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.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

Objective: To evaluate the efficacy of a short video based health education model in enhancing e-cigarette awareness among junior high school students, so as to provide empirical evidence for optimizing school based health education in the digital era. Methods: In December 2024, a cluster sampling method was applied to recruit 465 eighth grade students from a middle school in Kunming for a survey. The intervention was implemented through playing short videos produced by the research team in the classroom, and a self designed adolescent e-cigarette questionnaire was used to conduct assessments before and after intervention, along with qualitative interviews with 60 teachers and students by purposive sampling. Pre and post intervention outcomes were compared by using paired t-test and Chi-square test. Qualitative data underwent a three stage coding process of "open, axial, and selective coding" to construct an explanatory framework. Results: Quantitative analysis showed significant post intervention increases in both baseline awareness scores（92.1±6.6）and deep awareness scores (70.0±17.6) compared with pre intervention( 78.2± 14.0，46.1±20.5)( t =23.54，26.72，both P <0.05), both meeting the criteria for large effect sizes (Cohen s d =1.09, 1.24). The improvement in deep awareness was particularly pronounced, specifically regarding addictive ingredients, illicit additives(tiletamine,metomidate,etomidate), and misconceptions about smoking cessation efficacy ( χ 2=150.54,113.27,117.40,112.92, 69.93 , all P <0.01). Qualitative insights revealed that narrative transportation and visual enhancement were the core mechanisms of efficacy: 87.3% of students preferred contextualized narratives, 85.5% of students decoded cognitive bottlenecks more effectively because of visual enhancement, and 72.7% relied on short videos for micro learning. Conclusion Short video based health education can effectively enhance e-cigarette awareness among junior high school students, offering a pragmatically viable digital pathway for school based health education.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

ObjectiveThis paper aims to investigate the intervention effect and molecular mechanism of Gancao Fuzitang （GCFZT） in knee osteoarthritis （KOA）. MethodsNetwork pharmacology was employed to predict the key targets and signaling pathways of GCFZT. Fifty SD rats were randomly divided into a sham group， a model group （KOA）， a low-dose GCFZT group （GCFZT-L， 2.8 g·kg^-1）， a high-dose GCFZT group （GCFZT-H， 5.6 g·kg^-1）， and a positive drug celecoxib group （Celecoxib， 20 mg·kg^-1）， with 10 rats in each group. The rats in the sham group and the model group were given an equal volume of distilled water. Except for the sham group， the other four groups underwent anterior cruciate ligament transection to establish the KOA rat model. After successful modeling， the rats in each group received intragastric administration once a day for eight consecutive weeks. The structural changes of cartilage and subchondral bone were assessed via micro-computed tomography （micro-CT） and histological staining. The levels of inflammatory factors in the serum， such as interleukin-1β （IL-1β）， IL-6， and tumor necrosis factor-α （TNF-α） were measured using an enzyme linked immunosorbent assay （ELISA） kit. Real-time quantitative polymerase chain reaction （Real-time PCR）， Western blot， and immunohistochemistry were used to detect changes in the expression of autophagy-related proteins such as microtubule-associated protein 1 light chain 3B （LC3B）， selective autophagy junction protein 62 （p62）， and autophagy key molecule yeast Atg6 homolog （Beclin-1） in articular cartilage， as well as key molecules of the phosphatidylinositol 3 kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR） signaling pathway. ResultsNetwork pharmacology analysis suggests that GCFZT may exert anti-osteoarthritic effects through regulating the PI3K/Akt/mTOR pathway. In vivo experiment shows that GCFZT can significantly improve cartilage degeneration and attenuate subchondral bone destruction in KOA rats. Detection results of inflammatory factors in the serum reveal that， compared with those in the sham group， the levels of IL-6， IL-1β， and TNF-α in the serum of rats in the KOA group are significantly increased （P<0.05）. Compared with those in the KOA group， the levels of these three inflammatory factors in the GCFZT-L， GCFZT-H， and Celecoxib groups were significantly decreased （P<0.05）. However， there was no statistically significant difference in these three inflammatory factor levels between the GCFZT-H group and the celecoxib group. These findings suggest that GCFZT can effectively inhibit the systemic inflammatory response in KOA rats. Mechanism research indicates that GCFZT inhibits activation of the PI3K/Akt/mTOR pathway， thereby enhancing autophagic activity and improving chondrocyte function and matrix degeneration. ConclusionGCFZT improves cartilage and subchondral bone damage in KOA rats by inhibiting the PI3K/Akt/mTOR signaling pathway and promoting autophagy. These findings provide theoretical evidence for the application of GCFZT in the prevention and treatment of osteoarthritis.

Acute burns and chronic wounds frequently fail to heal owing to various reasons. Most drugs currently used for wound therapy in clinical practice have notable drawbacks, making their application a substantial concern. For instance, anti-inflammatory drugs can exert multisystem toxicity, and cellular therapies are costly and difficult to retain. In recent years, natural functional proteins derived from animals and plants have gained increasing attention owing to their unique biological activities, low cost, and broad application prospects in wound therapy. Herein, we isolated a new protein (JH015Y) from amphibians and demonstrated its excellent wound repair and regeneration properties compared with those of epidermal growth factor, both in vitro and in vivo. JH015 protein increased the proliferative ability of human keratinocytes and skin fibroblasts by 47.73 and 41.40%, respectively. In vivo, the medium-dose (0.5 mg/dose) groups of JH015Y protein demonstrated accelerated wound healing from day 4, with wound healing rates 1.26, 1.27, and 1.14 times that of the blank group in acute wounds, burn wounds, and diabetic ulcer, respectively. Histological analysis of Masson-stained sections indicated that the JH015Y protein contributed to collagen deposition on the wound surface, markedly reduced inflammatory cell infiltration, and exhibited low biological toxicity. Accordingly, the JH015Y protein is a promising biotherapeutic agent for accelerated wound repair and regeneration.

Acute burns and chronic wounds frequently fail to heal owing to various reasons. Most drugs currently used for wound therapy in clinical practice have notable drawbacks, making their application a substantial concern. For instance, anti-inflammatory drugs can exert multisystem toxicity, and cellular therapies are costly and difficult to retain. In recent years, natural functional proteins derived from animals and plants have gained increasing attention owing to their unique biological activities, low cost, and broad application prospects in wound therapy. Herein, we isolated a new protein (JH015Y) from amphibians and demonstrated its excellent wound repair and regeneration properties compared with those of epidermal growth factor, both in vitro and in vivo. JH015 protein increased the proliferative ability of human keratinocytes and skin fibroblasts by 47.73 and 41.40%, respectively. In vivo, the medium-dose (0.5 mg/dose) groups of JH015Y protein demonstrated accelerated wound healing from day 4, with wound healing rates 1.26, 1.27, and 1.14 times that of the blank group in acute wounds, burn wounds, and diabetic ulcer, respectively. Histological analysis of Masson-stained sections indicated that the JH015Y protein contributed to collagen deposition on the wound surface, markedly reduced inflammatory cell infiltration, and exhibited low biological toxicity. Accordingly, the JH015Y protein is a promising biotherapeutic agent for accelerated wound repair and regeneration.

Objective:To understand the information needs and experiences of primary caregivers of patients in the emergency resuscitation room of the emergency department, and to provide a reference for clinical staff to meet caregivers′ information needs as well as to develop targeted and effective health information support for doctors and patients.Methods:A descriptive phenomenological research method was used to conduct semi-structured interviews with primary caregivers of 14 patients in the emergency resuscitation room of the First Affiliated Hospital of Nanjing Medical University from November 2023 to February 2024 through purposive sampling, and the Colaizzi 7-step analysis method was applied to summarize and analyze the interview data and refine the themes.Results:Totally 14 respondents aged 28-66, including 6 males and 8 females. Four themes were refined including diverse information needs, information access dilemma, integration of doctor-patient information for joint decision-making and communication, and desire for information and emotional support.Conclusions:The information needs of primary caregivers of patients in the emergency department were diverse, and caregivers were eager to seek patient-related information and crave emotional support and communication when faced with the onset of a patient's illness. Healthcare professionals should strengthen the assistance of caregivers′ information needs to improve the experience of patients and caregivers in medical consultation services and realize the sustainable development of the doctor-patient relationship.

Objective:To investigate the effect of KRAS,NRAS and BRAF gene mutations on the efficacy of pre-operative short-course radiotherapy combined with chemotherapy and postoperative liver metastasis in patients with stage Ⅱ～Ⅲ mid-low rectal cancer.Methods:The clinical data of 149 patients with stage Ⅱ～Ⅲ low rectal cancer admitted to Dongnan Hospital of Xiamen University from January 2017 to June 2020 were retrospectively analyzed.All patients received neoadjuvant therapy with preoperative short-course radiotherapy combined with chemotherapy and radical surgery,and were followed up until June 30,2023.The mutations of KRAS,NRAS and BRAF genes were de-tected by pathological tissue before surgery.The effect of neoadjuvant therapy was evaluated according to tumor re-gression grade(TRG).The risk factors of postoperative liver metastasis were analyzed by Logistic multivariate analysis.Results:There were 44 cases of KRAS,10 cases of NRAS and 12 cases of BRAF gene mutation in 149 patients with stage Ⅱ～Ⅲ low rectal cancer,and the mutation rates were 29.53%,6.71%and 8.05%.The incidence of positive vas-cular invasion in patients with KRAS gene mutation was higher than negative(P＜0.05).In NRAS mutation patients,the incidence of positive lymph node metastasis was higher than negative(P＜0.05),and the incidence of maximum tumor diameter≥5 cm was higher than that of maximum tumor diameter＜5 cm(P＜0.05).The clinical stage of BRAF muta-tion was higher in stage Ⅲ than in stage Ⅱ(P＜0.05),and the incidence of positive lymph node metastasis was higher than negative(P＜0.05).During the follow-up period,liver metastasis occurred in 42 patients,and the liver metastasis rate was 28.18%.The KRAS,NRAS and BRAF gene mutations in the effective group were 25.81%,2.15%and 3.23%,lower than those in the ineffective group(35.71%,14.29%and 17.07%,P＜0.05).Multiple factors found clinical stage Ⅲ(OR=10.620,95%CI:2.645～22.575),lymph node metastasis was positive(OR=8.774,95%CI:1.878～19.645),neoadju-vant therapy failed(OR=3.373,95%CI:1.014～11.218),KRAS gene mutation(OR=6.245,95%CI:1.876～20.789),BRAF gene mutation(OR=9.497,95%CI:1.754～19.335)were independent risk factors for postoperative liver metastasis of stage Ⅱ～Ⅲ mid-low rectal cancer.Conclusion:Mutations in the KRAS and BRAF genes of middle are associated with poorer efficacy of neoadjuvant therapy in patients with stage Ⅱ～Ⅲ mid-low rectal cancer and are also indepen-dent risk factors for postoperative liver metastasis.