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.

Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

Objective To observe the effect of emodin on lung injury in rats with stroke associated pneumonia(SAP)through regulating Janus kinase 2(JAK2)/signal transducer and activators of transcription 3(STAT3)signaling pathway.Methods The SAP rat model was established by modified thread embolization method combined with intratracheal injection of Pseudomonas aeruginosa method.The successfully modeled rats were randomly divided into model group,emodin low-and high-dose groups and emodin high-dose+coumermycin(JAK2 activator)group,with 12 rats in each group,and another 12 SD rats were selected as the sham-operated group.After the intervention,the partial pressure of arterial blood gas indexes such as carbon dioxide(PaCO2)and partial pressure of oxygen(PaO2)were measured,the ratio of lung wet/dry mass(W/D)was determined,the inflammatory cell count in the bronchoalveolar lavage fluid(BALF)was detected,the histopathological feature in the lung tissues was observed by hematoxylin-eosin(HE)staining and the pathological injury was scored,enzyme-linked immunosorbent assay(ELISA)was used to detect myeloperoxidase(MPO)activity in the lung tissues and interleukin 6(IL-6)and cyclooxygenase 2(COX-2)levels in BALF and serum,and Western Blot was used to detect the expression of JAK2/STAT3 pathway key proteins in lung tissues.Results Compared with the sham-operated group,the model group rats showed that more obvious pathological injury in lung tissues was seen,and PaCO2 value,ratio of lung W/D,white blood cell count and eosinophils count in BALF,pathological injury score,MPO activity in lung tissues,IL-6 and COX-2 levels in BALF and serum,and ratios of p-JAK2/JAK2 and p-STAT3/STAT3 in lung tissues were significantly increased,and PaO2 value was significantly decreased,the differences being statistically significant(P<0.05);compared with the model group,the emodin low-and high-dose groups rats showed that the pathological injury in lung tissues was reduced,PaCO2 value,ratio of lung W/D,white blood cell count and eosinophils count in BALF,pathological injury score,MPO activity in lung tissues,IL-6 and COX-2 levels in BALF and serum,and ratios of p-JAK2/JAK2 and p-STAT3/STAT3 in lung tissues were all decreased,and PaO2 value was increased,the differences being statistically significant(P<0.05),and the improvement effect was more stronger in high-dose emodin group;coumermycin attenuated the improvement effect of emodin on the above various indexes in the model rats.Conclusion Emodin can reduce the inflammation levels in SAP rats through inhibiting the activation of JAK2/STAT3 signaling pathway,thus reducing the lung tissue damage and improving the lung function of rats.

Objective To explore the application effect of multimodal somatosensory exercise based on artificial intelligence technology in home rehabilitation exercise for elderly patients with chronic obstructive pulmonary dis-ease(COPD),so as to promote COPD patients to participate in home rehabilitation exercise.Methods Using the convenient sampling method,80 elderly patients with COPD admitted to the Department of Respiratory Medicine of a tertiary A hospital in Urumqi from November 2023 to February 2024 were selected as the research subjects.Ac-cording to the random number table method,they were divided into a control group and an experimental group,with 40 cases in each group.The control group adopted the traditional exercise training method,and the experimental group adopted the multi-modal somatosensory movement based on artificial intelligence technology for exercise in-tervention,with 5 times a week,and the intervention was implemented for 12 weeks.The pulmonary function index,modified Medical Research Council scale score,physical fitness level,Chronic Obstructive Pulmonary Disease As-sessment Test scale score and exercise compliance of the 2 groups were compared before intervention and 12 weeks after intervention.Results 77 patients completed the study,with 39 in the experimental group and 38 in the control group.The forced vital capacity,forced expiratory volume in one second,forced expiratory volume in one second to forced vital capacity ratio,physical fitness level and exercise compliance of the experimental group were higher than those of the control group,while the modified British Medical Research Council scale score and Chron-ic Obstructive Pulmonary Disease Assessment Test score were lower than those of the control group.The differences were statistically significant(P＜0.05).Conclusion Somatosensory exercise based on artificial intelligence technology can improve the lung function of the patients with COPD,improve the exercise compliance and physical fitness in-dicators of elderly patients and improve the quality of life of the patients.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection,with a high mortality rate.Sirtuin 3,a deacetylase within mitochondria,plays an important regulatory role in cellular metabolism,oxidative stress,and inflammatory responses.In recent years,significant progress has been made in the study of the function and regulatory role of sirtuin 3 in sepsis-related diseases.Research has shown that sirtuin 3 can alleviate organ damage caused by sepsis by regulating mitochondrial function,reducing oxidative stress,and inhibiting inflammatory responses.The specific mechanisms include the regulation of mitochondrial bioenergetics,activation of antioxidant enzyme systems,and inhibition of inflammatory mediator expression.In addition,sirtuin 3 plays a protective role in the pathological process of sepsis by interacting with multiple signaling pathways.This article summarizes the functions and regulatory mechanisms of sirtuin 3 in various sepsis-related diseases,aiming to provide new targets and strategies for the prevention and treatment of sepsis in the future.
Sepsis/metabolism* ; Sirtuin 3/physiology* ; Humans ; Animals ; Oxidative Stress ; Mitochondria/metabolism* ; Signal Transduction

Objective: To review the current development of artificial intelligence (AI) technology in the field of transfusion medicine. Methods: A systematic search was conducted in the Clarivate Web of Science Database from inception to December 2024 for literature related to AI and transfusion. A total of 4 775 publications were identified. Based on inclusion and exclusion criteria, 133 original studies were ultimately included and analyzed using a narrative synthesis approach. Results: Research on AI in transfusion has surged since 2020 (accounting for 77% of all publications), with China ranking second globally in publication volume. Among the included studies, 69.2% focused on predicting individual transfusion needs, followed by inventory management (8.3%), diagnosis and prediction of adverse transfusion reactions (6.0%), factors influencing transfusion outcomes (5.3%), blood group identification (5.3%), blood quality testing (4.5%), and precise blood volume measurement (1.5%). Additionally, 4.5% of the studies were published in journals with an impact factor greater than 10; 19.5% developed software or applications; 31.5% were multi-center studies; 48.1% utilized decision tree methods, while 31.5% employed neural network approaches; and 14.2% conducted external validation of the algorithms. Conclusion: AI demonstrates significant potential in transfusion risk prediction, decision support, and blood management. However, challenges remain, including limited model generalizability, insufficient algorithm interpretability, and barriers to clinical translation. The deep integration of AI with transfusion medicine will accelerate the advent of precision transfusion era, maximizing blood resource utilization, reducing waste, and ensuring transfusion safety.

Objective Based on 25 indicators including immune factors, cell count classification, and smear results of the knee joint fluid, machine learning models were established to distinguish between osteoarthritis (OA) and rheumatoid arthritis (RA). Methods 100 OA and 40 RA patients scheduled for total knee arthroplasty were enrolled respectively. Each patient's knee joint fluid was collected preoperatively. Nucleated cells were counted and classified. The expression levels of immune factors, including tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), IL-6, IL-8, IL-15, matrix metalloproteinase 3 (MMP3), MMP9, MMP13, rheumatoid factor (RF), serum amyloid A (SAA), C-reactive protein (CRP), and others were measured. Smears and microscopic classification of all the immune factors were performed. Independent influencing factors for OA or RA were identified using univariate binary logistic regression, Lasso regression, and multivariate binary logistic regression. Based on the independent influencing factors, three machine learning models were constructed which are logistic regression, random forest, and support vector machine. Receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to evaluate and compare the models. Results A total of 5 indicators in the knee joint fluid were screened out to distinguish OA and RA, which were IL-1β(odds ratio(OR)=10.512, 95× confidence interval (95×CI) was 1.048-105.42, P=0.045), IL-6 (OR=1.007, 95×CI was 1.001-1.014, P=0.022), MMP9 (OR=3.202, 95×CI was 1.235-8.305, P=0.017), MMP13 (OR=1.002, 95× CI was 1-1.004, P=0.049), and RF (OR=1.091, 95×CI was 1.01-1.179, P=0.026). According to the results of ROC, calibration curve and DCA, the accuracy (0.979), sensitivity (0.98) and area under the curve (AUC, 0.996, 95×CI was 0.991-1) of the random forest model were the highest. It has good validity and feasibility, and its distinguishing ability is better than the other two models. Conclusion The machine learning model based on immune factors in the knee joint fluid holds significant value in distinguishing OA and RA. It provides an important reference for the clinical early differential diagnosis, prevention and treatment of OA and RA.
Humans ; Arthritis, Rheumatoid/metabolism* ; Machine Learning ; Male ; Female ; Middle Aged ; Aged ; Synovial Fluid/immunology* ; Osteoarthritis, Knee/metabolism* ; Knee Joint/metabolism* ; ROC Curve ; Diagnosis, Differential

OBJECTIVE: To investigate the clinical characteristics and prognosis of primary pulmonary lymphoma (PPL). METHODS: The clinical data of 17 patients with PPL admitted to Gansu Provincial Hospital from January 2013 to June 2023 were collected, and their clinical characteristics and prognosis were retrospectively analyzed and summarized. RESULTS: The median age of the 17 patients was 56 (29-73) years old. There were 8 males and 9 females. According to Ann Arbor staging system, there were 9 patients with stage I-II and 8 patients with stage III-IV. There were 14 patients with IPI score of 0-2 and 3 patients with IPI score of 3-4. All 17 patients had symptoms at the initial diagnosis, most of the first symptoms were cough, and 6 patients had B symptoms.Among the 17 patients, there were 8 cases of diffuse large B-cell lymphoma (DLBCL), 5 cases of mucosa-associated lymphoid tissue (MALT) lymphoma, 1 case of gray zone lymphoma (GZL), and 3 cases of Hodgkin's lymphoma (HL). 15 patients received chemotherapy, of which 3 cases received autologous hematopoietic stem cell transplantation(ASCT) and 3 cases received radiotherapy; 2 patients did not receive treatment. The median number of chemotherapy courses was 6(2-8). The short-term efficacy was evaluated, 12 patients achieved complete remission (CR) and 3 patients achieved partial remission (PR). The age, pathological subtype, sex, Ann Arbor stage, β₂-microglobulin(β₂-MG) level, lactate dehydrogenase(LDH) level were not correlated with CR rate (P >0.05), while IPI score was correlated with recent CR rate (P < 0.05 ). The median follow-up time was 31(2-102) months. One of the 12 CR patients died of COVID-19, and the rest survived. Among the 3 patients who did not reach CR, 1 died after disease progression, while the other 2 survived. One of the 2 untreated patients died one year after diagnosis. Both the median progression-free survival (PFS) time and overall survival (OS) time of the 17 patients were both 31 (2-102) months. CONCLUSION The incidence of PPL is low, and the disease has no specific clinical manifestations, which is easily missed and misdiagnosed. The pathological subtypes are mainly MALT lymphoma and DLBCL, and the treatment is mainly combined chemotherapy. The IPI score is related to the treatment efficacy.
Humans ; Middle Aged ; Male ; Female ; Adult ; Prognosis ; Aged ; Lung Neoplasms/therapy* ; Retrospective Studies ; Neoplasm Staging ; Lymphoma/therapy* ; Lymphoma, Large B-Cell, Diffuse