The mechanism of Xihuang pills' intervention in the tumour immune microenvironment for the treatment of liver cancer based on the STAT3-PDL1 pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Xihuang pills, a time-honored Chinese compound formula with a history spanning thousands of years, have demonstrated remarkable efficacy in treating various cancers, such as breast cancer, colon cancer, and liver cancer. Clinical applications over the years have established their effectiveness. Several scholars conducting experimental studies have elucidated the potent tumor-suppressing effects of Xihuang pills. While the inhibition of tumor vascular development and prevention of tumor cell invasion and metastasis have been well-explored mechanisms, the impact on the tumor immune microenvironment has received less attention. This study focuses on investigating the immune microenvironment adjustments induced by Xihuang pills in hepatocellular carcinoma. AIM OF THE STUDY: Tumour cells will find an escape phenomenon during tumour immunotherapy, which will affect immunotherapy results. We will research the regulation of the tumour immune microenvironment, to provide a more complete and precise basis for the elucidation of the mechanism of Xihuang pills in treating cancers. It provides new research ideas for people to treat liver cancer. MATERIALS AND METHODS: Through in vivo and in vitro assessments confirming the intervention effects of Xihuang pills, we observed alterations in T cell typing, macrophage polarization, and tumor-associated cytokine levels. The primary active ingredients of Xihuang pills were identified using UPLC-MS/GC-MS, and relevant pathways in the treatment of hepatocellular carcinoma were predicted through network pharmacology. Combining the network pharmacology approach, we predicted the pathways relevant to Xihuang pills in treating hepatocellular carcinoma and experimentally validated the involvement of PD-1/PD-L1, a key immunity-related axis. RESULTS: Xihuang Pill has a regulatory effect on the tumor immune microenvironment. CONCLUSIONS: The results indicated that Xihuang pills could impact splenic lymphocyte phenotyping, macrophage polarization, and IL-6 cytokine expression in liver cancer mice. The mechanism of action was associated with the regulation of the PD-1/PD-L1 signaling pathway by the STAT3 protein.

Differentiation and Regulation of Bovine Th2 Cells In Vitro.

Bovine Th2 cells have usually been characterized by IL4 mRNA expression, but it is unclear whether their IL4 protein expression corresponds to transcription. We found that grass-fed healthy beef cattle, which had been regularly exposed to parasites on the grass, had a low frequency of IL4+ Th2 cells during flow cytometry, similar to animals grown in feedlots. To assess the distribution of IL4+ CD4+ T cells across tissues, samples from the blood, spleen, abomasal (draining), and inguinal lymph nodes were examined, which revealed limited IL4 protein detection in the CD4+ T cells across the examined tissues. To determine if bovine CD4+ T cells may develop into Th2 cells, naïve cells were stimulated with anti-bovine CD3 under a Th2 differentiation kit in vitro. The cells produced primarily IFNγ proteins, with only a small fraction (<10%) co-expressing IL4 proteins. Quantitative PCR confirmed elevated IFNγ transcription but no significant change in IL4 transcription. Surprisingly, GATA3, the master regulator of IL4, was highest in naïve CD4+ T cells but was considerably reduced following differentiation. To determine if the differentiated cells were true Th2 cells, an unbiased proteomic assay was carried out. The assay identified 4212 proteins, 422 of which were differently expressed compared to those in naïve cells. Based on these differential proteins, Th2-related upstream components were predicted, including CD3, CD28, IL4, and IL33, demonstrating typical Th2 differentiation. To boost IL4 expression, T cell receptor (TCR) stimulation strength was reduced by lowering anti-CD3 concentrations. Consequently, weak TCR stimulation essentially abolished Th2 expansion and survival. In addition, extra recombinant bovine IL4 (rbIL4) was added during Th2 differentiation, but, despite enhanced expansion, the IL4 level remained unaltered. These findings suggest that, while bovine CD4+ T cells can respond to Th2 differentiation stimuli, the bovine IL4 pathway is not regulated in the same way as in mice and humans. Furthermore, Ostertagia ostertagi (OO) extract, a gastrointestinal nematode in cattle, inhibited signaling via CD3, CD28, IL4, and TLRs/MYD88, indicating that external pathogens can influence bovine Th2 differentiation. In conclusion, though bovine CD4+ T cells can respond to IL4-driven differentiation, IL4 expression is not a defining feature of differentiated bovine Th2 cells.

Unveiling the intricate connection between per- and polyfluoroalkyl substances and prostate hyperplasia.

The presence of perfluoroalkyl and polyfluoroalkyl substances (PFAS) in various everyday products has raised concerns about their potential impact on prostate health. This study aimed to investigate the effects of different types of PFAS on prostate health, including PFDeA, PFOA, PFOS, PFHxS, and PFNA. To assess the relationship between PFAS exposure and prostate injury, machine learning algorithms were employed to analyze prostate-specific antigen (PSA) metrics. The analysis revealed a linear and positive dose-dependent association between PFOS and the ratio of free PSA to total PSA (f/tPSA). Non-linear dose-response relationships were observed between the other four types of PFAS and the f/tPSA ratio. Additionally, the analysis showed a positive association between the mixture of PFAS and prostate hyperplasia, with PFNA having the highest impact followed by PFOS. These findings suggest that elevated serum levels of PFDeA, PFOA, PFOS, and PFNA are linked to prostate hyperplasia. Therefore, this study utilized advanced machine learning techniques to uncover potential hazardous effects of PFAS exposure on prostate health, specifically the positive association between PFAS and prostate hyperplasia.

Impact of active pharmaceutical ingredient variables and oleaginous base on the in vitro drug release from ophthalmic ointments: An investigation using dexamethasone as a model drug.

The present study systematically investigates the impact of active pharmaceutical ingredient (API) variables and oleaginous base characteristics on the in vitro release (IVR) performance of ophthalmic ointments, utilizing dexamethasone as a model drug. The interplay between selected attributes (i.e., particle size distribution, crystallinity, and polymorphic form for API, and rheological factors for compendial-grade white petrolatum) and IVR performance was investigated. APIs from different vendors exhibited variations in crystallinity and polymorphism. Ointments containing amorphous dexamethasone presented higher release amounts/rates compared to crystalline counterparts, emphasizing the role of physical state in release kinetics. Variations in particle size of this lipophilic API (5.4 - 21.2 µm) did not appear to impact IVR performance significantly. In contrast, white petrolatum's rheological attributes, which varied substantially within USP-grade petrolatum, were found to critically affect the drug release rate and extent of the ointment. The study's comprehensive analysis establishes a coherent connection between the quality attributes of both API and petrolatum and IVR, delineating their intricate interdependent effects on ophthalmic ointment performance. These findings provide reference to formulation design, quality control, and regulatory considerations within the pharmaceutical industry, fostering a robust foundational understanding of commonly overlooked quality attributes in ophthalmic ointments.

Hydrogen gas inhalation ameliorates LPS-induced BPD by inhibiting inflammation via regulating the TLR4-NFκB-IL6/NLRP3 signaling pathway in the placenta.

INTRODUCTION: Hydrogen (H2) is regarded as a novel therapeutic agent against several diseases owing to its inherent biosafety. Bronchopulmonary dysplasia (BPD) has been widely considered among adverse pregnancy outcomes, without effective treatment. Placenta plays a role in defense, synthesis, and immunity, which provides a new perspective for the treatment of BPD. This study aimed to investigate if H2 reduced the placental inflammation to protect the neonatal rat against BPD damage and potential mechanisms. METHODS: We induced neonatal BPD model by injecting lipopolysaccharide (LPS, 1 µg) into the amniotic fluid at embryonic day 16.5 as LPS group. LPS + H2 group inhaled 42% H2 gas (4 h/day) until the samples were collected. We primarily analyzed the neonatal outcomes and then compared inflammatory levels from the control group (CON), LPS group and LPS + H2 group. HE staining was performed to evaluate inflammatory levels. RNA sequencing revealed dominant differentially expressed genes. Bioinformatics analysis (GO and KEGG) of RNA-seq was applied to mine the signaling pathways involved in protective effect of H2 on the development of LPS-induced BPD. We further used qRT-PCR, Western blot and ELISA methods to verify differential expression of mRNA and proteins. Moreover, we verified the correlation between the upstream signaling pathways and the downstream targets in LPS-induced BPD model. RESULTS: Upon administration of H2, the inflammatory infiltration degree of the LPS-induced placenta was reduced, and infiltration significantly narrowed. Hydrogen normalized LPS-induced perturbed lung development and reduced the death ratio of the fetus and neonate. RNA-seq results revealed the importance of inflammatory response biological processes and Toll-like receptor signaling pathway in protective effect of hydrogen on BPD. The over-activated upstream signals [Toll-like receptor 4 (TLR4), nuclear factor kappa-B p65 (NF-κB p65), Caspase1 (Casp1) and NLR family pyrin domain containing 3 (NLRP3) inflammasome] in LPS placenta were attenuated by H2 inhalation. The downstream targets, inflammatory cytokines/chemokines [interleukin (IL)-6, IL-18, IL-1ß, C-C motif chemokine ligand 2 (CCL2) and C-X-C motif chemokine ligand 1 (CXCL1)], were decreased both in mRNA and protein levels by H2 inhalation in LPS-induced placentas to rescue them from BPD. Correlation analysis displayed a positive association of TLR4-mediated signaling pathway both proinflammatory cytokines and chemokines in placenta. CONCLUSION: H2 inhalation ameliorates LPS-induced BPD by inhibiting excessive inflammatory cytokines and chemokines via the TLR4-NFκB-IL6/NLRP3 signaling pathway in placenta and may be a potential therapeutic strategy for BPD.

Risk prediction model based on machine learning for predicting miscarriage among pregnant patients with immune abnormalities.

Introduction: It is known that patients with immune-abnormal co-pregnancies are at a higher risk of adverse pregnancy outcomes. Traditional pregnancy risk management systems have poor prediction abilities for adverse pregnancy outcomes in such patients, with many limitations in clinical application. In this study, we will use machine learning to screen high-risk factors for miscarriage and develop a miscarriage risk prediction model for patients with immune-abnormal pregnancies. This model aims to provide an adjunctive tool for the clinical identification of patients at high risk of miscarriage and to allow for active intervention to reduce adverse pregnancy outcomes. Methods: Patients with immune-abnormal pregnancies attending Sichuan Provincial People's Hospital were collected through electronic medical records (EMR). The data were divided into a training set and a test set in an 8:2 ratio. Comparisons were made to evaluate the performance of traditional pregnancy risk assessment tools for clinical applications. This analysis involved assessing the cost-benefit of clinical treatment, evaluating the model's performance, and determining its economic value. Data sampling methods, feature screening, and machine learning algorithms were utilized to develop predictive models. These models were internally validated using 10-fold cross-validation for the training set and externally validated using bootstrapping for the test set. Model performance was assessed by the area under the characteristic curve (AUC). Based on the best parameters, a predictive model for miscarriage risk was developed, and the SHapley additive expansion (SHAP) method was used to assess the best model feature contribution. Results: A total of 565 patients were included in this study on machine learning-based models for predicting the risk of miscarriage in patients with immune-abnormal pregnancies. Twenty-eight risk warning models were developed, and the predictive model constructed using XGBoost demonstrated the best performance with an AUC of 0.9209. The SHAP analysis of the best model highlighted the total number of medications, as well as the use of aspirin and low molecular weight heparin, as significant influencing factors. The implementation of the pregnancy risk scoring rules resulted in accuracy, precision, and F1 scores of 0.3009, 0.1663, and 0.2852, respectively. The economic evaluation showed a saving of ¥7,485,865.7 due to the model. Conclusion: The predictive model developed in this study performed well in estimating the risk of miscarriage in patients with immune-abnormal pregnancies. The findings of the model interpretation identified the total number of medications and the use of other medications during pregnancy as key factors in the early warning model for miscarriage risk. This provides an important basis for early risk assessment and intervention in immune-abnormal pregnancies. The predictive model developed in this study demonstrated better risk prediction performance than the Pregnancy Risk Management System (PRMS) and also demonstrated economic value. Therefore, miscarriage risk prediction in patients with immune-abnormal pregnancies may be the most cost-effective management method.

Risk of Enzyme- and Transporter-Mediated Drug Interactions With Drugs Approved by the US Food and Drug Administration in 2022: A Detailed Analysis of In Vitro and Clinical Data Available in New Drug Application Reviews.

PURPOSE: This analysis aimed to provide mechanistic understanding and clinical relevance of pharmacokinetic drug-drug interactions (DDIs) associated with drugs approved by the Food and Drug Administration in 2022. METHODS: Drug metabolism, transport, and DDI data available in New Drug Applications (NDAs) of small molecular drugs approved (n = 22) was analyzed. The mechanism and clinical magnitude of these interactions were characterized based on in vitro, in silico, and clinical data. FINDINGS: As victims, 10 drugs were identified as clinical substrates. Of these, 7 drugs were substrates of CYP3A, including the sensitive substrates daridorexant and mitapivat. As perpetrators, 3 drugs (adagrasib, lenacapavir, and vonoprazan) were clinical inhibitors of CYP enzymes, and 2 drugs (mavacamten and mitapivat) showed induction. Regarding transporter data, abrocitinib and deucravacitinib were found to be substrates of OAT3 and P-gp/BCRP, respectively, and 4 drugs (abrocitinib, adagrasib, lenacapavir, and oteseconazole) were found to inhibit P-gp and/or BCRP. As expected, all clinical DDIs with AUC changes ≥ 2-fold triggered label recommendations. Over half of DDIs with an AUC change < 2 also had label recommendations, pertaining most often to the concomitant use of drugs with a narrow therapeutic index. Overall, CYP3A played a major role in the drug disposition of the drugs approved in 2022, mediating all strong drug interactions. IMPLICATIONS: The mechanistic information obtained from studying these new therapeutics with marker compounds can be extrapolated to common concomitant medications sharing the same pharmacokinetic properties, enhancing the safe and effective administration of these products in situations of polytherapy.

Effects of coastal saline-alkali soil on rhizosphere microbial community and crop yield of cotton at different growth stages.

Soil salinization is a global constraint that significantly hampers agricultural production, with cotton being an important cash crop that is not immune to its detrimental effects. The rhizosphere microbiome plays a critical role in plant health and growth, which assists plants in resisting adverse abiotic stresses including soil salinization. This study explores the impact of soil salinization on cotton, including its effects on growth, yield, soil physical and chemical properties, as well as soil bacterial community structures. The results of ß-diversity analysis showed that there were significant differences in bacterial communities in saline-alkali soil at different growth stages of cotton. Besides, the more severity of soil salinization, the more abundance of Proteobacteria, Bacteroidota enriched in rhizosphere bacterial composition where the abundance of Acidobacteriota exhibited the opposite trend. And the co-occurrence network analysis showed that soil salinization affected the complexity of soil bacterial co-occurrence network. These findings provide valuable insights into the mechanisms by which soil salinization affects soil microorganisms in cotton rhizosphere soil and offer guidance for improving soil salinization using beneficial microorganisms.

A contrastive learning approach to integrate spatial transcriptomics and histological images.

The rapid growth of spatially resolved transcriptomics technology provides new perspectives on spatial tissue architecture. Deep learning has been widely applied to derive useful representations for spatial transcriptome analysis. However, effectively integrating spatial multi-modal data remains challenging. Here, we present ConGcR, a contrastive learning-based model for integrating gene expression, spatial location, and tissue morphology for data representation and spatial tissue architecture identification. Graph convolution and ResNet were used as encoders for gene expression with spatial location and histological image inputs, respectively. We further enhanced ConGcR with a graph auto-encoder as ConGaR to better model spatially embedded representations. We validated our models using 16 human brains, four chicken hearts, eight breast tumors, and 30 human lung spatial transcriptomics samples. The results showed that our models generated more effective embeddings for obtaining tissue architectures closer to the ground truth than other methods. Overall, our models not only can improve tissue architecture identification's accuracy but also may provide valuable insights and effective data representation for other tasks in spatial transcriptome analyses.

Demand analysis of health care services for community-dwelling breast cancer survivors based on the Kano model: A cross-sectional study.

Objectives: Providing satisfactory healthcare services for breast cancer survivors can effectively reduce their burden and the pressure on medical resources. The aim of this study was to explore health care service demands for community-dwelling breast cancer survivors using the Kano model. Methods: A cross-sectional survey was conducted from January to March 2023 among breast cancer survivors discharged from a tertiary cancer hospital. Participants were asked to fill out a self-designed questionnaire involving the Kano model, which helped to categorize and prioritize the attributes of healthcare services. The questionnaire included 30 health care services. Additionally, their social demographic characteristics were collected during the survey. Results: A total of 296 valid questionnaires were collected, and demand attributes of the 30 health care services were evaluated. The findings revealed that one of 30 services was classified as "must-be attributes" (body image management), 13 as "one-dimensional attributes" (focused on medical security support, health management, and health counseling), 3 as "attractive attributes" (focused on communication needs and telehealth services), and 11 as "indifferent attributes" (mainly in the area of psycho-social services). Conclusions: Breast cancer survivors in the community have different levels of need for various health care services. It's crucial for healthcare providers to identify these needs and devise effective strategies to deliver the appropriate services. Services with must-be and one-dimensional attributes should be given priority, and efforts should be made to provide services with attractive attributes, hence improving the quality of life of breast cancer survivors.

Priority establishment of soil bacteria in rhizosphere limited the spread of tetracycline resistance genes from pig manure to soil-plant systems based on synthetic communities approach.

The spread of antibiotic resistance genes (ARGs) in agroecosystems through the application of animal manure is a global threat to human and environmental health. However, the adaptability and colonization ability of animal manure-derived bacteria determine the spread pathways of ARG in agroecosystems, which have rarely been studied. Here, we performed an invasion experiment by creating a synthetic communities (SynCom) with ten isolates from pig manure and followed its assembly during gnotobiotic cultivation of a soil-Arabidopsis thaliana (A. thaliana) system. We found that Firmicutes in the SynCom were efficiently filtered out in the rhizosphere, thereby limiting the entry of tetracycline resistance genes (TRGs) into the plant. However, Proteobacteria and Actinobacteria in the SynCom were able to establish in all compartments of the soil-plant system thereby spreading TRGs from manure to soil and plant. The presence of native soil bacteria prevented the establishment of manure-borne bacteria and effectively reduced the spread of TRGs. Achromobacter mucicolens and Pantoea septica were the main vectors for the entry of tetA into plants. Furthermore, doxycycline stress promoted the horizontal gene transfer (HGT) of the conjugative resistance plasmid RP4 within the SynCom in A. thaliana by upregulating the expression of HGT-related mRNAs. Therefore, this study provides evidence for the dissemination pathways of ARGs in agricultural systems through the invasion of manure-derived bacteria and HGT by conjugative resistance plasmids and demonstrates that the priority establishment of soil bacteria in the rhizosphere limited the spread of TRGs from pig manure to soil-plant systems.

Incidence of cardiovascular mortality among head and neck cancer patients.

BACKGROUND: While treatment advancements have prolonged the lives of patients with head and neck cancer, the subgroups of these patients at higher risk for cardiovascular disease (CVD) mortality remain unclear. METHODS: We analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with head and neck cancer from 2000 to 2019. We compared their CVD mortality against the general US population using standardized mortality ratios (SMRs). RESULTS: Our analysis included 474,366 patients, identifying that 14% of deaths were due to CVD, with an SMR of 1.19. Notably, patients under the age of 39 had a CVD SMR increase of over 100-fold. Those with distant tumor stages showed the highest CVD SMR of 1.52 (95% CI 1.50-1.54). An upward trend in SMR to 2.53 (95% CI 2.51-2.56) was observed from 2011 to 2019. Within the initial 5-year post-diagnosis, the SMR for CVD was 3.17 (95% CI 3.14-3.20), which exceeded the general population's rates but declined in the 5-20-year range after diagnosis. Patients who did not any therapy had the greatest CVD SMR of 2.26 (95% CI 2.24-2.28). Hypopharyngeal cancer patients exhibited the highest CVD SMR of 1.54 (95% CI 1.52-1.56). CONCLUSIONS: The study highlights that head and neck cancer patients, especially younger individuals and those with advanced disease stages, face substantial CVD mortality risks. The CVD SMR peaks within 5 years following diagnosis. Patients abstaining from treatment bear the highest risk of CVD mortality. Cardioprotective measures should be considered critical for this patient population.

Soil microeukaryotic communities and phosphorus-cycling microorganisms respond to chloropicrin fumigation and azoxystrobin application.

Fumigants and fungicides are effective at controlling soil-borne pathogens but might also adversely affect soil beneficial microbes, such as soil phosphorus (P) solubilizing microbes, further altering nutrient cycling processes. Therefore, this study investigated the effects of the fumigant chloropicrin (CP) and the fungicide azoxystrobin (AZO) on soil microeukaryotes and P-cycling related soil bacteria through a greenhouse experiment. Soil microeukaryotic communities and bacterial communities containing two phosphomonoesterase encoding genes (phoC and phoD) were analysed using high-throughput sequencing methods. Results showed that, when applied at the field recommended application dosage, the fungicide AZO had no significant influence on the community structure of soil microeukaryotes and phoD-containing bacteria. However, in CP-fumigated soils, the soil microeukaryotic community composition changed from fungi-dominated to protist-dominated. CP fumigation significantly decreased the total phoC/phoD gene copy number but increased the relative abundance of some phoC/phoD-containing bacteria (such as Sinorhizobium and Streptomyces), which are significantly positively correlated to available P compositions in soil. The structural equation model (SEM) confirmed that CP fumigation could affect soil available P content directly by altering phoC-/phoD-containing bacteria, or indirectly by affecting phoC/phoD gene abundance and acid/alkaline phosphatases activity in soil. The inconsistent changes in phoC/phoD-containing bacteria, phoC/phoD gene number, and the phosphomonoesterase activities indicated that enzyme secretion may not be the only way for P solubilizing soil microorganisms to regulate P availability after soil fumigation. The outcome of this study can provide theoretical support for the design of soil beneficial microorganism recovery strategies and the regulation of phosphate fertilizer after soil fumigation.

Pharmacokinetics, Pharmacodynamics, Safety, and Tolerability of Oral AL01211 in Healthy Chinese Volunteers.

BACKGROUND AND OBJECTIVE: Aberrant accumulation of glycosphingolipids (GSLs) in the lysosome leads to GSL storage diseases. Glucosylceramide synthase inhibitors (GCSi) have the potential to treat several GSL storage diseases by reducing the synthesis of the disease-causing GSLs. AL01211 is a potent oral GCSi under investigation for Type 1 Gaucher disease and Fabry disease. Here, we evaluate the pharmacokinetics, pharmacodynamics, safety, and tolerability of AL01211 in healthy Chinese volunteers. METHODS: AL01211 was tested in a Phase 1, single-center, randomized, double-blind, placebo-controlled study with single-dose (15 and 60 mg) and multiple-dose (30 mg) arms. RESULTS: Results of AL01211 demonstrated dose-dependent pharmacokinetics, rapid absorption (median time to maximum plasma concentration [tmax] 2.5-4 hours), relatively slow clearance rate (mean apparent total clearance from plasma [CL/F] 88.3-200 L/h) and the mean terminal half-life above 30 hours. Repeated once-daily oral administration of AL01211 for 14 days had an approximately 2-fold accumulation, reaching steady-state levels between 7 and 10 days, and led to a 73% reduction in plasma glucosylceramide (GL1) on Day 14. AL01211 was safe and well tolerated, with no identified serious adverse events. CONCLUSION: AL01211 showed a favorable pharmacokinetic, pharmacodynamics, safety, and tolerability profile in healthy Chinese volunteers. These data support the further clinical development of AL01211 as a therapy for GSL storage diseases. CLINICAL TRIAL REGISTRY: Clinical Trial Registry no. CTR20221202 ( http://www.chinadrugtrials.org.cn ) registered on 6 June 2022 and ChiCTR2200061431 ( http://www.chictr.org.cn ) registered on 24 June 2022.

Predicting bladder cancer survival with high accuracy: insights from MAPK pathway-related genes.

The mitogen-activated protein kinase (MAPK) pathway plays a critical role in tumor development and immunotherapy. Nevertheless, additional research is necessary to comprehend the relationship between the MAPK pathway and the prognosis of bladder cancer (BLCA), as well as its influence on the tumor immune microenvironment. To create prognostic models, we screened ten genes associated with the MAPK pathway using COX and least absolute shrinkage and selection operator (LASSO) regression analysis. These models were validated in the Genomic Data Commons (GEO) cohort and further examined for immune infiltration, somatic mutation, and drug sensitivity characteristics. Finally, the findings were validated using The Human Protein Atlas (HPA) database and through Quantitative Real-time PCR (qRT-PCR). Patients were classified into high-risk and low-risk groups based on the prognosis-related genes of the MAPK pathway. The high-risk group had poorer overall survival than the low-risk group and showed increased immune infiltration compared to the low-risk group. Additionally, the nomograms built using the risk scores and clinical factors exhibited high accuracy in predicting the survival of BLCA patients. The prognostic profiling of MAPK pathway-associated genes represents a potent clinical prediction tool, serving as the foundation for precise clinical treatment of BLCA.

UDP-glycosyltransferase UGT96C10 functions as a novel detoxification factor for conjugating the activated dinitrotoluene sulfonate in switchgrass.

Dinitrotoluene sulfonates (DNTSes) are highly toxic hazards regulated by the Resource Conservation and Recovery Act (RCRA) in the United States. The trinitrotoluene (TNT) red water formed during the TNT purification process consists mainly of DNTSes. Certain plants, including switchgrass, reed and alfalfa, can detoxify low concentrations of DNTS in TNT red water-contaminated soils. However, the precise mechanism by which these plants detoxify DNTS remains unknown. In order to aid in the development of phytoremediation resources with high DNTS removal rates, we identified and characterized 1-hydroxymethyl-2,4-dinitrobenzene sulfonic acid (HMDNBS) and its glycosylated product HMDNBS O-glucoside as the degradation products of 2,4-DNT-3-SO3Na, the major isoform of DNTS in TNT red water-contaminated soils, in switchgrass via LC-MS/MS- and NMR-based metabolite analyses. Transcriptomic analysis revealed that 15 UDP-glycosyltransferase genes were dramatically upregulated in switchgrass plants following 2,4-DNT-3-SO3Na treatment. We expressed, purified and assayed the activity of recombinant UGT proteins in vitro and identified PvUGT96C10 as the enzyme responsible for the glycosylation of HMDNBS in switchgrass. Overexpression of PvUGT96C10 in switchgrass significantly alleviated 2,4-DNT-3-SO3Na-induced plant growth inhibition. Notably, PvUGT96C10-overexpressing transgenic switchgrass plants removed 83.1% of 2,4-DNT-3-SO3Na in liquid medium after 28 days, representing a 3.2-fold higher removal rate than that of control plants. This work clarifies the DNTS detoxification mechanism in plants for the first time, suggesting that PvUGT96C10 is crucial for DNTS degradation. Our results indicate that PvUGT96C10-overexpressing plants may hold great potential for the phytoremediation of TNT red water-contaminated soils.

The impact of square dancing on psychological well-being and life satisfaction among aging women.

As the most popular sport among middle-aged and elderly women in China, square dancing has both physical and psychological benefits for menopausal women. Previous studies have shown that square dance exercises can promote the physical health of older women, but there is a lack of research on the influence of middle-aged and elderly women on mental health and mediating variables. Therefore, this study starts with one of the important indicators of mental health-positive affects, aiming to explore the impact of square dance on the positive emotions of elderly women and further explore the mediating mechanisms involved. We send out The Physical Activity Rating Scale, the Positive and Negative Affect Scale, the Connor-Davidson Resilience Scale, and the Satisfaction With Life Scale to a total of 2311 middle-aged and elderly women. SPSS 23 software and PROCESS were used to perform regression analysis and establish mediation models. Modeling results show square dance exercises could positively predict positive affect through the chain mediating effect of psychological resilience and life satisfaction. The results of this study are of great significance for promoting the extensive participation of middle-aged and elderly women in sports and protecting their mental health.