Association Between Nickel Exposure and Metabolic Syndrome: Data from NHANES 2017-2018.

Previous studies have found a possible association between nickel and metabolic syndrome (MetS), but with conflicting results. No studies have determined whether nickel exposure increases the prevalence of MetS in the general U.S. population. Therefore, we used data from the National Health and Nutrition Examination Survey (NHANES) to assess the association between urinary nickel and MetS. Since urinary nickel levels were presented as a skewed distribution, they were normalized using a logarithmic transformation. Weighted multivariate logistic models, restricted cubic spline, threshold effect analysis, and subgroup analyses were used to examine the association between urinary nickel concentration and the risk of MetS and its components. Based on data from 1577 participants, individuals in the second, third, and fourth quartiles of urinary nickel had an adjusted OR for MetS of 1.42 (95% CI: 0.88, 2.28), 2.00 (95% CI: 1.22, 3.28), and 1.68 (95% CI: 1.05, 2.70), respectively, representing an inverted "L"-shaped nonlinear dose-response relationship with an inflection point at 0.2141 ng/L. Patients over the age of 40, males, less educated, and smokers are more susceptible to nickel exposure. In addition, there were significant associations between nickel and most components of the MetS, with the strongest to weakest correlations being high fasting glucose, reduced high-density lipoprotein, abdominal obesity, and elevated blood pressure; however, there was no significant correlation between nickel and hyperlipidemia. In conclusion, environmental nickel exposure increases the prevalence of MetS in U.S. adults, particularly in males over 40 years of age, those with less education, and smokers.

Nanoengineered Nonenzymatic Paper-Based Fluorescent Platform for Pre-Dilution-Free and Visual Real-Time Home Monitoring of Urea for Early Warning of Abnormal Nitrogen-Based Unhealthy Issues.

Distorted urea levels indicate several liver, kidney, or metabolic diseases; however, traditional clinical urea detection relies on urease-based methods enslaved to well-known limitations of high-price, unstable properties, complicated sample pretreatment and analysis procedures, and difficult visual real-time monitoring. Herein, nonenzymatic paper-based fluorescent materials (UFP-BP) are strategically integrated with an on-demand fluorescent-sensor (UFP) self-aggregated nanoparticle on commercial filter paper for pre-dilution-free and visual real-time urea monitoring. The UFP is synthesized and self-aggregated into the fluorescent nanoparticles for selective urea recognition. Then, the nanoparticles are interstitially loaded on filter paper to nanoengineer the UFP-BP, achieving selective quantitative urea detection in the normal concentration range (10-1000 mm). UFP and UFP-BP can successfully monitor urea levels in real rat urine, artificial simulants, and milk. The proposed sensing platform, integrated with smartphones, offers accurate, quantitative, nonenzymatic, noninvasive, pre-dilution-free, on-site, rapid, low-cost, easy-to-operate, real-time visual urea detection in food samples and human body fluids. The designed sensing system can provide early warnings of abnormal nitrogen-based health issues.

Reducing overconfident errors in molecular property classification using Posterior Network.

Deep-learning-based classification models are increasingly used for predicting molecular properties in drug development. However, traditional classification models using the Softmax function often give overconfident mispredictions for out-of-distribution samples, highlighting a critical lack of accurate uncertainty estimation. Such limitations can result in substantial costs and should be avoided during drug development. Inspired by advances in evidential deep learning and Posterior Network, we replaced the Softmax function with a normalizing flow to enhance the uncertainty estimation ability of the model in molecular property classification. The proposed strategy was evaluated across diverse scenarios, including simulated experiments based on a synthetic dataset, ADMET predictions, and ligand-based virtual screening. The results demonstrate that compared with the vanilla model, the proposed strategy effectively alleviates the problem of giving overconfident but incorrect predictions. Our findings support the promising application of evidential deep learning in drug development and offer a valuable framework for further research.

FERONIA homologs in stress responses of horticultural plants: current knowledge and missing links.

Owing to its versatile roles in almost all aspects of plants, FERONIA (FER), a receptor-like kinase of the Catharanthus roseus receptor-like kinase 1-like (CrRLK1L) subfamily, has received extensive research interests during the past decades. Accumulating evidence has been emerged that FER homologs in horticultural crops also play crucial roles in reproductive biology and responses to environmental stimuli (abiotic and biotic stress factors). Here, we provide a review for the latest advances in the studies on FER homologs in modulating stress responses in horticultural crops, and further analyze the underlying mechanisms maintained by FER. Moreover, we also envisage the missing links in current work and provide a perspective for future studies on this star protein.

Biocompatible and Biodegradable 3D Graphene/Collagen Fiber Hybrids for High-Performance Conductive Networks and Sensors.

Polymer-based flexible conductive materials are crucial for wearable electronics, electronic skin, and other smart materials. However, their development and commercial applications have been hampered by the lack of strain tolerance in the conductive network, poor bonding with polymers, discomfort during wear, and a lack of biocompatibility. This study utilized oil-tanned leather with a natural network structure, high toughness, and high tensile deformation recovery as a structural template. A graphene (Gr) conductive network was then constructed on the collagen network of the leather, with coordination cross-linking between Gr and collagen fibers through aluminum ions (Al3+). A new flexible conductive material (Al-GL) was then constructed. Molecular dynamics simulations and experimental validation revealed the existence of physical adsorption, hydrogen bonding adsorption, and ligand bonding between Al3+, Gr, and collagen fibers. Although we established that the binding sites between Al3+ and collagen fibers were primarily on carboxyl groups (-COOH), the mechanism of chemical bonding between Gr and collagen fibers remains unclear. The Al-GL composite exhibited a high shrinkage temperature (67.4 °C) and low electrical resistance (16.1 kΩ·sq-1), as well as good softness (9.33 mN), biocompatibility, biodegradability (<60 h), and air and moisture permeability. Furthermore, the incorporation of Al3+ resulted in a heightened Gr binding strength on Al-GL, and the resistance remained comparable following 1 h of water washing. The Al-GL sensor prepared by WPU encapsulation not only demonstrated highly sensitive responses to diverse motion signals of the human body but also retained a certain degree of response to external mechanical effects underwater. Additionally, the Al-GL-based triboelectric nanogenerator (Al-GL TENG) exhibited distinct response signals to different materials. The Al-GL prepared by the one-pot method proposed in this study offers a novel approach to combining functional nanofillers and substrate materials, providing a theoretical foundation for collagen fiber-based flexible conductive materials.

Modular Biomimetic Strategy Enables Discovery and SAR Exploration of Oxime Macrocycles as Influenza A Virus (H1N1) Inhibitors.

Although vaccination remains the prevalent prophylactic means for controlling Influenza A virus (IAV) infections, novel structural antivirus small-molecule drugs with new mechanisms of action for treating IAV are highly desirable. Herein, we describe a modular biomimetic strategy to expeditiously achieve a new class of macrocycles featuring oxime, which might target the hemagglutinin (HA)-mediated IAV entry into the host cells. SAR analysis revealed that the size and linker of the macrocycles play an important role in improving potency. Particularly, as a 14-membered macrocyclic oxime, 37 exhibited potent inhibitory activity against IAV H1N1 with an EC50 value of 23 nM and low cytotoxicity, which alleviated cytopathic effects and protected cell survival obviously after H1N1 infection. Furthermore, 37 showed significant synergistic activity with neuraminidase inhibitor oseltamivir in vitro.

Association between magnesium deficiency score and sleep quality in adults: A population-based cross-sectional study.

BACKGROUND: The association between magnesium status and sleep quality is unclear. The aim of this study was to determine the relationship between renal reabsorption-related magnesium depletion score (MDS) and sleep quality. METHODS: This study was conducted through a cross-sectional survey of adults aged ≥20 years who participated in NHANES 2005-2014. We used weighted logistic regression to examine the association between MDS and sleep quality and performed trend tests to analyze for the presence of a dose-response relationship. Subgroup analyses were performed based on various sleep outcomes and covariates. RESULTS: A total of 20,585 participants were included in the study, with a mean age of 48.8 years and 50.7 % female. After adjusting for all covariates, we found a graded dose-response relationship between MDS and sleep trouble as well as sleep disorder. Further analyses revealed a significant positive association between MDS and sleep apnea (OR = 3.01; 95 % CI 1.37-6.62), but no association with restless legs, insomnia or insufficient sleep. In addition, subgroup analyses revealed that middle-aged, male, obese, low magnesium intake, and depressed patients were more prone to sleep trouble and sleep disorder; interestingly, MDS was positively associated with excessive sleep in subjects ≥60 years and without depression. CONCLUSIONS: Our study found a significant association between MDS and sleep quality, particularly sleep apnea, but adequate magnesium intake may be beneficial in mitigating this association. MDS may be associated with excessive sleep in older adults, but not with insufficient sleep or insomnia.

Interferon-induced transmembrane protein-1 competitively blocks Ephrin receptor A2-mediated Epstein-Barr virus entry into epithelial cells.

Epstein-Barr virus (EBV) can infect both B cells and epithelial cells (ECs), causing diseases such as mononucleosis and cancer. It enters ECs via Ephrin receptor A2 (EphA2). The function of interferon-induced transmembrane protein-1 (IFITM1) in EBV infection of ECs remains elusive. Here we report that IFITM1 inhibits EphA2-mediated EBV entry into ECs. RNA-sequencing and clinical sample analysis show reduced IFITM1 in EBV-positive ECs and a negative correlation between IFITM1 level and EBV copy number. IFITM1 depletion increases EBV infection and vice versa. Exogenous soluble IFITM1 effectively prevents EBV infection in vitro and in vivo. Furthermore, three-dimensional structure prediction and site-directed mutagenesis demonstrate that IFITM1 interacts with EphA2 via its two specific residues, competitively blocking EphA2 binding to EBV glycoproteins. Finally, YTHDF3, an m6A reader, suppresses IFITM1 via degradation-related DEAD-box protein 5 (DDX5). Thus, this study underscores IFITM1's crucial role in blocking EphA2-mediated EBV entry into ECs, indicating its potential in preventing EBV infection.

Matching actions to needs: shifting policy responses to the changing health needs of Chinese children and adolescents.

China is home to the second largest population of children and adolescents in the world. Yet demographic shifts mean that the government must manage the challenge of fewer children with the needs of an ageing population, while considering the delicate tension between economic growth and environmental sustainability. We mapped the health problems and risks of contemporary school-aged children and adolescents in China against current national health policies. We involved multidisciplinary experts, including young people, with the aim of identifying actionable strategies and specific recommendations to promote child and adolescent health and wellbeing. Notwithstanding major improvements in their health over the past few decades, contemporary Chinese children and adolescents face distinct social challenges, including high academic pressures and youth unemployment, and new health concerns including obesity, mental health issues, and sexually transmitted infections. Inequality by gender, geography, and ethnicity remains a feature of health risks and outcomes. We identified a mismatch between current health determinants, risks and outcomes, and government policies. To promote the health of children and adolescents in China, we recommend a set of strategies that target government-led initiatives across the health, education, and community sectors, which aim to build supportive and responsive families, safe communities, and engaging and respectful learning environments. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Corrigendum: In vitro and in vivo antitumor activity of cucurbitacin C, a novel natural product from cucumber.

[This corrects the article DOI: 10.3389/fphar.2019.01287.].

The inhibition of YTHDF3/m6A/LRP6 reprograms fatty acid metabolism and suppresses lymph node metastasis in cervical cancer.

The lipid synthesis of fatty acid (FA) represents a significant hallmark in the occurrence and progression of malignant tumor, which are associated with lymph node (LN) metastasis. Elucidation of the molecular mechanisms underlying LN metastasis could provide therapeutic strategies for cervical cancer (CCa). N6-Methyladenosine (m6A), the most prevalent and abundant RNA modification, exerts specific regulatory control over a series of oncogene expressions. This study demonstrated a clinical correlation between the upregulation of the m6A reader YTHDF3 and LN metastasis, thereby contributing to poor overall survival probability (OS) among CCa patients. The mechanistic investigation revealed that SREBF1 transcriptionally activated YTHDF3 expression by binding to its promoter. Functional experiments demonstrated that the upregulation of YTHDF3 significantly enhanced the in vitro proliferative, migratory, and invasive capacities of CCa cells, while also promoting lymphangiogenesis and facilitating LN metastasis in vivo. Mechanistically, the upregulation of LRP6 through YTHDF3-mediated m6A modification resulted in increased expression of FASN and ACC1, leading to both lipolysis of lipid droplets and synthesis of free fatty acid. Ultimately, this promoted fatty acid metabolism and enhanced LN metastasis by activating the LRP6-YAP-VEGF-C axis, which could induce lymphangiogenesis in CCa. Our study highlighted that YTHDF3 can serve as a promising therapeutic target and predictive biomarker for CCa patients with LN metastasis.

Application of ensemble learning for predicting GABAA receptor agonists.

BACKGROUND: Over the past few decades, agonists binding to the benzodiazepine site of the GABAA receptor have been successfully developed as clinical drugs. Different modulators (agonist, antagonist, and reverse agonist) bound to benzodiazepine sites exhibit different or even opposite pharmacological effects, however, their structures are so similar that it is difficult to distinguish them based solely on molecular skeleton. This study aims to develop classification models for predicting the agonists. METHODS: 306 agonists or non-agonists were collected from literature. Six machine learning algorithms including RF, XGBoost, AdaBoost, GBoost, SVM, and ANN algorithms were employed for model development. Using six descriptors including 1D/2D Descriptors, ECFP4, 2D-Pharmacophore, MACCS, PubChem, and Estate fingerprint to characterize chemical structures. The model interpretability was explored by SHAP method. RESULTS: The best model demonstrated an AUC value of 0.905 and an MCC value of 0.808 for the test set. The PubMac-based model (PubMac-GB) achieved best AUC values of 0.935 for test set. The SHAP analysis results emphasized that MaccsFP62, ECFP_624, ECFP_724, and PubchemFP213 were the crucial molecular features. Applicability domain analysis was also performed to determine reliable prediction boundaries for the model. The PubMac-GB model was applied to virtual screening for potential GABAA agonists and the top 100 compounds were given. CONCLUSION: Overall, our ensemble learning-based model (PubMac-GB) achieved comparable performance and would be helpful in effectively identifying agonists of GABAA receptors.

KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling.

Kinase inhibitors are crucial in cancer treatment, but drug resistance and side effects hinder the development of effective drugs. To address these challenges, it is essential to analyze the polypharmacology of kinase inhibitor and identify compound with high selectivity profile. This study presents KinomeMETA, a framework for profiling the activity of small molecule kinase inhibitors across a panel of 661 kinases. By training a meta-learner based on a graph neural network and fine-tuning it to create kinase-specific learners, KinomeMETA outperforms benchmark multi-task models and other kinase profiling models. It provides higher accuracy for understudied kinases with limited known data and broader coverage of kinase types, including important mutant kinases. Case studies on the discovery of new scaffold inhibitors for membrane-associated tyrosine- and threonine-specific cdc2-inhibitory kinase and selective inhibitors for fibroblast growth factor receptors demonstrate the role of KinomeMETA in virtual screening and kinome-wide activity profiling. Overall, KinomeMETA has the potential to accelerate kinase drug discovery by more effectively exploring the kinase polypharmacology landscape.

Computing the relative binding affinity of ligands based on a pairwise binding comparison network.

Structure-based lead optimization is an open challenge in drug discovery, which is still largely driven by hypotheses and depends on the experience of medicinal chemists. Here we propose a pairwise binding comparison network (PBCNet) based on a physics-informed graph attention mechanism, specifically tailored for ranking the relative binding affinity among congeneric ligands. Benchmarking on two held-out sets (provided by Schrödinger and Merck) containing over 460 ligands and 16 targets, PBCNet demonstrated substantial advantages in terms of both prediction accuracy and computational efficiency. Equipped with a fine-tuning operation, the performance of PBCNet reaches that of Schrödinger's FEP+, which is much more computationally intensive and requires substantial expert intervention. A further simulation-based experiment showed that active learning-optimized PBCNet may accelerate lead optimization campaigns by 473%. Finally, for the convenience of users, a web service for PBCNet is established to facilitate complex relative binding affinity prediction through an easy-to-operate graphical interface.

Estradiol and Benzo[a]pyrene Co-Exposure Contributes to Lung Cancer Cell A549 Proliferation through AHR/AKT/ERK1/2 Pathway.

OBJECTIVE: Estrogen may have a certain role in promoting lung cancer caused by tobacco. Our understanding of the carcinogenic effects and mechanisms of carcinogen mixture estrogen is limited and mostly relies on the findings from studying individual factors. METHODS: To test this hypothesis, an in-vitro study was used to investigate the effects of 17 ß-estradiol (E2) on benzo[a]pyrene (Bap)-induced lung cancer cell A549 proliferation. RESULTS: We first found that E2 was increased in serum samples from lung adenocarcinoma cancer (LUAD) patients, even to a small extent. We found that Bap could enhance colony formation ability, up-regulate proliferating cell nuclear antigen (PCNA) and B-cell lymphoma-2 (Bcl-2) expression, induce cell proliferation and inhibit apoptosis in A549 cells. E2 promoted these effects of Bap. Moreover, E2 and Bap co-exposure promoted lung cancer cell proliferation by activating the aryl hydrocarbon receptor (AHR)/protein kinase B (AKT)/extracellular regulated protein kinases (ERK1/2) signaling pathway. Inhibition of the AKT and ERK1/2 signaling pathways suppressed E2 and Bap co-exposure's effect on A549 cells proliferation and apoptosis. CONCLUSIONS: Collectively, we conclude that E2 could promote the proliferative and antiapoptotic effects of Bap on A549 cells, and activation of the AHR/AKT/ERK1/2 pathway may be involved in this process.

Global and Chinese perspectives on adolescent health and development / 中国学校卫生

Abstract@#Through a review of the current state and risks of adolescent health in the world and in China, the main health issues faced by adolescents are summarized. The importance of promoting adolescent health and the importance of effective adolescent health services are highlighted. The past 30 years important documents of international adolescent health and development have been sorted out. The history of the development of adolescent health care in China has been reviewed. It was pointed out that the health and development of adolescents has become a hot spot and focus of international attention, and it has received more and more attention in China. The adolescent health care has ushered in a new opportunity for development, which will help the health and development of adolescents in China.