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.

As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Objective To investigate the relationship of skin failure (SF) with nutritional status in elderly critically ill patients and analyze the predictive efficiency of nutritional status on SF. Methods A total of 340 elderly critically ill patients admitted to the hospital from January 2020 to January 2025 were selected as research subjects. According to whether skin failure occurred, the above patients were classified into skin failure group and non-skin failure group. The nutritional status indicators [serum albumin (ALB), prealbumin (PA), total protein (TP), hemoglobin (Hb), body mass index (BMI), nutritional risk score (NRS 2002)] were compared between both groups. Multivariate analysis was performed on statistically significant indicators, and ROC curve was applied to analyze the predictive value. Results Among the 340 elderly critically ill patients, 142 cases (41.76%) developed skin failure. The ALB, PA, TP, Hb and BMI in the skin failure group were lower than those in the non-skin failure group (P<0.05) while the NRS2002 score was higher (P<0.05). After logistic multivariate analysis, ALB, PA and Hb were independent influencing factors of skin failure (P<0.05). ROC curve analysis revealed that the predictive value of ALB (AUC=0.850, 95%CI: 0.808-0.888, Z=-3.707, P<0.001) was better than that of PA (AUC=0.770, 95%CI: 0.717-0.816, Z=-3.100, P=0.002) or Hb (AUC=0.773, 95%CI: 0.722-0.819, Z=-2.556, P=0.011). Conclusion The occurrence of skin failure in elderly critically ill patients is closely related to nutritional status. ALB, PA and Hb are independent risk factors of SF, and ALB has the best predictive efficiency on SF.

BACKGROUND/OBJECTIVES: Deoxyshikonin (DSK) has been reported to inhibit tumor growth in various types of cancers, but its roles and action mechanisms in breast cancer (BC) are unclear. This study examined the anti-cancer function and mechanism of DSK in BC.MATERIALS/METHODS: MDA-MB-231 and BT549, human BC cells, were used. The cell viability and apoptosis levels were examined using Cell Counting Kit-8 experiments and flow cytometry, respectively. The expression of apoptosis-related factors (Ki-67, Bax, and Bcl-2), CD206, CD168, and proteins involved in the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)uclear factor (NF)-κB pathway was evaluated by Western blot analysis. The cell invasion ability was determined using the Transwell experiment. The levels of interleukin (IL)-10 and transforming growth factor (TGF)-β were detected using an enzyme-linked immunosorbent assay. The in vivo functions of DSK were assessed using a xenograft mouse model. RESULTS: DSK inhibited cell proliferation, enhanced cell apoptosis, and reduced the cell invasion of MDA-MB-231 and BT549 cells. DSK also reduced the levels of CD206 and CD168 proteins, as well as IL-10 and TGF-β in phorbol 12-myristate 13-acetate-induced THP-1 cells.DSK downregulated the expression of the phosphorylated (p)-PI3K, p-AKT, and p-NF-κB proteins in cells. These effects were reversed by 740 Y-P (PI3K/AKT activator). In addition, DSK significantly reduced the tumor volume and weight in a xenograft mouse model. DSK increased the level of cell apoptosis and decreased the expression of Ki-67 and CD206 in subcutaneous tumor tissue. DSK also inactivated the PI3K/AKT/NF-κB pathway proteins. CONCLUSION DSK inhibits the proliferation, invasion, and tumor immune microenvironment of BC cells by inactivating the PI3K/AKT/NF-κB pathway, indicating that DSK may be a potential therapeutic option for BC treatment.

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.

Definitive chemoradiotherapy (dCRT) has become a cornerstone in the treatment of locally advanced esophageal cancer; however, local control remains suboptimal, and persistent lesions or locoregional recurrences after treatment are not uncommon. For patients without distant metastases but with local failure, whether surgical intervention can still offer curative potential remains a major clinical dilemma. Salvage esophagectomy (SE) offers potential long-term survival for selected patients, but this procedure is performed in the context of severe fibrosis, impaired local blood supply, and obscured anatomical planes following chemoradiotherapy, resulting in significantly higher perioperative risk compared to primary esophagectomy. Consequently, controversies exist regarding patient selection, preoperative restaging, choice of surgical approach, extent of lymphadenectomy, gastrointestinal reconstruction, and perioperative management. In recent years, with the refinement of restaging modalities such as PET/CT, the accumulation of experience in high-volume centers, and emerging evidence from clinical studies, the clinical role of SE has gradually shifted from a "high-risk salvage measure" to a "selective curative strategy aimed at achieving long-term survival in carefully selected patients". Nevertheless, standardized guidelines for patient selection, technical approaches, and perioperative management are still lacking. Based on current evidence and clinical experience, experts organized by the Integrated Esophageal Cancer Committee of Chinese Anti-Cancer Association systematically reviewed key issues regarding SE, including its definition, indications, preoperative evaluation, choice of surgical approach, lymphadenectomy, gastrointestinal reconstruction, and perioperative management, and formulated a Chinese expert consensus. This consensus aims to provide guidance for standardized assessment, appropriate referral, individualized surgical decision-making, and optimized perioperative management of patients with locoregional failure after dCRT. Ultimately, this will increase the likelihood of R0 resection, reduce the risk of severe complications, and promote the safer, more judicious, and standardized implementation of SE in high-risk scenarios.

With the aging population and the widespread implementation of lung cancer screening programs, an increasing number of elderly patients are undergoing curative lung resection. Due to diminished physiological reserve and complex comorbidities, this demographic exhibits a significantly higher incidence of severe perioperative complications (defined as Clavien-Dindo grade≥Ⅲ), which adversely affects both perioperative safety and long-term prognosis. In recent years, the research paradigm has shifted from univariate analysis toward multidimensional risk integration and the development of predictive models. This article systematically reviews the key risk factors for severe perioperative complications in elderly lung cancer patients, encompassing biological aging processes, frailty and sarcopenia, cardiopulmonary and renal functional reserves, inflammatory-immune and coagulation status, and perioperative interventions. Furthermore, it traces the evolution of risk assessment tools from traditional regression models to machine learning models that integrate multimodal data. The review also discusses common challenges in this field, including the standardization of outcome definitions, external validation, calibration assessment, and clinical translation. Future efforts should prioritize the deep integration of predictive tools with clinical decision support systems to establish a closed-loop care pathway from risk identification to stratified intervention, thereby effectively reducing complication rates and enhancing surgical outcomes for elderly lung cancer patients.

A 71-year-old male presented with esophageal cancer and severe aortic valve regurgitation. Treatment strategies for such patients are controversial. Considering the risks of cardiopulmonary bypass and potential esophageal cancer metastasis, we successfully performed transcatheter aortic valve implantation and minimally invasive three-incision thoracolaparoscopy combined with radical resection of esophageal cancer (McKeown) simultaneously in the elderly patient who did not require neoadjuvant treatment. This dual minimally invasive procedure took 6 hours and the patient recovered smoothly without any surgical complications.

Objective::Elderly individuals are at high risk for stroke. With China transitioning into an aging society, it is essential to implement measures to prevent stroke in the middle-aged and elderly. This study aimed to investigate the prevalence and associated factors of stroke in middle-aged and older Chinese individuals using national survey data from the China Health and Retirement Longitudinal Study.Methods::This cross-sectional study used data from the 2015 China Health and Retirement Longitudinal Survey. Participants without complete data on stroke and its associated factors—including demographics, health behaviors, and disease-related factors—were excluded. Independent samples t-test and χ2 test were used to examine differences in associated factors between the stroke and non-stroke groups. Variables with P-values ≤0.1 in all univariate comparisons were included in the final binary logistic regression model to identify the independent factors associated with stroke. Results::A total of 11,969 participants were included in this study. The prevalence of stroke in middle-aged and older individuals in China was 2.170%. The most significant factors associated with stroke included smoking (odds ratio (OR): 1.471, 95% confidence interval (CI): 1.132-1.913), alcohol consumption (OR: 0.548, 95%CI: 0.405-0.743), nap time ≥30 min and < 60 min (OR: 0.502, 95%CI: 0.296-0.851), nap time ≥60 min and <90 min (OR: 0.703, 95%CI: 0.505-0.978), hypertension (OR: 3.310, 95%CI: 2.515-4.357), dyslipidemia (OR: 1.874, 95%CI: 1.446-2.428), and diabetes (OR: 1.424, 95%CI: 1.052-1.927).Conclusion::This study reveals a high prevalence of stroke in middle-aged and older people in China. Several factors, including smoking, alcohol consumption, nap time, hypertension, dyslipidemia, and diabetes, were identified as significant associated factors of stroke prevalence in this population. These findings can inform the development of stroke prevention strategies and health planning for middle-aged and older adults and provide insights for future research.

Objective::Elderly individuals are at high risk for stroke. With China transitioning into an aging society, it is essential to implement measures to prevent stroke in the middle-aged and elderly. This study aimed to investigate the prevalence and associated factors of stroke in middle-aged and older Chinese individuals using national survey data from the China Health and Retirement Longitudinal Study.Methods::This cross-sectional study used data from the 2015 China Health and Retirement Longitudinal Survey. Participants without complete data on stroke and its associated factors—including demographics, health behaviors, and disease-related factors—were excluded. Independent samples t-test and χ2 test were used to examine differences in associated factors between the stroke and non-stroke groups. Variables with P-values ≤0.1 in all univariate comparisons were included in the final binary logistic regression model to identify the independent factors associated with stroke. Results::A total of 11,969 participants were included in this study. The prevalence of stroke in middle-aged and older individuals in China was 2.170%. The most significant factors associated with stroke included smoking (odds ratio (OR): 1.471, 95% confidence interval (CI): 1.132-1.913), alcohol consumption (OR: 0.548, 95%CI: 0.405-0.743), nap time ≥30 min and < 60 min (OR: 0.502, 95%CI: 0.296-0.851), nap time ≥60 min and <90 min (OR: 0.703, 95%CI: 0.505-0.978), hypertension (OR: 3.310, 95%CI: 2.515-4.357), dyslipidemia (OR: 1.874, 95%CI: 1.446-2.428), and diabetes (OR: 1.424, 95%CI: 1.052-1.927).Conclusion::This study reveals a high prevalence of stroke in middle-aged and older people in China. Several factors, including smoking, alcohol consumption, nap time, hypertension, dyslipidemia, and diabetes, were identified as significant associated factors of stroke prevalence in this population. These findings can inform the development of stroke prevention strategies and health planning for middle-aged and older adults and provide insights for future research.