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: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

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.

The new cultural construction of high-quality development of public hospitals proposes a patient-oriented ap-proach.People with disabilities,represented by the hearing-impaired community,faces many difficulties in the process of seeking medical care,and their needs have not been adequately addressed.This inadequacy adversely affects the development of harmoni-ous doctor-patient relationships and the patient medical experience.This study takes the deaf assistance outpatient clinic,first es-tablished by Shanghai East Hospital as an example to elaborate the practice of cultural brand construction under the leadership of Party building.Medical social workers,healthcare professionals,and volunteers work together to build a cultural brand through institutional guarantees,detailed care,and the establishment of a full process service system.This is expected to provide refer-ences for the construction of hospital cultural brands..

Objective To investigate the correlation between serum uric acid(SUA)levels and incident chronic kidney disease(CKD)in middle-aged and elderly Chinese population and gender differences.Methods Based on the longitudinal survey data of China Health and Retirement Longitudinal Study from 2011 to 2015,the CKD-Epidemiology Collaboration cystatin C formula was used to estimate the glomerular filtration rate(eGFR),and 4 119 participants with normal renal function(eGFR≥60 mL·min-1·1.72 m-2)at baseline were included.Incident CKD was defined as eGFR<60 mL·min-1·1.72 m-2 at the follow-up in 2015.Logistic regression analysis was used to analysis the association of SUA levels at baseline and incident CKD among different genders.Restricted cubic spline analysis was used to analyze the dose-response relationship.Results After 4-year follow-up,127 participants developed incident CKD,including 57 males and 70 females.Multivariate Logistic regression analysis showed that elevated SUA levels were independently associated with the risk of incident CKD(OR=1.532,P<0.001).For each 1 mg/dL increase in SUA,the risk of incident CKD increased by 33.6%in males(OR=1.336,P=0.012)and 77.5%in females(OR=1.755,P<0.001).Restricted cubic spline analysis showed a linear positive correlation between SUA levels and incident CKD in both males and females.Participants were divided into four groups according to SUA quartiles(Q1-Q4).Multivariate Logistic regression analysis indicated a significant increase in the risk of incident CKD in Q3 group(3.75 mg/dL4.43 mg/dL)compared with Q1 group in females(Q3 group:OR=2.571,P=0.045;Q4 group:OR=3.666,P=0.005).Conclusion SUA is an independent risk factor for incident CKD in the middle-aged and elderly population.In females,serum uric acid levels exceeding 3.75 mg/dL are associated with an increased risk of incident CKD.