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.

Colorectal cancer (CRC) poses a severe global health challenge with high incidence and mortality rates. USP37 has been identified as the bona fide deubiquitinase of SND1, playing a critical role in stabilizing SND1, thereby augmenting its oncogenic potential. The interaction between USP37 and SND1 was confirmed through extensive proteomics, ubiquitinomics, and interactomics, underscoring their synergistic effects on CRC proliferation and metastasis. Additionally, CDK1 has emerged as a pivotal regulator of USP37, phosphorylating it at threonine 631 rather than serine 628, enhancing its deubiquitinase activity, and consequently stabilizing SND1 to drive CRC malignancy further. Histological analyses of human CRC samples linked the upregulation of CDK1 and USP37 with increased SND1 levels and poor patient prognosis. High-throughput virtual screening and subsequent experimental validation identified Dacarbazine as a pharmacological inhibitor of USP37, and its inhibition disrupted SND1 stability, hindering CRC cell proliferation and metastasis. This study reveals a novel and promising molecular mechanism driving CRC progression through the CDK1-USP37-SND1 axis, highlighting the clinical importance of targeting this pathway to improve patient outcomes.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation and joint damage, accompanied by the accumulation of plasma cells, which contributes to its pathogenesis. Understanding the genetic alterations occurring during plasma cell differentiation in RA can deepen our comprehension of its pathogenesis and guide the development of targeted therapeutic interventions. Here, our study elucidates the intricate molecular mechanisms underlying plasma cell differentiation by demonstrating that PRDX1 interacts with DOK3 and modulates its degradation by the autophagy-lysosome pathway. This interaction results in the inhibition of plasma cell differentiation, thereby alleviating the progression of collagen-induced arthritis. Additionally, our investigation identifies Salvianolic acid B (SAB) as a potent small molecular glue-like compound that enhances the interaction between PRDX1 and DOK3, consequently impeding the progression of collagen-induced arthritis by inhibiting plasma cell differentiation. Collectively, these findings underscore the therapeutic potential of developing chemical stabilizers for the PRDX1-DOK3 complex in suppressing plasma cell differentiation for RA treatment and establish a theoretical basis for targeting PRDX1-protein interactions as specific therapeutic targets in various diseases.

OBJECTIVES: To analyze the differentially expressed exosomal miRNAs in patients with chronic heart failure (CHF) complicated by hyperuricemia (HUA) and explore their potential as novel diagnostic molecular markers and their target genes. METHODS: This study was conducted among 30 CHF patients with HUA (observation group) and 30 healthy volunteers (control group) enrolled between September, 2020 and September, 2023. Peripheral blood samples were collected from 6 CHF patients with HUA for analyzing exosomal miRNAs by high-throughput sequencing, and the results were validated in the remaining 24 patients using qRT-PCR. GO and KEGG enrichment analyses were performed to predict the the target genes of the identified differential miRNAs. We also validated the differentially expressed miRNAs by animal experiment. RESULTS: A total of 42 differentially expressed exosomal miRNAs were detected in observation group by high-throughput sequencing; among them, miR-27a-5p was significantly upregulated (P=0.000179), and miR-139-3p was significantly downregulated (P=0.000058). In the 24 patients with both CHF and PUA, qRT-PCR validated significant upregulation of miR-27a-5p (P=0.004) and downregulation of miR-139-3p (P=0.005) in serum exosomes. When combined, miR-27a-5p and miR-139-3p had a maximum area under the curve (AUC) of 0.899 (95% CI: 0812-0.987) for predicting CHF complicated by HUA. GO and KEGG enrichment analyses suggested that the differential expressions of miR-27a-5p and miR-139-3p was associated with the activation of the AMPK-mTOR signaling pathway to activate the autophagic response. We obtained the same conclusion from animal experiment. CONCLUSIONS Upregulated exosomal miR-27a-5p combined with downregulated exosomal miR-139-3p expression can serve as a novel molecular marker for diagnosis of CHF complicated by HUA, and their differential expression may promote autophagy in cardiomyocytes by activating the AMPK-mTOR signaling pathway.
Humans ; Hyperuricemia/diagnosis* ; Heart Failure/genetics* ; MicroRNAs/metabolism* ; Exosomes/metabolism* ; Chronic Disease ; Male ; Female ; Middle Aged ; Animals

This study employed 16S r RNA gene high-throughput sequencing and metabolomics to explore the mechanism of Angelicae Dahuricae Radix polysaccharides(RP) in the treatment of ulcerative colitis(UC). A mouse model of UC was induced with 2. 5% dextran sulfate sodium. The therapeutic effects of RP on UC in mice were evaluated based on changes in body weight, disease activity index( DAI), and colon length, as well as pathological changes. RT-qPCR was performed to assess the m RNA levels of interleukin(IL)-6, IL-1β, tumor necrosis factor(TNF)-α, myeloperoxidase(MPO), mucin 2(Muc2), Occludin, Claudin2, and ZO-1 in the mouse colon tissue. ELISA was employed to measure the expression of IL-1β and TNF-α in the colon tissue. The intestinal permeability of mice was evaluated by the fluorescent dye permeability assay. Immunohistochemistry was employed to detect the expression of Muc2 and occludin in the colon tissue. Changes in gut microbiota and metabolites were analyzed by 16S r RNA sequencing and ultra-high-performance liquid chromatography coupled with quadrupole-orbitrap mass spectrometry( UPLC-Q-Exactive Plus Orbitrap MS), respectively. The results indicated that low-dose RP alleviated general symptoms, reduced colonic inflammation and intestinal permeability, and promoted Muc2 secretion and tight junction protein expression in UC mice. In addition, low-dose RP increased gut microbiota diversity in UC mice and decreased the relative abundance of harmful bacteria such as Ochrobactrum and Streptococcus. Twenty-seven differential metabolites were identified in feces, and low-dose RP restored the levels of disturbed metabolites. Notably, arginine and proline metabolism were the most significantly altered amino acid metabolic pathways following lowdose RP intervention. In conclusion, RP can ameliorate general symptoms, inhibit colonic inflammation, and maintain intestinal mucosal barrier integrity in UC mice by modulating gut microbiota composition and arginine and proline metabolism.
Animals ; Gastrointestinal Microbiome/drug effects* ; Colitis, Ulcerative/genetics* ; Mice ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Polysaccharides/administration & dosage* ; Angelica/chemistry* ; Humans ; Colon/metabolism* ; Disease Models, Animal ; Mucin-2/metabolism* ; Tumor Necrosis Factor-alpha/metabolism*

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures

PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

Objective:To analyze the associated factors and cumulative effects of cardiometabolic multimorbidity (CMM) among residents in southern Xinjiang.Methods:A stratified random cluster sampling method was used to conduct questionnaire surveys, physical examinations and laboratory tests among the personnel of the 51st Brigade, 3rd Division, Xinjiang, in 2016. The multivariate logistic regression, multivariate linear regression, restricted cubic spline, and network analysis methods were used to study the association of lifestyle (smoking, alcohol consumption and physical activity), socioeconomic (occupation, education and marital status) and clinical factors (waist circumference, body mass index and family history) with CMM.Results:A total of 12 773 study subjects were included. The prevalence of cardiovascular metabolic diseases among residents in southern Xinjiang was 52.49%. Specifically, the prevalence rates of dyslipidemia, hypertension, coronary heart disease, diabetes, and stroke were 31.14%, 29.95%, 6.78%, 6.26%, and 2.47%, respectively, and the prevalence of CMM was 19.06%. Multivariate logistic regression analysis revealed that the associations between clinical and socioeconomic factors and CMM significantly increased with higher scores. Specifically, the OR rose from 1.75 (clinical factors) and 1.07 (socioeconomic factors) on a score of 1 to 4.41 and 1.93 on a score of 3, respectively. The association between lifestyle factors and CMM was only observed at higher scores ( OR=1.26, 95% CI:1.07~1.62). The trend test using the scores of each group as continuous variables in the model showed that the risk of disease increased with the accumulation of clinical, socioeconomic and lifestyle factors (all P<0.05). Restricted cubic spline analysis demonstrated a non-linear relationship between the total number of associated factors and CMM ( Poverall<0.05 and Pnon-linear<0.05). Network analysis identified hypertension (strength=0.42) as the “core node” among the five diseases. When analyzing the three types of influencing factors, hypertension (strength=0.68), dyslipidemia (strength=0.47), coronary heart disease (strength=0.37), and clinical factors (strength=0.53) emerged as “core nodes”. In the network of nine associated factors, abnormal waist circumference and BMI (strength=0.90 and 0.84) were identified as “key factors”, while hypertension (strength=0.68) and dyslipidemia (strength=0.52) were identified as “key diseases”. Conclusion:The prevalence of CMM among residents in southern Xinjiang is high, and there is a cumulative effect of multiple factors. Hypertension and dyslipidemia are key diseases in the multimorbidity network, while abnormal BMI and waist circumference are key associated factors.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.