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.

[摘 要] 目的：探讨复发/转移性鼻咽癌（NPC）接受含PD-1单抗免疫治疗的临床特征和预后影响因素。方法：回顾性分析2019年3月至2024年7月期间南部战区总医院确诊的95例NPC患者的临床资料和外周血生化及免疫学指标。预后分析采用Kaplan-Meier曲线，组间比较使用Log-rank检验，采用Cox比例风险模型进行单因素和多因素分析。结果：95例患者中男性81例，女性14例，中位年龄49.72岁（16~74岁），Ⅳ期91例（95.79%），所有患者均采用免疫治疗，联合或不联合化疗方案治疗，中位无进展生存期（mPFS）为10.5个月，客观缓解率（ORR）70.53%，疾病控制率（DCR）89.47%，接受含铂治疗方案患者PFS相对更长，且差异有统计学意义。紫杉醇 + 顺铂 + 氟尿嘧啶（TPF）对比吉西他滨 + 顺铂（GP）和紫杉醇 + 顺铂（TP）显示出更长的PFS，但差异无统计学意义。不同PD-1单抗治疗组间的PFS未显示出有统计学意义的差异。单因素及多因素Cox回归分析结果显示，肿瘤复发状态、初始血浆EBV感染状态、治疗周期数、基线外周血SII是复发/转移性NPC患者接受PD-1抑制剂治疗疗效预测的独立相关因素（均P < 0.05），并且非复发患者、初始血浆EBV DNA阳性、接受 ≥ 4治疗周期、基线外周血SII < 772.81的患者接受PD-1抑制剂治疗预后相对更好。结论：在接受PD-1抑制剂治疗的复发/转移性NPC患者中，非复发患者、初始血浆EBV DNA阳性、≥ 4治疗周期且外周血SII < 772.81者PFS相对更长，可早期识别免疫治疗效果不佳患者并精准干预。

ObjectiveTo delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

Obesity represents a critical global health challenge characterized by a complex pathogenesis involving dysregulated adipogenesis and lipid metabolism. In recent years, long non-coding RNAs (lncRNAs) have been established as crucial regulators in the initiation and progression of obesity. These RNA molecules, typically exceeding 200 nucleotides in length, have emerged as key modulators of various biological processes through multiple molecular mechanisms. This review innovatively defines lncRNAs as “molecular switches” in energy metabolism—they regulate adipogenesis and lipid metabolism through key signaling pathways, and exert bidirectional control over obesity via ceRNA mechanisms or recruitment of chromatin-modifying complexes in tissues such as adipose and liver. Additionally, circulating lncRNAs, owing to their tissue specificity and stability, hold promise as non-invasive liquid biopsy biomarkers for obesity and related metabolic disorders. Furthermore, we systematically summarize lncRNA-based intervention strategies, including targeting pathogenic lncRNAs using antisense oligonucleotides (ASOs) or CRISPR/Cas gene editing systems, utilizing viral vectors (such as adeno-associated virus, AAV) to deliver or mimic beneficial lncRNAs in target tissues, and employing exercise as a non-pharmacological intervention that ameliorates obesity and its related complications at multiple levels, offering novel insights for personalized therapeutic approaches. We also critically assess the current challenges in clinical translation, particularly addressing issues related to delivery efficiency, target specificity, and long-term safety concerns. Future research should focus on the following directions: integrating multi-omics with functional screening to elucidate the regulatory networks of lncRNAs in obesity and its complications; leveraging artificial intelligence to construct predictive models of lncRNA-target gene interactions; developing efficient and safein vivo delivery systems, and optimizing drug design to enhance specificity and safety; establishing highly sensitive detection methods and stable circulating lncRNA biomarkers to enable precise patient stratification and real-time monitoring of therapeutic responses; investigating the synergistic effects of lncRNAs with existing treatments (e.g., GLP-1 receptor agonists, lifestyle interventions) to develop combination therapies and establish a multidimensional, personalized precision medicine framework for obesity. This review aims to provide novel perspectives for understanding the molecular mechanisms underlying obesity and to establish a solid theoretical foundation for developing lncRNA-targeted precision medicine strategies against obesity and its associated metabolic complications.

Obesity represents a critical global health challenge characterized by a complex pathogenesis involving dysregulated adipogenesis and lipid metabolism. In recent years, long non-coding RNAs (lncRNAs) have been established as crucial regulators in the initiation and progression of obesity. These RNA molecules, typically exceeding 200 nucleotides in length, have emerged as key modulators of various biological processes through multiple molecular mechanisms. This review innovatively defines lncRNAs as “molecular switches” in energy metabolism—they regulate adipogenesis and lipid metabolism through key signaling pathways, and exert bidirectional control over obesity via ceRNA mechanisms or recruitment of chromatin-modifying complexes in tissues such as adipose and liver. Additionally, circulating lncRNAs, owing to their tissue specificity and stability, hold promise as non-invasive liquid biopsy biomarkers for obesity and related metabolic disorders. Furthermore, we systematically summarize lncRNA-based intervention strategies, including targeting pathogenic lncRNAs using antisense oligonucleotides (ASOs) or CRISPR/Cas gene editing systems, utilizing viral vectors (such as adeno-associated virus, AAV) to deliver or mimic beneficial lncRNAs in target tissues, and employing exercise as a non-pharmacological intervention that ameliorates obesity and its related complications at multiple levels, offering novel insights for personalized therapeutic approaches. We also critically assess the current challenges in clinical translation, particularly addressing issues related to delivery efficiency, target specificity, and long-term safety concerns. Future research should focus on the following directions: integrating multi-omics with functional screening to elucidate the regulatory networks of lncRNAs in obesity and its complications; leveraging artificial intelligence to construct predictive models of lncRNA-target gene interactions; developing efficient and safein vivo delivery systems, and optimizing drug design to enhance specificity and safety; establishing highly sensitive detection methods and stable circulating lncRNA biomarkers to enable precise patient stratification and real-time monitoring of therapeutic responses; investigating the synergistic effects of lncRNAs with existing treatments (e.g., GLP-1 receptor agonists, lifestyle interventions) to develop combination therapies and establish a multidimensional, personalized precision medicine framework for obesity. This review aims to provide novel perspectives for understanding the molecular mechanisms underlying obesity and to establish a solid theoretical foundation for developing lncRNA-targeted precision medicine strategies against obesity and its associated metabolic complications.

ObjectiveTo investigate the mechanism by which Shaoyaotang regulates the miRNA-155-mediated suppressor of cytokine signaling 1 （SOCS1）/Janus kinase 1 （JAK1）/signal transducer and activator of transcription 1 （STAT1） signaling pathway and thereby affects macrophage polarization. MethodsThe cell-counting kit-8 （CCK-8） assay was used to detect the effect of drug-containing serum of Shaoyaotang at different concentrations on the viability of RAW 264.7 cells. A cell model of inflammation was established by stimulating RAW264.7 cells with lipopolysaccharide （LPS） at a concentration of 10 mg·L^-1 The modeled cells were assigned by the random number table method into seven groups： LPS-induced M1 polarization （model）， M1+miRNA-155 mimics， M1+miRNA-155 inhibitor， M1+Shaoyaotang-containing serum， M1+miRNA-155 mimics+Shaoyaotang-containing serum， M1+miRNA-155 inhibitor+Shaoyaotang-containing serum， and M1+blank serum. Enzyme-linked immunosorbent assay was employed to measure the levels of inflammatory factors ［tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and interleukin-1β （IL-1β）］. Immunofluorescence assay was used to detect the expression of macrophage polarization markers ［inducible nitric oxide synthase （iNOS） and macrophage mannose receptor 1 （CD206）］. Real-time PCR was employed to measure the expression of miRNA-155 in cells. Western blot was performed to determine the protein levels of SOCS1， STAT1， and JAK1. ResultsCompared with the LPS-induced M1 polarization （model） group， the M1+miRNA-155 mimics group showed up-regulated expression of miRNA-155， JAK1， STAT1， TNF-α， IL-6， IL-1β， and iNOS （P<0.05） and down-regulated expression of CD206 （P<0.05）. In both the M1+miRNA-155 inhibitor group and the M1+Shaoyaotang-containing serum group， the expression levels of miRNA-155， JAK1， STAT1， TNF-α， IL-6， IL-1β， and iNOS were down-regulated （P<0.05）， while those of SOCS1 and CD206 were up-regulated （P<0.05）. Compared with the M1+miRNA-155 mimics group， the M1+miRNA-155 mimics+Shaoyaotang-containing serum group showed down-regulated expression of miRNA-155， JAK1， STAT1， TNF-α， IL-6， IL-1β， and iNOS （P<0.05） and up-regulated expression of SOCS1 and CD206 （P<0.05）. Compared with the M1+miRNA-155 inhibitor group， the M1+miRNA-155 inhibitor+Shaoyaotang-containing serum group showed down-regulated expression of miRNA-155， JAK1， STAT1， TNF-α， IL-6， IL-1β， and iNOS （P<0.05） and up-regulated expression of SOCS1 and CD206 （P<0.05）. ConclusionShaoyaotang regulates macrophage polarization by modulating miRNA-155 expression and interfering with the SOCS1/JAK1/STAT1 signaling pathway. The findings provide new experimental evidence for the treatment of ulcerative colitis with Shaoyaotang.

ObjectiveTo investigate the potential role and underlying mechanisms of Shaoyaotang in intervening macrophage glycolytic reprogramming in ulcerative colitis （UC）. MethodsForty-eight C57BL/6 mice were randomly divided into six groups： Normal control group， model group， mesalazine group （0.39 g·kg^-1）， Shaoyaotang group （15.54 g·kg^-1）， 2-deoxy-D-glucose （2-DG） group （glycolysis inhibitor， 100 mg·kg^-1）， and 2-DG + Shaoyaotang combined group （100 mg·kg^-1+15.54 g·kg^-1）. Except for the normal control group， mice in the other five groups were induced to establish UC models using dextran sulfate sodium （DSS）. The normal control group was administered pure water via intragastric gavage， while the other groups received intragastric gavage of mesalazine solution， intragastric gavage of Shaoyaotang， and the 2-DG group was treated with 2-DG via intraperitoneal injection. After 7 consecutive days of treatment， colonic tissues were extracted. Hematoxylin and eosin （HE） staining was performed to evaluate histopathological changes and tissue injury in the colon. Enzyme-linked immunosorbent assay （ELISA） was used to detect the expression of interleukin-10 （IL-10） and tumor necrosis factor-α （TNF-α） in colonic tissues. Western blot analysis was employed to determine the expression levels of hypoxia-inducible factor-1α （HIF-1α）， glucose transporter （GLUT1）， lactate dehydrogenase A （LDHA）， pyruvate kinase M2 （PKM2）， and 6-phosphofructo-2-kinase/fructose-2，6-biphosphatase 3 （PFKFB3） in colonic tissues. Immunofluorescence was conducted to detect the expression of CD206 and inducible nitric oxide synthase （iNOS） in colonic tissues. Liquid chromatography-mass spectrometry （LC-MS） was utilized to measure lactate and citrate levels in colonic tissues. ResultsCompared with the normal control group， mice in the model group exhibited a significant increase in disease activity index （DAI） scores， accompanied by colonic mucosal congestion， edema， and inflammatory cell infiltration， significantly elevated expression of the inflammatory cytokine TNF-α （P<0.05）， significantly decreased IL-10 expression （P<0.05）， significantly increased levels of HIF-1α， GLUT1， LDHA， PKM2， and PFKFB3 in colonic tissues （P<0.05）， markedly elevated iNOS expression （P<0.05）， significantly decreased CD206 expression （P<0.05）， and significantly elevated lactate and citrate levels in colonic tissues （P<0.05）. In contrast to the model group， the Shaoyaotang group， inhibitor group， and Shaoyaotang combined with inhibitor group demonstrated amelioration of mucosal injury in colonic tissues， markely decreased expression levels of the inflammatory cytokine TNF-α （P<0.05）， elevated IL-10 expression levels， significantly decreased expression of HIF-1α， GLUT1， LDHA， PKM2， and PFKFB3 （P<0.05）， markedly reduced iNOS expression levels （P<0.05）， significantly increased CD206 expression （P<0.05） and significantly decreased lactate and citrate levels （P<0.05）. ConclusionShaoyaotang ameliorates symptoms of DSS-induced UC in mice， and its therapeutic mechanism may be associated with regulating macrophage glycolytic reprogramming via modulation of the HIF-1α signaling pathway.

ObjectiveTo investigate the role of microRNA-155-5p （miR-155-5p） in ulcerative colitis （UC） and study the molecular mechanism of Shaoyaotang in the treatment of UC by regulating miR-155-5p. MethodsForty-eight SPF-grade male C57BL/6 mice were selected and assigned via the random number table method into 6 groups （n=8）： A blank control group， a model group， a mesalazine （0.39 g·kg^-1） group， a Shaoyaotang （31.08 g·kg^-1） group， a Janus kinase 1 （JAK1） inhibitor （baricitinib， 10 mg·kg^-1） group， and a Shaoyaotang combined with inhibitor （baricitinib 10 mg·kg^-1 + Shaoyaotang 31.08 g·kg^-1） group. After successful modeling of UC by gavage of 3% dextran sulphate sodium solution， each group received corresponding drug intervention for 7 days. Shaoyaotang and mesalazine were administered by gavage， and baricitinib by intraperitoneal injection. Twenty-four hours after the last administration， mice were anesthetized by intraperitoneal injection of pentobarbital sodium， and blood was collected for determination of white blood cell count and erythrocyte sedimentation rate （ESR）. Mice were then sacrificed for measurement of colon length. Hematoxylin-eosin staining was used to observe colonic pathological changes and perform pathological scoring. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was employed to determine the relative expression of miR-155-5p in the colonic tissue， and Western blot was used to determine the protein levels of JAK1， phosphorylated JAK1 （p-JAK1）， suppressor of cytokine signaling 1 （SOCS1）， signal transducer and activator of transcription 1 （STAT1）， and phosphorylated STAT1 （p-STAT1）. ResultsCompared with the blank control group， the model group showed increased disease activity index （DAI） score and pathological score， shortened colon， upregulated relative expression of miR-155-5p and protein levels of p-JAK1 and p-STAT1， downregulated protein level of SOCS1 in the colonic tissue， prolonged time of erythrocyte sedimentation， and increased white blood cell count （P<0.01）. Compared with the model group， all drug-treated groups exhibited improvements in the above indicators （P<0.01）. Moreover， the Shaoyaotang group showed better therapeutic effects than the mesalazine group in regulating miR-155-5p expression， related protein levels， DAI score， and colonic pathological score （P<0.01）. ConclusionShaoyaotang may downregulate miR-155-5p to relieve its inhibition on SOCS1， thereby suppressing the excessive activation of the JAK1/STAT1 signaling pathway and ultimately alleviating intestinal inflammatory damage.