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.

Abstract To estavlish a more comprehensive theoretical framework for the weight management of children and adolescents, the study systematically expounds on the two core strategies for dietary and exercise intervention. It explores the mechanism of diet, physical activity, breating exercise, functional movement correction and multi dimensional integrated exercise modalities in preventing weight rebound after weight loss in overweight and obesity children and adolescents. Future advancements in research methodology are expected to improve the evidence system of collaborative interventions, so as to provide precise strategies for obesity management in children and adolescents.

ObjectiveThis paper aims to investigate and evaluate the staged efficacy and safety of the representative empirical prescription of the “Zhu Ke Jiao” theory， Qijia Rougan prescription， combined with entecavir in the treatment of hepatic fibrosis in chronic hepatitis B. MethodsA multicenter randomized controlled clinical study was conducted， and 101 patients diagnosed with chronic hepatitis B-related hepatic fibrosis （CHB-HF） who met the diagnosis and inclusion criteria were randomly assigned to an observation group （Qijia Rougan prescription + entecavir） and a control group （entecavir）. The treatment duration was 24 weeks. Liver stiffness measurement （LSM）， fibrosis-4 index （FIB-4）， portal vein diameter， hepatitis B serology， biochemical indicators， hepatic fibrosis markers in serum ［hyaluronic acid （HA）， laminin （LN）， procollagen Ⅲ peptide （PⅢP）， and type Ⅳ collagen （Ⅳ-C）］， and traditional Chinese medicine syndrome scores were used as efficacy evaluation indicators. Efficacy assessments and explorations of different staged subgroups of Qijia Rougan prescription were conducted according to LSM values based on the Metavir pathological staging standard. ResultsA total of 98 cases were included for statistical analysis， with 49 cases in the observation group and 49 in the control group. The general data of the patients in both groups were comparable. Compared with the same group before treatment， the observation group showed a significant reduction in LSM and FIB-4 （P<0.01）， as well as notable improvements in LN， Ⅳ-C， and various TCM syndrome scores （P<0.05， P<0.01）. When compared to the control group after treatment， the observation group demonstrated significant improvements in LSM， FIB-4， and various TCM syndrome score indicators （P<0.05， P<0.01）， indicating that the observation group performed better than the control group. Subgroup analysis of the regression of hepatic fibrosis stages showed that compared to the same group before treatment， the observation group had better improvement in regression of stages F2 and F3 （P<0.05）. When compared to the control group after treatment， the observation group exhibited superior improvement in regression of stage F3 （P<0.05）. No adverse events occurred in either group during the treatment period. ConclusionCompared with entecavir alone， the combination of Qijia Rougan prescription and entecavir significantly improves the degree of hepatic fibrosis and clinical TCM symptoms in patients. The optimal intervention period is primarily during stage F3， which is a potential “interception” point of the “Zhu Ke Jiao” theory.

ObjectiveTo investigate whether Huanglian Jiedutang （HLJD） and its major active constituents （geniposide， baicalin， and berberine） can inhibit the inflammatory response of BV2 cells under lipopolysaccharide （LPS） stimulation via the high-mobility group protein B1 （HMGB1）/Toll-like receptor 4 （TLR4）/nuclear factor-κB （NF-κB） signaling pathway， and to explore differences in therapeutic efficacy among the three monomers， their combined formula， and HLJD under equal content ratios. MethodsBV2 microglial cells were used as the primary experimental model. Cell viability was assessed using the cell counting kit-8 （CCK-8） method to examine the effects of different concentrations of dimethyl sulfoxide （DMSO， 0.8%， 0.4%， 0.2%， 0.1%， and 0.05%） on cell viability. IncuCyte was employed to monitor the growth of cells under different concentrations of HLJD （200， 100， 50， 25， 12.5， 6.25 mg·L^-1）. Nitric oxide （NO） assay was used to screen the optimal HLJD concentration. High-performance liquid chromatography （HPLC） determined the content of geniposide， baicalin， and berberine in HLJD， and experimental groups were subsequently established according to the relative proportions of these constituents. CCK-8 assay evaluated cell viability under different treatments. Enzyme-linked immunosorbent assay （ELISA） measured levels of inflammatory factors （TNF-α， IL-1β， IL-6， IL-10） in the supernatant. Flow cytometry assessed the effects of treatments on M1-type polarization of BV2 cells. Western blot determined the expression levels of HMGB1， TLR4， and NF-κB-related proteins. ResultsCompared with the blank group， DMSO at concentrations ≤0.2% did not affect cell viability within 48 h. BV2 cell growth plateaued at 24 h after treatment with 200 mg·L^-1 HLJD. Under stimulation with 2 mg·L^-1 LPS， this concentration of HLJD effectively reduced NO release， and 6 h pre-treatment had a stronger inhibitory effect on NO than direct administration. HPLC results showed that 1 mg of HLJD freeze-dried powder contained approximately 24 μg of geniposide， 15 μg of baicalin， and 30 μg of berberine. Based on these ratios， experimental groups were blank， LPS （2 mg·L^-1）， HLJD （200 mg·L^-1）， monomer combination， geniposide （4.8 mg·L^-1）， baicalin （3 mg·L^-1）， and berberine （6 mg·L^-1）. The monomer combination group consisted of all three active constituents dissolved together. LPS and HLJD or its active constituents did not affect cell viability compared with the blank group. LPS significantly increased TNF-α， IL-1β， IL-6， and IL-10 in the supernatant （P<0.01）. HLJD and its active constituents significantly reduced pro-inflammatory factors TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01） while upregulating anti-inflammatory IL-10 （P<0.01）， with the monomer combination showing the strongest effect （P<0.05， P<0.01）. Compared with the blank group， LPS significantly increased the proportion of CD80⁺CD86⁺ （M1-type） BV2 cells （P<0.01）. HLJD and its constituents partially inhibited M1 polarization （P<0.05， P<0.01）， with the monomer combination exhibiting the most pronounced effect （P<0.05， P<0.01）. Compared with the blank group， LPS upregulated HMGB1， TLR4， and NF-κB-related proteins （P<0.01）， whereas HLJD and its active constituents significantly reduced their expression （P<0.05， P<0.01）， with the monomer combination having the strongest regulatory effect （P<0.05， P<0.01）. ConclusionHLJD and its major active constituents （geniposide， baicalin， berberine） can inhibit LPS-induced inflammatory responses in BV2 cells. The combination of the three active constituents demonstrates the most potent anti-inflammatory effect， significantly attenuating M1-type polarization of BV2 cells via the HMGB1/TLR4/NF-κB signaling pathway.

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.