Wintertime ozone surges: The critical role of alkene ozonolysis.

Ozone (O3) pollution is usually linked to warm weather and strong solar radiation, making it uncommon in cold winters. However, an unusual occurrence of four high O3 episode days (with maximum hourly concentrations exceeding 100 ppbv and peaking at 121 ppbv) was recorded in January 2018 in Lanzhou city, China. During these episodes, the average daytime concentration of total non-methane volatile organic compounds (TVOCs) reached 153.4 ± 19.0 ppbv, with alkenes-largely emitted from the local petrochemical industry-comprising 82.3 ± 13.1 ppbv. Here we show a photochemical box model coupled with a Master Chemical Mechanism to elucidate the mechanisms behind this unusual wintertime O3 pollution. We find that the typically low temperatures (-1.7 ± 1.3 °C) and weak solar radiation (263.6 ± 60.7 W m- 2) of those winter episode days had a minimal effect on the reactivity of VOCs with OH radicals. Instead, the ozonolysis of alkenes generated Criegee intermediates, which rapidly decomposed into substantial RO x radicals (OH, HO2, and RO2) without sunlight. This radical production led to the oxidation of VOCs, with alkene ozonolysis ultimately contributing to 89.6 ± 8.7% of the O3 formation during these episodes. This mechanism did not activate at night due to the depletion of O3 by the NO titration effect. Furthermore, the findings indicate that a reduction of alkenes by 28.6% or NO x by 27.7% in the early afternoon could significantly mitigate wintertime O3 pollution. Overall, this study unravels the unique mechanism of alkene-induced winter O3 pollution and offers a reference for winter O3 reduction strategies in the petrochemical industrial regions.

Combination of Cytologic Findings and Circulating Tumor DNA From Cerebrospinal Fluid Revealed SCLC Transformation in Patients With Leptomeningeal Metastases of Lung Adenocarcinoma.

Introduction: Transformation to SCLC is a resistance mechanism to tyrosine kinase inhibitor in EGFR-mutated lung adenocarcinoma (LUAD). Nevertheless, the clinical and molecular features of SCLC transformation in LUAD with leptomeningeal metastases (LM) are scarce. Methods: We retrospectively collected 237 patients with NSCLC who underwent lumbar puncture owing to suggestion of LM. All SCLC transformation in cerebrospinal fluid (CSF) was confirmed by two experienced pathologists using cytologic evaluation. CSF circulating tumor DNA (ctDNA) was tested by next-generation sequencing. Results: Tumor cells in CSF samples were found in 111 patients (111 of 237, 46.8%), and eight cases (eight of 111, 7.2%) were identified as having SCLC cells in CSF. Seven patients carried the EGFR mutation, including four patients with EGFR exon 19 deletion and three patients with EGFR exon 21 L858R mutation. Another patient harbored ERBB2 insertion. Seven of these patients were resistant to targeted therapy. CSF ctDNA analysis reported that TP53 and RB1 mutations were common. The median time from the diagnosis of advanced NSCLC to SCLC transformation found in CSF was 9.7 months (95% confidence interval [CI]: 4.0-17.5 mo). The median overall survival since the initial diagnosis of metastatic NSCLC was 15.3 months (95% CI: 1.2-29.4 mo). The median overall survival after SCLC transformation detected in CSF was 5.0 months (95% CI: 4.0-5.9 mo). Conclusions: SCLC transformation may be revealed in CSF by both cytologic evaluation and ctDNA, not just in tissue that underwent rebiopsy. SCLC transformation of CSF is informative for resistance mechanism in patients with LUAD with LM on tyrosine kinase inhibitor progression, which was associated with poor survival.

Alectinib Versus Crizotinib in Asian Patients With Treatment-Naïve Advanced ALK-Positive NSCLC: Five-Year Update From the Phase 3 ALESIA Study.

Introduction: Previous results from the phase 3 ALESIA study (NCT02838420) revealed that alectinib (a central nervous system [CNS]-active, ALK inhibitor) had clinical benefits in treatment-naïve Asian patients with advanced ALK-positive NSCLC, consistent with the global ALEX study. We present updated data after more than or equal to 5 years of follow-up from the "last patient in" date. Methods: Adult patients with treatment-naïve, advanced ALK-positive NSCLC from mainland China, South Korea, and Thailand were randomized 2:1 to receive twice-daily 600 mg alectinib (n = 125) or 250 mg crizotinib (n = 62). The primary endpoint was investigator-assessed progression-free survival. Secondary or exploratory endpoints included overall survival, objective response rate, time to CNS progression, and safety. Results: At the data cutoff (May 16, 2022), the median survival follow-up was 61 and 51 months in the alectinib and crizotinib arms, respectively. Median progression-free survival was 41.6 months with alectinib versus 11.1 months with crizotinib (stratified hazard ratio = 0.33, 95% confidence interval: 0.23-0.49). Overall survival data remain immature; 5-year overall survival rates were 66.4% (alectinib arm) versus 56.1% (crizotinib arm). Objective response rate was 91.2% versus 77.4% with alectinib and crizotinib, respectively. CNS progression was delayed with alectinib versus crizotinib (cause-specific hazard ratio = 0.16, 95% confidence interval: 0.08-0.32). Median treatment duration was longer with alectinib versus crizotinib (42.3 versus 12.6 mo). No new safety signals were observed. Conclusions: With four additional years of follow-up, these updated results confirm the clinical benefit and manageable safety of alectinib in Asian patients with advanced ALK-positive NSCLC, and confirm alectinib as a standard-of-care treatment for patients with advanced ALK-positive NSCLC.

Blood cadmium concentration and pulmonary function injury: potential mediating role of oxidative stress in chronic obstructive pulmonary disease patients.

BACKGROUND: Exposure to cadmium (Cd) is associated with a reduction in lung function among patients with chronic obstructive pulmonary disease (COPD). The longitudinal relationship and mechanism underlying the link between Cd exposure and lung function changes among COPD patients are yet unknown. METHODS: The cohort study included 259 eligible patients who underwent regular professional follow-ups. Blood Cd levels and serum 8-iso-prostaglandin F2 alpha (8-iso-PGF2α) levels were assessed. Lung function was determined at baseline and follow-up research. The associations between changes in lung function and blood Cd concentration were analysed using multivariate linear and logistic regression models. RESULTS: Each 1-ppb elevation in blood Cd content resulted in a 0.420 L decrease in forced vital capacity (FVC), a 0.424 L decrease in forced expiratory volume in 1 s (FEV1), a 4.341% decrease in FEV1/FVC%, and a 8.418% decrease in FEV1% predicted in patients with COPD. Blood Cd concentration showed a positive correlation with serum 8-iso-PGF2α levels in a specific range. The relative contribution of increased serum levels of 8-iso-PGF2α to Cd-induced declines in FEV1, predicted FEV1%, and FEV1/FVC% were 2.08%, 8.08%, and 13.19%, respectively. CONCLUSION: Blood Cd levels are associated with lung function changes in COPD patients. Oxidative stress is thought to be an important mediator in Cd-induced reduction of pulmonary function.

NAC1 promotes stemness and regulates myeloid-derived cell status in triple-negative breast cancer.

Triple negative breast cancer (TNBC) is a particularly lethal breast cancer (BC) subtype driven by cancer stem cells (CSCs) and an immunosuppressive microenvironment. Our study reveals that nucleus accumbens associated protein 1 (NAC1), a member of the BTB/POZ gene family, plays a crucial role in TNBC by maintaining tumor stemness and influencing myeloid-derived suppressor cells (MDSCs). High NAC1 expression correlates with worse TNBC prognosis. NAC1 knockdown reduced CSC markers and tumor cell proliferation, migration, and invasion. Additionally, NAC1 affects oncogenic pathways such as the CD44-JAK1-STAT3 axis and immunosuppressive signals (TGFß, IL-6). Intriguingly, the impact of NAC1 on tumor growth varies with the host immune status, showing diminished tumorigenicity in natural killer (NK) cell-competent mice but increased tumorigenicity in NK cell-deficient ones. This highlights the important role of the host immune system in TNBC progression. In addition, high NAC1 level in MDSCs also supports TNBC stemness. Together, this study implies NAC1 as a promising therapeutic target able to simultaneously eradicate CSCs and mitigate immune evasion.

Organocatalytic Hydrogen Evolution Reaction by Diazaphospholenes.

The electrochemical hydrogen evolution reaction (HER) is currently recognized as a prospective way to obtain clean energy. The electrocatalysts used currently are dominantly based on transition metals. In this work, we have demonstrated a diazaphospholene (N-heterocyclic phosphine (NHP))-type small molecular organocatalyst that can catalyze the HER with a maximum current density of 130 mA·cm-2, an overpotential of 354 mV, and a faradaic efficiency of 90%. Mechanistic studies verify a Heyrovsky-type process with NHP, whereas its hydricity and aromaticity favor hydrogen release and catalyst regeneration.

Novel Combination Therapy for Heart Failure: Trimebutine-Methoxsalen Identified through Synergistic Network Virtual Screening and Experimental Validation.

Combination therapy is increasingly favored by pharmaceutical companies and researchers as an effective way to quickly discover new drugs with excellent efficacy, especially in the treatment of complex diseases. Previously, we successfully developed a computational screening method to identify such combinations, although it fell short in elucidating their synergistic mechanisms. In this work, we have transitioned to a highest single agent (HSA) synergy model for network screening, which streamlines the discovery of promising combinations and facilitates the investigation of their synergistic effects. Through this refined approach, the trimebutine-methoxsalen combination emerged as a promising candidate for heart failure (HF) treatment, exhibiting significant in vitro cardioprotective effects and effectively mitigating isoproterenol (ISO)-induced structural remodeling in the mouse heart. Further mechanistic studies have demonstrated that trimebutine and methoxsalen could synergistically inhibit intracellular calcium overload in myocardial cells and reduce the production of ROS, thus exerting cardioprotective effects. Overall, this study introduces an advanced computational strategy that not only identifies a novel combination therapy against HF but also sheds light on its underlying synergistic mechanisms.

SGLT2 inhibitors ameliorate NAFLD in mice via downregulating PFKFB3, suppressing glycolysis and modulating macrophage polarization.

Sodium-glucose co-transporter 2 (SGLT2) inhibitor (SGLT2i) is a novel class of anti-diabetic drug, which has displayed a promising benefit for non-alcoholic fatty liver disease (NAFLD). In this study, we investigated the protective effects of SGLT2i against NAFLD and the underlying mechanisms. The db/db mice and western diet-induced NAFLD mice were treated with dapagliflozin (1 mg·kg-1·d-1, i.g.) or canagliflozin (10 mg·kg-1·d-1, i.g.) for 8 weeks. We showed that the SGLT2i significantly improved NAFLD-associated metabolic indexes, and attenuated hepatic steatosis and fibrosis. Notably, SGLT2i reduced the levels of pro-inflammatory cytokines and chemokines, downregulated M1 macrophage marker expression and upregulated M2 macrophage marker expression in liver tissues. In cultured mouse bone marrow-derived macrophages and human peripheral blood mononuclear cell-derived macrophages, the SGLT2i (10, 20 and 40 µmol/L) significantly promoted macrophage polarization from M1 to M2 phenotype. RNA sequencing, Seahorse analysis and liquid chromatography-tandem mass spectrometry analysis revealed that the SGLT2i suppressed glycolysis and triggered metabolic reprogramming in macrophages. By using genetic manipulation and pharmacological inhibition, we identified that the SGLT2i targeted PFKFB3, a key enzyme of glycolysis, to modulate the macrophage polarization of M1 to M2 phenotype. Using a co-culture of macrophages with hepatocytes, we demonstrated that the SGLT2i inhibited lipogenesis in hepatocytes via crosstalk with macrophages. In conclusion, this study highlights a potential therapeutic application for repurposing SGLT2i and identifying a potential target PFKFB3 for NAFLD treatment.

Association between plasma CC16 levels and lung function changes in coke oven workers: A cohort study from 2014 to 2023.

Club cell secretory protein (CC16) is considered a biological marker indicating lung epithelial and lung permeability. The joint effect of polycyclic aromatic hydrocarbons (PAHs) exposure on CC16 levels and the association between CC16 levels and long-term lung function changes lacks epidemiological evidence. To investigate the effect of PAHs exposure on plasma CC16 levels and the association between CC16 levels and long-term lung function changes, this study enrolled 307 coke oven workers in 2014, measured their baseline concentrations of urinary PAHs metabolites and plasma CC16, with follow-up after nine years. Bayesian kernel machine regression (BKMR) was employed to analyze the effect of mixed PAHs metabolites. The dose-effect association between baseline CC16 levels and lung function during 2014-2023 was explored using restricted cubic spline (RCS) models, and stratified analysis investigated the effect modification of PAHs exposure and smoking status on this association. The median age of the participants was 40 years, with 93.81 % male. The results showed that plasma CC16 levels decreased by 2.02 ng/mL (95 % CI: -3.77, -0.27) among all participants and FVC (% predicted) decreased by 2.87 % (95 % CI: -5.59, -0.14) in the low CC16 group with each unit increase in log-transformed 2-OHNAP. The BKMR model revealed a negative association between PAHs metabolites and both plasma CC16 levels and FVC (% predicted). Plasma CC16 decreased by 1.05 units when all PAHs metabolites at P65 compared to those at P50. After 9 years of follow-up, baseline CC16 levels were significantly associated with follow-up FVC (% predicted), FEV1 (% predicted), and small airway dysfunction risk. Furthermore, high PAHs exposure and smoking enhanced the association between CC16 and lung function. In conclusion, PAHs exposure decreases CC16 levels, and coking workers with low baseline CC16 levels may experience more severe future lung function decline.

Comprehensive hepatotoxicity prediction: ensemble model integrating machine learning and deep learning.

Background: Chemicals may lead to acute liver injuries, posing a serious threat to human health. Achieving the precise safety profile of a compound is challenging due to the complex and expensive testing procedures. In silico approaches will aid in identifying the potential risk of drug candidates in the initial stage of drug development and thus mitigating the developmental cost. Methods: In current studies, QSAR models were developed for hepatotoxicity predictions using the ensemble strategy to integrate machine learning (ML) and deep learning (DL) algorithms using various molecular features. A large dataset of 2588 chemicals and drugs was randomly divided into training (80%) and test (20%) sets, followed by the training of individual base models using diverse machine learning or deep learning based on three different kinds of descriptors and fingerprints. Feature selection approaches were employed to proceed with model optimizations based on the model performance. Hybrid ensemble approaches were further utilized to determine the method with the best performance. Results: The voting ensemble classifier emerged as the optimal model, achieving an excellent prediction accuracy of 80.26%, AUC of 82.84%, and recall of over 93% followed by bagging and stacking ensemble classifiers method. The model was further verified by an external test set, internal 10-fold cross-validation, and rigorous benchmark training, exhibiting much better reliability than the published models. Conclusion: The proposed ensemble model offers a dependable assessment with a good performance for the prediction regarding the risk of chemicals and drugs to induce liver damage.

Molecular phylogeny and species diversity of the genus Dichaetophora Duda and related taxa (Diptera: Drosophilidae).

Our intensive surveys of wild drosophilids in East and Southeast Asia discovered a great species diversity (more than 100 putatively new species) of the genus Dichaetophora, which is currently comprised of 67 formally described species assigned into five species groups, i.e., agbo, tenuicauda, acutissima, sinensis and trilobita. In the present study, we delimited species from a huge amount of samples of Dichaetophora and allied taxa (the genus Mulgravea and the subgenus Dudaica of Drosophila) collected from a wide range of the Oriental and east Palearctic regions. We first sorted all specimens into morpho-species, and representative specimen(s) selected from each morpho-species were subjected to barcoding of COI (the cytochrome c oxidase subunit I gene) sequences. The applied ASAP (Assemble Species by Automatic Partitioning) analysis estimated a total of 166 to 168 MOTUs (molecular operational taxonomic units). Integrating this result with morphological evidence from re-examined, detailed structures of male terminalia, we recognized a total of 144 (109 new and 35 known) species in our sample. Out of them, 83 species representing the supraspecific taxa of Dichaetophora, Mulgravea and Dudaica were selected, along with 33 species from major genera and subgenera of Drosophila in the tribe Drosophilini, as in-group and four species from the tribe Colocasiomyini as out-group for phylogenetic reconstruction based on 12 nuclear gene markers. In the trees constructed by the maximum likelihood and Bayesian inference methods, the three focal taxa (i.e., Dichaetophora, Mulgravea and Dudaica) formed a clade provisionally called the "pan-Dichaetophora". Within this large clade, the agbo, tenuicauda, sinensis and trilobita groups of Dichaetophora, Mulgravea and Dudaica were recovered as monophyletic groups, but Dichaetophora and its acutissima group were regarded as paraphyletic. In addition, two clusters were recognized among ungrouped species of Dichaetophora. Thus, the present study has uncovered some issues concerning the taxonomy of the pan-Dichaetophora. Such issues will be addressed elsewhere in the phylogenetic reclassification of the pan-Dichaetophora, along with descriptions/redescriptions of a large number of new/known species delimited in the present study.

FGTN: Fragment-based graph transformer network for predicting reproductive toxicity.

Reproductive toxicity is one of the important issues in chemical safety. Traditional laboratory testing methods are costly and time-consuming with raised ethical issues. Only a few in silico models have been reported to predict human reproductive toxicity, but none of them make full use of the topological information of compounds. In addition, most existing atom-based graph neural network methods focus on attributing model predictions to individual nodes or edges rather than chemically meaningful fragments or substructures. In current studies, we develop a novel fragment-based graph transformer network (FGTN) approach to generate the QSAR model of human reproductive toxicity by considering internal topological structure information of compounds. In the FGTN model, the compound is represented by a graph architecture using fragments to be nodes and bonds linking two fragments to be edges. A super molecule-level node is further proposed to connect all fragment nodes by undirected edges, obtaining global molecular features from fragment embeddings. The FGTN model achieved an accuracy (ACC) of 0.861 and an area under the receiver operating characteristic curve (AUC) value of 0.914 on nonredundant blind tests, outperforming traditional fingerprint-based machine learning models and atom-based GCN model. The FGTN model can attribute toxic predictions to fragments, generating specific structural alerts for the positive compound. Moreover, FGTN may also have the capability to distinguish various chemical isomers. We believe that FGTN can be used as a reliable and effective tool for human reproductive toxicity prediction in contribution to the advancement of chemical safety assessment.

Divergent Synthesis and Antigenicity Evaluation of Core Oligosaccharides of the Lipopolysaccharides from Acinetobacter baumannii SMAL and ATCC 19606.

Acinetobacter baumannii poses a serious threat to human health. Pathogenic bacterial lipopolysaccharides (LPSs) are potent immunogens for the development of antibacterial vaccines. To investigate the antigenic properties of A. baumannii LPS, five well-defined core oligosaccharide fragments from the LPS of A. baumannii SMAL and ATCC 19606 were synthesized. A divergent synthesis strategy based on orthogonally protected α-(2 → 5)-linked Kdo dimer 6 was developed. Selective exposure of different positions in this key precursor and then elongation of sugar chains via stereocontrolled formation of both 1,2-trans and 1,2-cis-2-aminoglycosidic linkages permitted the efficient synthesis of the targets. The synthetic route also highlights a 4-O and then 7-O glycosylation sequence for assembly of the novel 4,7-branched Kdo framework. Antigenicity assay using the glycan microarray technique disclosed that tetrasaccharide 3 featuring both 4,7-branch and α-(2 → 5)-Kdo-Kdo structural elements was a potential antigenic determinant.

Development and validation of a nomogram for predicting critical respiratory events during early anesthesia recovery in elderly patients.

BACKGROUND: Elderly patients undergoing recovery from general anesthesia face a heightened risk of critical respiratory events (CREs). Despite this, there is a notable absence of effective predictive tools tailored to this specific demographic. This study aims to develop and validate a predictive model (nomogram) to address this gap. CREs pose significant risks to elderly patients during the recovery phase from general anesthesia, making it an important issue in perioperative care. With the increasing aging population and the complexity of surgical procedures, it is crucial to develop effective predictive tools to improve patient outcomes and ensure patient safety during post-anesthesia care unit (PACU) recovery. METHODS: A total of 324 elderly patients who underwent elective general anesthesia in a grade A tertiary hospital from January 2023 to June 2023 were enrolled. Risk factors were identified using least absolute shrinkage and selection operator (LASSO) regression. A multivariate logistic regression model was constructed and represented as a nomogram. Internal validation of the model was performed using Bootstrapping. This study followed the TRIPOD checklist for reporting. RESULTS: The indicators included in the nomogram were frailty, snoring, patient-controlled intravenous analgesia (PCIA), emergency delirium and cough intensity at extubation. The diagnostic performance of the nomogram model was satisfactory, with AUC values of 0.990 and 0.981 for the training set and internal validation set, respectively. The optimal cutoff value was determined to be 0.22, based on a Youden index of 0.911. The F1-score was 0.927, and the MCC was 0.896. The calibration curve, Brier score (0.046), and HL test demonstrated acceptable consistency between the predicted and actual results. DCA revealed high net benefits of the nomogram prediction across all threshold probabilities. CONCLUSIONS: This study developed and validated a nomogram to identify elderly patients in the PACU who are at higher risk of CREs. The identified predictive factors included frailty condition, snoring syndrome, PCIA, emergency delirium, and cough intensity at extubation. By identifying patients at higher risk of CREs early on, medical professionals can implement targeted strategies to mitigate the occurrence of complications and provide better postoperative care for elderly patients recovering from general anesthesia.

Single-cell RNA sequencing to map tumor heterogeneity in gastric carcinogenesis paving roads to individualized therapy.

Gastric cancer (GC) is a highly heterogeneous disease with a complex tumor microenvironment (TME) that encompasses multiple cell types including cancer cells, immune cells, stromal cells, and so on. Cancer-associated cells could remodel the TME and influence the progression of GC and therapeutic response. Single-cell RNA sequencing (scRNA-seq), as an emerging technology, has provided unprecedented insights into the complicated biological composition and characteristics of TME at the molecular, cellular, and immunological resolutions, offering a new idea for GC studies. In this review, we discuss the novel findings from scRNA-seq datasets revealing the origin and evolution of GC, and scRNA-seq is a powerful tool for investigating transcriptional dynamics and intratumor heterogeneity (ITH) in GC. Meanwhile, we demonstrate that the vital immune cells within TME, including T cells, B cells, macrophages, and stromal cells, play an important role in the disease progression. Additionally, we also overview that how scRNA-seq facilitates our understanding about the effects on individualized therapy of GC patients. Spatial transcriptomes (ST) have been designed to determine spatial distribution and capture local intercellular communication networks, enabling a further understanding of the relationship between the spatial background of a particular cell and its functions. In summary, scRNA-seq and other single-cell technologies provide a valuable perspective for molecular and pathological disease characteristics and hold promise for advancing basic research and clinical practice in GC.

Discovery of SILA-123 as a Highly Potent FLT3 Inhibitor for the Treatment of Acute Myeloid Leukemia with Various FLT3 Mutations.

The FLT3-ITD (internal tandem duplication) mutant has been a promising target for acute myeloid leukemia (AML) drug discovery but is now facing the challenge of resistance due to point mutations. Herein, we have discovered a type II FLT3 inhibitor, SILA-123. This inhibitor has shown highly potent inhibitory effects against FLT3-WT (IC50 = 2.1 nM) and FLT3-ITD (IC50 = 1.0 nM), tumor cells with the FLT3-ITD mutant such as MOLM-13 (IC50 = 0.98 nM) and MV4-11 (IC50 = 0.19 nM), as well as BaF3 cells associated with the FLT3-ITD mutant and point mutations like BaF3-FLT3-ITD-G697R (IC50 = 3.0 nM). Moreover, SILA-123 exhibited promising kinome selectivity against 310 kinases (S score (10) = 0.06). In in vivo studies, SILA-123 significantly suppressed the tumor growth in MV4-11 (50 mg/kg/d, TGI = 87.3%) and BaF3-FLT3-ITD-G697R (50 mg/kg/d, TGI = 60.0%) cell-inoculated allograft models. Our data suggested that SILA-123 might be a promising drug candidate for FLT3-ITD-positive AML.

Fusarium graminearum spores disrupt gut microbiota and metabolome via the lung-gut axis in mice.

Fusarium graminearum, the primary pathogen responsible for wheat Fusarium head blight, can induce pulmonary damage through its spores. However, the detailed mechanism by which these spores cause intestinal injury is not yet fully understood. This study aimed to investigate the impact of exposure to fungal spores on the intestinal microbiota using a mice model that mimics the effects of fusarium graminearum spores on the gut microbiota and its metabolic profile. The study utilized 16S rRNA sequencing and metabolomics methodologies to analyze the contents of the cecum and feces in mice. The results showed that exposure to fungal spores led to significant changes in the composition of the intestinal microbiota in mice, characterized by an increase in Akkermansia and Staphylococcus populations. A non-targeted metabolomics analysis identified 316 metabolites associated with various metabolic pathways, particularly galactose metabolism. Pre-exposure to antibiotics before fungal spore exposure resulted in a decrease in the metabolic capacity of the intestinal microbiota in mice. This research demonstrates that fusarium graminearum spores can disrupt the intestinal microbiota and metabolome via the lung-gut axis. These findings provide valuable insights into the intestinal damage caused by fungal spores and offer important support for the development of therapeutic strategies for intestinal diseases.

A pH-Responsive Drug-Delivery System Based on Apatinib-Loaded Metal-Organic Frameworks for Ferroptosis-Targeted Synergistic Anti-Tumor Therapy.

Purpose: The efficacy of systemic therapy for hepatocellular carcinoma (HCC) is limited mainly by the complex tumor defense mechanism and the severe toxic side-effects of drugs. The efficacy of apatinib (Apa), a key liver cancer treatment, is unsatisfactory due to inadequate targeting and is accompanied by notable side-effects. Leveraging nanomaterials to enhance its targeting represents a crucial strategy for improving the effectiveness of liver cancer therapy. Patients and Methods: A metal polyphenol network-coated apatinib-loaded metal-organic framework-based multifunctional drug-delivery system (MIL-100@Apa@MPN) was prepared by using metal-organic frameworks (MOFs) as carriers. The nanoparticles (NPs) were subsequently characterized using techniques such as X-ray diffraction (XRD), transmission electron microscopy (TEM), zeta potential measurements, and particle size analysis. In vitro experiments were conducted to observe the drug release kinetics and cytotoxic effects of MIL-100@Apa@MPN on HepG2 cells. The in vivo anti-tumor efficacy of MIL-100@Apa@MPN was evaluated using the H22 tumor-bearing mouse model. Results: The formulated MIL-100@Apa@MPN demonstrates remarkable thermal stability and possesses a uniform structure, with measured drug-loading (DL) and encapsulation efficiency (EE) rates of 28.33% and 85.01%, respectively. In vitro studies demonstrated that HepG2 cells efficiently uptake coumarin-6-loaded NPs, and a significant increase in cumulative drug release was observed under lower pH conditions (pH 5.0), leading to the release of approximately 73.72% of Apa. In HepG2 cells, MIL-100@Apa@MPN exhibited more significant antiproliferative activity compared to free Apa. In vivo, MIL-100@Apa@MPN significantly inhibited tumor growth, attenuated side-effects, and enhanced therapeutic effects in H22 tumor-bearing mice compared to other groups. Conclusion: We have successfully constructed a MOF delivery system with excellent safety, sustained-release capability, pH-targeting, and improved anti-tumor efficacy, highlighting its potential as a therapeutic approach for the treatment of HCC.

Socioeconomic inequalities, genetic susceptibility, and risks of depression and anxiety: A large-observational study.

OBJECTIVES: This study aimed to investigate the interplay between genetic susceptibility and socioeconomic disparities on psychiatric disorders. METHODS: In this study, we utilized data from the UK Biobank to analyze the Generalized Anxiety Disorder (GAD)-7 scale (N = 74,425) and the Patient Health Questionnaire (PHQ)-9 (N = 74,101), along with the Index of Multiple Deprivation (IMD). The polygenic risk score (PRS) was calculated to assess the genetic risk associated with GAD-7/PHQ-9 scores, and the individuals were classified into low, medium, and high genetic risk groups according to tertiles of PRSs related to the GAD-7/PHQ-9. Linear regression models were used to explore the relationships between GAD-7/PHQ-9 scores and IMD scores in patients with different genetic susceptibilities. RESULTS: Disadvantaged socioeconomic status was associated with the risk of anxiety and depression across all strata of genetic risk, and stronger associations were shown for individuals with greater genetic susceptibility. From low to high genetic risk, the risk of psychiatric disorders increased for the GAD-7 (ß = 0.002 to 0.032) and PHQ-9 (ß = 0.003 to 0.045) scores. In addition, strong associations of high genetic risk with anxiety (ß = 0.875) and depression (ß = 1.152) were detected in the IMD quartile 4 group compared with the least deprivation quartile group. Furthermore, income and employment were estimated to contribute strongly to anxiety (ßemployment = 7.331, ßincome = 4.492) and depression (ßemployment = 9.951, ßincome = 6.453) in the high genetic risk group. CONCLUSION: The results suggest that we should pay more attention to psychiatric disorders with high genetic susceptibility and try to improve their socioeconomic status to prevent the development of psychiatric disorders.

Correlative Effects of Carbon Support Structures and Surface Properties on ORR Catalytic Activities of Loaded Catalysts.

As a complex three-phase heterogeneous catalyst, the oxygen reduction reaction (ORR) catalyst activity is determined by the interfacial and surface structures and chemical state of the catalyst support. As a typical biomass carbon-based support, rice husk-based porous carbon (RHPC) has natural unique hierarchical porous structures, which easily regulate the microstructure and surface properties. This study explored the correlative effects of RHPC structure and surface properties on ORR catalytic activity through the typical modification methods, namely, alkali etching, high temperature, oxidation, and ball milling. The various factors for the joint effects are defined as the specific surface area, oxygen-containing functional groups, graphite edge defects, resistivity, and contact angle. The analysis of such joint influences is difficult to quantitatively evaluate due to the large number of experimental factors and small sample sizes. Partial least-squares (PLS) can better deal with such problems. Therefore, a PLS regression model was established to evaluate the relative weight of each factor on the catalytic activity for the RHPC-based support catalysts. The results reveal that the regression coefficients of four factors yield similar magnitude for the effect of the half-wave potential (E1/2). However, graphite edge defects had a more significant impact on the limiting diffusion current density (J) and electron transfer number (n). Furthermore, an optimal support named BM-RHPC-3 was prepared with more defects and oxygen-containing functional groups, which prepared Fe-NS/BM-RHPC-3 presenting the best ORR catalytic activity (E1/2 = 0.880 V, J of 5.15 mA cm-2), superior to Pt/C (E1/2 = 0.844 V, J of 4.99 mA cm-2). The statistical regression model is validated with a relative error of less than 5% between predicted and true values for analyzing RHPC-based ORR catalysts' catalytic performance. It shows the feasibility of experiment-informed learning for data-driven material discovery and design.