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.

AIM:To analyze the efficacy of modified Zhujing formula combined with intravitreal ranibizumab(IVR)injection in the treatment of wet age-related macular degeneration(wARMD).METHODS: A prospective study was conducted on wARMD patients at the Ophthalmology Department of Yulin Hospital of Traditional Chinese Medicine from September 2022 to October 2024. The study subjects were divided into the experimental group and the control group according to the random number table method. The control group received IVR treatment, while the experimental group was treated with modified Zhujing formula in addition to IVR injection. The clinical efficacy, TCM symptom scores, central retinal thickness(CRT), best corrected visual acuity(BCVA), macular hemorrhage area, choroidal neovascularization area(CNV), ocular hemodynamic parameters [resistance index(RI), maximum diastolic blood flow(EDV), maximum systolic blood flow(PSV)], and 1-year recurrence rate were compared between the two groups.RESULTS: This study included 60 eyes from 60 wARMD patients. Among them, the control group consisted of 30 patients and 30 eyes, while the experimental group consisted of 30 patients and 30 eyes. The age of the control group was 67.52±3.12 y, with 17 males and 13 females. The age of the experimental group was 67.62±3.04 y, with 18 males and 12 females.The clinical efficacy of the experimental group(97%)was higher than that of the control group(73%)(P<0.05). After treatment, the scores of blurred vision, soreness and weakness of the waist and knees, restlessness and insomnia, dizziness and tinnitus in the experimental group were all lower than those in the control group(all P<0.05); the EDV and PSV in the experimental group were both higher than those in the control group(both P<0.05); the BCVA, CRT, macular hemorrhage area, CNV and RI of the experimental group were all lower than those of the control group(all P<0.05), and the 1-year recurrence rate in the experimental group(3%)was lower than that in the control group(27%)(P<0.05). CONCLUSION:The combined use of modified Zhujing formula and IVR can effectively alleviate symptoms such as blurred vision and retinal hemorrhage in wARMD patients, improve vision and ocular hemodynamic conditions, and reduce the recurrence rate. This suggests that there may be a synergistic enhancing effect.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Objective To develop and validate a prediction model for in-hospital recurrent intensive care unit (ICU) admission in critically ill patients with ischemic stroke (IS) based on machine learning (ML) algorithms. Methods Clinical data from 2 929 IS patients were included from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Least absolute shrinkage and selection operator (LASSO) regression was used to identify predictive factors, and the synthetic minority over-sampling technique (SMOTE) was employed to create a derivation cohort comprising 2 583 patients. These patients were randomly divided into a training set (n=2 066) and a test set (n=517) at an 8:2 ratio. Five ML algorithms, including decision tree, random forest, adaptive boosting (AdaBoost), gradient boosting decision tree (GBDT), and support vector machine (SVM), were performed to construct prediction models. Five-fold cross-validation was used to evaluate the performance of the model in the training set. The area under the receiver operating characteristic curve (ROC-AUC) and decision curve analysis (DCA) were used to assess and compare the models in the testing set. The best-performing model was interpreted by shapley additive explanations (SHAP). Results Among the 2 929 patients included, 704 (24.0%) experienced in-hospital recurrent ICU admission. Among the five ML models, the random forest model demonstrated the best predictive performance, with an AUC of 0.839 (95%CI 0.801–0.877). Feature importance analysis identified five most significant features affecting model prediction, including APS Ⅲ score, albumin, age, heart rate, and SOFA score. Conclusions ML-based models can effectively predict the risk of in-hospital recurrent ICU admission in critically ill patients with IS. The random forest model showed superior predictive performance, which may have potential applications in early clinical risk stratification and intervention.

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 analyze the incidence rate and risk factors of atrial fibrillation (AF) in elderly patients with chronic obstructive pulmonary disease (COPD). Methods A total of 392 patients with COPD in the hospital were selected from December 2020 to December 2024. Patients' data (medical history, echocardiographic data, etc.) were recorded. The incidence rate of AF in patients was recorded and the patients were grouped according to whether or not they developed AF. The differences were compared between the two groups, and the risk factors of AF occurrence in elderly patients with COPD were analyzed. Results Among the 392 patients with COPD, 127 cases (32.40%) met the diagnostic criteria of AF. There were statistically significant differences in age, pulmonary infection, heart failure, diabetes, smoking history, disease duration, LAD, severe renal insufficiency and coronary heart disease between the AF group and the non-AF group (P<0.05). Multivariate logistic regression analysis suggested that age, pulmonary infection, heart failure, diabetes mellitus, smoking history, disease course, LAD, severe renal insufficiency and coronary heart disease were all risk factors for elderly patients with COPD (OR=1.129, 4.246, 3.955, 4.125, 2.038, 1.112, 1.102, 4.397, and 3.865, P<0.05). Conclusion The incidence rate of AF is high in elderly patients with COPD. Age, pulmonary infection, heart failure, diabetes mellitus, smoking history, course of disease, LAD, severe renal insufficiency, and coronary heart disease are all risk factors for AF.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

Brucellosis is one of the most widespread zoonoses globally, which poses serious threats to both global public health and development of animal husbandry. Conventional brucellosis control measures suffer problems of surveillance coordination, regional joint prevention, and policy implementation, which are insufficient to address the challenges of ecological risks and crosshost transmission. The One Health approach allocates interdisciplinary and intersectoral collaborations to achieve systemic health of humans, animals, and environments, which provides new insights into brucellosis control programmes. This review describes the pathogenic biological characteristics, global epidemiological landscape, and transmission ecology of brucellosis, evaluates the main limitations of current control strategies, summarizes the experiences from successful One Health practices across countries at different stages of development, and proposes the brucellosis control strategy based on the One Health concept with adaptations to the current epidemiology of brucellosis in China, so as to provide the theoretical evidence and practical framework for the national brucellosis control programmes in China, thereby facilitating the effective control and the ultimate elimination of brucellosis.

Collagen is a major structural protein in the matrix of animal cells and the most widely distributed and abundant functional protein in mammals. Collagen’s good biocompatibility, biodegradability and biological activity make it a very valuable biomaterial. According to the source of collagen, it can be broadly categorized into two types: one is animal collagen; the other is recombinant collagen. Animal collagen is mainly extracted and purified from animal connective tissues by chemical methods, such as acid, alkali and enzyme methods, etc. Recombinant collagen refers to collagen produced by gene splicing technology, where the amino acid sequence is first designed and improved according to one’s own needs, and the gene sequence of improved recombinant collagen is highly consistent with that of human beings, and then the designed gene sequence is cloned into the appropriate vector, and then transferred to the appropriate expression vector. The designed gene sequence is cloned into a suitable vector, and then transferred to a suitable expression system for full expression, and finally the target protein is obtained by extraction and purification technology. Recombinant collagen has excellent histocompatibility and water solubility, can be directly absorbed by the human body and participate in the construction of collagen, remodeling of the extracellular matrix, cell growth, wound healing and site filling, etc., which has demonstrated significant effects, and has become the focus of the development of modern biomedical materials. This paper firstly elaborates the structure, type, and tissue distribution of human collagen, as well as the associated genetic diseases of different types of collagen, then introduces the specific process of producing animal source collagen and recombinant collagen, explains the advantages of recombinant collagen production method, and then introduces the various systems of expressing recombinant collagen, as well as their advantages and disadvantages, and finally briefly introduces the application of animal collagen, focusing on the use of animal collagen in the development of biopharmaceutical materials. In terms of application, it focuses on the use of animal disease models exploring the application effects of recombinant collagen in wound hemostasis, wound repair, corneal therapy, female pelvic floor dysfunction (FPFD), vaginal atrophy (VA) and vaginal dryness, thin endometritis (TE), chronic endometritis (CE), bone tissue regeneration in vivo, cardiovascular diseases, breast cancer (BC) and anti-aging. The mechanism of action of recombinant collagen in the treatment of FPFD and CE was introduced, and the clinical application and curative effect of recombinant collagen in skin burn, skin wound, dermatitis, acne and menopausal urogenital syndrome (GSM) were summarized. From the exploratory studies and clinical applications, it is evident that recombinant collagen has demonstrated surprising effects in the treatment of all types of diseases, such as reducing inflammation, promoting cell proliferation, migration and adhesion, increasing collagen deposition, and remodeling the extracellular matrix. At the end of the review, the challenges faced by recombinant collagen are summarized: to develop new recombinant collagen types and dosage forms, to explore the mechanism of action of recombinant collagen, and to provide an outlook for the future development and application of recombinant collagen.

AIM: To evaluate the effectiveness and safety of compound anisodine combined with laser photocoagulation in the treatment of diabetic retinopathy(DR).METHODS: A prospective cohort study was used to select 80 patients(160 eyes)diagnosed with severe non-proliferative diabetic retinopathy(NPDR)and proliferative diabetic retinopathy(PDR)in Beijing Tongren Hospital, Capital MedTcal University and Beijing Daxing District People's Hospital from May 2023 to July 2023. They were divided into control group(40 cases, 80 eyes)and observation group(40 cases, 80 eyes)by random number table method. The control group only received 532 nm laser panretinal photocoagulation(PRP)treatment, while the observation group received PRP treatment together with superficial temporal subcutaneous injection of compound anisodine. The clinical efficacy, changes in hemorheology, changes in retinal blood vessels, and incidence of adverse reactions in the two groups were observed before and at 2 mo after treatment.RESULTS: The visual acuity, fundus changes and hemorheological parameters of the two groups were analyzed before and after treatment. There were no significant differences in the two groups before treatment(all P>0.05). The best corrected visual acuity of the observation group was better than that of the control group at 2 mo after treatment(P<0.05), and the clinical curative effect of fundus was also better than that of the control group(all P<0.05). The hemorheological indexes of central retinal artery blood flow(peak systolic velocity and end diastolic velocity)in the observation group were higher than those of the control group(all P<0.05), and the blood flow resistance index was lower than that of the control group(P<0.05).CONCLUSION: Compound anisodine combined with 532 nm laser photocoagulation is safe and effective in the treatment of DR, and the visual recovery effect is better.