Objective To evaluate the predictive value of different machine learning models constructed in a multicenter environment for potential organ donors and verify their clinical application feasibility. Methods The study included 2 000 inpatients admitted to five domestic tertiary hospitals from January 2020 to December 2023, who met the criteria for potential organ donation assessment. They were randomly divided into a training set and an internal validation set (7∶3). Another 300 similar patients admitted to the First Affiliated Hospital of Harbin Medical University from January 2024 to April 2025 were included as an external validation set. The area under the curve (AUC), sensitivity, specificity, accuracy and F1-score of three models were compared, and the consistency of the potential organ donor determination process was tested. Multivariate logistic regression analysis was used to identify predictive factors of potential organ donors. Decision curve analysis (DCA) was employed to verify the resource efficiency of each model, and the threshold interval and intervention balance point were assessed. Results Apart from age, there were no significant differences in other basic characteristics among the centers (all P>0.05). The consistency of the potential organ donor determination process among researchers in each center was good [all 95% confidence interval (CI) lower limits >0]. In the internal validation set, the XGBoost model had the best predictive performance (AUC=0.92, 95% CI 0.89-0.94) and the best calibration (P=0.441, Brier score 0.099). In the external validation set, the XGBoost model also had the best predictive performance (AUC=0.91, 95% CI 0.88-0.94), outperforming logistic regression and random forest models. Multivariate logistic regression showed that mechanical ventilation had the greatest impact (odds ratio=2.06, 95% CI 1.54-2.76, P<0.001). DCA indicated that the XGBoost model had the highest net benefit in the threshold interval of 0.2-0.6. The “treat all” strategy only had a slight advantage at extremely low thresholds. The recommended threshold interval, which balances intervention costs and clinical benefits, considers ≥50% positive predictive value (PPV) and ≤50 referrals per 100 high-risk patients. Conclusions The XGBoost model established in a multicenter environment is accurate and well-calibrated in predicting potential organ donors. Combined with DCA, it may effectively guide the timing of clinical interventions and resource allocation, providing new ideas for the assessment and management of organ donation after brain death.

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.

LIU Wansu， as the foremost of the four great masters of the Jin-Yuan period， established the "theory of fire-heat'' and extended the fire-heat pathogenesis framework to the field of stroke， thereby forming the theory of ''fire-heat inducing stroke''. This achieved a paradigmatic shift in stroke etiology from ''exogenous wind inducing stroke'' to ''fire-heat inducing stroke''. This paper systematically reviews the developmental trajectory of LIU Wansu's ''fire-heat inducing stroke'' theory and explores the social background， academic origins， and core connotations of its theoretical construction. The study found that， based on the ''Nineteen Pathomechanisms'' in the Huangdi's Internal Classic （Huang Di Nei Jing） and combined with clinical practice， LIU Wansu proposed that fire-heat is the fundamental cause of stroke， and that the Six Climatic Factors and the Five Zhi-Emotions can all transform into fire. He further constructed a stratified syndrome differentiation and therapeutic system centered on clearing heat and purging fire， emphasizing differentiated treatment of exterior and interior syndromes， Six Meridians syndrome differentiation， and seasonally adjusted medication. This theory not only resolved the diagnostic and therapeutic dilemmas of febrile epidemic diseases during the Jin-Yuan period， but also exerted a profound influence on later physicians such as ZHANG Zihe and ZHU Danxi， thereby promoting the pluralistic development of stroke theory in traditional Chinese medicine （TCM）. Modern pharmacological research provides solid scientific evidence， confirming that the ''fire-heat'' pathological state is highly associated with key mechanisms such as excessive inflammatory responses， oxidative stress， and excitatory amino acid toxicity following cerebral ischemia. Heat-clearing and fire-purging prescriptions and agents， such as Huanglian Jiedu Tang and baicalin， can exert multi-target neuroprotective effects by regulating inflammatory signaling， enhancing antioxidant enzyme activity， and balancing neurotransmitters. This not only verifies the scientific basis of the ''fire-heat inducing stroke'' theory from a modern biological perspective but also provides conclusive evidence for the clinical application of heat-clearing and fire-purging therapy. LIU Wansu's ''fire-heat inducing stroke'' theory represents a major milestone in the historical understanding of stroke pathogenesis， and its academically transitional insights continue to hold core guiding value for the pattern identification and treatment of ischemic stroke today.

LIU Wansu， as the foremost of the four great masters of the Jin-Yuan period， established the "theory of fire-heat'' and extended the fire-heat pathogenesis framework to the field of stroke， thereby forming the theory of ''fire-heat inducing stroke''. This achieved a paradigmatic shift in stroke etiology from ''exogenous wind inducing stroke'' to ''fire-heat inducing stroke''. This paper systematically reviews the developmental trajectory of LIU Wansu's ''fire-heat inducing stroke'' theory and explores the social background， academic origins， and core connotations of its theoretical construction. The study found that， based on the ''Nineteen Pathomechanisms'' in the Huangdi's Internal Classic （Huang Di Nei Jing） and combined with clinical practice， LIU Wansu proposed that fire-heat is the fundamental cause of stroke， and that the Six Climatic Factors and the Five Zhi-Emotions can all transform into fire. He further constructed a stratified syndrome differentiation and therapeutic system centered on clearing heat and purging fire， emphasizing differentiated treatment of exterior and interior syndromes， Six Meridians syndrome differentiation， and seasonally adjusted medication. This theory not only resolved the diagnostic and therapeutic dilemmas of febrile epidemic diseases during the Jin-Yuan period， but also exerted a profound influence on later physicians such as ZHANG Zihe and ZHU Danxi， thereby promoting the pluralistic development of stroke theory in traditional Chinese medicine （TCM）. Modern pharmacological research provides solid scientific evidence， confirming that the ''fire-heat'' pathological state is highly associated with key mechanisms such as excessive inflammatory responses， oxidative stress， and excitatory amino acid toxicity following cerebral ischemia. Heat-clearing and fire-purging prescriptions and agents， such as Huanglian Jiedu Tang and baicalin， can exert multi-target neuroprotective effects by regulating inflammatory signaling， enhancing antioxidant enzyme activity， and balancing neurotransmitters. This not only verifies the scientific basis of the ''fire-heat inducing stroke'' theory from a modern biological perspective but also provides conclusive evidence for the clinical application of heat-clearing and fire-purging therapy. LIU Wansu's ''fire-heat inducing stroke'' theory represents a major milestone in the historical understanding of stroke pathogenesis， and its academically transitional insights continue to hold core guiding value for the pattern identification and treatment of ischemic stroke today.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

ObjectiveTo investigate the liver histopathological features of HBeAg-negative patients in the indeterminate phase of low-viral-load chronic hepatitis B virus （HBV） infection. MethodsA total of 271 patients with low-viral-load HBeAg-negative chronic HBV infection who underwent liver biopsy in Department of Infectious Diseases， Affiliated Hospital of Yan’an University， from September 2013 to June 2021 were enrolled as subjects， and the degree of liver injury was compared between patients based on age， sex， presence or absence of the family history of hepatitis B， HBsAg， and alanine aminotransferase （ALT） level. The chi-square test was used for comparison of categorical data between two groups. ResultsAmong the 271 patients with HBeAg-negative chronic HBV infection， 86 patients （31.73%） grade≥A2 liver inflammatory activity， 72 （26.57%） had a liver fibrosis stage of ive， and 112 （41.33%） had moderate or severe liver histological injury. The proportion of patients with grade≥A2 liver inflammatory activity in the patients with ALT>20 U/L was significantly higher than that in the patients with ALT≤20 U/L （χ²=3.938， P=0.047）. There were no significant differences in the proportion of patients with grade≥A2 liver inflammatory activity between the patients with different ages， sexes， family history of hepatitis B， HBsAg levels （all P>0.05），there were no significant differences in the proportion of patients with a liver fibrosis stage of ≥F2 between the patients with different ages， sexes， family history of hepatitis B， HBsAg， and ALT levels （all P>0.05）， and the stratified analysis of patients aged≤30 years and patients without the family history of hepatitis B showed no statistical significance between groups （all P>0.05）. There was no significant difference in the degree of liver histological injury between the patients with different ages， sexes， family history of hepatitis B， HBsAg， and ALT levels （all P>0.05）. ConclusionSignificant liver injury is observed in more than 40% of the patients with low-viral-load HBeAg-negative chronic HBV infection， and there is no significant difference in the degree of liver histological injury between the patients with different ages， sexes， family history of hepatitis B， HBsAg， and ALT levels. Even for the patients aged≤30 years who deny the family history of hepatitis B， there is still a considerable proportion of patients with liver injury， which should be taken seriously by clinicians.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

A growing body of research points out that gut microbiota plays a key role in tumor immunotherapy. By optimizing the composition of intestinal microbiota, it is possible to effectively improve immunotherapy resistance and enhance its therapeutic effect. This article comprehensively analyzes the mechanism of intestinal microbiota influencing tumor immunotherapy resistance, expounds the current strategies for targeted regulation of intestinal microbiota, such as traditional Chinese medicine and plant components, fecal microbiota transplantation, probiotics, prebiotics and dietary therapy, and explores the potential mechanisms of these strategies to improve patients' resistance to tumor immunotherapy. At the same time, the article also briefly discusses the prospects and challenges of targeting intestinal microbiota to improve tumor immunotherapy resistance, which provides a reference for related research to help the strategy research of reversing tumor immunotherapy resistance.

Taxifolin (Tax) has been proved to be a medicinal edible substance with protective effects against alcoholic liver injury, however, its poor hydrophilicity and permeability have hindered the clinical application of Tax. In this study, we prepared taxifolin-phosphatidylcholine/sodium deoxycholate/PVP-K30 micells (Tax-MLs). Box-Behnken test was used to obtain the optimal preparation process, and Tax-MLs were characterised by transmission electron microscopy and fourier transform infrared spectroscopy. Physicochemical parameters such as proximate micelle concentration, equilibrium solubility and oil-water partition coefficient were determined, and the release pattern of Tax-MLs was investigated by in vitro digestion simulation. Alcoholic liver injury model to explore the in vivo efficacy of Tax-MLs. The results showed that the average particle size, polydispersity index (PDI) and zeta potential of Tax-MLs were 36.90 ± 4.57 nm, 0.194 ± 0.01 and -32.6 ± 0.35 mV, respectively, and the uniform size and distribution of Tax-MLs were observed by transmission electron microscopy. The formation of Tax-MLs was proved by differential scanning calorimetry and fourier transform infrared spectroscopy. In terms of physicochemical properties, the solubility of Tax-MLs in water increased by 92.02 times compared with Tax, and its oil-water partition coefficient in water increased from 0.43 to 1.14, which proved that Tax-MLs could improve its solubility and permeability. The in vivo pharmacodynamic results showed that compared with the Tax group, Tax-MLs low, medium and high dose groups showed a significant reduction in liver indices and serum levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) (P < 0.05), and enhanced the activities of superoxide dismutase (SOD) and glutathione (GSH), and lowered the levels of malondialdehyde (MDA) more significantly in the hepatic tissues. Tax-MLs effectively improved drug solubility and permeability, and enhanced the protective effect against alcoholic liver injury. Animal experiments were conducted with approval from the Animal Ethics Committee of Changchun University of Traditional Chinese Medicine (approval number: 2023601).