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.

OBJECTIVE To confirm trigger items for adverse drug reaction （ADR） induced by bevacizumab， to identify and analyze the occurrence of related ADR， and to establish a predictive model for severe adverse reaction （SAR） caused by this drug. METHODS Based on the global trigger tool （GTT） theory， and referencing the GTT White Paper， drug package inserts and relevant literature， trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items， electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects （divided into training and test sets at a ratio of 7∶3）， candidate feature variables were selected from 39 related variables using the Boruta algorithm， and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features， Logistic Regression， Extreme Gradient Boosting， Light Gradient Boosting Machine， Random Forest， and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve （AUC） of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations （SHAP） method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined， comprising 17 laboratory indicators， 13 clinical manifestations， and 8 intervention measures. In total， 483 patients with positive trigger items were included， and 318 patients with bevacizumab-induced ADR were identified， including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% （708/1 625） and 63.84% （318/483）， respectively. Bevacizumab-induced ADR involved 7 systems/organs， with the hematological system being the most frequently involved （64.15%）. The Boruta algorithm selected 7 vari ables： serum potassium， hematocrit， albumin-to-globulin ratio， prealbumin， hypertension history， age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR （OR＝0.234， P ＝0.002）， while a history of hypertension （OR＝2.642， P ＝0.006） and increased age （OR＝1.040， P ＝0.025） were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC， F1 score and recall rate （0.761， 0.447， 0.607）， compared to other models. SHAP evaluation results indicated that variables such as serum potassium， hematocrit， and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR， whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

Central sensitization(CS) is an important factor in inducing neuropathic pain(NPP), and the association between signal transduction protein 1(Epac1) and piezoelectric type mechanosensitive ion channel component 2(Piezo2) is a new and significant pathway for initiating CS. This study whether the central analgesic effect of Maxiong Powder is achieved through the synchronized regulation of the Epac1-Piezo2 signaling pathway in the medial habenular nucleus(MHb) and interpeduncular nucleus(IPN) of the brain. Dynamic in vivo microdialysis, combined with high-performance liquid chromatography-fluorescence detection(HPLC-RFC), behavioral assessments, immunohistochemistry, Western blot, and quantitative reverse transcription PCR, were employed in rats with partial sciatic nerve injury(SNI) to investigate the distribution and expression of Epac1 and Piezo2 proteins and genes in the MHb and IPN regions, and the changes in the extracellular levels of glutamate(Glu), aspartic acid(Asp), and glycine(Gly). Compared with the sham group, rats in the SNI group showed significantly reduced analgesic activity, a significant increase in cold pain sensitivity scores, and elevated Glu levels in the MHb and IPN regions. Additionally, the number of Piezo2-positive cells in these regions, as well as the expression levels of Epac1 and Piezo2 proteins and genes, were significantly increased. Compared with the SNI group, after Maxiong Powder administration, the analgesic activity in rats significantly increased, and cold pain sensitivity scores were significantly reduced. Maxiong Powder also significantly decreased the Glu content in the MHb and IPN regions and the Gly content in the MHb region, while significantly increasing the Asp content in both regions. Furthermore, Maxiong Powder significantly reduced the number of Piezo2-positive cells and lowered the protein and gene expression levels of Epac1 and Piezo2 in both brain regions. The central analgesic effect of Maxiong Powder may be related to its inhibition of Glu and Gly release in the extracellular fluid of the MHb and IPN regions, the increase of Asp levels in these regions, and the regulation of the Epac1-Piezo2 pathway through the reduction of Epac1 and Piezo2 protein and gene expression. These results provide partial scientific evidence for the clinical analgesic efficacy of Maxiong Powder and offer new ideas and approaches for the clinical treatment of NPP.
Animals ; Neuralgia/genetics* ; Rats ; Signal Transduction/drug effects* ; Male ; Rats, Sprague-Dawley ; Guanine Nucleotide Exchange Factors/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Habenula/drug effects* ; Ion Channels/genetics* ; Humans

Based on the ultra performance liquid chromatography-quadrupole Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology, combined with related literature, databases, and reference material information, this study qualitatively analyzed the components of Dayuanyin in the tissue of rats after gavage and employed molecular docking technology to predict the rationality of the mechanism behind the antipyretic effect of the in vivo components in Dayuanyin. A total of 21, 26, 20, 21, 14, and 31 prototype components and 3, 16, 3, 7, 5, and 24 metabolites were identified from the heart, liver, spleen, lung, kidney, and hypothalamus of the rats, respectively, and the binding ability of key components and targets was further verified by molecular docking. The results showed that all components had good binding ability with targets. The established UPLC-Q-Exactive Orbitrap-MS could effectively and quickly identify the Dayuanyin components distributed in tissue and preliminarily identify their metabolites. Many components were identified in the hypothalamus, which suggested that the components delivered to the brain should be focused on in the study on Dayuanyin in the treatment of febrile diseases. The molecular docking technology was used to predict the rationality of the mechanism behind its antipyretic effect, which lays the foundation for the clarification of the material basis and action mechanism of Dayuanyin, the development of new preparations, and the prediction of quality markers.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Molecular Docking Simulation ; Male ; Antipyretics/metabolism* ; Rats, Sprague-Dawley ; Tissue Distribution ; Mass Spectrometry ; Chromatography, High Pressure Liquid ; Hypothalamus/metabolism*

The quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.
Drugs, Chinese Herbal/chemistry* ; Biosensing Techniques/methods* ; TRPV Cation Channels/chemistry* ; Tablets/chemistry* ; Receptors, G-Protein-Coupled/genetics* ; Quality Control ; Taste ; Humans ; Mass Spectrometry

This study established the HPLC fingerprints and a multi-component content determination method for Bidens pilosa var. radiata and B. pilosa and conducted comprehensive evaluation by integrating fingerprint similarity comparison, cluster analysis(CA), and principal component analysis(PCA), aiming to provide a reference for the establishment of quality standards for Bidentis Herba. HPLC was launched on an Agilent Poroshell 120 EC-C_(18) chromatographic column(4.6 mm×250 mm, 4 μm) by gradient elution with a mobile phase of 0.1% aqueous phosphoric acid-acetonitrile at a flow rate of 0.7 mL·min~(-1), detection wavelength of 270 nm, column temperature of 25 ℃, and an injection volume of 5 μL. The fingerprint similarity of 20 batches of Bidentis Herba ranged from 0.775 to 0.979. A total of 20 common peaks were identified, and seven components were confirmed through comparison with reference substances: neochlorogenic acid, chlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, isochlorogenic acid C, rutin, and hyperoside. These seven components exhibited good linearity within the ranges of 3.4-67.4, 33.0-660.3, 26.6-531.2, 3.5-70.5, 6.2-124.9, 2.4-48.3, and 4.6-91.5 μg·mL~(-1), respectively, with correlation coefficients(r) greater than 0.999. The average recovery rates ranged from 96.47% to 104.6%. CA and PCA classified the 20 batches of Bidentis Herba into two categories. PCA yielded two principal components, with a cumulative variance contribution rate of 80.557%. The established HPLC fingerprints and multi-component content determination method are simple and accurate, providing a scientific basis for the quality control and quality standard formulation of Bidentis Herba.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Chemometrics/methods* ; Bidens/chemistry* ; Principal Component Analysis

In this study, the pharmacodynamic components and potential pharmacological functions of Danzhi Xiaoyao Formula in treating nervous system diseases were investigated by hippocampal component characterization and network pharmacology. After rats were administrated with Danzhi Xiaoyao Formula by gavage, high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry(HPLC-Q-TOF-MS/MS) was employed to explore the components in the hippocampus of rats. Fifty-seven components were identified in the hippocampus of rats by comparing the extract of Danzhi Xiaoyao Formula, herbal components in the hippocampus after administration, and blank samples. KEGG and GO analyses predicted 74 core targets including GSK3B, MAPK1, AKT, IL6. These targets were involved in PI3K/Akt, NF-κB, MAPK, JAK/STAT, Wnt, and other signaling pathways. The results indicated that Danzhi Xiaoyao Formula may ameliorate other nervous system diseases enriched in DO, such as neurodegenerative diseases, cerebrovascular diseases, and mental and emotional disorders by mediating target pathways, inhibiting inflammation, reducing neuronal damage, and alleviating hippocampal atrophy. The relevant activities exhibited by this formula in nervous system diseases such as Alzheimer's disease, Parkinson's disease, and diabetic neuropathy have extremely high development value and are worthy of further in-depth research. This study provides a theoretical basis and practical guidance for expanding the application of Danzhi Xiaoyao Formula in the treatment of nervous system diseases.
Drugs, Chinese Herbal/administration & dosage* ; Animals ; Rats ; Hippocampus/metabolism* ; Network Pharmacology ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Rats, Sprague-Dawley ; Male ; Nervous System Diseases/genetics* ; Humans ; Signal Transduction/drug effects*