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.

Despite significant advances in the field of critical care medicine over the past three decades, veno-arterial extracorporeal membrane oxygenation (V-A ECMO) remains the primary temporary mechanical circulatory support modality for patients with acute severe circulatory failure. With the accumulation of clinical experience and the increasing maturity of operational techniques in V-A ECMO, its technical management—particularly hemodynamic management—has become a key factor influencing patient outcomes. To further improve patient survival, the Chinese Critical Care Ultrasound Study Group, in collaboration with the Hemodynamic Therapy of Critical Care Collaborative Group and the Critical Care Medicine Branch of the China International Exchange and Promotive Association for Medical and Health Care, organized experts in critical care medicine to develop the Consensus on Hemodynamic Management in Adult Veno-Arterial Extracorporeal Membrane Oxygenation (2026 Edition). Based on years of clinical experience and the latest evidence-based medical evidence, this consensus formulates 15 systematic recommendations covering the entire process of V-A ECMO, including initiation, management during support, and weaning, aiming to promote standardized application of hemodynamic management in V-A ECMO.

Acute kidney injury (AKI) is a prevalent and life-threatening clinical syndrome characterised by a rapid decline in renal function and diverse pathological etiologies. The condition has been demonstrated to be associated with elevated mortality rates and an increased risk of progression to chronic kidney disease. At present, clinicians depend heavily on conventional functional markers, such as serum creatinine and urine output, for the diagnosis and staging of the disease. It is evident that these conventional indicators characteristically manifest a considerable temporal delay and only undergo modification subsequent to considerable tissue damage. This severely restricts the timeframe for early detection and timely therapeutic intervention. Furthermore, standard markers fail to provide specific biological information regarding the underlying cellular injury mechanisms. The utilisation of advanced probe technologies in molecular imaging offers a robust alternative to overcome these inherent diagnostic limitations.This comprehensive review systematically evaluates recent progress in the design and application of two primary categories of molecular imaging tools for acute kidney disease, specifically reactive probes and enzyme-activated probes. Reactive probes are engineered to specifically interact with redox-active chemical species, including hydrogen peroxide, peroxynitrite, hypochlorous acid, and sulfur dioxide. Because oxidative stress constitutes a primary early event in acute renal tubular damage, these probes enable researchers and clinicians to visualize early cellular injury and radical accumulation well before global renal functional decline becomes evident. We discuss the application of these reactive probes across multiple imaging modalities including fluorescence imaging, magnetic resonance imaging (MRI), positron emission tomography (PET), and photoacoustic techniques. Photoacoustic imaging combines high spatial resolution with deep tissue penetration and has successfully demonstrated the ability to provide diagnostic alerts up to 12 h before any detectable rise in serum creatinine levels. Additionally, specific reactive probes have shown promising translational potential when tested by high-throughput screening in clinical human urine samples. Enzyme-activated probes target the specific catalytic activity of disease-relevant enzymes. These include well-documented renal tubular structural biomarkers such as NAG, GGT, and ALP, along with apoptosis-related caspases and specific nitroreductases. By responding only to enzymatic cleavage, these tools provide highly specific and pathology-directed imaging readouts. Recent structural design strategies in this field have advanced significantly beyond single-enzyme detection. Researchers are now focusing on sophisticated dual-target recognition to minimize background noise, multimodal integration to cross-validate imaging signals, and theranostic applications where probes simultaneously deliver diagnostic feedback and therapeutic agents to injured tissues. Nanotechnology serves as a fundamental enabler for realizing these advanced probe functions. By precisely optimizing nanoparticle parameters such as hydrodynamic size, surface charge, and targeting ligands, researchers can achieve amplified signal output, highly precise kidney delivery, and protection against premature degradation in the systemic circulation. For example, modifying surface charges can significantly enhance the active uptake of nanoprobes by damaged renal tubular epithelial cells.While preclinical probe development has progressed rapidly, moving these technologies into routine clinical practice remains a major challenge. We analyze the translational feasibility and current obstacles from biological, technological, and regulatory perspectives. Although biological targets such as KIM-1, FAP, and ALP have been validated in extensive patient cohorts, practical barriers severely limit their immediate clinical application. These obstacles involve complex changes in in vivo pharmacokinetics. During an acute injury episode, the extreme drop in the glomerular filtration rate alters probe clearance and can cause unwanted systemic accumulation or confusing background imaging signals. Other major hurdles include a lack of comprehensive long-term toxicity data and the absence of standardized manufacturing protocols to ensure batch-to-batch consistency. Future successful translation will require rigorous multi-center clinical studies to confirm the true diagnostic value of these probes over traditional markers. Researchers must also establish strict standardization of imaging procedures and comprehensive safety evaluations. Ultimately, this review provides a thorough reference framework for designing clinically translatable molecular probes and building a precision diagnostic imaging system for acute kidney injury.

Objective: To understand the current status of psychological sub health among secondary vocational school students and explore its related factors, so as to provide a scientific basis for improving their mental health. Methods: From September to December 2024, a convenience sampling method was used to conduct a questionnaire survey among 5 141 secondary vocational school students from 16 schools across 8 provinces and municipalities (Fujian, Chongqing, Guangdong, Guangxi, Hubei, Jiangxi, Shanghai, Zhejiang). A self designed questionnaire was used to collect data on students demographic characteristics and lifestyle behaviors. The Multidimensional Sub health Questionnaire of Adolescents was adopted to assess psychological sub health status. Multivariate binary Logistic stepwise regression analysis was performed to explore the related factors of psychological sub health among secondary vocational school students. Results: The detection rate of psychological sub health among secondary vocational school students was 11.0%, with detection rates of emotional problems, conduct problems, and social adaptation difficulty being 12.3 %, 12.5%, and 9.5%, respectively. Logistic regression analysis revealed that boys and students whose fathers had an educational level of primary school or below, and junior high school, had relatively lower risks of developing psychological sub health or emotional problems, conduct problems, and social adaptation difficulty ( OR =0.55-0.64, all P <0.05). Conversely, students with urban household registration, those with left behind experience, those with poor self rated family economic status, those from other family structures, those classified as overweight and obesity, and those with sleep disorders, frequent consumption of sugar sweetened beverages, frequent consumption of takeout/delivery food, smoking, alcohol consumption, and low to moderate physical activity levels exhibited significantly higher risks across psychological sub health or emotional problems,conduct problems, and social adaptation difficulty ( OR =1.25-4.79, all P <0.05). Conclusions The psychological sub health condition of secondary vocational school students should not be neglected. Psychological sub health of secondary vocational school students is related to multiple factors such as demographic characteristics and lifestyle behaviors. Multi dimensional intervention measures should be implemented to improve their mental health.

Objective To investigate the effects of fractionated low-dose ionizing radiation (LDIR) on the ferroptosis in human bronchial epithelial (HBE) cells as well as the associated differentially expressed genes (DEGs), biological processes, and signaling pathways. Methods HBE cells were exposed to different single doses of X-ray irradiation (0, 25, 50, 75, and 100 mGy) for 24, 48, and 72 h, respectively. The change in cell viability was detected by MTT assay. Cells were irradiated with 0, 25, 50, and 100 mGy X-rays 5 times, with 48 h between each irradiation and a dose rate of 50 mGy/min. Cells were harvested 24 h after irradiation for the measurement of the expression of ferroptosis-related genes SLC7A11 and GPX4 at the mRNA and protein levels, cellular iron content, and the expression of FTH1 and FTL mRNAs. High-throughput sequencing was used to screen for the DEGs in each dose group, followed by Gene Ontology-Biological Process (GO-BP) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and Gene Set Enrichment Analysis (GSEA). Results Compared with the control group, single-dose LDIR significantly increased cell proliferation at 75 mGy after 24 h (P < 0.05), at 50, 75, and 100 mGy after 48 h (P < 0.05), and at 75 and 100 mGy after 72 h (P < 0.05). Compared with the control group, at the end of the fifth fractionated LDIR, SLC7A11 and GPX4 mRNAs decreased at all doses (P < 0.05), SLC7A11 protein decreased at all doses, GPX4 protein decreased at 25 and 100 mGy, iron content increased at all doses, and FTH1 and FTL mRNAs decreased at all doses (P< 0.05). Sequencing analysis identified 248, 30, and 291 DEGs and 10, 2, and 9 ferroptosis-associated genes at the three doses compared to the control. Gene Ontology-Biological Process analysis showed that DEGs were mainly enriched in biological processes such as response to lipids, cell death, and response to unfolded proteins. Kyoto Encyclopedia of Genes and Genomes analysis showed that DEGs were mainly enriched in the JAK-STAT signaling pathway, lipids and atherosclerosis, ferroptosis, protein processing in the endoplasmic reticulum, and FoxO signaling pathway. Gene set enrichment analysis showed that DEGs were mainly enriched in ferroptosis, fatty acid degradation, and glutathione metabolism. Conclusion Fractionated low-dose radiation induced ferroptosis in HBE cells, and DEGs were predominantly enriched in biological processes and signaling pathways related to inflammation, ferroptosis, and endoplasmic reticulum stress.

Objective:To present an evaluation indicator system for access to cancer screening services.Methods:The evaluation indicator pool was constructed through a scoping review. The theoretical framework was constructed based on the multi-source indicators, and the qualitative expert consultation method was employed to form the initial version of the three-level evaluation indicator system. Delphi expert consultation method was conducted in two rounds to evaluate the relevance, importance, and availability of the proposed evaluation indicator system. The expert positive coefficient, authority coefficient, coordination degree of expert opinions, and concentration of expert opinions were subjected to analysis. Subsequently, the three-level evaluation indicator system for access to cancer screening services was adjusted and determined based on the boundary value method and the open opinions of experts. Finally, the combination weight method was employed to determine the weight.Results:The initial version of the indicator system comprised 3 primary (first-level) indicators, 11 secondary (second-level) indicators, and 46 tertiary (third-level) indicators. Delphi expert consultation was conducted for the initial version, and 17 experts ultimately completed it, exhibiting a positive coefficient of 100% and an authority coefficient of 0.87. In comparison to the initial round of consultation, Kendall's W coefficient ranges (0.15-0.43, all P<0.05) of relevance, importance, and availability scores for each tertiary indicator in the second round exhibited an improvement. The analysis of the importance dimension indicates that expert opinions are also more concentrated, as evidenced by an increase of 8.5% and 7.0% in the proportion of the tertiary indicators with an arithmetic mean above 8 and a full mark ratio above 0.5, respectively. The final evaluation indicator system comprises three primary indicators, with the weights of structure evaluation, process evaluation, and outcome evaluation being 0.338, 0.378, and 0.285, respectively. It also comprises 11 secondary indicators and 45 tertiary indicators. Conclusions:The evaluation indicator system developed in this article can be an effective evaluation tool for quantitative comparison of access to cancer screening services across different populations, cancer types, and before and after intervention. Furthermore, it is recommended that the system undergo continuous optimization concerning its application.

Objective:To analyze the epidemiological characteristics of the population receiving assisted reproductive technology (ART) therapy and the health status of their offspring in Shanghai from 2011 to 2020.Methods:Based on the birth cohort of the entire population in Shanghai, the proportion and trend changes of ART offspring in the birth cohort were analyzed. The characteristics of ART and naturally conceived populations, including household registration, education level, maternal age, and reproductive history, were examined. Additionally, the health status between ART offspring and naturally conceived offspring were compared.Results:From 2011 to 2020, a total of 70 729 ART offspring were born in Shanghai, accounting for 3.69% of the total births. In 2020, this proportion reached 7.79%. The ART conception rate for primiparous women was higher than that for multiparous women, with both showing upward trends and reaching 9.87% and 2.36%, respectively, in 2020. The ART conception rate was higher in women with higher education levels and local household registration than in those with lower education levels and non-local household registration. The incidence rates of preterm birth and low birth weight in ART singleton offspring were 7.76% and 4.82%, respectively, higher than the 4.69% and 2.87% in naturally conceived offspring, but no increasing trend was observed in naturally conceived offspring. Among twin and multiple newborns, the incidence rates of preterm birth and low birth weight were 56.98% and 46.82% for ART, lower than the 58.51% and 51.32% for natural conception.Conclusions:The difference in social and demographic characteristics was obvious in population receiving ART, suggesting that the differed demand of some people for ART therapy, and it is necessary to strengthen the construction of public health services and further expand the coverage and accessibility of ART services. With technological advancements, the rates of preterm birth and low birth weight remain relatively stable, and even decrease in twin and multiple newborns.

Objective:To investigate the current status and challenges of pediatric life support training in China and provide references for improving training quality.Methods:A cross-sectional study was conducted to collect data from pediatric life support training centers across the country，covering basic institutional information，training capacity and training faculty，training program funding，as well as existing challenges and issues.The domestic registry of training centers in 2023 was obtained through the American Heart Association's online platform.After contacting and verifying each center，an online questionnaire was distributed，and the aggregated data were statistically analyzed.Results:A total of 42 institutions participated in the survey，including 19 children's hospitals，14 general hospitals，6 maternal and child health hospitals，2 women and children’s hospitals，and 1 training institution.The distribution of training centers showed a concentration in coastal areas，with the top three provinces/municipalities being Guangdong（7/42，16.7%），Zhejiang（6/42，14.3%），and Shanghai（4/42，9.5%）.As of December 31 2023，the 42 institutions had an annual basic life support（BLS）training volume of 8 587 individuals，the median was 120 (100,200)，and an annual pediatric advanced life support（PALS）training volume of 2 448 individuals，the median was 30 (20,50).Among the 42 institutions，there were 598 BLS instructors and 306 PALS instructors.Among the surveyed institutions，24（24/42，57.1%）reported BLS instructor teams comprising fewer than 10 members，and 33（33/42，78.6%）reported PALS instructor teams comprising fewer than 10.Only 7 centers(7/42,16.7%）reported having dedicated funding support.The top three challenges were：training sessions occupying instructors’personal time（27/42，64.3%），low instructor compensation（16/42，38.1%），and issues with the data submission system（16/42，38.1%）.Conclusion:Pediatric life support training centers in China are primarily children’s hospitals，with a geographical concentration in coastal areas，which is also reflected in the distribution of training scale and instructor resources.Most centers have relatively small training scales and limited instructor capacity，with many instructors conducting training during their personal time.These issues may hinder the implementation and effectiveness of training programs.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective To investigate the therapeutic efficacy of artesunate(AS)on polycystic ovary syndrome(PCOS)in mice and explore the potential mechanism primarily.Methods Twenty-five female C57BL/6J mice were randomly divided into Control group,model group(PCOS group),low-and high-dose AS groups(AS15 and AS30 groups)and metformin group(Met group).In addition to the Control group,the mouse model of PCOS was established by subcutaneous injection of dehydroepiandrosterone(DHEA,60 mg/kg)following by a high-fat diet for 21 d.After modeling,AS of 15 and 30 mg/kg was intraperitoneally injected into the mice of the AS 15 and AS30 groups,respectively,and 200 mg/kg Met was given to those of the Met group by gavage,once per day,for 6 weeks.ELISA was used to detect serum testosterone(T),fasting insulin(FINS),luteinizing hormone(LH)and follicle-stimulating hormone(FSH),and the LH/FSH ratio was calculated.The levels of fasting blood glucose(FBG),triglyceride(TG)and total cholesterol(TC)were detected by automatic biochemical analyzer,and the homeostasis model assessment of insulin resistance(HOMA-IR)was calculated.The estrous cycle was observed,and HE staining was performed for pathological changes in the ovary and uterus.Immunofluorescence assay was employed to measure the expression of p-eIF2α,ATF4 and CHOP in the ovarian tissue.After steroidogenic human granulosa-like tumor cell line KGN were exposed to 100 μmol/L DHEA to simulate the hyperandrogen environment of PCOS,and then treated with 5 and 10 μg/mL AS for 24 h,the protein levels of endoplasmic reticulum stress signaling pathway was detected by Western blotting.Results Compared with the Control group,the PCOS mice had disturbed estrous cycle,polycystic changes in the ovaries,and significantly increased serum T level and LH/FSH ratio(P＜0.05),and obviously elevated HOMA-IR,TC and TG levels in terms of metabolism(P＜0.01).The expression levels of p-eIF2α,ATF4 and CHOP were notably up-regulated in the ovarian granulosa cells of PCOS mice and KGN cells after DHEA exposure(P＜0.05).Additionally,AS treatment attenuated the pathological changes of ovary and uterine expression,decreased the serum T level and the LH/FSH ratio(P＜0.05),and reduced HOMA-IR,TC and TG levels(P＜0.05)when compared with the PCOS mice.Moreover,the expression levels of p-eIF2α,ATF4 and CHOP were significantly down-regulated after AS treatment in both ovarian granulosa cells of PCOS mice and KGN cells(P＜0.05).Conclusion AS significantly improves glycolipid metabolic disorder and reproductive dysfunction in PCOS mice,which may be associated with its suppressing endoplasmic reticulum stress by inhibiting the PERK/eIF2α/ATF4/CHOP pathway.