BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:High-frequency repetitive transcranial magnetic stimulation has garnered significant attention due to its potential non-invasive benefits in modulating brain function.However,no studies have comprehensively analyzed the current research landscape and development trends of this field from a macroscopic perspective.OBJECTIVE:To explore research hotspots,current trends,and emerging frontiers in the field of high-frequency repetitive transcranial magnetic stimulation through visualized analysis.METHODS:Data were collected from the Web of Science Core Collection database from January 1,2014 to November 15,2024.CiteSpace was used for analyzing publication volume,collaborations among countries/regions,institutions and authors,citation analysis of journals and co-cited literature,as well as disciplinary distribution.Additionally,keyword co-occurrence,clustering,and burst analyses were conducted,and visualized knowledge maps were generated.RESULTS AND CONCLUSION:A total of 860 articles were included.The publication volume of high-frequency repetitive transcranial magnetic stimulation showed an overall upward trend from 2014 to 2022,followed by a decline from 2022 to 2024.China had the highest publication volume,while Ghent University ranked as the most productive institution.Universities acted as the most high-output institutions.Chris Baeken from Ghent University was identified as the most prolific author.Collaboration among leading authors and institutions worldwide remained limited.The main research hotspots in this field were associated with keywords such as depression,stroke,neuropathic pain,and Parkinson's disease.Burst keywords focused on mild cognitive impairment,reflecting a diversification in research directions.The overall research activity in high-frequency repetitive transcranial magnetic stimulation continues to rise,with primary focuses on its clinical applications for psychiatric and neurological disorders,as well as explorations of its underlying mechanisms.Future research may focus on optimizing treatment parameters for targeting different brain regions in clinical applications and expanding its applications and mechanisms across various domains.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:High-frequency repetitive transcranial magnetic stimulation has garnered significant attention due to its potential non-invasive benefits in modulating brain function.However,no studies have comprehensively analyzed the current research landscape and development trends of this field from a macroscopic perspective.OBJECTIVE:To explore research hotspots,current trends,and emerging frontiers in the field of high-frequency repetitive transcranial magnetic stimulation through visualized analysis.METHODS:Data were collected from the Web of Science Core Collection database from January 1,2014 to November 15,2024.CiteSpace was used for analyzing publication volume,collaborations among countries/regions,institutions and authors,citation analysis of journals and co-cited literature,as well as disciplinary distribution.Additionally,keyword co-occurrence,clustering,and burst analyses were conducted,and visualized knowledge maps were generated.RESULTS AND CONCLUSION:A total of 860 articles were included.The publication volume of high-frequency repetitive transcranial magnetic stimulation showed an overall upward trend from 2014 to 2022,followed by a decline from 2022 to 2024.China had the highest publication volume,while Ghent University ranked as the most productive institution.Universities acted as the most high-output institutions.Chris Baeken from Ghent University was identified as the most prolific author.Collaboration among leading authors and institutions worldwide remained limited.The main research hotspots in this field were associated with keywords such as depression,stroke,neuropathic pain,and Parkinson's disease.Burst keywords focused on mild cognitive impairment,reflecting a diversification in research directions.The overall research activity in high-frequency repetitive transcranial magnetic stimulation continues to rise,with primary focuses on its clinical applications for psychiatric and neurological disorders,as well as explorations of its underlying mechanisms.Future research may focus on optimizing treatment parameters for targeting different brain regions in clinical applications and expanding its applications and mechanisms across various domains.

OBJECTIVE To provide a scientific basis for the quality evaluation and clinical application of Qingwen hufei granules. METHODS Fourteen batches of Qingwen hufei granules were used as samples to establish high-performance liquid chromatography （HPLC） fingerprints using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 Edition）. The chromatographic peaks were identified and the similarity was evaluated. Cluster analysis （CA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were used to conduct chemical pattern recognition analysis on the 14 batches of samples. Meanwhile， the contents of neochlorogenic acid （NGA）， chlorogenic acid （CHA）， cryptochlorogenic acid （CGA）， forsythoside A （FTA）， 3，5-O-dicaffeoylquinic acid （3，5-O- DA）， 4，5-O-dicaffeoylquinic acid （4，5-O-DA）， and angoroside C （AGC） in the samples were determined by HPLC. RESULTS The methodological investigation results of both the fingerprint and the content determination complied with the relevant requirements. Fourteen common peaks were indicated in the HPLC fingerprints of the 14 batches of samples， and 7 of them were identified [NGA （peak 2）， CHA （peak 3）， CGA （peak 5）， FTA （peak 11）， 3，5-O-DA （peak 12）， 4，5-O-DA （peak 13）， and AGC （peak 14）]； the similarity of each sample was greater than 0.94. The results of CA and PCA showed that the samples could be classified into 3 categories； the results of OPLS-DA indicated that peak 4 （unknown）， peak 11 （FTA）， peak 8 （unknown）， peak 9 （unknown）， and peak 1 （unknown） were the differential components. The content ranges of NGA， CHA， CGA， 3，5-O-DA， FTA， 4，5-O-DA and AGC in the 14 batches of samples were 0.210 4-0.458 7， 0.269 1-0.506 3， 0.228 1-0.461 1， 0.443 9-1.044 6， 0.066 7-0.155 7， 0.062 8-0.143 8， and 0.057 4-0.105 7 mg/g， respectively. CONCLUSIONS The HPLC fingerprint and multi-component content determination methods established in this study are efficient and reliable， and can be used for the quality evaluation of Qingwen hufei granules.

Irritable bowel syndrome with diarrhea （IBS-D）， as a prototypical disorder involving the microbiota-gut-brain axis， remains poorly understood in terms of its pathogenesis， posing ongoing challenges for clinical diagnosis. Omics technologies， leveraging their high-throughput detection and systematic analysis advantages， has emerged as a critical tool for deciphering the complex mechanisms underlying traditional Chinese medicine （TCM） treatment of IBS-D. This systematic review summarizes the research progress of transcriptomics， proteomics， metabolomics， microbiomics， and multi-omics integration techniques in TCM interventions for IBS-D. In single-omics studies， transcriptomics using techniques like RNA-seq， reveals the regulatory mechanisms of TCM on IBS-related signaling pathways. Proteomics， leveraging quantitative technologies such as 2D-difference gel electrophoresis and tandem mass tag， identifies differentially expressed proteins and elucidates the action targets of TCM in treating IBS-D. Metabolomics， employing methods like UPLC-Q-TOF-MS and LC-MS/MS， discovers metabolic pathways regulated by TCM to improve metabolic disturbances in IBS-D. Microbiomics， based on 16S rRNA sequencing， confirms that TCM can reshape the gut microbiota structure and restore the intestinal microecological balance， thereby improving IBS-D. Multi-omics integration further overcomes the limitations of single-omics approaches by synthesizing information from transcriptomics， proteomics， metabolomics， and microbiomics， enabling a more comprehensive and systematic elucidation of the complex mechanisms underlying TCM treatment for IBS-D. In the future， research related to IBS-D should be advanced from three aspects： stratified clinical research based on TCM syndrome types， multi-omics integration verification mechanisms， and emerging omics to explore new mechanisms， providing more innovative ideas for the precise diagnosis and treatment of this disease.

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 address the safety challenges arising from the rapid development of nuclear energy and technology, assess the current status of health emergency response capabilities in nuclear radiation emergencies, and promote capacity enhancement. Methods A preliminary evaluation system for health emergency response capability in nuclear radiation emergencies was developed based on a literature review. Two rounds of Delphi expert consultation (n = 20) were conducted, and the analytic hierarchy process was employed to establish judgment matrices for assigning indicator weights. Results The finalized system included six primary indicators (radiation protection capability, triage capability, decontamination and evacuation capability, medical treatment capability, radiation detection capability, and radiation dose estimation capability), along with 29 secondary indicators, such as capability for setting up emergency zones, capability for protecting personnel from internal and external contamination, on-site first aid capability, and personal dose monitoring capability. The expert response rate was 0.95, and the expert authority coefficient reached 0.80. The Kendall’s coefficient of concordance was W = 0.288 (P<0.01) for the first round of expert consultation and W = 0.308 (P<0.01) for the second round. Both rounds demonstrated high agreement among experts, and the consultation questionnaires passed reliability and validity tests. Conclusion By integrating qualitative analysis and quantitative calculation, this study developed a scientifically sound and operationally feasible evaluation system. This system will help identify gaps in health emergency response capabilities and provide scientific guidance and a decision-making basis for optimizing emergency plans and improving the level of health emergency response in nuclear radiation emergencies.

ObjectiveTo investigate the effects of the classical Chinese medicine compound prescription Erjingwan on the inflammatory response and apoptosis of skeletal muscle cells in a mouse model of sarcopenia and decipher the mechanism based on the silent information regulator 1 （SIRT1）/nuclear factor erythroid 2-related factor 2 （Nrf2）/heme oxygenase-1 （HO-1） signaling pathway. MethodsForty C57/BL6 male mice were randomized into a control group， a model group， and groups with different doses of Erjingwan （8，16，32 g·kg^-1）. The mouse model of sarcopenia was established by D-gal-induced skeletal muscle senescence. The body weight and grip strength of mice treated with different doses of Erjingwan were examined to evaluate their physiological functions. Hematoxylin-eosin （HE） staining and Masson staining were used to observe the pathological changes and fibrosis in the skeletal muscle of mice. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of tumor necrosis factor-α （TNF-α） and interleukin-6 （IL-6） in the serum samples of mice， and biochemical tests were conducted to quantify the levels of superoxide dismutase （SOD）， malondialdehyde （MDA）， and glutathione （GSH） in the serum. The protein and mRNA levels of SIRT1， Nrf2， B-cell lymphoma （Bcl-2）， and Bcl-2-associated X protein （Bax） were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， respectively. ResultsAfter 4 weeks of drug intervention， the model group exhibited significant reductions in body weight and grip strength （P0.01） compared with the control group. Compared with the model group， all doses of Erjingwan increased the body weight in mice at week 8 （P0.01） and grip strength from week 6 （P0.01）. HE staining revealed clear muscle fiber structure in the control group， muscle fiber rupture and atrophy in the model group， and dose-dependent repair of muscle fiber structure in the Erjingwan groups. Masson staining showed minimal collagen fibers and mild fibrosis in the control group， collagen fiber proliferation and severe fibrosis in the model group， and collagen proliferation with dose-dependent inhibition of fibrosis in the Erjingwan groups. ELISA results showed that serum levels of TNF-α and IL-6 were elevated in the model group compared with those in the control group （P0.01）. After intervention， the low-dose Erjingwan group exhibited a decreased TNF-α level （P0.05）， while the medium and high-dose groups showed decreases in both TNF-α and IL-6 levels （P0.01）. Biochemical assays revealed that the model group had decreased SOD and GSH levels （P0.01） and an increased MDA level （P0.01） compared with the control group. The medium and high-dose Erjingwan groups exhibited increases in SOD and GSH levels （P0.01） and decreases in MDA level （P0.01）， compared with the model group. WB and Real-time PCR results showed that compared with the control group， the model group presented down-regulated protein and mRNA levels of SIRT1， Nrf2， HO-1， and Bcl-2 in the muscle tissue （P0.01） and up-regulated protein and mRNA levels of Bax （P0.01）. Compared with the model group， Erjingwan at different doses up-regulated the protein levels of SIRT1， Nrf2， HO-1， and Bcl-2 （P0.01） and down-regulated the protein and mRNA levels of Bax （P0.01） in the muscle tissue. Low-dose Erjingwan elevated the mRNA levels of Nrf2 and HO-1 （P0.05， P0.01）， and medium and high-dose Erjingwan up-regulated the mRNA levels of SIRT1， Nrf2， HO-1， and Bcl-2 （P0.01）. ConclusionErjingwan reduced the content of inflammatory factors in skeletal muscle cells， improved the antioxidant capacity， and attenuated pathological changes and fibrosis in the muscle of the mouse model of sarcopenia by regulating the SIRT1/Nrf2/HO-1 pathway， inflammatory response， and apoptosis network.

ObjectiveTo explore the effects of Yimei Baijiang formula （YMBJF） on colitis-associated colorectal cancer （CAC） and the nuclear factor kappaB （NF-κB） signaling pathway in mice. MethodsSixty male Balb/c mice of 4-6 weeks old were randomized into 6 groups： Normal， model， capecitabine （0.83 g·kg^-1）， and low-， medium-， and high-dose （4.63， 9.25， 18.50 g·kg^-1， respectively） YMBJF. The mouse model of CAC was established by combining azoxymethane （AOM， 10 mg·kg^-1） and dextran sulfate sodium （DSS， 2%）. At the 5^th week after the start of modeling， the capecitabine group and the YMBJF groups were respectively administrated with the corresponding doses of drugs by gavage once a day for a total of 6 weeks. The body weights and general conditions of mice were measured and observed， and the disease activity index （DAI） was scored. The tumors in the colorectal tissue were counted， and the colorectal length was measured. The histological features of the colorectal tissue in each group of mice were observed by hematoxylin-eosin （HE） staining. The levels of inflammatory cytokines including interleukin-6 （IL-6）， interleukin-1β （IL-1β）， and tumor necrosis factor-α （TNF-α） in the serum were determined by enzyme-linked immunosorbent assay （ELISA）. The expression and localization of proliferating cell nuclear antigen-67 （Ki67）， proliferating cell nuclear antigen （PCNA）， and phosphorylated nuclear transcription factor-κB p65 （p-NF-κB p65） proteins were observed by immunohistochemistry （IHC）. The apoptosis of tumor cells was observed by the TUNEL assay. The mRNA levels of IL-6，IL-1β， TNF-α， nuclear transcription factor-κB p65 （NF-κB p65）， NF-κB inhibitor alpha （IκBα）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax） in the colorectal tissue were quantified by Real-time polymerase chain reaction（Real-time PCR）. The protein levels of NF-κB p65， phosphorylated （p）-NF-κB p65， IκBα， p-IκBα， Bcl-2， and Bax in the colorectal tissue were determined by Western blot. ResultsCompared with the model group， each YMBJF group showed decreases in DAI and tumor number （P0.01）， and the medium-dose and high-dose YMBJF groups showed increases in colorectal length （P0.05）. In addition， each YMBJF group showed alleviated colorectal mucosal pathological injury， declined levels of IL-6， IL-1β， and TNF-α in the serum （P0.05）， reduced expression of Ki67 and PCNA （P0.01）， and down-regulated expression of p-NF-κB p65 （P0.05）. The apoptosis in the medium-dose and high-dose YMBJF groups increased （P0.01）. Each YMBJF group and the capecitabine group showed down-regulated mRNA levels of IL-1β， TNF-α， IL-6， NF-κB p65， and Bcl-2 （P0.05） and up-regulated mRNA levels of IκBα and Bax （P0.05）. The mRNA level of IκBα was up-regulated， and that of Bcl-2 was down-regulated （P0.05） in the high-dose YMBJF group. The protein levels of p-IκBα and Bcl-2 were down-regulated （P0.05） in each YMBJF group. The protein levels of IκBα and Bax were up-regulated in the medium-dose and high-dose YMBJF groups （P0.01）， while those of NF-κB p65 and p-NF-κB p65 were down-regulated （P0.05）. ConclusionYMBJF can reduce the number of tumors， reduce the levels of inflammatory factors， promote tumor cell apoptosis， and inhibit tumor cell proliferation by regulating the direct effector molecules of the NF-κB signaling pathway in the mouse model of CRC.