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.

ObjectiveTo analyze the infection characteristics of human respiratory syncytial virus (HRSV) among children hospitalized with acute lower respiratory tract infection (ALRTI) in a specialized pediatric hospital in Shanghai, so as to provide evidence-based support for optimizing the prevention and control strategies and clinical diagnosis and treatment of respiratory tract infections in children in this region. MethodsA retrospective analysis was performed to the clinical and etiological data of 29 260 children hospitalized for ALRTI in Shanghai Children’s Hospital from January 2021 to December 2024. HRSV and 12 other common respiratory pathogens were detected with multiplex polymerase chain reaction (PCR) and capillary electrophoresis. Demographic and clinical data were collected for statistical analyses. A total of2 412 cases with positive HRSV were divided into the severe group and the non-severe group. Clinical characteristics between the two groups were compared using the Mann-Whitney U test and the chi- square (χ²) test. Additionally, the related influencing factors of severe HRSV infection were explored. ResultsThe overall positivity rate of HRSV from 2021 to 2024 was 8.24% (2 412/29 260), with statistically significant differences observed across the four years (χ²=389.42, P<0.001). The highest positivity rate was in 2021 (14.76%), with a high prevalence throughout the year. In 2022, when non-pharmaceutical interventions (NPIs) were implemented, the HRSV positivity rate was the lowest (4.93%), with a winter-dominant epidemic pattern. In 2023, after the NPIs were lifted, the HRSV positivity rate showed a slight rebound (8.14%), presenting a double-peak pattern. In 2024, the HRSV positivity rate slightly decreased compared to that in 2023 (6.29%), exhibiting a winter and spring-dominant epidemic pattern. Among the hospitalized children with ALRTI, the HRSV positivity rate in males (8.85%) was higher than that in females (7.51%), and the difference was statistically significant (χ²=17.33, P<0.001). Age distribution showed that 82.26% (1 984/2 412) of HRSV infections occurred in children aged 3 years old and below. Besides, as age increased, the infection rate of HRSV showed a gradually decreasing trend (P<0.001). Among the 2 412 children with HRSV infection, the proportion of severe cases was 22.31% (538/2 412), while the non-severe cases accounted for 77.69% (1 874/2 412). Compared with non-severe cases, severe cases were more frequently presented with high fever, longer duration of wheezing, as well as higher rates of underlying diseases or co-infection with Mycoplasma pneumoniae (P<0.001). ConclusionThe prevalence intensity of HRSV varied yearly from 2021 to 2024. After the removal of NPIs in 2023, a slight rebound with a double-peak epidemic pattern was observed. HRSV remained a common pathogen in children hospitalized for ARLTI, and children aged 3 years old and below constituted the highest proportion for infection. Compared with non-severe cases, those with severe HRSV infections were more prone to presenting with high fever and a longer duration of wheezing. Children with positive HRSV who had underlying diseases or co-infection with Mycoplasma pneumonia were more likely to develop severe conditions.

Disease computable phenotype is a data model designed to identify specific clinical conditions or characteristics, which automatically extracts information from clinical databases such as electronic health records through algorithms. Phenotypic data for rare diseases often reside in unstructured text. Due to the scarcity of rare disease cases, atypical symptoms, and insufficient physician experience, misdiagnosis and underdiagnosis rates remain high. In this context, the application of computable phenotype technology holds promise for improving the accuracy and efficiency of rare disease diagnosis. This article reviews the current research status, challenges, and opportunities of computable phenotype technology in biomedicine, particularly in the field of rare diseases, and proposes a development and validation framework for rare disease computable phenotypes, aiming to provide research and development insights for computable phenotypes to empower the diagnosis and treatment of rare diseases.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

In recent decades,the incidence of human papillomavirus(HPV)-associated oropharyngeal squamous cell carcinoma(OPSCC)has shown a marked increase.Significant changes have also occurred in the OPSCC diagnosis and treatment paradigm.Deter-mining HPV status prior to treatment is now essential,and radiotherapy/chemotherapy,immunotherapy,and minimally invasive surgical techniques have progressively emerged as key modalities for managing OPSCC.However,alongside these paradigm shifts,a comprehen-sive technical consensus guiding the entire diagnostic and therapeutic process for OPSCC patients is currently lacking.Given China's large population base and the rising incidence of OPSCC,an expert panel convened to develop a clinical technical consensus on OPSCC diagno-sis and management tailored to China's specific context.This consensus aims to further enhance and standardize understanding of OPSCC management techniques among relevant healthcare professionals.

Objective·To investigate the bidirectional causal relationships between celiac disease(CeD)and Hashimoto thyroiditis(HT)as well as Graves disease(GD),using a two-sample Mendelian randomization(MR)approach.Methods·Single nucleotide polymorphisms(SNPs)related to CeD,HT and GD were extracted from publicly available Genome-Wide Association Studies(GWAS)databases and used as instrumental variables.The inverse-variance weighted(IVW)method served as the primary analytical approach,supplemented by MR-Egger,weighted median(WME)and weighted mode(WMO)methods,to evaluate the causal associations between CeD and both HT and GD.Replication analyses using alternative GWAS datasets were conducted to validate the robustness of the results.Heterogeneity was assessed using Cochran's Q test,and pleiotropy was evaluated via MR-Egger intercept test.Leave-one-out analyses were performed to assess the impact of individual SNPs on the results.Results·The IVW analysis results indicated that genetically predicted CeD significantly increased the risk of HT[discovery group:OR=1.186(95%CI 1.114?1.262),P<0.001;replication group:OR=1.218(95%CI 1.090?1.361),P<0.001]and GD[discovery group:OR=1.214(95%CI 1.155?1.276),P<0.001;replication group:OR=1.273(95%CI 1.161?1.396),P<0.001].However,reverse MR analyses did not provide evidence for a causal relationship between HT and CeD,while genetically predicted GD significantly increased the risk of CeD[discovery group:OR=1.259(95%CI 1.006?1.576),P=0.044;replication group:OR=1.387(95%CI 1.233?1.560),P<0.001].Sensitivity analyses suggested that the results were not influenced by horizontal pleiotropy.Conclusion·CeD may be causally associated with a higher risk of HT and GD,while GD may increase the risk of developing CeD.HT does not appear to have an impact on CeD.

Objective:To observe the effects of Maxing Loushi decoction on the inflammatory response and inflammatory indicators in mice with chronic obstructive pulmonary disease (COPD) models.Methods:Thirty-six BALB/C mice were randomly divided into 4 groups by random number table method: 10 mice in the COPD model group (referred to as the model group), 10 mice in the Maxing Loushi decoction group (referred to as the traditional Chinese medicine group), 10 mice in the programmed death receptor-1 (PD-1) inhibitor group (referred to as the control group), and 6 mice in the normal group. The COPD models of mice in the model group, the traditional Chinese medicine group and the control group were prepared by cigarette smoking combined with lipopolysaccharide (LPS) induction method. During the modeling process, the model group and the traditional Chinese medicine group were respectively given normal saline and Maxing Loushi decoction by gavage. The control group was given intraperitoneal injection of PD-1 inhibitor, while the normal group was given intragastric administration of normal saline. Pathological changes of lung tissues in each group of mice were detected by HE staining. The levels of inflammatory factors [monocyte chemotactic protein-1 (MCP-1), macrophage inflammatory protein-1α (MIP-1α), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α)] in the plasma and alveolar lavage fluid (BALF) of mice in each group were determined by enzyme-linked immunosorbent assay (ELISA). The effects of Maxing Loushi decoction intervention on inflammatory responses and inflammatory factors were evaluated.Results:The lung tissue structure in the normal group was basically normal. There was no thickening of the alveolar walls, no infiltration of neutrophils in the tissues, and no obvious inflammatory infiltration. In the model group, the lung tissue structure was slightly abnormal. A small amount of alveolar atrophy could be observed, the alveolar walls were slightly thickened, and inflammatory infiltration could be seen. In the traditional Chinese medicine group, the lung tissue structure was slightly abnormal. A small amount of alveolar atrophy and collapse could be observed, the alveolar walls were not thickened, and individual neutrophil infiltration could be seen in the tissue. In the control group, the lung tissue structure was slightly abnormal, some alveoli atrophied, and a small amount of neutrophil infiltration could be seen in the tissue. The levels of MCP-1 and MIP-1α in plasma and lavage fluid of the model group were significantly higher than those of the normal group (all P<0.05), while the levels of MCP-1 and MIP-1α in plasma and lavage fluid of the traditional Chinese medicine group and the control group were significantly lower than those of the model group (all P<0.05). Moreover, the levels of plasma MCP-1 and MIP-1α in the traditional Chinese medicine group were significantly lower than those in the control group (all P<0.05), while there was no statistically significant difference in the levels of MCP-1 and MIP-1α in alveolar lavage fluid between the traditional Chinese medicine group and the control group (all P>0.05). The levels of IL-6 and TNF-α in plasma and alveolar lavage fluid of the model group were significantly higher than those of the normal group (all P<0.05), while the levels of IL-6 and TNF-α in plasma and alveolar lavage fluid of the traditional Chinese medicine group and the control group were significantly lower than those of the model group (all P<0.05). Moreover, the levels of IL-6 and TNF-α in plasma and alveolar lavage fluid of the traditional Chinese medicine group were significantly lower than those of the control group (all P<0.05). Conclusions:The intervention of Maxing Loushi decoction has a significant improvement effect on the inflammatory response of COPD model mice. Inflammatory factors such as MCP-1, MIP-1α, IL-6, and TNF-α can be used as indicators to determine the degree of COPD inflammation.

Objective:To establish a health economics evaluation-based adjustment mechanism for the medical insurance fund package in compact county-level medical community.Methods:A health risk assessment system was designed,with weights determined using the Delphi method.Population health risks were evaluated via rapid assessment methods to calculate health risk scores for each county(city,district),which were then used to determine the medical insurance fund package adjustment amount.Results:The county-level health risk evaluation index system encompassed four dimensions:health risk influencing factor,health protection resource,population health risk,and health level.Through information collection and field surveys,health risk scores for counties(cities,districts)in a case prefecture-level city were obtained,serving as a tool for allocating medical consortium package adjustment funds.Conclusion:The health economics evaluation-based medical insurance fund adjustment mechanism enhances the equity of total medical insurance fund allocation,activates the incentive role of medical insurance in healthcare delivery,and transmits intervention pressure to reduce residents'health risks to public management departments at the county level.This approach realizes mutual benefits among medical insurance,residents,and healthcare providers.