and sucrose metabolism, galactose metabolism, glycerolipid metabolism, the citrate cycle and linoleic acid metabolism. These results suggest that these pathways underwent significant perturbations over the exposure period

Prediction of Specific Anxiety Symptoms and Virtual Reality Sickness Using In Situ Autonomic Physiological Signals During Virtual Reality Treatment in Patients With Social Anxiety Disorder: Mixed Methods Study

Background: Social anxiety disorder (SAD) is the fear of social situations where a person anticipates being evaluated negatively. Changes in autonomic response patterns are related to the expression of anxiety symptoms. Virtual reality (VR) sickness can inhibit VR experiences. Objective: This study aimed to predict the severity of specific anxiety symptoms and VR sickness in patients with SAD, using machine learning based on in situ autonomic physiological signals (heart rate and galvanic skin response) during VR treatment sessions. Methods: This study included 32 participants with SAD taking part in 6 VR sessions. During each VR session, the heart rate and galvanic skin response of all participants were measured in real time. We assessed specific anxiety symptoms using the Internalized Shame Scale (ISS) and the Post-Event Rumination Scale (PERS), and VR sickness using the Simulator Sickness Questionnaire (SSQ) during 4 VR sessions (#1, #2, #4, and #6). Logistic regression, random forest, and naive Bayes classification classified and predicted the severity groups in the ISS, PERS, and SSQ subdomains based on in situ autonomic physiological signal data. Results: The severity of SAD was predicted with 3 machine learning models. According to the F1 score, the highest prediction performance among each domain for severity was determined. The F1 score of the ISS mistake anxiety subdomain was 0.8421 using the logistic regression model, that of the PERS positive subdomain was 0.7619 using the naive Bayes classifier, and that of total VR sickness was 0.7059 using the random forest model. Conclusions: This study could predict specific anxiety symptoms and VR sickness during VR intervention by autonomic physiological signals alone in real time. Machine learning models can predict the severe and nonsevere psychological states of individuals based on in situ physiological signal data during VR interventions for real-time interactive services. These models can support the diagnosis of specific anxiety symptoms and VR sickness with minimal participant bias

GSK3B induces autophagy by phosphorylating ULK1

Unc-51-like autophagy activating kinase 1 (ULK1), a mammalian homolog of the yeast kinase Atg1, has an essential role in autophagy induction. In nutrient and growth factor signaling, ULK1 activity is regulated by various posttranslational modifications, including phosphorylation, acetylation, and ubiquitination. We previously identified glycogen synthase kinase 3 beta (GSK3B) as an upstream regulator of insulin withdrawal-induced autophagy in adult hippocampal neural stem cells. Here, we report that following insulin withdrawal, GSK3B directly interacted with and activated ULK1 via phosphorylation of S405 and S415 within the GABARAP-interacting region. Phosphorylation of these residues facilitated the interaction of ULK1 with MAP1LC3B and GABARAPL1, while phosphorylation-defective mutants of ULK1 failed to do so and could not induce autophagy flux. Furthermore, high phosphorylation levels of ULK1 at S405 and S415 were observed in human pancreatic cancer cell lines, all of which are known to exhibit high levels of autophagy. Our results reveal the importance of GSK3B-mediated phosphorylation for ULK1 regulation and autophagy induction and potentially for tumorigenesis. © 2021, The Author(s).1

Identification of Linkages between EDCs in Personal Care Products and Breast Cancer through Data Integration Combined with Gene Network Analysis

Approximately 1000 chemicals have been reported to possibly have endocrine disrupting effects, some of which are used in consumer products, such as personal care products (PCPs) and cosmetics. We conducted data integration combined with gene network analysis to: (i) identify causal molecular mechanisms between endocrine disrupting chemicals (EDCs) used in PCPs and breast cancer; and (ii) screen candidate EDCs associated with breast cancer. Among EDCs used in PCPs, four EDCs having correlation with breast cancer were selected, and we curated 27 common interacting genes between those EDCs and breast cancer to perform the gene network analysis. Based on the gene network analysis, ESR1, TP53, NCOA1, AKT1, and BCL6 were found to be key genes to demonstrate the molecular mechanisms of EDCs in the development of breast cancer. Using GeneMANIA, we additionally predicted 20 genes which could interact with the 27 common genes. In total, 47 genes combining the common and predicted genes were functionally grouped with the gene ontology and KEGG pathway terms. With those genes, we finally screened candidate EDCs for their potential to increase breast cancer risk. This study highlights that our approach can provide insights to understand mechanisms of breast cancer and identify potential EDCs which are in association with breast cancer

Electrophoretic Deposition of Aged and Charge Controlled Colloidal Copper Sulfide Nanoparticles

Colloidal nanoparticles (NPs) have been recently spotlighted as building blocks for various nanostructured devices. Their collective properties have been exhibited by arranging them on a substrate to form assembled NPs. In particular, electrophoretic deposition (EPD) is an emerging fabrication method for such nanostructured films. To maximize the benefits of this method, further studies are required to fully elucidate the key parameters that influence the NP deposition. Herein, two key parameters are examined, namely: (i) the aging of colloidal NPs and (ii) the charge formation by surface ligands. The aging of Cu2-xS NPs changes the charge states, thus leading to different NP deposition behaviors. The SEM images of NP films, dynamic light scattering, and zeta potential results demonstrated that the charge control and restoration of interparticle interactions for aged NPs were achieved via simple ligand engineering. The charge control of colloidal NPs was found to be more dominant than the influence of aging, which can alter the surface charges of the NPs. The present results thus reveal that the charge formation on the colloidal NPs, which depends on the surface ligands, is an important controllable parameter in EPD

Effect of Efavirenz on UDP-Glucuronosyltransferase 1A1, 1A4, 1A6, and 1A9 Activities in Human Liver Microsomes

Efavirenz is a non-nucleoside reverse transcriptase inhibitor used for the treatment of human immunodeficiency virus type 1 infections. Drug interactions of efavirenz have been reported due to in vitro inhibition of CYP2C9, CYP2C19, CYP3A4, and UDP-glucuronosyltransferase 2B7 (UGT2B7) and in vivo CYP3A4 induction. The inhibitory potentials of efavirenz on the enzyme activities of four major UDP-glucuronosyltransferases (UGTs), 1A1, 1A4, 1A6, and 1A9, in human liver microsomes were investigated using liquid chromatography-tandem mass spectrometry. Efavirenz potently inhibited UGT1A4-mediated trifluoperazine N-glucuronidation and UGT1A9-mediated propofol glucuronidation, with Ki values of 2.0 and 9.4 μM, respectively. [I]/Ki ratios of efavirenz for trifluoperazine N-glucuronidation and propofol glucuronidation were 6.5 and 1.37, respectively. Efavirenz also moderately inhibited UGT1A1-mediated 17β-estradiol 3-glucuronidation, with a Ki value of 40.3 μM, but did not inhibit UGT1A6-mediated 1-naphthol glucuronidation. Those in vitro results suggest that efavirenz should be examined for potential pharmacokinetic drug interactions in vivo due to strong inhibition of UGT1A4 and UGT1A9

In-situ spectroelectrochemical analysis: Irreversible deformation of cesium lead bromide Perovskite Quantum Dots in SiOx matrices

To practically utilized the organometallic lead halide perovskites to optoelectronic devices and photoelectrochemical cells, numerous efforts have been utilized to obtain the perovskites with low-energy process with coverage of various inorganic mediums to improve stability against humidity. By utilizing ligand-assisted reprecipitation process, under ambient condition at room temperature, the dimensionally confined perovskite quantum dots in silica matrices (PQD@SiOx) were obtained, and they were stable under several months under the ambient condition. To apply the PQD@SiOx to the photoelectrochemical cells by introducing direct contact between PQD@SiOx and electrolyte, the material/photophysical properties under electrochemical conditions are necessary to be studied. However, the role of silica coverage to the electrochemical behaviors of the PQD cores in the silica medium were not yet studied. In this work, under the electrochemical conditions, the oxidative and reductive behaviors of the PQD@SiOx were studied. Also, through in-situ spectroelectrochemical study, the electrochemically induced irreversible deformation process were tracked. The findings of this study could be used to understand role of silica coverage and develop the strategy to improve the protecting behavior of the silica for the PQD cores to utilize into the photoelectrochemical cells

Effect of Efavirenz on UDP-Glucuronosyltransferase 1A1, 1A4, 1A6, and 1A9 Activities in Human Liver Microsomes

Efavirenz is a non-nucleoside reverse transcriptase inhibitor used for the treatment of human immunodeficiency virus type 1 infections. Drug interactions of efavirenz have been reported due to in vitro inhibition of CYP2C9, CYP2C19, CYP3A4, and UDP-glucuronosyltransferase 2B7 (UGT2B7) and in vivo CYP3A4 induction. The inhibitory potentials of efavirenz on the enzyme activities of four major UDP-glucuronosyltransferases (UGTs), 1A1, 1A4, 1A6, and 1A9, in human liver microsomes were investigated using liquid chromatography-tandem mass spectrometry. Efavirenz potently inhibited UGT1A4-mediated trifluoperazine N-glucuronidation and UGT1A9-mediated propofol glucuronidation, with Ki values of 2.0 and 9.4 μM, respectively. [I]/Ki ratios of efavirenz for trifluoperazine N-glucuronidation and propofol glucuronidation were 6.5 and 1.37, respectively. Efavirenz also moderately inhibited UGT1A1-mediated 17β-estradiol 3-glucuronidation, with a Ki value of 40.3 μM, but did not inhibit UGT1A6-mediated 1-naphthol glucuronidation. Those in vitro results suggest that efavirenz should be examined for potential pharmacokinetic drug interactions in vivo due to strong inhibition of UGT1A4 and UGT1A9