Objective To comprehensively investigate the levels of exposure and distribution characteristics of trihalomethanes (THMs) in drinking water in Guangzhou City, and evaluate the health risks of different groups of children, adolescents and adults, and to provide data and evidence for protecting human health and promoting risk control of drinking water. Methods According to the technical requirements of the ^"Standards for Drinking Water Quality Testing Methods^" (GB/T 5750-2023), the concentration of THMs, including trichloromethane (TCM), bromodichloromethane (BDCM), dibromochloromethane (DBCM), and tribromomethane (TBM) in drinking water in Guangzhou City from 2023-2024 were detected. The health risk model recommended by USEPA was used for risk assessment．Results TCM, BDCM and DBCM were detected in the factory water and terminal water, with TCM contributing the most. There was a statistically significant difference (P<0.05) between the wet and dry seasons, and the concentration of TCM in the wet season was higher than that in the dry season. Among the multiple exposure factors, the amount of exposure through drinking water intake was much greater than that through skin absorption. The carcinogenic risk index of THMs for children, adolescents, and adults was 22.0×10^-6, 12.2×10^-6, and 11.4×10^-6, respectively, while the non-carcinogenic risk was less than 1. Conclusion The exposure risks of THMs in children, adolescents, and adults is within an acceptable range, but monitoring needs to be strengthened, with a particular focus on children.

Hepatocellular carcinoma (HCC) develops within a profoundly immunosuppressive tumor immune microenvironment (TIME), which limits the efficacy of immunotherapy. Polarization of tumor-associated macrophages (TAMs) toward a pro-tumorigenic M2 phenotype is a major driver of immune escape. Ferroptosis, an iron-dependent regulated cell death program, intersects with hepatic iron metabolism and immune regulation and thus offers promising points of therapeutic intervention. This review systematically elucidates the mechanistic role of TAM ferroptosis in HCC immune evasion and highlights a “bidirectional regulation” intervention strategy grounded in the Traditional Chinese medicine (TCM) principle of “fortifying healthy qi and eliminating pathogens” (Fuzheng Quxie). This strategy employs “eliminating pathogens” (Quxie) approaches to exploit the metabolic vulnerability of M2-like TAMs and precisely induce their ferroptosis. Moreover, it utilizes “fortifying healthy qi” (Fuzheng) approaches to protect M1-like TAMs and CD8⁺ T cells from oxidative damage. This parallel “induction-protection” paradigm demonstrates the unique advantages of TCM in systemically remodeling TIME through multitarget synergistic actions. Accordingly, precision regulation of TAM ferroptosis based on the Fuzheng Quxie theory represents a promising integrative Chinese-Western medicine strategy for overcoming current bottlenecks in HCC immunotherapy, although its clinical translational potential warrants further validation.

Objective To construct a dynamic prediction model for JC polyomavirus (JCV) reactivation after kidney transplantation. Methods A retrospective analysis was conducted on the clinical data of 128 recipients who met the inclusion criteria and received kidney transplantation in Nanfang Hospital, Southern Medical University, from June 2021 to December 2024. Dynamic Cox regression and dynamic restricted mean survival time (RMST) regression based on the landmark method were adopted to establish the dynamic prediction models, and Monte Carlo cross-validation was used to evaluate model performance. Results The dynamic models could predict the incidence and onset time of JCV reactivation within the subsequent 3 months according to covariates at each landmark time point from the 1st to the 6th month after transplantation. Remuzzi score, body mass index and warm ischemia time were independent risk factors for JCV reactivation, while a history of urinary BK polyomavirus reactivation served as a protective factor. The median values of the area under the curve, C-index and Brier score of the dynamic Cox model were 0.873, 0.851 and 0.065 respectively, and the C-index of the dynamic RMST model was 0.829, all of which were superior to those of the static model. Conclusions The landmark-based dynamic models exhibit excellent predictive performance, which may integrate baseline data and post-transplant follow-up information to realize dynamic assessment of the risk and time window of JCV reactivation, thereby providing evidence for optimizing post-operative monitoring and individualized intervention strategies.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Bacterial biofilms can make traditional antibiotics impenetrable and even promote the development of antibiotic-resistant strains. Therefore, non-antibiotic strategies to effectively penetrate and eradicate the formed biofilms are urgently needed. Here, we demonstrate the development of self-propelled biohybrid microrobots that can enhance the degradation and penetration effects for Pseudomonas aeruginosa biofilms in minimally invasive strategy. The biohybrid microrobots (CR@Alg) are constructed by surface modification of Chlamydomonas reinhardtii (CR) microalgae with alginate lyase (Alg) via biological orthogonal reaction. By degrading the biofilm components, the number of CR@Alg microrobots with fast-moving capability penetrating the biofilm increases by around 2.4-fold compared to that of microalgae. Massive reactive oxygen species are subsequently generated under laser irradiation due to the presence of chlorophyll, inherent photosensitizers of microalgae, thus triggering photodynamic therapy (PDT) to combat bacteria. Our algae-based microrobots with superior biocompatibility eliminate biofilm-infections efficiently and tend to suppress the inflammatory response in vivo, showing huge promise for the active treatment of biofilm-associated infections.

The transcription factor HOXB13 plays crucial roles in cancer development. HOXB13 is abnormally expressed in most cancers, which makes it a valuable therapeutic target for cancer therapy. The level of HOXB13 differs significantly between healthy and cancer tissues, which indicates that the level of HOXB13 is closely related to carcinogenesis. The regulatory network mediated by HOXB13 in cancer proliferation, metastasis, and invasion has been systematically investigated. Moreover, HOXB13 variants play distinct roles in different cancers and populations. By understanding the molecular mechanisms and mutation features of HOXB13, we provide a comprehensive overview of carcinogenesis networks dependent on HOXB13. Finally, we discuss advancements in anticancer therapy targeting HOXB13 and the roles of HOXB13 in drug resistance to molecular-targeted therapies, which serves as a foundation for developing HOXB13-targeted drugs for clinical diagnosis and cancer therapies.
Humans ; Neoplasms/metabolism* ; Homeodomain Proteins/metabolism* ; Carcinogenesis/genetics* ; Mutation ; Gene Expression Regulation, Neoplastic ; Molecular Targeted Therapy ; Drug Resistance, Neoplasm/genetics*

Diabetic kidney disease (DKD) with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression. Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials. In this study, we integrated large-scale plasma proteomics, genetic-driven causal inference, and experimental validation to identify prioritized targets for DKD using the UK Biobank (UKB) and FinnGen cohorts. Among 2844 diabetic patients (528 with DKD), we identified 37 targets significantly associated with incident DKD, supported by both observational and causal evidence. Of these, 22% (8/37) of the potential targets are currently under investigation for DKD or other diseases. Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4 (IGFBP4), family with sequence similarity 3 member C (FAM3C), and prostaglandin D2 synthase (PTGDS)-were associated with a 4.35, 3.51, and 3.57-fold increased likelihood of developing DKD, respectively. In addition, population-level protein-altering variants (PAVs) analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD, through the classic NLR family pyrin domain containing 3 (NLRP3)-caspase-1-gasdermin D (GSDMD) apoptotic axis. Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.

OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients. METHODS: This secondary analysis of data from a randomized controlled trial involved 1,720 elderly participants in five tertiary hospitals in Beijing, China. Participants aged 60-90 years undergoing major non-cardiac surgery under general anesthesia. The primary outcome metric of the study was the occurrence of PCCs, according to the European Society of Cardiology and the European Society of Anaesthesiology diagnostic criteria. The analysis metrics contained 67 candidate variables, including baseline characteristics, laboratory tests, and scale assessments. RESULTS: Our feature selection process identified key variables that significantly impact patient outcomes, including the duration of ICU stay, surgery, and anesthesia; APACHE-II score; intraoperative average heart rate and blood loss; cumulative opioid use during surgery; patient age; VAS-Move-Median score on the 1st to 3rd day; Charlson comorbidity score; volumes of intraoperative plasma, crystalloid, and colloid fluids; cumulative red blood cell transfusion during surgery; and endotracheal intubation duration. Notably, our Random Forest model demonstrated exceptional performance with an accuracy of 0.9872. CONCLUSION We have developed and validated an algorithm for predicting PCCs in elderly patients by identifying key risk factors.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; Machine Learning ; Postoperative Complications/etiology* ; Risk Factors ; Randomized Controlled Trials as Topic ; Secondary Data Analysis

Soil cadmium pollution can adversely affect the cultivation of the ornamental plant, Coleus scutellarioides. Upon cadmium contamination of the soil, the growth of C. scutellarioides is impeded, and it may even succumb to the toxic accumulation of cadmium. In this study, we investigated the effects of arbuscular mycorrhizal fungi (AMF) on the adaptation of C. scutellarioides to cadmium stress, by measuring the physiological metabolism and the degree of root damage of C. scutellarioides, with Aspergillus oryzae as the test fungi. The results indicated that cadmium stress increased the activity of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), and the content of malondialdehyde (MDA) and proline (Pro) within the cells of C. scutellarioides, but inhibited mycorrhizal infestation rate, root vigour and growth rate to a great degree. With the same cadmium concentration, the inoculation of AMF significantly improved the physiological indexes of C. scutellarioides. The maximum decrease of MDA content was 42.16%, and the content of secondary metabolites rosemarinic acid and anthocyanosides could be increased by up to 27.43% and 25.72%, respectively. Meanwhile, the increase of root vigour was as high as 35.35%, and the DNA damage of the root system was obviously repaired. In conclusion, the inoculation of AMF can promote the accumulation of secondary metabolites, alleviate root damage, and enhance the tolerance to cadmium stress in C. scutellarioides.
Cadmium/toxicity* ; Mycorrhizae/physiology* ; Plant Roots/drug effects* ; Soil Pollutants/toxicity* ; Stress, Physiological ; Superoxide Dismutase/metabolism*

ObjectiveTo investigate the mechanism of Huangqi Gegentang （HGT） in the treatment of type 2 diabetes mellitus （T2DM） through the application of proteomic techniques. MethodsThe rat model of T2DM was established by streptozotocin combined with a high-fat， high-sugar diet. Thirty-two male SD rats were randomized into four groups： blank， model， HGT （8.10 g·kg^-1·d^-1）， and positive control （metformin hydrochloride， 76.5 mg·kg^-1·d^-1）. After 6 weeks of drug intervention， the fasting blood glucose level was measured， and an oral glucose tolerance test （OGTT） was performed. The area under the curve （AUC） was calculated. Enzyme-linked immunosorbent assay was performed to assess the level of glycated hemoglobin （GHbA1c） in the serum. The limulus amebocyte lysate assay was employed to measure the serum level of lipopolysaccharide （LPS）. Pathological changes in the colon were observed by hematoxylin-eosin staining. The mRNA levels of pro-inflammatory cytokines including tumor necrosis factor （TNF）-α， interleukin （IL）-6， and IL-1β in the colon tissue were quantified via Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. Additionally， the protein and mRNA levels of zonula occludens-1 （ZO-1）， Occludin， and Claudin-1 in the colon tissue were assessed by Western blot and Real-time PCR， respectively. Label-free quantitative proteomics was employed to identify the differentially expressed proteins between the colon tissue samples from the blank， model， and HGT groups. Key proteins identified were subsequently validated by Western blot and Real-time PCR. Finally， bioinformatics analysis was conducted on the differentially expressed proteins. ResultsCompared with the blank group， the model group exhibited increased fasting blood glucose， AUC， and GHbA1c levels （P<0.01）， damaged colonic mucosal epithelial structure and inflammatory cell infiltration， up-regulated mRNA levels of TNF-α， IL-6， and IL-1β in the colon and an increase in serum LPS content （P<0.05， P<0.01）， and down-regulated protein and mRNA levels of ZO-1， Occludin， and Claudin-1 in the colon （P<0.01）. Compared with the model group， the HGT group showed reductions in fasting blood glucose， AUC， and GHbA1c （P<0.01）， alleviated damage to the colonic mucosal epithelium， down-regulated mRNA levels of TNF-α， IL-6， and IL-1β in the colon， a reduction in serum LPS content （P<0.05， P<0.01）， and up-regulated protein and mRNA levels of ZO-1， Occludin， and Claudin-1 in the colon （P<0.05， P<0.01）. Proteomics analysis identified 70 differentially expressed proteins that exhibited a downward trend in the model group relative to the blank group and an upward trend in the HGT group relative to the model group. These findings were corroborated by Western blot and Real-time PCR， which confirmed that the protein and mRNA levels of mucin 2 （Muc2） and transforming growth factor （TGF）-beta receptor 1 （Tgfbr1） in the colon tissue were consistent with the proteomic data. Bioinformatics analysis showed that these 70 differentially expressed proteins identified were significantly enriched in multiple signaling pathways， among which the TGF-β and advanced glycation endproduct （AGE）/receptor for advanced glycation endproduct （RAGE） signaling pathways were closely associated with damage to the intestinal mucosal barrier. This suggests that HGT may ameliorate intestinal mucosal barrier damage by regulating these pathways. ConclusionHGT potentially exerts anti-T2DM effects by influencing AGE/RAGE and TGF-β signaling pathways， thereby contributing to the restoration of the intestinal mucosal barrier.