Effects of neonicotinoid residues on non-target soil animals: A case study of meta-analysis.

Neonicotinoids (NEOs) are currently the fastest-growing and most widely used insecticide class worldwide. Increasing evidence suggests that long-term NEO residues in the environment have toxic effects on non-target soil animals. However, few studies have conducted surveys on the effects of NEOs on soil animals, and only few have focused on global systematic reviews or meta-analysis to quantify the effects of NEOs on soil animals. Here, we present a meta-analysis of 2940 observations from 113 field and laboratory studies that investigated the effects of NEOs (at concentrations of 0.001-78,600.000 mg/kg) on different soil animals across five indicators (i.e., survival, growth, behavior, reproduction, and biochemical biomarkers). Furthermore, we quantify the effects of NEOs on different species of soil animals. Results show that NEOs inhibit the survival, growth rate, behavior, and reproduction of soil animals, and alter biochemical biomarkers. Both the survival rate and longevity of individuals decreased by 100 % with NEO residues. The mean values of juvenile survival, cocoon number, and egg hatchability were reduced by 97 %, 100 %, and 84 %, respectively. Both individual and cocoon weights were reduced by 82 %, while the growth rate decreased by 88 % with NEO residues. Our meta-analysis confirms that NEOs pose significant negative impacts on soil animals.

The relationship between sarcopenia and metabolic dysfunction-associated fatty liver disease among the young and middle-aged populations.

BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD) has been proposed as a new term for diagnosing fatty liver disease, which is considered to be a multi-systemic disease with multiple extrahepatic manifestations, including sarcopenia. The link between sarcopenia and MAFLD remains uncertain, especially among young and middle-aged adults. Thus, we examined the relationship between MAFLD and sarcopenia in young and middle-aged individuals in this study. METHODS: A total of 2214 individuals with laboratory tests, dual-energy X-ray absorptiometry and ultrasound transient elastography from NHANES 2017-2018 were selected for this study. MAFLD was diagnosed as fatty liver disease with any one of the situations: overweight/obesity, diabetes mellitus, presence of metabolic dysregulation. Sarcopenia was defined by appendicular lean mass adjusted for body mass index (BMI). Multivariable logistic regression and restricted cubic spline (RCS) model were applied to explore the relationship between MAFLD and sarcopenia, and the mediation analyses were also conducted. Moreover, subgroup analyses stratified by BMI and lifestyles were done. RESULTS: The prevalence of MAFLD was 47.85%, and nearly 8.05% of participants had sarcopenia. The prevalence of sarcopenia was higher in participants with MAFLD (12.75%; 95% CI 10.18-15.31%) than in the non-MAFLD (3.73%; 95% CI 2.16-5.31%). MAFLD was significantly positively associated with sarcopenia after adjustments [OR = 2.87 (95% CI: 1.62-5.09)]. Moreover, significant positive associations were observed between liver fibrosis and sarcopenia prevalence in MAFLD patients (OR = 2.16; 95% CI 1.13-4.15). The RCS curve revealed that MAFLD was linearly associated with sarcopenia. The relationship between the MAFLD and sarcopenia were mediated by C-reactive protein (mediation proportion: 15.9%) and high-density lipoprotein cholesterol (mediation proportion: 18.9%). Subgroup analyses confirmed the association between MAFLD and sarcopenia differed in different lifestyle groups. CONCLUSIONS: Both MAFLD prevalence and severity was significantly associated with sarcopenia. Thus, clinicians should advise comorbidity screening and lifestyle changes to young and middle-aged patients.

Spermidine attenuates monocrotaline-induced pulmonary arterial hypertension in rats by inhibiting purine metabolism and polyamine synthesis-associated vascular remodeling.

Ensuring the homeostatic integrity of pulmonary artery endothelial cells (PAECs) is essential for combatting pulmonary arterial hypertension (PAH), as it equips the cells to withstand microenvironmental challenges. Spermidine (SPD), a potent facilitator of autophagy, has been identified as a significant contributor to PAECs function and survival. Despite SPD's observed benefits, a comprehensive understanding of its protective mechanisms has remained elusive. Through an integrated approach combining metabolomics and molecular biology, this study uncovers the molecular pathways employed by SPD in mitigating PAH induced by monocrotaline (MCT) in a Sprague-Dawley rat model. The study demonstrates that SPD administration (5 mg/kg/day) significantly corrects right ventricular impairment and pathological changes in pulmonary tissues following MCT exposure (60 mg/kg). Metabolomic profiling identified a purine metabolism disorder in MCT-treated rats, which SPD effectively normalized, conferring a protective effect against PAH progression. Subsequent in vitro analysis showed that SPD (0.8 mM) reduces oxidative stress and apoptosis in PAECs challenged with Dehydromonocrotaline (MCTP, 50 µM), likely by downregulating purine nucleoside phosphorylase (PNP) and modulating polyamine biosynthesis through alterations in S-adenosylmethionine decarboxylase (AMD1) expression and the subsequent production of decarboxylated S-adenosylmethionine (dcSAM). These findings advocate SPD's dual inhibitory effect on PNP and AMD1 as a novel strategy to conserve cellular ATP and alleviate oxidative injuries, thus providing a foundation for SPD's potential therapeutic application in PAH treatment.

Hydroxy-Safflower Yellow A Mitigates Vascular Remodeling in Rat Pulmonary Arterial Hypertension.

Purpose: The underlying causes of pulmonary arterial hypertension (PAH) often remain obscure. Addressing PAH with effective treatments presents a formidable challenge. Studies have shown that Hydroxysafflor yellow A (HSYA) has a potential role in PAH, While the mechanism underlies its protective role is still unclear. The study was conducted to investigate the potential mechanisms of the protective effects of HSYA. Methods: Using databases such as PharmMapper and GeneCards, we identified active components of HSYA and associated PAH targets, pinpointed intersecting genes, and constructed a protein-protein interaction (PPI) network. Core targets were singled out using Cytoscape for the development of a model illustrating drug-component-target-disease interactions. Intersection targets underwent analysis for Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Selected components were then modeled for target interaction using Autodock and Pymol. In vivo validation in a monocrotaline-induced PAH (MCT-PAH) animal model was utilized to substantiate the predictions made by network pharmacology. Results: We associated HSYA with 113 targets, and PAH with 1737 targets, identifying 34 mutual targets for treatment by HSYA. HSYA predominantly affects 9 core targets. Molecular docking unveiled hydrogen bond interactions between HSYA and several PAH-related proteins such as ANXA5, EGFR, SRC, PPARG, PGR, and ESR1. Conclusion: Utilizing network pharmacology and molecular docking approaches, we investigated potential targets and relevant human disease pathways implicating HSYA in PAH therapy, such as the chemical carcinogenesis receptor activation pathway and the cancer pathway. Our findings were corroborated by the efficacious use of HSYA in an MCT-induced rat PAH model, confirming its therapeutic potential.

Sodium butyrate alleviates right ventricular hypertrophy in pulmonary arterial hypertension by inhibiting H19 and affecting the activation of let-7g-5p/IGF1 receptor/ERK.

Pulmonary arterial hypertension (PAH) is a complex and fatal cardio-pulmonary vascular disease. Decompensated right ventricular hypertrophy (RVH) caused by cardiomyocyte hypertrophy often leads to fatal heart failure, the leading cause of mortality among patients. Sodium butyrate (SB), a compound known to reduce cardiac hypertrophy, was examined for its potential effect and the underlying mechanism of SB on PAH-RVH. The in vivo study showed that SB alleviated RVH and cardiac dysfunction, as well as improved life span and survival rate in MCT-PAH rats. The in vivo and in vitro experiments showed that SB could attenuate cardiomyocyte hypertrophy by reversing the expressions of H19, let-7g-5p, insulin-like growth factor 1 receptor (IGF1 receptor), and pERK. H19 inhibition restored the level of let-7g-5p and prevented the overexpression of IGF1 receptor and pERK in hypertrophic cardiomyocytes. In addition, dual luciferase assay revealed that H19 demonstrated significant binding with let-7g-5p, acting as its endogenous RNA. Briefly, SB attenuated PAH-RVH by inhibiting the H19 overexpression, restoring the level of let-7g-5p, and hindering IGF1 receptor/ERK activation.

EISA-EXPOSOME: One Highly Sensitive and Autonomous Exposomic Platform with Enhanced in-Source Fragmentation/Annotation.

Lacking a highly sensitive exposome screening technique is one of the biggest challenges in moving exposomic research forward. Enhanced in-source fragmentation/annotation (EISA) has been developed to facilitate molecular identification in untargeted metabolomics and proteomics. In this work, with a mixture of 50 pesticides at three concentration levels (20, 4, and 0.8 ppb), we investigated the analytical performance of the EISA technique over the well-accepted targeted MS/MS mode (TMM) in the detection and identification of chemicals at low levels using a quadrupole time-of-flight (qTOF) instrument. Compared with the TMM method, the EISA technique can recognize additional 1, 20, and 23 chemicals, respectively, at the three concentration levels (20, 4, and 0.8 ppb, respectively) investigated. At the 0.8 ppb level, intensities of precursor ions and fragments observed using the EISA technique are 30-1,154 and 3-80 times higher, respectively, than those observed at the TMM mode. A higher matched fragment ratio (MFR) between the EISA technique and the TMM method was recognized for most chemicals. We further developed a chemical annotation informatics algorithm, EISA-EXPOSOME, which can automatically search each precursor ion (m/z) in the MS/MS library against the EISA MS1 spectra. This algorithm then calculated a weighted score to rank the candidate features by comparing the experimental fragment spectra to those in the library. The peak intensity, zigzag index, and retention time prediction model as well as the peak correlation coefficient were further adopted in the algorithm to filter false positives. The performance of EISA-EXPOSOME was demonstrated using a pooled dust extract with a pesticide mixture (n = 200) spiked at 5 ppb. One urine sample spiked with a contaminant mixture (n = 50) at the 5 ppb level was also used for the validation of the pipeline. Proof-of-principal application of EISA-EXPOSOME in the real sample was further evaluated on the pooled dust sample with a modified T3DB database (n = 1650). Our results show that the EISA-EXPOSOME algorithm can remarkably improve the detection and annotation coverage at trace levels beyond the traditional approach as well as facilitate the high throughput screening of suspected chemicals.

A ring N(CH3)2-based derivative of resveratrol inhibits pulmonary vascular remodeling in hypoxia pulmonary hypertension.

Pulmonary artery smooth muscle cells (PASMCs) phenotypic switching and pulmonary artery endothelial cells (PAECs) endothelial-mesenchymal transition (EndMT) are important in promoting pulmonary hypertension (PH)-pulmonary vascular remodeling (PVR). Resveratrol can efficiently inhibit the proliferation of PASMCs, but its application is limited due to its low bioavailability and solubility. In this study, we modified resveratrol to assess the role of A ring N(CH3)2-based derivatives of resveratrol (Res4) in PVR-PASMCs phenotypic switching and PVR-PAECs EndMT. Chemical methods were used for the preparation of Res4; NMRS and HPLC were used to authenticate Res4. Mice developed PVR after 4 weeks of hypoxia (10% O2). Res4 (50 mg/kg/d) attenuated right ventricular systolic pressure, right ventricular hypertrophy, and PVR. PASMCs developed phenotypic switching and PAECs developed EndMT after 2 days of hypoxia (3% O2). Res4 (10 µM) could inhibit PASMCs and PAECs viability. Res4 could decrease proliferating cell nuclear antigen (PCNA) and osteopontin (OPN) expression, and increase α-smooth muscle actin (α-SMA) and vimentin expression in PASMCs. It could also decrease PCNA, α-SMA, vimentin expression and increase platelet endothelial cell adhesion molecule (CD31) expression in PAECs. Notably, Res4 inhibited the phosphorylation levels of mitogen-activated protein kinase kinase (MEK), extracellular signal-regulated protein kinase (ERK), Jun-N-terminal kinase (JNK), and p38 kinase in hypoxia-treated PASMCs and PAECs, indicating MAPK pathway may be involved in Res4-induced inhibition of PASMCs phenotypic switching and PAECs EndMT. Our data demonstrated that Res4 exerts antiproliferative effects by regulating PASMCs phenotypic switching and PAECs EndMT. Res4 may be potentially used as a drug against PH-PVR.

Identification of Zip8-correlated hub genes in pulmonary hypertension by informatic analysis.

Background: Pulmonary hypertension (PH) is a syndrome characterized by marked remodeling of the pulmonary vasculature and increased pulmonary vascular resistance, ultimately leading to right heart failure and even death. The localization of Zrt/Irt-like Protein 8 (ZIP8, a metal ion transporter, encoded by SLC39A8) was abundantly in microvasculature endothelium and its pivotal role in the lung has been demonstrated. However, the role of Zip8 in PH remains unclear. Methods: Bioinformatics analysis was employed to identify SLC39A8 expression patterns and differentially expressed genes (DEGs) between PH patients and normal controls (NC), based on four datasets (GSE24988, GSE113439, GSE117261, and GSE15197) from the Biotechnology Gene Expression Omnibus (NCBI GEO) database. Gene set enrichment analysis (GSEA) was performed to analyze signaling pathways enriched for DEGs. Hub genes were identified by cytoHubba analysis in Cytoscape. Reverse transcriptase-polymerase chain reaction was used to validate SLC39A8 and its correlated metabolic DEGs expression in PH (SU5416/Hypoxia) mice. Results: SLC39A8 expression was downregulated in PH patients, and this expression pattern was validated in PH (SU5416/Hypoxia) mouse lung tissue. SLC39A8-correlated genes were mainly enriched in the metabolic pathways. Within these SLC39A8-correlated genes, 202 SLC39A8-correlated metabolic genes were screened out, and seven genes were identified as SLC39A8-correlated metabolic hub genes. The expression patterns of hub genes were analyzed between PH patients and controls and further validated in PH mice. Finally, four genes (Fasn, Nsdhl, Acat2, and Acly) were downregulated in PH mice. However, there were no significant differences in the expression of the other three hub genes between PH mice and controls. Of the four genes, Fasn and Acly are key enzymes in fatty acids synthesis, Nsdhl is involved in cholesterol synthesis, and Acat2 is implicated in cholesterol metabolic transformation. Taken together, these results provide novel insight into the role of Zip8 in PH.

CIL-ExPMRM: An Ultrasensitive Chemical Isotope Labeling Assisted Pseudo-MRM Platform to Accelerate Exposomic Suspect Screening.

Exposome is the future of next-generation environmental health to establish the association between environmental exposure and diseases. However, due to low concentrations of exposure chemicals, exposome has been hampered by lacking an effective analytical platform to characterize its composition. In this study, by combining the benefit of chemical isotope labeling and pseudo-multiple reaction monitoring (CIL-pseudo-MRM), we have developed one highly sensitive and high-throughput platform (CIL-ExPMRM) by isotope labeling urinary exposure biomarkers. Dansyl chloride (DnsCl), N-methylphenylethylamine (MPEA), and their isotope-labeled forms were used to derivatize polar hydroxyl and carboxyl compounds, respectively. We have programmed a series of scripts to optimize MRM transition parameters, curate the MRM database (>70,000 compounds), predict accurate retention time (RT), and automize dynamic MRMs. This was followed by an automated MRM peak assignment, peak alignment, and statistical analysis. A computational pipeline was eventually incorporated into a user-friendly website interface, named CIL-ExPMRM (http://www.exposomemrm.com/). The performance of this platform has been validated with a relatively low false positive rate (10.7%) across instrumental platforms. CIL-ExPMRM has systematically overcome key bottlenecks of exposome studies to some extent and outperforms previous methods due to its independence of MS/MS availability, accurate RT prediction, and collision energy optimization, as well as the ultrasensitivity and automated robust intensity-based quantification. Overall, CIL-ExPMRM has great potential to advance the exposomic studies based on urinary biomarkers.

HExpPredict: In Vivo Exposure Prediction of Human Blood Exposome Using a Random Forest Model and Its Application in Chemical Risk Prioritization.

BACKGROUND: Due to many substances in the human exposome, there is a dearth of exposure and toxicity information available to assess potential health risks. Quantification of all trace organics in the biological fluids seems impossible and costly, regardless of the high individual exposure variability. We hypothesized that the blood concentration (CB) of organic pollutants could be predicted via their exposure and chemical properties. Developing a prediction model on the annotation of chemicals in human blood can provide new insight into the distribution and extent of exposures to a wide range of chemicals in humans. OBJECTIVES: Our objective was to develop a machine learning (ML) model to predict blood concentrations (CBs) of chemicals and prioritize chemicals of health concern. METHODS: We curated the CBs of compounds mostly measured at population levels and developed an ML model for chemical CB predictions by considering chemical daily exposure (DE) and exposure pathway indicators (δij), half-lives (t1/2), and volume of distribution (Vd). Three ML models, including random forest (RF), artificial neural network (ANN) and support vector regression (SVR) were compared. The toxicity potential or prioritization of each chemical was represented as a bioanalytical equivalency (BEQ) and its percentage (BEQ%) estimated based on the predicted CB and ToxCast bioactivity data. We also retrieved the top 25 most active chemicals in each assay to further observe changes in the BEQ% after the exclusion of the drugs and endogenous substances. RESULTS: We curated the CBs of 216 compounds primarily measured at population levels. RF outperformed the ANN and SVF models with the root mean square error (RMSE) of 1.66 and 2.07µM, the mean absolute error (MAE) values of 1.28 and 1.56µM, the mean absolute percentage error (MAPE) of 0.29 and 0.23, and R2 of 0.80 and 0.72 across test and testing sets. Subsequently, the human CBs of 7,858 ToxCast chemicals were successfully predicted, ranging from 1.29×10-6 to 1.79×10-2 µM. The predicted CBs were then combined with ToxCast in vitro bioassays to prioritize the ToxCast chemicals across 12 in vitro assays with important toxicological end points. It is interesting that we found the most active compounds to be food additives and pesticides rather than widely monitored environmental pollutants. DISCUSSION: We have shown that the accurate prediction of "internal exposure" from "external exposure" is possible, and this result can be quite useful in the risk prioritization. https://doi.org/10.1289/EHP11305.

An automated toxicity based prioritization framework for fast chemical characterization in non-targeted analysis.

Identification of environmental pollutants with harmful effects is commonly conducted by non-targeted analysis (NTA) using liquid chromatography coupled with high-resolution mass spectrometry. Prioritization of possible candidates is important yet challenging because of the large number of candidates from MS acquisitions. We aimed to prioritize candidates to the exposure potential of organic chemicals by their toxicity and identification evidence in the matrix. We have developed an R package application, "NTAprioritization.R", for fast prioritization of suspect lists. In this workflow, the identification levels of candidates were first rated according to spectral matching and retention time prediction. The toxicity levels were rated according to candidates' toxicity of different endpoints or ToxPi score. Finally, the various levels of candidates were identified as Tier 1 - 5 descending in priority. For validation, we used this workflow to identify pollutants in a sludge water sample spiked with 28 environmental pollutants. The workflow reduced the candidate list of over 6,982 candidates to a final list of 2,779 compounds and prioritized them to 5 tiers (Tier 1 - 5), including 21 out of 28 spiked standards. Overall, this study shows the added value of an automated prioritization R package for the fast screening of environmental pollutants based on the NTA method.

Liquid Crystal Monomer: A Potential PPARγ Antagonist.

Liquid crystal monomers (LCMs) are a large family of artificial ingredients that have been widely used in global liquid crystal display (LCD) industries. As a major constituent in LCDs as well as the end products of e-waste dismantling, LCMs are of growing research interest with regard to their environmental occurrences and biochemical consequences. Many studies have analyzed LCMs in multiple environmental matrices, yet limited research has investigated the toxic effects upon exposure to them. In this study, we combined in silico simulation and in vitro assay validation along with omics integration analysis to achieve a comprehensive toxicity elucidation as well as a systematic mechanism interpretation of LCMs for the first time. Briefly, the high-throughput virtual screen and reporter gene assay revealed that peroxisome proliferator-activated receptor gamma (PPARγ) was significantly antagonized by certain LCMs. Besides, LCMs induced global metabolome and transcriptome dysregulation in HK2 cells. Notably, fatty acid ß-oxidation was conspicuously dysregulated, which might be mediated through multiple pathways (IL-17, TNF, and NF-kB), whereas the activation of AMPK and ligand-dependent PPARγ antagonism may play particularly important parts. This study illustrated LCMs as a potential PPARγ antagonist and explored their toxicological mode of action on the trans-omics level, which provided an insightful overview in future chemical risk assessment.

Development and validation of a new nomogram to screen for MAFLD.

BACKGROUND AND AIM: Metabolic dysfunction-associated fatty liver disease (MAFLD) poses significant health and economic burdens on all nations. Thus, identifying patients at risk early and managing them appropriately is essential. This study's goal was to develop a new predictive model for MAFLD. Additionally, to improve the new model's clinical utility, researchers limited the variables to readily available simple clinical and laboratory measures. METHODS: Based on the National Health and Nutrition Examination Survey (NHANES) cycle 2017-2020.3, the study was a retrospective cross-sectional study involving 7300 participants. By least absolute shrinkage and selection operator (LASSO) regression, significant indicators independently associated with MAFLD were identified, and a predictive model called the MAFLD prediction nomogram (MPN) was developed. The study then compared the MPN with six existing predictive models for MAFLD. The model was evaluated by measuring the area under receiver operating characteristic curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA) curve. RESULTS: In this study, researchers identified nine predictors from 33 variables, including age, race, arm circumference (AC), waist circumference (WC), body mass index (BMI), alanine aminotransferase (ALT)-to-aspartate aminotransferase (AST) ratio, triglyceride-glucose index (TyG), hypertension, and diabetes. The diagnostic accuracy of the MPN for MAFLD was significantly better than that of the other six existing models in both the training and validation cohorts (AUC 0.868, 95% confidence interval (CI) 0.858-0.877, and AUC 0.863, 95% CI 0.848-0.878, respectively). The MPN showed a higher net benefit than the other existing models. CONCLUSIONS: This nonimaging-assisted nomogram based on demographics, laboratory factors, anthropometrics, and comorbidities better predicted MAFLD than the other six existing predictive models. Using this model, the general population with MAFLD can be assessed rapidly.

Exposure assessment of aryl-organophosphate esters based on specific urinary biomarkers and their associations with reproductive hormone homeostasis disruption in women of childbearing age.

The effects of aryl-organophosphate esters (aryl-OPEs) on female reproduction health are still unclear owing to the lack of specific exposure biomarkers. Here, we analyzed the hydroxylated metabolites of three aryl-OPEs (phenyl diphenyl phosphate [TPhP], 2-ethylhexyl diphenyl phosphate [EHDPP], and tricresyl phosphate [TCrP]) and diphenyl phosphate (DPhP) in urine samples from 913 women of childbearing age, and explored the association between exposure to the aryl-OPEs and reproductive hormone levels. The detection frequencies of 2-ethyl-5-hydroxyhexyl diphenyl phosphate (5-OH-EHDPP), phenyl di-p-tolyl phosphate (4-OH-MDTP), and 4-hydroxyphenyl diphenyl phosphate (4-OH-TPhP) were 94.6 %, 93.3 %, and 84.2 %, respectively. Multivariate linear regression analyses revealed that the quartiles of 4-OH-TPhP were positively associated with the progesterone (P4) level (p-trend = 0.008), and the P level in the highest quartile of 5-OH-EHDPP was 7.2 % (95 % CI, 5.7 % to 8.7 %) higher than that in the lowest quartile. The 17ß-estradiol levels in the highest quartiles of 4-OH-TPhP and 5-OH-EHDPP were 15.0 % (95 % CI, 13.7 % to16.1 %) and 5.9 % (95 % CI, 15.7 % to 16.1 %) lower than those in the lowest quartiles, respectively. The anti-Müllerian hormone level linearly increased across the quartiles of 4-OH-MDTP (p-trend = 0.036), and the follicle-stimulating hormone exhibited the opposite trend (p-trend = 0.0047). These results indicate that aryl-OPEs may disrupt hormone homeostasis using their specific biomarkers and may negatively affect female reproduction.

FGF9 Alleviates the Fatty Liver Phenotype by Regulating Hepatic Lipid Metabolism.

Although the fatty liver has been linked to numerous impairments of energy homeostasis, the molecular mechanism responsible for fatty liver development remains largely unknown. In the present study, we show that fibroblast growth factors 9 (FGF9) expression is increased in the liver of diet-induced obese (DIO), db/db, and ob/ob mice relative to their respective controls. The long-term knockdown of hepatic FGF9 expression mediated by adeno-associated virus expressing FGF9-specific short hairpin RNA (AAV-shFGF9) aggravated the fatty liver phenotype of DIO mice. Consistently, downregulation of FGF9 expression mediated by adenovirus expressing FGF9-specific shRNA (Ad-shFGF9) in the primary hepatocyte promoted the cellular lipid accumulation, suggesting that FGF9 exerts its effects in an autocrine manner. In contrast, adenoviruses expressing FGF9 (Ad-FGF9) mediated FGF9 overexpression in the liver of DIO mice alleviated hepatic steatosis and improved the insulin sensitivity and glucose intolerance. Moreover, the liver-specific FGF9 transgenic mice phenocopied the Ad-FGF9-infected mice. Mechanistically, FGF9 inhibited the expression of genes involved in lipogenesis and increased the expression of genes involved in fatty acid oxidation, thereby reducing cellular lipid accumulation. Thus, targeting FGF9 might be exploited to treat nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome.

Risk-Based Chemical Ranking and Generating a Prioritized Human Exposome Database.

BACKGROUND: Due to the ubiquitous use of chemicals in modern society, humans are increasingly exposed to thousands of chemicals that contribute to a major portion of the human exposome. Should a comprehensive and risk-based human exposome database be created, it would be conducive to the rapid progress of human exposomics research. In addition, once a xenobiotic is biotransformed with distinct half-lives upon exposure, monitoring the parent compounds alone may not reflect the actual human exposure. To address these questions, a comprehensive and risk-prioritized human exposome database is needed. OBJECTIVES: Our objective was to set up a comprehensive risk-prioritized human exposome database including physicochemical properties as well as risk prediction and develop a graphical user interface (GUI) that has the ability to conduct searches for content associated with chemicals in our database. METHODS: We built a comprehensive risk-prioritized human exposome database by text mining and database fusion. Subsequently, chemicals were prioritized by integrating exposure level obtained from the Systematic Empirical Evaluation of Models with toxicity data predicted by the Toxicity Estimation Software Tool and the Toxicological Priority Index calculated from the ToxCast database. The biotransformation half-lives (HLBs) of all the chemicals were assessed using the Iterative Fragment Selection approach and biotransformation products were predicted using the previously developed BioTransformer machine-learning method. RESULTS: We compiled a human exposome database of >20,000 chemicals, prioritized 13,441 chemicals based on probabilistic hazard quotient and 7,770 chemicals based on risk index, and provided a predicted biotransformation metabolite database of >95,000 metabolites. In addition, a user-interactive Java software (Oracle)-based search GUI was generated to enable open access to this new resource. DISCUSSION: Our database can be used to guide chemical management and enhance scientific understanding to rapidly and effectively prioritize chemicals for comprehensive biomonitoring in epidemiological investigations. https://doi.org/10.1289/EHP7722.

Plastic Additives in Ambient Fine Particulate Matter in the Pearl River Delta, China: High-Throughput Characterization and Health Implications.

Elucidation of the chemical components of airborne fine particulate matter (PM2.5) facilitates the characterization of atmospheric contamination sources and associated human exposure risks. In the present study, we employed a high-throughput analytical approach to investigate the abundance and distribution of 163 plastic additives in ambient PM2.5 collected from 94 different sites across the Pearl River Delta region, China. These chemicals are from six categories, including organophosphate esters (OPEs), phthalate esters (PAEs), PAE replacements, bisphenol analogues, UV stabilizers, and antioxidants. Ninety-three of them exhibited a detection frequency greater than 50% in PM2.5, while the combined concentrations of target plastic additives ranged from 610 to 49,400 µg/g (median: 3500 µg/g) across sites. By category, concentrations of PAEs (median: 2710 µg/g) were one to three orders of magnitude greater than those of other groups, followed by PAE replacements (540 µg/g) and OPEs (76.2 µg/g). Chemical-dependent exposure risks to PM2.5-bound plastic additives were characterized via the estimated daily intake and hazard quotient (HQ) approaches, which resulted in two different risk prioritization systems. Although the HQ approach suggested no or very low health concerns when considering individual chemicals, the complexity of co-concurrent chemicals in PM2.5 raises the concern on potential health risks from exposure to airborne particles and a cocktail of chemical components.

The antihypertension effect of hydrogen sulfide (H2S) is induced by activating VEGFR2 signaling pathway.

AIMS: Previous studies demonstrated that H2S has an antihypertension effect on hypertension, but the mechanism involved is unclear until now. The aim of the study is to elucidate the effect of H2S on PH and the mechanism involved. MAIN METHODS: In this study, GYY4137 (a H2S donor) were administered to spontaneously hypertensive rats (SHR) and normotensive Wistar-Kyoto rats (WKY) by intraperitoneally injection daily for consecutive 14 days. Systolic blood pressure (SBP), endothelial-dependent relaxation (EDR), plasma malondialdehyde (MDA), superoxide dismutase (SOD), and H2S levels were measured. Human umbilical vein endothelial cells (HUVECs) were also used to elucidate the mechanism involved in the protect effect of H2S on the injured vessels. KEY FINDINGS: Our results showed that GYY4137 normalized the SBP (P < 0.0001), increased EDR (P < 0.01), reduced oxidative stress (increased the content of SOD and reduced the content of MDA) of SHR. Meanwhile, GYY4137 could promote the proliferation (P < 0.01) and migration (P < 0.01) of HUVECs, increase the expression of endothelial NO synthase (eNOS) and Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) both in SHR and HUVECs treated with GYY4137. In addition to the above results, the PIP3/Akt signaling pathway was activated and the expression of caspase 3 was increased by GYY4137. However, all the above effects of GYY4137 were blocked by ZD6474 (a VEGFR2 inhibitor). SIGNIFICANCE: GYY4137 had a hypotensive and vascular protect effect on PH. This effect might be mediated through upregulating the expression of VEGFR2, which subsequently alleviating oxidant-provoked vascular endothelial dysfunction, and promoting the proliferation and migration of endothelial cells in SHR.

Metabolomic and Transcriptomic Analysis of MCF-7 Cells Exposed to 23 Chemicals at Human-Relevant Levels: Estimation of Individual Chemical Contribution to Effects.

BACKGROUND: Humans are constantly being exposed to various xenobiotics at relatively low concentrations. To date, limited evidence is available to ascertain whether a complex xenobiotic mixture at human-relevant levels causes any health effect. Moreover, there is no effective method to pinpoint the contribution of each chemical toward such an effect. OBJECTIVES: This study aims to understand the responses of cells to a mixture containing 23 xenobiotics at human-relevant levels and develop a feasible method to decipher the chemical(s) that contribute significantly to the observed effect. METHODS: We characterized the metabolome and transcriptome of breast cancer cells (MCF-7) before and after exposure to the mixture at human-relevant levels; preexposure levels were derived from existing large-scale biomonitoring data. A high-throughput metabolomics-based "leave-one-out" method was proposed to understand the relative contribution of each component by comparing the metabolome with and without the particular chemical in the mixture. RESULTS: The metabolomic analysis suggested that the mixture altered metabolites associated with cell proliferation and oxidative stress. For the transcriptomes, gene ontology terms and pathways including "cell cycle," "cell proliferation," and "cell division" were significantly altered after mixture exposure. The mixture altered genes associated with pathways such as "genotoxicity" and "nuclear factor erythroid 2-related factor 2 (Nrf2)." Through joint pathways analysis, metabolites and genes were observed to be well-aligned in pyrimidine and purine metabolisms. The leave-one-out results showed that many chemicals made their contributions to specific metabolic pathways. The overall metabolome pattern of the absence of 2,4-dihyroxybenzophenone (DHB) or bisphenol A (BPA) showed great resemblance to controls, suggesting their higher relative contribution to the observed effect. DISCUSSION: The omics results showed that exposure to the mixture at human-relevant levels can induce significant in vitro cellular changes. Also, the leave one out method offers an effective approach for deconvoluting the effects of the mixture. https://doi.org/10.1289/EHP6641.

Triphenyl Phosphate at Environmental Levels Retarded Ovary Development and Reduced Egg Production in Japanese Medaka (Oryzias latipes).

Since triphenyl phosphate (TPhP) elicits both antiestrogenic activities via blocking the estrogen receptor (ER) and estrogenic activity by elevating 17ß-estradiol (17ß-E2) synthesis, its adverse effect on female reproduction is uncertain. In this study, we exposed Japanese medaka to TPhP at 131, 363, and 1773 ng/L for 100 days following hatching. TPhP significantly induced ovary retardation in all exposure groups (incidence: from 11.9 to 37.8%) and reduced egg production by 38.9 and 50.9% in the 363 and 1773 ng/L exposure groups, respectively. Vitellogenin (vtg) transcription was significantly downregulated by 35.4-57.4% after TPhP exposure, explaining the ovary retardation. Considering that 17ß-E2 was only significantly decreased in the 1773 ng/L exposure group, ER antagonism could be the dominant contributor to the inhibition of vtg transcription and female reproductive toxicity of TPhP. As 4-hydroxyphenyl diphenyl phosphate, a metabolite of TPhP, was detected in livers with similar concentration [68.4-1237 ng/g lipid weight (lw)] to that of TPhP (485-1594 ng/g lw) and elicited medaka ER antagonistic activity (50% inhibitory concentration = 78.1 µM), TPhP and its metabolite should both contribute to the reproductive inhibition. We demonstrate that TPhP at environmentally relevant concentrations is toxic to female reproduction, which poses an ecological risk to wild fish at the population level.