Long-term exposure to major constituents of fine particulate matter and neurodegenerative diseases: A population-based survey in the Pearl River Delta Region, China.

BACKGROUND: Exposure to PM2.5 has been linked to neurodegenerative diseases, with limited understanding of constituent-specific contributions. OBJECTIVES: To explore the associations between long-term exposure to PM2.5 constituents and neurodegenerative diseases. METHODS: We recruited 148,274 individuals aged ≥ 60 from four cities in the Pearl River Delta region, China (2020 to 2021). We calculated twenty-year average air pollutant concentrations (PM2.5 mass, black carbon (BC), organic matter (OM), ammonium (NH4+), nitrate (NO3-) and sulfate (SO42-)) at the individuals' home addresses. Neurodegenerative diseases were determined by self-reported doctor-diagnosed Alzheimer's disease (AD) and Parkinson's disease (PD). Generalized linear mixed models were employed to explore associations between pollutants and neurodegenerative disease prevalence. RESULTS: PM2.5 and all five constituents were significantly associated with a higher prevalence of AD and PD. The observed associations generally exhibited a non-linear pattern. For example, compared with the lowest quartile, higher quartiles of BC were associated with greater odds for AD prevalence (i.e., the adjusted odds ratios were 1.81; 95% CI, 1.45-2.27; 1.78; 95% CI, 1.37-2.32; and 1.99; 95% CI, 1.54-2.57 for the second, third, and fourth quartiles, respectively). CONCLUSIONS: Long-term exposure to PM2.5 and its constituents, particularly combustion-related BC, OM, and SO42-, was significantly associated with higher prevalence of AD and PD in Chinese individuals. ENVIRONMENTAL IMPLICATION: PM2.5 is a routinely regulated mixture of multiple hazardous constituents that can lead to diverse adverse health outcomes. However, current evidence on the specific contributions of PM2.5 constituents to health effects is scarce. This study firstly investigated the association between PM2.5 constituents and neurodegenerative diseases in the moderately to highly polluted Pearl River Delta region in China, and identified hazardous constituents within PM2.5 that have significant impacts. This study provides important implications for the development of targeted PM2.5 prevention and control policies to reduce specific hazardous PM2.5 constituents.

LncRNA NR_030777 promotes mitophagy by targeting CDK1-related mitochondrial fission and ATG12 to attenuate paraquat-induced Parkinson's disease.

With the evidence emerging that abnormal expression of long noncoding RNAs (lncRNAs) are involved in onset of Parkinson's disease (PD), the role of NR_030777 contributing to this disease is of great interest. We recently found that a novel lncRNA "NR_030777" demonstrates protective effects on PQ-induced neurodegeneration. However, the underlying molecular mechanisms of NR_030777 in the regulation of mitochondrial fission and mitophagy involved in PQ-induced neuronal damage remain to be explored. NR_030777 brain conditional overexpressing mice as well as in vitro primary neuronal cells from cerebral cortex and Neuro2a cells were adopted. Immunofluorescence, Immunohistochemistry, qRT-PCR and Western blotting were used to evaluate the expression levels of RNA and proteins. RNA immunoprecipitation and RNA pulldown experiment were used to evaluate the interaction of NR_030777 with its target proteins. NR_030777 and mitophagy were increased, and tyrosine hydroxylase (TH) levels recovered after NR_030777 overexpression upon PQ treatment. The overexpression and knockdown of NR_030777 unveiled that NR_030777 positively regulated mitophagy such as the upregulation of LC3B-II:I, ATG12-ATG5, p62 and NBR1. Moreover, the application of mdivi-1, a DRP-1 inhibitor, in combination with NR_030777 genetic modified cells unveiled that NR_030777 promoted DRP1-mediated mitochondrial fission and mitophagy. Furthermore, NR_030777 were directly bound to CDK1 to increase p-DRP1 levels at the Ser616 site, leading to mitochondrial fission and mitophagy. On the other hand, NR_030777 acted directly on ATG12 within the ATG12-ATG5 complex in the 800-1400 nt region to modulate the membrane formation. Accordingly, NR_030777 deficiency in neuron cells compromised cell mitophagy. Finally, the above findings were confirmed using NR_030777-overexpressing mice. NR_030777 exerted a protective effect on PQ-exposed mice by enhancing mitophagy. Our data provide the first scientific evidence for the precise invention of PQ-induced PD. Our findings further propose a breakthrough for understanding the regulatory relationship between NR_030777, CDK1, ATG12 and mitophagy in PQ-induced PD.

Development of a rapid aptamer-chemiluminescence sensor for detecting glyphosate pesticide residue in soybeans.

Glyphosate (GLY) is a widely used herbicide worldwide, particularly in cultivating genetically modified soybeans resistant to GLY. However, routine multi-residue analysis does not include GLY due to the complexity of soybean matrix components that can interfere with the analysis. This study presented the development of an aptamer-based chemiluminescence (Apt-CL) sensor for rapidly screening GLY pesticide residue in soybeans. The GLY-binding aptamer (GBA) was developed to bind to GLY specifically, and the remaining unbound aptamers were adsorbed onto gold nanoparticles (AuNPs). The signal was in the form of luminol-H2O2 emission, catalyzed by the aggregation of AuNPs in a chemiluminescent reaction arising from the GLY-GBA complex. The outcomes demonstrated a robust linear relationship between the CL intensity of GLY-GBA and the GLY concentration. In the specificity test of the GBA, only GLY and Profenofos were distinguished among the fifteen tested pesticides. Furthermore, the Apt-CL sensor was conducted to determine GLY residue in organic soybeans immersed in GLY as a real sample, and an optimal linear concentration range for detection after extraction was found to be between 0.001 and 10 mg/L. The Apt-CL sensor exploits the feasibility of real-time pesticide screening in food safety.

Hepatic injury and ileitis associated with gut microbiota dysbiosis in mice upon F-53B exposure.

Chlorinated polyfluorinated ether sulfonate (F-53B), a substitute of perfluorooctane sulfonic acid (PFOS), has attracted significant attention for its link to hepatotoxicity and enterotoxicity. Nevertheless, the underlying mechanisms of F-53B-induced enterohepatic toxicity remain incompletely understood. This study aimed to explore the role of F-53B exposure on enterohepatic injury based on the gut microbiota, pathological and molecular analysis in mice. Here, we exposed C57BL/6 mice to F-53B (0, 4, 40, and 400 µg/L) for 28 days. Our findings revealed a significant accumulation of F-53B in the liver, followed by small intestines, and feces. In addition, F-53B induced pathological collagen fiber deposition and lipoid degeneration, up-regulated the expression of fatty acid ß-oxidation-related genes (PPARα and PPARγ, etc), while simultaneously down-regulating pro-inflammatory genes (Nlrp3, IL-1ß, and Mcp1) in the liver. Meanwhile, F-53B induced ileal mucosal barrier damage, and an up-regulation of pro-inflammatory genes and mucosal barrier-related genes (Muc1, Muc2, Claudin1, Occludin, Mct1, and ZO-1) in the ileum. Importantly, F-53B distinctly altered gut microbiota compositions by increasing the abundance of Akkermansia and decreasing the abundance of Prevotellaceae_NK3B31_group in the feces. F-53B-altered microbiota compositions were significantly associated with genes related to fatty acid ß-oxidation, inflammation, and mucosal barrier. In summary, our results demonstrate that F-53B is capable of inducing hepatic injury, ileitis, and gut microbiota dysbiosis in mice, and the gut microbiota dysbiosis may play an important role in the F-53B-induced enterohepatic toxicity.

Impact of protein coronas on nanoparticle interactions with tissues and targeted delivery.

A major challenge in advancing nanoparticle (NP)-based delivery systems stems from the intricate interactions between NPs and biological systems. These interactions are largely determined by the formation of the NP-protein corona (PC), in which proteins spontaneously adsorb to the surface of NPs. The PC endows the NPs with a new biological identity, capable of altering the interactions of NPs with targeting organs and subsequent biological fate. This review discusses the mechanisms behind PC-mediated effects on tissue distribution of NPs, aiming to provide insights into the role of PC and its potential applications in NP-based drug delivery.

Meta-Analysis of Nanoparticle Distribution in Tumors and Major Organs in Tumor-Bearing Mice.

Low tumor delivery efficiency is a critical barrier in cancer nanomedicine. This study reports an updated version of "Nano-Tumor Database", which increases the number of time-dependent concentration data sets for different nanoparticles (NPs) in tumors from the previous version of 376 data sets with 1732 data points from 200 studies to the current version of 534 data sets with 2345 data points from 297 studies published from 2005 to 2021. Additionally, the current database includes 1972 data sets for five major organs (i.e., liver, spleen, lung, heart, and kidney) with a total of 8461 concentration data points. Tumor delivery and organ distribution are calculated using three pharmacokinetic parameters, including delivery efficiency, maximum concentration, and distribution coefficient. The median tumor delivery efficiency is 0.67% injected dose (ID), which is low but is consistent with previous studies. Employing the best regression model for tumor delivery efficiency, we generate hypothetical scenarios with different combinations of NP factors that may lead to a higher delivery efficiency of >3%ID, which requires further experimentation to confirm. In healthy organs, the highest NP accumulation is in the liver (10.69%ID/g), followed by the spleen 6.93%ID/g and the kidney 3.22%ID/g. Our perspective on how to facilitate NP design and clinical translation is presented. This study reports a substantially expanded "Nano-Tumor Database" and several statistical models that may help nanomedicine design in the future.

Development and application of an interactive generic physiologically based pharmacokinetic (igPBPK) model for adult beef cattle and lactating dairy cows to estimate tissue distribution and edible tissue and milk withdrawal intervals for per- and polyfluoroalkyl substances (PFAS).

Humans can be exposed to per- and polyfluoroalkyl substances (PFAS) through dietary intake from milk and edible tissues from food animals. This study developed a physiologically based pharmacokinetic (PBPK) model to predict tissue and milk residues and estimate withdrawal intervals (WDIs) for multiple PFAS including PFOA, PFOS and PFHxS in beef cattle and lactating dairy cows. Results showed that model predictions were mostly within a two-fold factor of experimental data for plasma, tissues, and milk with an estimated coefficient of determination (R2) of >0.95. The predicted muscle WDIs for beef cattle were <1 day for PFOA, 449 days for PFOS, and 69 days for PFHxS, while the predicted milk WDIs in dairy cows were <1 day for PFOA, 1345 days for PFOS, and zero day for PFHxS following a high environmental exposure scenario (e.g., 49.3, 193, and 161 ng/kg/day for PFOA, PFOS, and PFHxS, respectively, for beef cattle for 2 years). The model was converted to a web-based interactive generic PBPK (igPBPK) platform to provide a user-friendly dashboard for predictions of tissue and milk WDIs for PFAS in cattle. This model serves as a foundation for extrapolation to other PFAS compounds to improve safety assessment of cattle-derived food products.

Fetal Glucocorticoid Mediates the Association between Prenatal Per- and Polyfluoroalkyl Substance Exposure and Neonatal Growth Index: Evidence from a Birth Cohort Study.

Glucocorticoid plays a key role in the growth and organ maturation of fetus. However, the effect of glucocorticoid on the association between per- and polyfluoroalkyl substance (PFAS) exposure and fetal growth is still unknown. We detected cord cortisol (active glucocorticoid in human) and 34 PFAS concentrations in the maternal serum samples, which were collected from 202 mother-fetus pairs in the Maoming Birth Cohort from 2015 to 2018. The mediation effect of cord cortisol on the association between maternal PFAS and the neonatal growth index (NGI) was estimated. We found that higher PFAS concentrations were associated with lower NGI in terms of ponderal index, birth weight (BW), head circumference (HC), and its z-scores (BWZ and HCZ) (P < 0.05). Fetal cortisol could mediate 12.6-27.3% of the associations between PFAS and NGI. Specifically, cord cortisol mediated the association between branched perfluorooctane sulfonate (branched PFOS) and HCZ by 20.4% and between perfluorooctanoate (PFOA) and HCZ by 27.3%. Our findings provide the first epidemiological data evincing that fetal cortisol could mediate the association between prenatal PFAS exposure and fetal growth. Further investigations are recommended to elucidate the interactions among cord cortisol, PFAS, and fetal growth.

An artificial intelligence-assisted physiologically-based pharmacokinetic model to predict nanoparticle delivery to tumors in mice.

The critical barrier for clinical translation of cancer nanomedicine stems from the inefficient delivery of nanoparticles (NPs) to target solid tumors. Rapid growth of computational power, new machine learning and artificial intelligence (AI) approaches provide new tools to address this challenge. In this study, we established an AI-assisted physiologically based pharmacokinetic (PBPK) model by integrating an AI-based quantitative structure-activity relationship (QSAR) model with a PBPK model to simulate tumor-targeted delivery efficiency (DE) and biodistribution of various NPs. The AI-based QSAR model was developed using machine learning and deep neural network algorithms that were trained with datasets from a published "Nano-Tumor Database" to predict critical input parameters of the PBPK model. The PBPK model with optimized NP cellular uptake kinetic parameters was used to predict the maximum delivery efficiency (DEmax) and DE at 24 (DE24) and 168 h (DE168) of different NPs in the tumor after intravenous injection and achieved a determination coefficient of R2 = 0.83 [root mean squared error (RMSE) = 3.01] for DE24, R2 = 0.56 (RMSE = 2.27) for DE168, and R2 = 0.82 (RMSE = 3.51) for DEmax. The AI-PBPK model predictions correlated well with available experimentally-measured pharmacokinetic profiles of different NPs in tumors after intravenous injection (R2 ≥ 0.70 for 133 out of 288 datasets). This AI-based PBPK model provides an efficient screening tool to rapidly predict delivery efficiency of a NP based on its physicochemical properties without relying on an animal training dataset.

Per- and polyfluoroalkyl substances in ambient fine particulate matter in the Pearl River Delta, China: Levels, distribution and health implications.

Per- and polyfluoroalkyl substances (PFAS) have attracted worldwide attention as one of persistent organic pollutants; however, there is limited knowledge about the exposure concentrations of PFAS-contained ambient particulate matter and the related health risks. This study investigated the abundance and distribution of 32 PFAS in fine particulate matter (PM2.5) collected from 93 primary or secondary schools across the Pearl River Delta region (PRD), China. These chemicals comprise four PFAS categories which includes perfluoroalkyl carboxylic acids (PFCAs), perfluoroalkyl sulfonic acids (PFSAs), perfluoroalkyl acid (PFAA) precursors and PFAS alternatives. In general, concentrations of target PFAS ranged from 11.52 to 419.72 pg/m3 (median: 57.29 pg/m3) across sites. By categories, concentrations of PFSAs (median: 26.05 pg/m3) were the dominant PFAS categories, followed by PFCAs (14.25 pg/m3), PFAS alternatives (2.75 pg/m3) and PFAA precursors (1.10 pg/m3). By individual PFAS, PFOS and PFOA were the dominant PFAS, which average concentration were 24.18 pg/m3 and 6.05 pg/m3, respectively. Seasonal variation showed that the concentrations of PFCAs and PFSAs were higher in winter than in summer, whereas opposite seasonal trends were observed in PFAA precursors and PFAS alternatives. Estimated daily intake (EDI) and hazard quotient (HQ) were used to assess human inhalation-based exposure risks to PFAS. Although the health risks of PFAS via inhalation were insignificant (HQ far less than one), sufficient attention should be levied to ascertain the human exposure risks through inhalation, given that exposure to PFAS through air inhalation is a long term and cumulative process.

Human biomonitoring reference values, exposure distribution, and characteristics of metals in the general population of Taiwan: Taiwan environmental survey for Toxicants (TESTs), 2013-2016.

Human biomonitoring (HBM) provides information to identify chemicals that need to be assessed regarding potential health risks to human populations. We established a population-representative sample in Taiwan, namely the Taiwan Environmental Survey for Toxicants (TESTs) in 2013-2016. In total, 1871 participants (aged 7-97 years) were recruited from throughout Taiwan. A questionnaire survey was applied to obtain individuals' demographic characteristics, and urine samples were obtained to assess metal concentrations. Inductively coupled plasma-mass spectrometry was used to determine concentrations of urinary As (total), Cd, Co, Cr, Cu, Fe, Ga, In, Mn, Ni, Pb, Se, Sr, Tl, and Zn. The purpose of this study was to establish the human urinary reference levels (RVs) for metals in the general population of Taiwan. We found that median concentrations of urinary Cu, Fe, Pb, and Zn in males were statistically significant (p < 0.05) higher than in females (Cu: 11.48 vs. 10.00 µg/L; Fe: 11.48 vs. 10.46 µg/L; Pb: 0.87 vs. 0.76 µg/L; and Zn: 448.93 vs. 348.35 µg/L). On the contrary, Cd and Co were significantly lower in males than in females (Cd: 0.61 vs. 0.64 µg/L; and Co: 0.27 vs. 0.40 µg/L). Urinary Cd levels in the ≥18-year-old group (0.69 µg/L) were significantly higher than those in the 7-17-year-old group (0.49 µg/L, p < 0.001). Among the investigated metals, most were significantly higher in the 7-17-year-old group than in the ≥18-year-old group, except for Cd, Ga, and Pb. Participants who lived in central Taiwan had higher median levels of urinary Cd, Cu, Ga, Ni, and Zn than those in other regions. Median levels of urinary As, Cd, Pb, and Se were significantly higher in participants who lived in harbor (94.12 µg/L), suburban (0.68 µg/L), industrial (0.92 µg/L), and rural (50.29 µg/L) areas, respectively, than the others who lived in other areas. RV95 percentiles of urinary metals (ng/mL) for 7-17/≥18-year-old groups were As (346.9/370.0), Cd (1.41/2.21), Co (2.30/1.73), Cr (0.88/0.88), Cu (28.02/22.78), Fe (42.27/42.36), Ga (0.13/0.12), In (0.05/0.04), Mn (3.83/2.91), Ni (8.09/6.17), Pb (8.09/5.75), Se (122.4/101.9), Sr (556.5/451.3), Tl (0.57/0.49), and Zn (1314.6/1058.8). In this study, we have highlighted the importance of As, Cd, Pb, and Mn exposure in the general population of Taiwan. The established RV95 of urinary metals in Taiwanese would be fundamental information to promote the reduction of metal exposure or policy intervention. We concluded that urinary levels of exposure to certain metals in the general Taiwanese population varied by sex, age, region, and urbanization level. References of metal exposure in Taiwan were established in the current study.

An integrative analysis of lipidomics and transcriptomics in various mouse brain regions in response to real-ambient PM2.5 exposure.

Exposure to Fine particulate matter (PM2.5) has been associated with various neurological disorders. However, the underlying mechanisms of PM2.5-induced adverse effects on the brain are still not fully defined. Multi-omics analyses could offer novel insights into the mechanisms of PM2.5-induced brain dysfunction. In this study, a real-ambient PM2.5 exposure system was applied to male C57BL/6 mice for 16 weeks, and lipidomics and transcriptomics analysis were performed in four brain regions. The findings revealed that PM2.5 exposure led to 548, 283, 304, and 174 differentially expressed genes (DEGs), as well as 184, 89, 228, and 49 distinctive lipids in the hippocampus, striatum, cerebellum, and olfactory bulb, respectively. Additionally, in most brain regions, PM2.5-induced DEGs were mainly involved in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction, and calcium signaling pathway, while PM2.5-altered lipidomic profile were primarily enriched in retrograde endocannabinoid signaling and biosynthesis of unsaturated fatty acids. Importantly, mRNA-lipid correlation networks revealed that PM2.5-altered lipids and DEGs were obviously enriched in pathways involving in bile acid biosynthesis, De novo fatty acid biosynthesis, and saturated fatty acids beta-oxidation in brain regions. Furthermore, multi-omics analyses revealed that the hippocampus was the most sensitive part to PM2.5 exposure. Specifically, dysregulation of Pla2g1b, Pla2g, Alox12, Alox15, and Gpx4 induced by PM2.5 were closely correlated to the disruption of alpha-linolenic acid, arachidonic acid and linoleic acid metabolism in the hippocampus. In summary, our findings highlight differential lipidomic and transcriptional signatures of various brain regions by real-ambient PM2.5 exposure, which will advance our understanding of potential mechanisms of PM2.5-induecd neurotoxicity.

Unveiling the Hidden Dangers of Plasticizers: A Call for Immediate Action.

Over the last several decades, plasticizers have seamlessly integrated themselves into our daily routines, permeating a vast array of commonly encountered products such as food containers, toys, medicines, building materials, electronic devices, cosmetics, perfumes, and personal care items [...].

Reconstructing population exposures to acrylamide from human monitoring data using a pharmacokinetic framework.

BACKGROUND: Acrylamide toxicity involves several metabolic pathways. Thus, a panel of blood and urinary biomarkers for the evaluation of acrylamide exposure was deemed appropriate. OBJECTIVE: The study was designed to evaluate daily acrylamide exposure in US adults via hemoglobin adducts and urinary metabolites using a pharmacokinetic framework. METHODS: A cohort of 2798 subjects aged 20-79 was selected from the National Health and Nutrition Examination Survey (NHANES, 2013-2016) for analysis. Three acrylamide biomarkers including hemoglobin adducts of acrylamide in blood and two urine metabolites, N-Acetyl-S-(2-carbamoylethyl)cysteine (AAMA) and N-Acetyl-S-(2-carbamoyl-2-hydroxyethyl)-l-cysteine (GAMA) were used to estimate daily acrylamide exposure using validated pharmacokinetic prediction models. Multivariate regression models were also used to examine key factors in determining estimated acrylamide intake. RESULTS: The estimated daily acrylamide exposure varied across the sampled population. Estimated acrylamide daily exposure was comparable among the three different biomarkers (median: 0.4-0.7 µg/kg/d). Cigarette smoking emerged as the leading contributor to the acquired acrylamide dose. Smokers had the highest estimated acrylamide intake (1.20-1.49 µg/kg/d) followed by passive smokers (0.47-0.61) and non-smokers (0.45-0.59). Several covariates, particularly, body mass index and race/ethnicity, played roles in determining estimated exposures. DISCUSSION: Estimated daily acrylamide exposures among US adults using multiple acrylamide biomarkers were similar to populations reported elsewhere providing additional support for using the current approach in assessing acrylamide exposure. This analysis assumes that the biomarkers used indicate intake of acrylamide into the body, which is consistent with the substantial known exposures due to diet and smoking. Although this study did not explicitly evaluate background exposure arising from analytical or internal biochemical factors, these findings suggest that the use of multiple biomarkers may reduce uncertainties regarding the ability of any single biomarker to accurately represent actual systemic exposures to the agent. This study also highlights the value of integrating a pharmacokinetic approach into exposure assessments.

The NLR gene family: from discovery to present day.

The mammalian NLR gene family was first reported over 20 years ago, although several genes that were later grouped into the family were already known at that time. Although it is widely known that NLRs include inflammasome receptors and/or sensors that promote the maturation of caspase 1, IL-1ß, IL-18 and gasdermin D to drive inflammation and cell death, the other functions of NLR family members are less well appreciated by the scientific community. Examples include MHC class II transactivator (CIITA), a master transcriptional activator of MHC class II genes, which was the first mammalian NBD-LRR-containing protein to be identified, and NLRC5, which regulates the expression of MHC class I genes. Other NLRs govern key inflammatory signalling pathways or interferon responses, and several NLR family members serve as negative regulators of innate immune responses. Multiple NLRs regulate the balance of cell death, cell survival, autophagy, mitophagy and even cellular metabolism. Perhaps the least discussed group of NLRs are those with functions in the mammalian reproductive system. The focus of this Review is to provide a synopsis of the NLR family, including both the intensively studied and the underappreciated members. We focus on the function, structure and disease relevance of NLRs and highlight issues that have received less attention in the NLR field. We hope this may serve as an impetus for future research on the conventional and non-conventional roles of NLRs within and beyond the immune system.

Prenatal Exposure to Legacy and Alternative Per- and Polyfluoroalkyl Substances and Neuropsychological Development Trajectories over the First 3 Years of Life.

The neurotoxic effects of prenatal exposure to per- and polyfluoroalkyl substances (PFAS) on offspring animals are well-documented. However, epidemiological evidence for legacy PFAS is inconclusive, and for alternative PFAS, it is little known. In this investigation, we selected 718 mother-child pairs from the Chinese Maoming Birth Cohort Study and measured 17 legacy and alternative PFAS in the third-trimester serum. Neuropsychological developments (communication, gross motor function, fine motor function, problem solving ability, and personal-social skills) were assessed at 3, 6, 12, 18, 24, and 36 months using the Ages and Stages Questionnaires 3rd edition. Trajectories of each subscale were classified into persistently low and persistently high groups via group-based trajectory modeling. Logistic regression and grouped weighted quantile sum were fitted to assess the potential effects of individual PFAS and their mixtures, respectively. Higher linear PFHxS levels were associated with elevated odds for the persistently low trajectories of communication (OR = 1.73; 95% CI: 1.12, 2.66) and problem solving ability (OR = 2.11; 95% CI: 1.14, 3.90). Similar findings were observed for linear PFOS, 1m-PFOS, PFDA, PFDoDA, PFUnDA, and legacy PFAS mixture. However, no association was observed for alternative PFAS and their mixture. We provided insights into the longitudinal links between prenatal legacy/alternative PFAS exposure and neuropsychological development trajectories over the first 3 years of life.

Viral protease cleavage of MAVS in genetically modified mice with hepatitis A virus infection.

BACKGROUND & AIMS: Consistent with its relatively narrow host species range, hepatitis A virus (HAV) cannot infect C57BL/6 mice. However, in Mavs-/- mice with genetic deficiency of the innate immune signaling adaptor MAVS, HAV replicates robustly in the absence of disease. The HAV 3ABC protease cleaves MAVS in human cells, thereby disrupting virus-induced IFN responses, but it cannot cleave murine MAVS (mMAVS) due to sequence differences at the site of scission. Here, we sought to elucidate the role of 3ABC MAVS cleavage in determining HAV pathogenesis and host species range. METHODS: Using CRISPR/Cas9 gene editing, we established two independent lineages of C57BL/6 mice with knock-in mutations altering two amino acids in mMAVS ('mMAVS-VS'), rendering it susceptible to 3ABC cleavage without loss of signaling function. We challenged homozygous Mavsvs/vs mice with HAV, and compared infection outcomes with C57BL/6 and genetically deficient Mavs-/- mice. RESULTS: The humanized murine mMAVS-VS protein was cleaved as efficiently as human MAVS when co-expressed with 3ABC in Huh-7 cells. In embyronic fibroblasts from Mavsvs/vs mice, mMAVS-VS was cleaved by ectopically expressed 3ABC, significantly disrupting Sendai virus-induced IFN responses. However, in contrast to Mavs-/- mice with genetic MAVS deficiency, HAV failed to establish infection in Mavsvs/vs mice, even with additional genetic knockout of Trif or Irf1. Nonetheless, when crossed with permissive Ifnar1-/- mice lacking type I IFN receptors, Mavsvs/vsIfnar1-/- mice demonstrated enhanced viral replication coupled with significant reductions in serum alanine aminotransferase, hepatocellular apoptosis, and intrahepatic inflammatory cell infiltrates compared with Ifnar1-/- mice. CONCLUSIONS: MAVS cleavage by 3ABC boosts viral replication and disrupts disease pathogenesis, but it is not by itself sufficient to break the host-species barrier to HAV infection in mice. IMPACT AND IMPLICATIONS: The limited host range of human hepatitis viruses could be explained by species-specific viral strategies that disrupt innate immune responses. Both hepatitis A virus (HAV) and hepatitis C virus express viral proteases that cleave the innate immune adaptor protein MAVS, in human but not mouse cells. However, the impact of this immune evasion strategy has never been assessed in vivo. Here we show that HAV 3ABC protease cleavage of MAVS enhances viral replication and lessens liver inflammation in mice lacking interferon receptors, but that it is insufficient by itself to overcome the cross-species barrier to infection in mice. These results enhance our understanding of how hepatitis viruses interact with the host and their impact on innate immune responses.

Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling.

Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development and risk assessment of environmental chemicals. PBPK model development requires the collection of species-specific physiological, and chemical-specific absorption, distribution, metabolism, and excretion (ADME) parameters, which can be a time-consuming and expensive process. This raises a need to create computational models capable of predicting input parameter values for PBPK models, especially for new compounds. In this review, we summarize an emerging paradigm for integrating PBPK modeling with machine learning (ML) or artificial intelligence (AI)-based computational methods. This paradigm includes 3 steps (1) obtain time-concentration PK data and/or ADME parameters from publicly available databases, (2) develop ML/AI-based approaches to predict ADME parameters, and (3) incorporate the ML/AI models into PBPK models to predict PK summary statistics (eg, area under the curve and maximum plasma concentration). We also discuss a neural network architecture "neural ordinary differential equation (Neural-ODE)" that is capable of providing better predictive capabilities than other ML methods when used to directly predict time-series PK profiles. In order to support applications of ML/AI methods for PBPK model development, several challenges should be addressed (1) as more data become available, it is important to expand the training set by including the structural diversity of compounds to improve the prediction accuracy of ML/AI models; (2) due to the black box nature of many ML models, lack of sufficient interpretability is a limitation; (3) Neural-ODE has great potential to be used to generate time-series PK profiles for new compounds with limited ADME information, but its application remains to be explored. Despite existing challenges, ML/AI approaches will continue to facilitate the efficient development of robust PBPK models for a large number of chemicals.

A web-based interactive physiologically based pharmacokinetic (iPBPK) model for meloxicam in broiler chickens and laying hens.

Meloxicam is a non-steroidal anti-inflammatory drug (NSAID) commonly used in food-producing animals, including chickens in an extralabel manner. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model for meloxicam in broiler chickens and laying hens to facilitate withdrawal interval (WDI) estimations. The model structure for broiler chickens contained six compartments including plasma, muscle, liver, kidney, fat and rest of body, while an additional compartment of ovary was included for laying hens. The model adequately simulated available pharmacokinetic data of meloxicam in plasma of broiler chickens as well as tissue and egg data of laying hens. The model was converted to a web-based interface and used to predict WDIs following extralabel administrations. The results showed that the estimated WDIs were 50, 44, 11, 3, 3, 22 and 4 days for liver, kidney, muscle, fat, ovary, yolk and white, respectively in laying hens after 14 repeated oral administrations of meloxicam (1 mg/kg) at 24-h intervals. This model provides a useful and flexible tool for risk assessment and management of residues for meat and eggs from chickens treated with meloxicam and will serve as a basis for extrapolation to other NSAID drugs and other poultry species to aid animal-derived food safety assessment.