ObjectiveTo investigate the mechanisms by which Mahuang Lianqiao Chixiaodoutang （MLC） improves obesity-type polycystic ovary syndrome （PCOS） through the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway. MethodsThirty-six female Sprague-Dawley （SD） rats were randomly divided into a blank control group （Con） and an obesity-type PCOS model preparation group. The model was induced by gavage with letrozole （1 mg·kg^-1） combined with a high-fat diet （HFD）. After model establishment， the obesity-type PCOS model preparation group was further divided into the model group （Mod， normal saline）， metformin group （Met， 0.3 g·kg^-1）， low-dose MLC group （MLC-L， 4.3 g·kg^-1）， medium-dose MLC group （MLC-M， 8.6 g·kg^-1）， and high-dose MLC group （MLC-H， 17.2 g·kg^-1）. Active components of MLC and targets of obesity-type PCOS were screened from databases， a protein-protein interaction （PPI） network was constructed， and gene ontology（GO）and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis was performed. The gut microbiota structure was analyzed based on 16S rRNA sequencing and correlated with network pharmacology pathways. Body weight and estrous cycle were dynamically monitored. Ovarian morphology was observed by hematoxylin-eosin （HE） staining. Cell apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was used to detect levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， anti-Müllerian hormone （AMH）， testosterone （T）， and estradiol （E₂）. Western blot was used to detect the protein expression levels of phosphorylated PI3K/PI3K （p-PI3K/PI3K）， phosphorylated Akt/Akt （p-Akt/Akt）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. ResultsNetwork pharmacology screening identified 124 active components of MLC and 408 overlapping targets between the herbal formula and the disease. Core targets such as Akt1 and Bcl-2 were revealed. As indicated by 16S rRNA sequencing， the abundances of Lachnospiraceae， Lachnoclostridium， and Dorea were increased in the MLC groups （P<0.05）， while the abundance of Veillonella was decreased （P<0.05）. KEGG correlation analysis integrating network pharmacology and gut microbiota data showed significant enrichment of the PI3K/Akt signaling pathway. Animal experiments showed that， compared with the Mod group， body weight decreased to normal levels in the Met， MLC-M， and MLC-H groups. The estrous cycle became regular. The number of corpora lutea increased and cystic follicles decreased. Serum levels of T， FSH， and LH/FSH were reduced （P<0.05， P<0.01）， while the E₂ level was increased （P<0.01）. Ovarian cell apoptosis was reduced （P<0.01）， and the protein expression levels of p-PI3K/PI3K， p-Akt/Akt， and Bcl-2 in ovarian tissue were significantly increased， whereas Bax protein expression was significantly decreased （P<0.05， P<0.01）. ConclusionMLC can regulate gut microbiota structure， effectively improve ovarian pathology in rats with obesity-type PCOS， and inhibit ovarian granulosa cell apoptosis. The mechanism may be associated with upregulation of the PI3K/Akt signaling pathway.

ObjectiveTo investigate the mechanisms by which Mahuang Lianqiao Chixiaodoutang （MLC） improves obesity-type polycystic ovary syndrome （PCOS） through the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway. MethodsThirty-six female Sprague-Dawley （SD） rats were randomly divided into a blank control group （Con） and an obesity-type PCOS model preparation group. The model was induced by gavage with letrozole （1 mg·kg^-1） combined with a high-fat diet （HFD）. After model establishment， the obesity-type PCOS model preparation group was further divided into the model group （Mod， normal saline）， metformin group （Met， 0.3 g·kg^-1）， low-dose MLC group （MLC-L， 4.3 g·kg^-1）， medium-dose MLC group （MLC-M， 8.6 g·kg^-1）， and high-dose MLC group （MLC-H， 17.2 g·kg^-1）. Active components of MLC and targets of obesity-type PCOS were screened from databases， a protein-protein interaction （PPI） network was constructed， and gene ontology（GO）and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis was performed. The gut microbiota structure was analyzed based on 16S rRNA sequencing and correlated with network pharmacology pathways. Body weight and estrous cycle were dynamically monitored. Ovarian morphology was observed by hematoxylin-eosin （HE） staining. Cell apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was used to detect levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， anti-Müllerian hormone （AMH）， testosterone （T）， and estradiol （E₂）. Western blot was used to detect the protein expression levels of phosphorylated PI3K/PI3K （p-PI3K/PI3K）， phosphorylated Akt/Akt （p-Akt/Akt）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. ResultsNetwork pharmacology screening identified 124 active components of MLC and 408 overlapping targets between the herbal formula and the disease. Core targets such as Akt1 and Bcl-2 were revealed. As indicated by 16S rRNA sequencing， the abundances of Lachnospiraceae， Lachnoclostridium， and Dorea were increased in the MLC groups （P<0.05）， while the abundance of Veillonella was decreased （P<0.05）. KEGG correlation analysis integrating network pharmacology and gut microbiota data showed significant enrichment of the PI3K/Akt signaling pathway. Animal experiments showed that， compared with the Mod group， body weight decreased to normal levels in the Met， MLC-M， and MLC-H groups. The estrous cycle became regular. The number of corpora lutea increased and cystic follicles decreased. Serum levels of T， FSH， and LH/FSH were reduced （P<0.05， P<0.01）， while the E₂ level was increased （P<0.01）. Ovarian cell apoptosis was reduced （P<0.01）， and the protein expression levels of p-PI3K/PI3K， p-Akt/Akt， and Bcl-2 in ovarian tissue were significantly increased， whereas Bax protein expression was significantly decreased （P<0.05， P<0.01）. ConclusionMLC can regulate gut microbiota structure， effectively improve ovarian pathology in rats with obesity-type PCOS， and inhibit ovarian granulosa cell apoptosis. The mechanism may be associated with upregulation of the PI3K/Akt signaling pathway.

Objective To establish a standardized quality criterion for the formula of the Liuwei Runfu oil recipe. Methods The qualitative identification of the components, such as Cannabis sativa, Ligusticum chuanxiong, Angelica sinensis, Coix lacryma-jobi, and Glycyrrhiza uralensis, was conducted by thin layer chromatography （TLC）. The concentration of Senkyunolide A, ligustilide, and linoleic acid was determined by high-performance liquid chromatography （HPLC）. Results The TLC identification results demonstrated excellent differentiation and high selectivity, without any disruption from the negative samples. The reference standard for Senkyunolide A exhibited excellent linearity in the range of 25 to 300 µg （r=0.9999）, with an average recovery rate of 102.3% and a relative standard deviation （RSD） of 2.3%. The ligustilide reference standard exhibited strong linearity between the concentrations of 0.6875 and 8.25 µg （r=0.9993）, with an average recovery rate of 100.1% and a relative standard deviation （RSD） of 2.8%. The linoleic acid reference standard demonstrated strong linear correlation within the range of 2.8125 to 33.75 µg （r=0.9990）, with an average spiking recovery rate of 102.7% and a relative standard deviation （RSD） of 1.7%. Conclusion The established method with strong specificity was simple，accurate，reliable，which coulod provide a reference for the quality control of the Liuwei Runfu oil recipe.

Objective: To analyze the characteristics and key risk factors of abnormal blood disposal throughout the 2024-2025 blood collection and supply process based on nationwide multi-site monitoring data, develop a comprehensive prevention and control strategy across the entire chain, reduce preventable blood waste, and ensure clinical blood safety. Methods: According to the Guidelines for Haemovigilance (T/CSBT 001-2026), we extracted 74 cases of abnormal blood disposal events reported by the China Blood Transfusion Association′s Blood Safety Monitoring System from January 1 2024, to December 31 2025, and conducted descriptive statistical analysis on the distribution of events, types of deviations, root causes, and classifications of disposal manifestations. Results: A total of 664 adverse events related to blood collection and supply were reported over two years, with 74 cases involving discarded abnormal blood units, accounting for 11.1% of the total. Among these, blood component preparation (40.5%) and blood collection (37.8%) remained traditional high-risk stages. The proportion of blood waste occurring during storage, distribution, and transportation increased from 7.7% in 2024 to 34.3% in 2025. Deviations from standard operating procedures (SOP) by personnel were the primary cause, accounting for 74.3% of cases. Discarded blood units were categorized into four types: compromised closed blood bag systems (40 cases), mainly due to inadequate heat sealing, physical damage, or dropped bags; blood out of the cold chain (12 cases), primarily resulting from blood being left at work sites; imbalanced proportion of preservation solution (10 cases), mostly caused by blood collection volumes exceeding the standard capacity of blood bags; and other causes (12 cases). Conclusion: Human operational errors are the core cause of abnormal blood waste. The collection and preparation stages have long been at high-risk, and the risks in the storage and transportation stages have been increasing year by year. We should focus on standardizing personnel management, improving specialized operation norms such as heat sealing, transportation, and storage, establishing a full-process intelligent cold chain monitoring and multi-node visual verification mechanism, and systematically reducing the occurrence rate of abnormal blood waste through a closed-loop quality intervention system, thereby improving the utilization efficiency of voluntary blood donation resources.

Objective To develop and validate a nomogram model that integrates systemic inflammatory markers to predict the likelihood of pelvic lymph node metastasis(PLNM)in prostate cancer patients prior to surgery.Methods This study retrospectively analyzed the clinical data and preoperative inflammatory markers—including neutrophil-to-lymphocyte ratio(NLR),platelet-to-lymphocyte ratio(PLR),systemic immune-inflammation index(SII),and monocyte-to-lymphocyte ratio(MLR)—of patients diagnosed with prostate cancer.Univariate and multi-variate logistic regression analyses were conducted to identify markers that were significantly associated with PLNM.Based on the results of the multivariate analysis,a nomogram was developed and its predictive accuracy was assessed using receiver operating characteristic curves(ROC)and calibration plots.Results Among the 334 enrolled patients with prostate cancer,107 were identified with PLNM.Univariate analysis revealed statistically significant differences in free prostate-specific antigen(fPSA),Gleason score,NLR,PLR,MLR,and SII between the PLNM and non-pelvic lymph node metastasis(NPLNM)groups(P<0.05).Multivariate analysis confirmed that fPSA,Gleason score,and SII were independent predictors of PLNM(P<0.05).A nomogram incorporating these predic-tors exhibited strong discriminative ability,with an area under the ROC curve(AUC)of 0.79(95%CI:0.73～0.84).Calibration analysis further demonstrated good consistency between the predicted and observed probabilities of PLNM.Conclusions This study successfully developed a nomogram model based on systemic inflammatory markers for preoperative prediction of pelvic lymph node metastasis in prostate cancer.Owing to its user-friendly design and high predictive accuracy,this tool may serve as a valuable complementary method to conventional imaging techniques,thereby supporting personalized treatment decision-making.

The purpose of this study was to evaluate the application value of targeted next-generation sequencing(tNGS)for rapid detection of Mycobacterium tuberculosis.From September 2021 to October 2024,1 178 clinical samples from hospitalized pa-tients at the Non-tuberculous Mycobacteria Disease Diagnosis and Treatment Center of Guangzhou Chest Hospital were collected,in-cluding 272 sputum samples,871 broncho alveolar lavage fluid(BALF)samples,and 35 other samples.These samples were analyzed with tNGS and the liquid culture+DNA microarray chip method(referred to as the"culture identification method"),and the detection results between methods were compared.The numbers of Mycobacterium tuberculosis complex(MTBC)samples identified with tNGS and the culture identification method were 172 and 127,respectively,and the numbers of non-tuberculous mycobacteria(NTM)samples detected were 517 and 474,respectively.The detection rate of Mycobacterium was 56.88%with tNGS and was significantly lower(49.49%)with the culture identification method(χ2=13.27,P<0.05).For NTM identification,when sputum was used,the detection rate of tNGS was higher than that of the culture identification method(χ2=24.14,P<0.05).However,when BALF was used,no significant difference in detection rates was observed between tNGS and the culture identification method(χ2=3.97,P=0.06).When different sample types from the same patient were analyzed with tNGS for NTM,BALF was found to be a better choice than sputum(χ2=4.05,P<0.05).However,with the culture identification method,we observed no significant difference between sample types(χ2=2.72,P=0.10).Furthermore,both the MTBC and NTM sequences detected with tNGS were significantly higher in the culture-positive group than the culture-negative group.With increasing sequence numbers,the proportion of cases in the culture-positive group progressively rose,whereas an inverse trend was observed in the culture-negative group.With clinical diagno-sis as the reference standard,the sensitivity,specificity,and Kappa value of tNGS and the culture identification method in identifying mycobacterial diseases were 85.41%,91.32%,0.74 and 74.73%,93.15%,0.63,respectively.Compared with the culture identifica-tion method,tNGS for rapid detection of Mycobacterium exhibited excellent sensitivity,specificity and consistency,and its timeliness should help clinicians make precise individualized treatment plans earlier.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.