ObjectiveTo investigate the migration and distribution characteristics of chemical constituents in blood and hippocampal tissues before and after vinegar processing of Citri Reticulatae Pericarpium Viride（CRPV）， and to explore the potential material basis and mechanisms underlying their regulatory effects on emotional disorders by comparing the effects of raw and vinegar-processed products of CRPV. MethodsUltra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was employed to characterize and identify the chemical constituents of raw and vinegar-processed products of CRPV extracts， as well as their migrating components in blood and hippocampal tissues after oral administration. Reference standards， databases， and relevant literature were utilized for compound annotation， with data processing performed using PeakView 1.2 software. Seventy male C57BL/6 mice were randomly divided into seven groups， including the blank group， model group， diazepam group（2.5 mg·kg^-1）， raw CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， and vinegar-processed CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， with 10 mice per group. Except for the blank group， all other groups underwent chronic restraint stress（2 h·d^-1） for 20 d. Each drug-treated group received oral administration at the predetermined dose starting 10 d after modeling， with a total treatment duration of 10 d. Following model-based drug administration， mice underwent open-field， forced swimming， and elevated plus maze tests. After anesthesia with isoflurane， whole brains were collected from each group of mice， and hippocampi were dissected. Reactive oxygen species（ROS） level in hippocampal tissues was quantified by enzyme-linked immunosorbent assay（ELISA）. Hematoxylin-eosin（HE） staining was used to observe hippocampal tissue morphology. Immunofluorescence was performed to detect neuronal nuclei（NeuN） and peroxisome proliferator-activated receptor alpha（PPARα） expressions in hippocampal tissue. Then， pharmacodynamic evaluations were conducted to assess the effects of raw and vinegar-processed CRPV on mood disorders， exploring the potential mechanisms. ResultsVinegar processing caused significant changes in the chemical composition of CRPV， with 18 components showing increased relative content and 35 components showing decreased relative content. The primary changes occurred in flavonoid compounds， including 20 flavonoids， 20 flavonoid glycosides， 3 triterpenes， 3 phenolic acids， 1 alkaloid， and 6 other compounds. Twenty-one components were detected in blood（15 methoxyflavones， 4 flavonoid glycosides， and 2 phenolic acids）， with 17 shared between raw and vinegar-processed CRPV. Seven components reached hippocampal tissues（all common to both forms）. In regulating emotional disorders， Vinegar-processed CRPV exhibited superior antidepressant-like effects compared to raw products. HE staining revealed that both treatments improved hippocampal neuronal morphology， particularly in the damaged CA1 and CA3 regions. Immunofluorescence and ELISA analyses demonstrated that both raw and vinegar-processed CRPV significantly modulated NeuN and PPARα expressions in hippocampal tissue while alleviating oxidative stress induced by excessive ROS（P<0.05）. ConclusionThe chemical composition of CRPV undergoes changes after vinegar processing， but the migrating components in blood and hippocampus are primarily methoxyflavonoids. These components may serve as the potential material basis for activating the PPARα pathway， thereby negatively regulating ROS generation in the hippocampus， reducing oxidative stress， and promoting the development of NeuN-positive neurons. These findings provide experimental evidence for enhancing quality standards， pharmacodynamic material research， and active drug development of raw and vinegar-processed CRPV.

ObjectiveTo identify the pathogen species responsible for the wilt disease of Tetradium ruticarpum in Chongqing， investigate there biological characteristics， and screen effective fungicides， so as to provide a theoretical basis for disease control in production. MethodsThe pathogen was isolated via the tissue culture method. Pathogenicity was verified according to Koch's postulates. The pathogen was identified based on morphological characteristics and multi-gene phylogenetic analysis. The mycelial growth rate method was used for biological characterization of the pathogen and fungicide screening. ResultsThe pathogen colonies were nearly circular with irregular edges， white， short， velvety aerial hyphae， and pale purple undersides. Macroconidia were colorless， sickle-shaped， with 3-5 septa， while microconidia were transparent， elliptical， aseptate or with 1-2 septa. Multi-gene phylogenetic analysis showed that the pathogen clustered in the same clade as Fusarium fujikuroi with 100% support， which， combined with morphological characteristics， identified the pathogen causing wilt of T. ruticarpum in Chongqing as F. fujikuroi. The optimal conditions for the mycelial growth of F. fujikuroi were mung bean agar （MBA） with glucose as the carbon source， beef extract and yeast powder as nitrogen sources， 28 ℃， pH 7.0， and alternating light/dark conditions. The optimal conditions for sporulation were potato dextrose agar （PDA） with glucose as the carbon source， beef extract as the nitrogen source， 28 ℃， pH 7.0， and complete darkness. Among chemical fungicides， phenazine-1-carboxylic acid exhibited the strongest inhibitory effect on F. fujikuroi. Shenqinmycin and tetramycin were the most effective bio-fungicides. ConclusionThis study is the first to report F. fujikuroi as the causal agent of wilt disease in T. rutaecarpa. The chemical fungicide phenazine-1-carboxylic acid and the bio-fungicides shenqinmycin and tetramycin showed strong inhibitory effects against F. fujikuroi.

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 analyze the clinical and therapeutic characteristics of Epstein-Barr virus (EBV)-negative posttransplant lymphoproliferative disease (PTLD) with diffuse large B-cell lymphoma (DLBCL) in the context of specific cases and literature. Methods A case of EBV-negative DLBCL (GCB type) after kidney transplantation is reported. The patient was a 45-year-old male who underwent living-related kidney transplantation in 2016 and has been receiving triple immunosuppressive therapy with tacrolimus, mycophenolate mofetil and methylprednisolone since then. In 2024, the patient presented with intermittent fever, night sweats and gastrointestinal symptoms. The diagnosis was confirmed by endoscopic pathology, immunohistochemical staining and positron emission tomography/computed tomography. The R-CDOP regimen (rituximab + cyclophosphamide + liposomal doxorubicin + vincristine + dexamethasone) was used for treatment. Results The patient was diagnosed with EBV-negative DLBCL (GCB type, Ann Arbor stage Ⅳ B). After 4 cycles of R-CDOP chemotherapy, the efficacy assessment was partial remission, and the transplant kidney function remained stable. Conclusions For EBV-negative PTLD after kidney transplantation, it is necessary to break through the "virus-dependent" diagnostic thinking. In clinical practice, the focus should be on protecting the transplant kidney, and individualized treatment plans should be developed for patients.

ObjectiveTo explore the potential mechanism of Xiaoqinglongtang（XQL） in the prevention and treatment of high altitude pulmonary edema（HAPE） by network pharmacology， molecular docking， and molecular dynamics simulation， and to verify it by in vivo animal model. MethodsIn this study， the active ingredients， drug targets， and HAPE-related targets of XQL were collected from BATMAN-TCM， GeneCards， and Online Mendelian Inheritance in Man（OMIM） databases. The protein-protein interaction（PPI） network was constructed by using intersection targets， and the core targets were screened and visualized by Cytoscape software. Functional annotation and pathway analysis of the intersection targets were performed by gene ontology （GO） and Kyoto encyclopedia of genes and genomes （KEGG） functional enrichment. AutoDock and GROMACS were used to evaluate the binding ability of active ingredients to key targets. In the experimental verification part， a mouse model of HAPE induced by hypobaric hypoxia（simulated 6 000 m altitude for 48 h） was established. The control effect was evaluated by hematoxylin-eosin（HE） staining， lung tissue water content， lung tissue wet/dry weight ratio， real-time quantitative polymerase chain reaction（Real-time PCR） detection of gene expression levels， and immunohistochemistry and Western blot detection of key protein expression. ResultsA total of 355 active ingredients of XQL， 2 142 targets， 716 HAPE-related targets， and 236 intersection targets were obtained by network pharmacology analysis. Key core targets such as interleukin （IL）-6， tumor necrosis factor （TNF）， protein kinase B1 （Akt1）， and hypoxia-inducible factor-1α （HIF-1α） were screened. The results of GO analysis of common targets involved 738 biological processes（BP）， 72 cellular components（CC）， and 135 molecular functions（MF）. KEGG analysis effectively enriched two important signaling pathways： Phosphoinositol 3-kinase （PI3K）/Akt and HIF-1α. The results of molecular docking and molecular dynamics simulation showed that the screened active ingredients had good binding ability with key targets. In the HAPE model induced by hypobaric hypoxia（6 000 m， 48 h）， the lung tissue water content， lung tissue wet/dry weight ratio， and pathological injury score of the model group were significantly increased（P<0.01）， accompanied by exudation of a large number of red blood cells in the alveoli and alveolar interstitium， a significant increase in inflammatory cells， a significant widening of the alveolar septum， and mutual fusion between the alveoli. The XQL administration group significantly improved the above pathological changes（P<0.01）. The results of inflammatory factor expression showed that compared with the control group， the model group showed significantly up-regulated expression of TNF-α， IL-6， and IL-1β in the lung tissue（P<0.01）. Compared with the model group， the XQL administration group had significantly decreased expression of inflammatory factors（P<0.05， P<0.01）. The mRNA expression of key pathway related genes PI3K， Akt1， mammalian target of rapamycin（mTOR）， and HIF-1α was significantly increased in the model group（P<0.01）， and decreased in a concentration-dependent manner after XQL administration（P<0.05， P<0.01）. The expression levels of key proteins PI3K， phosphorylation（p）-PI3K， Akt1， p-Akt1， mTOR， p-mTOR， and HIF-1α in lung tissue were analyzed by immunohistochemistry and Western blot. Compared with the blank group， the model group showed increased expression of key proteins（P<0.05， P<0.01）. Compared with the model group， the XQL administration group exhibited decreased expression of key proteins（P<0.05， P<0.01）. ConclusionXQL can reduce lung inflammation and improve HAPE. The mechanism may be related to the regulation of PI3K/Akt/mTOR and HIF-1α pathways. This study provides a new idea and a theoretical basis for the treatment of HAPE with XQL.

ObjectiveTo explore the potential mechanism of Xiaoqinglongtang（XQL） in the prevention and treatment of high altitude pulmonary edema（HAPE） by network pharmacology， molecular docking， and molecular dynamics simulation， and to verify it by in vivo animal model. MethodsIn this study， the active ingredients， drug targets， and HAPE-related targets of XQL were collected from BATMAN-TCM， GeneCards， and Online Mendelian Inheritance in Man（OMIM） databases. The protein-protein interaction（PPI） network was constructed by using intersection targets， and the core targets were screened and visualized by Cytoscape software. Functional annotation and pathway analysis of the intersection targets were performed by gene ontology （GO） and Kyoto encyclopedia of genes and genomes （KEGG） functional enrichment. AutoDock and GROMACS were used to evaluate the binding ability of active ingredients to key targets. In the experimental verification part， a mouse model of HAPE induced by hypobaric hypoxia（simulated 6 000 m altitude for 48 h） was established. The control effect was evaluated by hematoxylin-eosin（HE） staining， lung tissue water content， lung tissue wet/dry weight ratio， real-time quantitative polymerase chain reaction（Real-time PCR） detection of gene expression levels， and immunohistochemistry and Western blot detection of key protein expression. ResultsA total of 355 active ingredients of XQL， 2 142 targets， 716 HAPE-related targets， and 236 intersection targets were obtained by network pharmacology analysis. Key core targets such as interleukin （IL）-6， tumor necrosis factor （TNF）， protein kinase B1 （Akt1）， and hypoxia-inducible factor-1α （HIF-1α） were screened. The results of GO analysis of common targets involved 738 biological processes（BP）， 72 cellular components（CC）， and 135 molecular functions（MF）. KEGG analysis effectively enriched two important signaling pathways： Phosphoinositol 3-kinase （PI3K）/Akt and HIF-1α. The results of molecular docking and molecular dynamics simulation showed that the screened active ingredients had good binding ability with key targets. In the HAPE model induced by hypobaric hypoxia（6 000 m， 48 h）， the lung tissue water content， lung tissue wet/dry weight ratio， and pathological injury score of the model group were significantly increased（P<0.01）， accompanied by exudation of a large number of red blood cells in the alveoli and alveolar interstitium， a significant increase in inflammatory cells， a significant widening of the alveolar septum， and mutual fusion between the alveoli. The XQL administration group significantly improved the above pathological changes（P<0.01）. The results of inflammatory factor expression showed that compared with the control group， the model group showed significantly up-regulated expression of TNF-α， IL-6， and IL-1β in the lung tissue（P<0.01）. Compared with the model group， the XQL administration group had significantly decreased expression of inflammatory factors（P<0.05， P<0.01）. The mRNA expression of key pathway related genes PI3K， Akt1， mammalian target of rapamycin（mTOR）， and HIF-1α was significantly increased in the model group（P<0.01）， and decreased in a concentration-dependent manner after XQL administration（P<0.05， P<0.01）. The expression levels of key proteins PI3K， phosphorylation（p）-PI3K， Akt1， p-Akt1， mTOR， p-mTOR， and HIF-1α in lung tissue were analyzed by immunohistochemistry and Western blot. Compared with the blank group， the model group showed increased expression of key proteins（P<0.05， P<0.01）. Compared with the model group， the XQL administration group exhibited decreased expression of key proteins（P<0.05， P<0.01）. ConclusionXQL can reduce lung inflammation and improve HAPE. The mechanism may be related to the regulation of PI3K/Akt/mTOR and HIF-1α pathways. This study provides a new idea and a theoretical basis for the treatment of HAPE with XQL.

[Objective] To explore the clinical features of IgG4-related urinary diseases so as to provide reference for the diagnosis and treatment of such diseases. [Methods] The clinical data of 4 cases of IgG4-related urinary system diseases diagnosed and treated in Xijing Hospital of Air Force Medical University during Aug.2019 and Dec.2023 were retrospectively collected.Here, we report on the diagnosis and treatment of these patients, analysing their symptoms, serology, imaging and pathology as well as their treatment and outcomes. [Results] The patients included 2 male and 2 female.The lesions were involved with the retroperitoneum and urinary system.Three patients had symptoms of lumbar pain.The imaging manifestations were complex, including retroperitoneal mass involving urinary system organs in 2 cases, tabdense shadow of the right kidney in 1 case, and simple cystic mass of kidney in 1 case.Serum IgG4 value was not detected before surgery.All patients underwent radical surgical treatment.Postoperative pathology showed fibrous tissue hyperplasia with a large number of plasma cells, lymphocytes, a few neutrophil infiltrates, and lymphoid follicles and obliterated vasculitis in some specimens.The number of IgG4⁺ plasma cells was more than 10 in all tissues under high power microscope.After surgery, 3 patients had symptoms improved, and serum IgG4 value was within the normal range; 1 patient (patem 3) had elevated IgG4 value during follow-up, received subsequent hormone therapy, and the serum IgG 4 level remained stable. [Conclusion] The symptoms of IgG4-related diseases involving the urinary system are non-specific, and the imaging findings are various, easily confused with other diseases.Early detection of serum IgG4 and biopsy pathology can help clinicians make correct diagnosis in the early stage.

[Objective] To investigate the seroprevalence characteristics of hepatitis E virus (HEV) among blood donors with hepatitis B virus (HBV) infection, so as to provide data support for the monitoring, prevention and treatment of HEV. [Methods] From January to December 2022, 219 samples positive for hepatitis B surface antigen (HBsAg), 142 occult hepatitis B virus infection (OBI) samples (HBV group) and 873 samples tested negative (control group) were collected. 361 samples were further tested with viral load assay and serological testing for five serological markers (HBsAg, HBsAb, HBeAg, HBeAb and HBcAb), and the DNA load was measured using real time fluorescence quantitative PCR. Commercially available enzyme-linked immunosorbent assays (ELISA) were used for the detection of anti-HEV IgG, anti-HEV IgM and HEV antigen (Ag). The Chi-square test or Fisher's exact test was used to assess the differences in the reactivity rates of anti-HEV IgG and anti-HEV IgM among different blood donor populations and different variables. Multivariable logistic regression was used to examine potential risk factors associated with anti-HEV IgG seroprevalence. [Results] In the HBV group, HBsAg positive donors exhibited low expression of antigen. The HBV DNA load of OBI infected donors ranged from 1 to 131.43 IU/mL (median 11.24 IU/mL). The prevalence of anti-HEV IgG and IgM antibody in the HBV group were 34.63% and 1.11%, respectively. Among them, the prevalence of anti-HEV IgG and anti-HEV IgM in the HBV group was 34.63% and 0, respectively (P<0.05), while in the OBI donors, they were 41.55% and 2.82%, respectively. In the normal donors, the reactivity rates for anti-HEV IgG and anti-HEV IgM were 18.67% and 1.49%, respectively. Statistical analysis showed that there was a difference in the reactivity rate of anti-HEV IgG between the HBV-infected donors and the normal donors (34.63% vs 18.67%, P<0.05), but no difference in the reactivity rate of anti-HEV IgM (1.11% vs 1.49%, P>0.05). No HEV Ag was detected in either group of blood donors. Multivariate logistic regression analysis indicated that age was an independent risk factor for anti-HEV IgG reactivity in both groups of blood donors. [Conclusion] The reactivity rate of anti-HEV IgG among HBV-infected blood donors was significantly higher than that in the normal donors in Wuhan, with age being an independent risk factor. Therefore, for HBV-infected donors, it is essential to strengthen and prioritize the prevention and treatment of HEV to reduce the spread of HEV.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.