Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

Although global brain science research has progressed rapidly in recent decades, several fundamental questions in neuroscience remain unresolved. In particular, the physical mechanism underlying neural signal transmission remains controversial, and the carriers responsible for neural information storage and retrieval have not yet been fully clarified. These unresolved issues motivate us to re-examine the processes of neural information generation, transmission, integration, storage, and retrieval from multiple perspectives. A key observation is that neural electromagnetic activities are closely associated with time. Their duration, temporal structure, and dynamic evolution play crucial roles in neural information processing. In this work, we analyze neural electromagnetic activities from the perspective of temporal scales (referred to here as the “time course”). By reviewing and integrating findings from previous studies, we examine the characteristic time requirements and dynamic features of neural processes occurring at different stages of information processing. These stages include neural signal generation, signal transmission along axons, synaptic integration, synaptic plasticity, and memory formation and retrieval. Based on this temporal analysis, we outline a framework describing neural electromagnetic activities across a wide range of time scales, spanning from microseconds to minutes, hours, or even longer periods associated with long-term memory, which suggests that neural information processing involves multiple physical processes operating at different time levels. Rapid electromagnetic events may occur on microsecond scales, whereas electrophysiological phenomena such as action potentials typically last on the order of milliseconds. Longer time scales are associated with synaptic plasticity and memory-related processes. From this perspective, we propose that the physical carrier of neural information may be transient electromagnetic pulses with durations on the microsecond scale. In this framework, action potentials can be interpreted as the macroscopic electrophysiological manifestation of underlying electromagnetic processes triggered by ionic currents across neuronal membranes. Rather than being the fundamental neural signal itself, the action potential may represent a measurable membrane-level response associated with the successful activation of these electromagnetic events. Moreover, we discuss a possible mechanism for long-term memory storage. Considering the apparent temporal contradiction between the millisecond-scale excitation of neurons and the long-term persistence of memories, we believe that long-term memory information may be stored within neural network topologies formed by electrical synapse coupling. Such structures, referred to as electrically coupled memory networks (ECMNs), may enable neurons within the same network to respond rapidly and synchronously to stimuli, thereby facilitating efficient memory retrieval. Overall, this study emphasizes the importance of considering the temporal organization of neural electromagnetic activities when interpreting neural signaling mechanisms. It may provide new insights into the physical nature of neural information carriers and the mechanisms of memory storage and retrieval. Furthermore, highlighting the potential role of electromagnetic interactions in neural activity may contribute to the development of new theoretical frameworks and experimental approaches in neuroscience. Such perspectives may also offer valuable references for future research on neural coding, brain function mechanisms, and neuromodulation technologies.

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.

Objective Pharmacovigilance,as an essential component of post-marketing drug regulation,plays a crucial role in ensuring the safety of public medication use.In recent years,Artificial intelligence(AI)technology,with its powerful data processing and analysis capabilities,has shown tremendous potential in the field of Pharmacovigilance.This article introduced and analyzed the application background of AI technology in Pharmacovigilance,its exploration and current status both internationally and within China,highlighted its application in the country,as well as the associated problems and challenges from the perspective of post-marketing regulation.It aims to provide reference for post-marketing regulation in China.Currently,China's exploration and application of AI in pharmacovigilance have just begun,and efforts should be intensified and the pace accelerated.Regulatory agencies should actively develop and implement regulatory standards or relevant guidelines for AI technologies throughout the product lifecycle,strengthen personnel training,talent cultivation,and introduction,actively promote close cooperation among regulatory agencies,pharmaceutical companies,research institutes,and universities,and jointly promote the innovative application of AI technology in the field of drug regulation.

Objective Pharmacovigilance,as an essential component of post-marketing drug regulation,plays a crucial role in ensuring the safety of public medication use.In recent years,Artificial intelligence(AI)technology,with its powerful data processing and analysis capabilities,has shown tremendous potential in the field of Pharmacovigilance.This article introduced and analyzed the application background of AI technology in Pharmacovigilance,its exploration and current status both internationally and within China,highlighted its application in the country,as well as the associated problems and challenges from the perspective of post-marketing regulation.It aims to provide reference for post-marketing regulation in China.Currently,China's exploration and application of AI in pharmacovigilance have just begun,and efforts should be intensified and the pace accelerated.Regulatory agencies should actively develop and implement regulatory standards or relevant guidelines for AI technologies throughout the product lifecycle,strengthen personnel training,talent cultivation,and introduction,actively promote close cooperation among regulatory agencies,pharmaceutical companies,research institutes,and universities,and jointly promote the innovative application of AI technology in the field of drug regulation.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Purpose Discover new prostate cancer-related single nucleotide variants.Methods Tissue wax blocks from 21 prostate cancer patients who underwent radical surgery and had relatively complete clinical data were collected for somatic mutation detection to analyze new mutated genes associated with prostate cancer.The levels of cor-responding proteins in the urine of prostate cancer patients were tested according to the results of the selected genes.Results All 21 prostate cancer patients showed obvious somatic mutations,and the mutation types were dominated by C＞T and G＞A.The number of somatic mutations was 521,of which 27 genes had high mutation proportions(≥2 ca-ses),including ZSWIM6(5/21),FOXA1(4/21),SPTA1(2/21),FAM47C(2/21),FLG2(2/21),PRSS3(2/21),TP53(2/21),FLG(2/21),UBR4(2/21),and the mutations occurring in ZSWIM6 were all deletion muta-tions,and the mutations occurring in FOXA1 were missense mutations,deletion mutations,and deletion insertion mu-tations.The urinary levels of UPF1,SPTA1,and IDH1 proteins of the 10 prostate cancer patients were significantly different than those of the healthy controls.Correlation analysis showed that FOXA1 was positively correlated with UBR4(r=0.669,P=0.001),SPTA1 was positively correlated with FLG2(r=1.000,P＜0.001),FAM47C was positively correlated with PRSS3(r=1.000,P＜0.001),and there was a significant positive correlation between TP53 and FLG(r=1.000,P＜0.001).ZSWIM6 and FOXA1 were not correlated with biochemical recurrence.SP-TA1 mutation affected progression-free survival(PFS)[(66.0±0)months vs(30.0±7.8)months,P=0.008].FAM47C was positively correlated with PFS[(66.0±0)months vs(19.0±0)months,P＜0.001].ZNF676 was correlated with PFS[(66.0±0)months vs(26.0±5.0)months,P=0.008].FLG2 was correlated with PFS[(66.0±0)months vs(30.0±7.8)months,P=0.008].PRSS3 was correlated with PFS[(66.0±0)months vs(19.0±0)months,P＜0.001].Conclusion All 21 prostate cancer patients harbored somatic mutations,including ZSWIM6(5/21)and FOXA1(4/21)mutations.SPTA1,FAM47C,ZNF676,FLG2,and PRSS3 may be associated with prognosis.

Aim To investigate the effects of rosavin on hepatocellular steatosis and its mechanism of action.Methods AML-12 and HepG2 cells were induced to undergo hepatocellular steatosis by free fatty acids(FFA),and the optimal inducing concentration was determined by oil red O staining and CCK-8 assay.The cell activity was detected by CCK-8 assay after ro-savin treatment,and the lipid droplet accumulation was observed by oil red O staining.The levels of triglycer-ide(TG),total cholesterol(TC),glutamic oxalacetic transaminase(AST),glutamic pyruvic transaminase(ALT),superoxide dismutase(SOD),glutathione per-oxidase(GSH-Px),and malondialdehyde(MDA)were detected by kits.The potential targets of rosavin in non-alcoholic fatty liver disease(NAFLD)were ana-lyzedby network pharmacology and molecular docking,and the expression of core candidate targets before and after the rosavin intervention was detected by real-time fluorescence quantitative PCR.Results Hepatocyte steatosis was induced by FFA,and the intervention of rosavin(25,50 μmol·L-1)reduced the number of intracellular lipid droplets in hepatocytes in a dose-de-pendent manner,also lowered the cellular levels of TG,TC,AST,ALT,elevated the levels of SOD and GSH-Px,and reduced the levels of MDA.Network pharma-cological analysis and molecular docking yielded five core candidate targets:NOS3,MAPK14,PPARG,TNF-α,and IGF-1,and real-time fluorescence quantitative PCR showed that the action of loxavir significantly re-duced the gene expression of TNF-α and PPARG in hepatocytes after FFA induction.Conclusions Rosa-vin can attenuate the inflammatory response,oxidative stress level,and lipid accumulation in hepatocytes by modulating TNF-α and PPARG,thereby ameliorating FFA-induced hepatocellular steatosis.

Objective To improve and refine the relevant regulations and guiding principles of warnings on drug instructions and labels in China.Methods This paper sorted out the drug instructions of small molecule anti-tumor drugs listed by the U.S.Food and Drug Administration(FDA)from 2005 to 2022,included the drugs mentioned in the QT interval prolongation risk,analyzed the clinical research and QT research results,and sorted out the identification and warning rules of the instructions.Results A total of 35 drugs were included,4 drugs wrote the risk of QT interval prolongation in the black box warning,21 drugs were wrote in the warning and precautions position,6 drugs were wrote in the adverse reaction section,and 2 drugs were only described under clinical pharmacology section.According to the severity of the QT interval prolongation caused by the drug and whether there were serious clinical consequences,they were displayed in the warnings(black box warnings),precautions(warnings and precautions)and adverse reactions in the instructions.Conclusion The aim of this article is to provide a reference for the writing of QT risk warning information of the instructions of domestic drug production enterprises and regulatory departments.It is recommended to clarify the severity of drug safety and the location of the instructions in clinical research,and continue to carry out safety monitoring and update the instructions in time after listing.