Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

Objective:To develop a bacterial endotoxin detection method suitable for mRNA vaccines based on lipid nanoparticle（LNP）delivery system.Methods:The gel clot limit test outlined in the third section of the Chinese Pharmacopoeia（2020 edition）was utilized. Taking the human herpesvirus type 2 mRNA vaccine as the detection object，the optimal conditions for bacterial endotoxin detection were established by evaluating sample dilution factors，diluents，and other interfering elements. The results were validated using the recombinant C factor method. Finally，the applicability of the established method was validated through testing the respiratory syncytial virus mRNA vaccine and the shingles mRNA vaccine.Results:Increasing the sample dilution factor to 480 times with a magnesium-containing buffer and using 0.06 EU/ml tachypleus amebocyte lysate effectively mitigated the interference caused by LNP on the test results of the human herpesvirus type 2 mRNA vaccine，the respiratory syncytial virus mRNA vaccine，and the shingles mRNA vaccine. The results from recombinant C factor method and the gel clot limit method were consistent.Conclusion:A bacterial endotoxin gel clot limit detection method tailored for human herpesvirus type 2 mRNA vaccine，respiratory syncytial virus mRNA vaccine，and shingles mRNA vaccine is successfully developed based on existing protocols in the Chinese Pharmacopoeia（2020 edition）. This study offers insights for the detection of bacterial endotoxin in LNP-based biological products.

Objective To investigate the effect and mechanism of hypoxia inducible factor-1 α/aquaporin-4(HIF-1α/AQP4)pathway in high altitude cerebral edema(HACE)after blood-brain barrier injury in rats.Methods Adult male SD rats(n=40)were randomly divided into two groups:control group(Ctrl,n=20)and high altitude cerebral edema group(HACE,n=20).The rats in the control group were reared in Xining(altitude 2261 m)for 4 days,and the rats in HACE group were reared in low-pressure simulation chamber(altitude 5000 m)for 4 days.Brain water content was measured by the method of dry and wet weight.The intracranial structure,morphology and signal changes of small animals were observed through T2 weighted image of 7.0 T MRI.The morphological changes of neurons and the apoptosis of nerve cells in the CA1 region of hippocampal tissue were observed by the staining of Nissl and TUNEL.Immunohistochemical staining was performed to observe the extravasation of immunoglobulin G(IgG).The expressions of HIF-1α,AQP4,matrix metalloproteinase-9(MMP-9),claudin-5,occludin and zonula occludens-1(ZO-1)in the tissue of hippocampal were detected by the method of Western blotting and immunofluorescent staining.Results The brain water content increased significantly in the HACE group(P＜0.05).The neurons in CA1 region of hippocampal tissue were atrophic and deformed,the arrangement of neurons was disordered in the HACE group.The number of neurons decreased significantly,the apoptosis of nerve cells increased significantly,and the IgG exudates obviously in the CA1 region of hippocampal tissue in the HACE group.The expressions of HIF-1α,AQP4 and MMP-9 proteins increased significantly,while claudin-5,occludin and ZO-1 proteins decreased significantly in the CA1 region of hippocampal tissue,which detected by the method of Western blotting and immunofluorescent staining(P＜0.05).Conclusion Acute high-altitude hypoxia can induce to blood-brain barrier disruption through the HIF-1α/AQP4 pathway,resulting in high-altitude cerebral edema.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective:To investigate outpatients with central venous catheters regarding their awareness and needs for internet-based nursing clinics for venous catheter maintenance, and to provide reference for the development of internet-based catheter care services.Methods:A convenience sampling method was used to recruit 280 patients with central venous catheters who visited the Outpatient Catheter Maintenance Room of Beijing Friendship Hospital, Capital Medical University, between November and December 2024. A self-designed questionnaire on awareness and needs regarding catheter venous catheters in internet-based nursing clinics was used to conduct the survey.Results:A total of 280 questionnaires were distributed and 271 valid questionnaires were recovered, yielding an effective response rate of 96.79%. Regarding awareness, 47.97% (130/271) of the patients were aware of internet-based catheter maintenance services, and 80.81% (219/271) expressed willingness to try them. Regarding outpatient demand, 62.73% (170/271) preferred video consultations and 20.66% (56/271) preferred online text-based consultations. A total of 55.35% (150/271) of patients hoped for 24-hour access to consultation services, and 49.45% (134/271) were very willing to pay additional service fees. In terms of service content, 86.72% (235/271) hoped for more convenient home-visit services, 91.14% (247/271) expected assistance with expert appointment booking, and 95.94% (260/271) wanted medication delivery services related to catheter maintenance. Regarding education and support, 83.76% (227/271) hoped to gain knowledge about disease prevention and management, and 73.80% (200/271) desired guidance on healthy lifestyle practices.Conclusions:Outpatients with central venous catheters have relatively low awareness of internet-based nursing clinics for venous catheter maintenance, but show high levels of service demand. They also express expectations for expanded service content and formats. Hospital administrators should gradually improve the service system based on patients' needs and enhance educational initiatives to improve patient awareness, ultimately delivering more timely, high-quality, and efficient nursing services.

Objective To analyze the research hotspots and development trends regarding the effect of proprioceptive training in the rehabilitation of anterior cruciate ligament(ACL)injury.Methods Relevant literatures on the effect of proprioceptive training on ACL injury rehabilitation were retrieved in the Web of Science Core Collection database from 2015 to 2024,and were analyzed with CiteSpace 6.2 R4.Results A total of 108 articles were included,with a fluctuating trend in publication volume,and the number of publica-tions peaked in 2021.The United States and China published the most articles.High-frequency keywords includ-ed posture balance,neuromuscular control,joint position sense,muscle strength and gait analysis.The most cen-tral keyword was posture stability.The research focused on improving the postoperative rehabilitation outcomes and efficiency of ACL injury,with particular emphasis on returning to play,posture stability,strength training and knee joint function.Conclusion Proprioceptive training can enhance proprioception and motor control of patients with ACL injury and im-prove rehabilitation outcomes by strengthening rehabilitation techniques and optimizing treatment approaches.Future research should continue to focus on the diversification of proprioceptive training,the individulization of rehabilitation plans and the application of new technologies.