The compilation instructions for the Expert Consensus on Clinical Application of Yifei Zhike Capsules systematically expound the development background， methodological framework， and core achievements of this consensus. In view of the problems existing in the clinical application of Yifei Zhike Capsules， such as insufficient efficacy evidence and lack of standardized syndrome differentiation， the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences took the lead and collaborated with 21 tertiary grade-A hospitals and research institutions across China to form a multidisciplinary expert group （comprising 30 experts in clinical medicine， pharmacy， and methodology）. The compilation work was carried out in strict accordance with the World Health Organization （WHO） guidelines， the GB/T 1.1-2020 standard， and the writing specifications for the explanatory notes of expert consensus on clinical application of Chinese patent medicines. Through systematic literature retrieval （including 32 studies， with 24 clinical studies）， Grading of Recommendations Assessment， Development and Evaluations （GRADE）-based evidence grading， and multiple rounds of discussions using the nominal group method （25 experts voted to determine 17 clinical questions）， 5 evidence-based recommendations and 11 expert consensus suggestions were formed. It is clarified that this medicine （Yifei Zhike Capsules） is applicable to the treatment of expectoration/hemoptysis in acute and chronic bronchitis and the adjuvant treatment of pulmonary tuberculosis. It is recommended that it can be used alone or in combination with anti-tuberculosis drugs. The safety evaluation shows that this medicine mainly induces the following adverse reactions： mild gastrointestinal reactions （such as nausea and abdominal pain） and rashes. The contraindicated populations include pregnant women and women during menstruation. The compilation process of the consensus underwent three rounds of expert letter reviews， two rounds of peer reviews， and quality control assessments to ensure methodological rigor and clinical applicability. In addition， through policy alignment， academic promotion， and a dynamic revision mechanism， the standardization of clinical application was promoted， providing a demonstration for the evidence-based transformation of characteristic therapies of Miao medicine.

As an exclusive Miao medicine of Honwing Pharma （Guizhou） Co. Ltd.， Yifei Zhike capsules are both a prescription drug and an over-the-counter （OTC） drug. Its main ingredients include Ranunculus ternatus and Panax notoginseng. With the effects of nourishing Yin and moistening the lungs， as well as relieving cough and reducing phlegm， Yifei Zhike capsules are often used in the treatment of acute and chronic bronchitis， pulmonary tuberculosis， and other diseases. However， there is insufficient understanding of their efficacy， suitable syndromes， and safety in clinical practice， with a lack of relevant expert consensus on clinical application. To standardize their clinical application， 30 experts from the fields of respiratory medicine， pharmacy， and evidence-based medicine were invited to develop an Expert Consensus on the Clinical Application of Yifei Zhike Capsules （Consensus for short） through evidence-based medicine methods. The Consensus clarified the syndrome characteristics， disease stages， dosages， treatment courses， combined medication， and other norms in the treatment of acute/chronic bronchitis and pulmonary tuberculosis and could be applicable to clinical physicians and pharmacists in medical and health institutions at all levels. In disease diagnosis， it provided diagnostic criteria for traditional Chinese medicine and Western medicine and clarified that the suitable traditional Chinese medicine syndrome was the syndrome of Qi-Yin deficiency with intermingled phlegm-blood stasis. Clinical studies have confirmed that Yifei Zhike capsules combined with standard anti-tuberculosis therapy can effectively improve the symptoms of pulmonary tuberculosis patients， increase the sputum smear conversion rate， and promote the absorption of lesions. When treating acute cough caused by respiratory tract infections， Yifei Zhike capsules can increase the markedly effective rate and the seven-day disappearance rate of cough symptoms. Meanwhile， recommendations for specific usage， dosages， and treatment courses were given for different diseases， and it was pointed out that long-term medication required key monitoring of adverse reactions. In safety， the adverse reactions of Yifei Zhike capsules involved multiple aspects such as the digestive system and allergic reactions， and pregnant women and women during menstruation were prohibited from using it. In addition， modern research has shown that Yifei Zhike capsules have an adjuvant therapeutic effect on tuberculous pleurisy and may be effective for inflammatory and benign pulmonary nodules. However， further research should be conducted on the toxicological safety of long-term medication. The formulation of the Consensus provides a scientific basis for the rational clinical application of Yifei Zhike capsules， which helps to improve clinical efficacy and reduce medication risks.

As an exclusive Miao medicine of Honwing Pharma （Guizhou） Co. Ltd.， Yifei Zhike capsules are both a prescription drug and an over-the-counter （OTC） drug. Its main ingredients include Ranunculus ternatus and Panax notoginseng. With the effects of nourishing Yin and moistening the lungs， as well as relieving cough and reducing phlegm， Yifei Zhike capsules are often used in the treatment of acute and chronic bronchitis， pulmonary tuberculosis， and other diseases. However， there is insufficient understanding of their efficacy， suitable syndromes， and safety in clinical practice， with a lack of relevant expert consensus on clinical application. To standardize their clinical application， 30 experts from the fields of respiratory medicine， pharmacy， and evidence-based medicine were invited to develop an Expert Consensus on the Clinical Application of Yifei Zhike Capsules （Consensus for short） through evidence-based medicine methods. The Consensus clarified the syndrome characteristics， disease stages， dosages， treatment courses， combined medication， and other norms in the treatment of acute/chronic bronchitis and pulmonary tuberculosis and could be applicable to clinical physicians and pharmacists in medical and health institutions at all levels. In disease diagnosis， it provided diagnostic criteria for traditional Chinese medicine and Western medicine and clarified that the suitable traditional Chinese medicine syndrome was the syndrome of Qi-Yin deficiency with intermingled phlegm-blood stasis. Clinical studies have confirmed that Yifei Zhike capsules combined with standard anti-tuberculosis therapy can effectively improve the symptoms of pulmonary tuberculosis patients， increase the sputum smear conversion rate， and promote the absorption of lesions. When treating acute cough caused by respiratory tract infections， Yifei Zhike capsules can increase the markedly effective rate and the seven-day disappearance rate of cough symptoms. Meanwhile， recommendations for specific usage， dosages， and treatment courses were given for different diseases， and it was pointed out that long-term medication required key monitoring of adverse reactions. In safety， the adverse reactions of Yifei Zhike capsules involved multiple aspects such as the digestive system and allergic reactions， and pregnant women and women during menstruation were prohibited from using it. In addition， modern research has shown that Yifei Zhike capsules have an adjuvant therapeutic effect on tuberculous pleurisy and may be effective for inflammatory and benign pulmonary nodules. However， further research should be conducted on the toxicological safety of long-term medication. The formulation of the Consensus provides a scientific basis for the rational clinical application of Yifei Zhike capsules， which helps to improve clinical efficacy and reduce medication risks.

Cardiotoxicity is a critical issue in drug development that poses serious health risks,including potentially fatal arrhythmias.The human ether-à-go-go related gene(hERG)potassium channel,as one of the pri-mary targets of cardiotoxicity,has garnered widespread attention.Traditional cardiotoxicity testing methods are expensive and time-consuming,making computational virtual screening a suitable alter-native.In this study,we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds,with the aim of improving prediction accuracy and efficiency.We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms,including Gaussian naive Bayes(NB),random forest(RF),support vector machine(SVM),K-nearest neighbors(KNN),eXtreme gradient boosting(XGBoost),and Trans-former models,to build predictive models.Our models demonstrated advanced predictive performance.The best machine learning model,XGBoost Morgan,achieved an accuracy(ACC)value of 0.84,and the deep learning model,Transformer_Morgan,achieved the best ACC value of 0.85,showing a high ability to distinguish between toxic and non-toxic compounds.On an external independent validation set,it achieved the best area under the curve(AUC)value of 0.93,surpassing ADMETlab3.0,Cardpred,and CardioDPi.In addition,we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods,such as voting and stacking,provided slight improvements in model stability.Furthermore,the SHapley Additive exPlanations(SHAP)explanations revealed the relationship between benzene rings,fluorine-containing groups,NH groups,oxygen in ether groups,and cardiotoxicity,highlighting the importance of these features.This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment.Using computational methods,this study facilitates a more efficient drug development process,reduces costs,and improves the safety of new drug candidates,ultimately benefiting medical and public health.

Objective:To investigate the clinical value of the prediction models constructed by CT based imaging features and radiomics for World Health Organization/International Society of Urological Pathology (WHO/ISUP) grading in pre-operative patients with T1 clear cell renal cell carcinoma (ccRCC).Methods:Ninety patients with ccRCC diagnosed at Hangzhou Hospital of Traditional Chinese Medicine from January 2016 to December 2023 were enrolled as the training set, and 43 patients diagnosed at the Sir Run Run Shaw Hospital from January 2017 to December 2018 were enrolled as the external validation set. According to the WHO/ISUP grading system, grades Ⅰ and Ⅱ were defined as the low grade group, and grades Ⅲ and Ⅳ were defined as the high grade group. In the training set, 64 patients were in the low grade group and 26 patients in the high grade group. In the external validation set, 33 patients were in the low grade group and 10 patients in the high grade group. The multivariate logistic regression was used to establish an imaging factor model based on CT imaging features in the training set. The 3-dimensional regions of interest were manually contoured at the cortical phase of enhanced CT, and the radiomics features were extracted. Linear correlation between features and L1 regularization were used for feature selection, and then linear support vector classification was used to construct the radiomics model. After that, a combined diagnostic model of nomogram combining the radiomics score and imaging factors was constructed using multivariate logistic regression analysis. The receiver operating characteristic (ROC) curve was used to evaluate the effectiveness of each model. The Delong test was used for comparison of the areas under the ROC curve.Results:The imaging factor model, the radiomics model, and the combined diagnostic model of nomogram were successfully constructed to predict the WHO/ ISUP grading in stage T1 ccRCC. The AUC value of the imaging factor model in the training and validation sets was 0.742 (95% CI: 0.623-0.860) and 0.664 (95% CI: 0.448-0.879), respectively. The AUC values of the radiomics model in the two sets were 0.914 (95% CI: 0.844-0.983) and 0.879 (95% CI: 0.718-1.000), and of the combined diagnostic model of nomogram in the two sets were 0.929 (95% CI: 0.858-0.999) and 0.882 (95% CI: 0.710-1.000), respectively. The AUCs of the radiomics model and combined diagnostic model of nomogram were significantly higher than that of the imaging factor model (both P＜0.05). There was no statistical difference in the AUCs between the combined diagnostic model of nomogram and the radiomics model (both P＞0.05). Conclusion:The CT-based radiomics model and combined diagnostic model of nomogram incorporating radiomics signature and imaging features showed favorable predictive efficacy for the preoperative prediction of WHO/ISUP grading in stage T1 ccRCC.

AIM:This study aims to investigate the mechanism by which LINC00973 regulates multidrug re-sistance of non-small-cell lung cancer(NSCLC).METHODS:The GEPIA database was employed to analyze the expres-sion levels of LINC00973 in NSCLC and its correlation with patient prognosis in clinical settings.RT-qPCR was utilized to assess LINC00973 expression in various NSCLC cell lines and chemoresistant cells.The migration,invasion,stemness ca-pacity,and drug sensitivity of NSCLC cells with either overexpression or knockdown of LINC00973 were evaluated using wound healing assay,Transwell assay,sphere formation assay,and CCK-8 assay.RNA sequencing was conducted on LINC00973-overexpressing and parental NSCLC cells to identify dysregulated pathways and targets.The LncBase Pre-dicted v.2 and TargetScan databases were used to predict the microRNAs(miRNAs)co-bound by LINC00973 and their target genes.Mimics and inhibitors of candidate miRNAs were synthesized and transfected into NSCLC cells subjected to LINC00973 overexpression or knockdown.Changes in the expression level of LINC00973,and the mRNA and protein ex-pression levels of its target genes were assessed using RT-qPCR and Western blot.RESULTS:Analysis of the GEPIA da-tabase revealed that LINC00973 was significantly up-regulated in lung adenocarcinoma and lung squamous cell carcino-ma,correlating with poor prognosis of NSCLC patients.The LINC00973 expression was elevated in various NSCLC and chemoresistant cell lines(A549/DDP and A549/5-FU).Overexpression of LINC00973 in A549 and H520 cells markedly enhanced their migration,invasion,and stemness capabilities,while concurrently reducing sensitivity to chemotherapy and targeted therapies.RNA sequencing,along with RT-qPCR results,indicated that ATP-binding cassette transporter G5(ABCG5)was activated in LINC00973-overexpressing A549 and H520 cells.Further database analyses and dual trans-fection experiments confirmed that LINC00973 regulated ABCG5 expression through competitive binding with hsa-miR-150-5p.CONCLUSION:LINC00973,which is aberrantly up-regulated in NSCLC specimens and associated with poor clinical prognosis,promotes the expression of ABCG5 through competitive binding with hsa-miR-150-5p.This interaction leads to en-hanced invasion,stemness,and multidrug resistance in NSCLC cells.

Objective:To investigate the clinicopathological and molecular genetic characteristics of intracranial mesenchymal tumors with FET::CREB fusion transcript.Methods:The clinical and imaging data of 6 cases of intracranial mesenchymal tumors with FET::CREB fusion from December 2018 to December 2023 were collected at the First Affiliated Hospital of Zhengzhou University. Their histological features, immunophenotype and molecular characteristics were analyzed.Results:Among the 6 patients, 4 were males and 2 were females, and the median age was 20 years. The clinical symptoms were increased intracranial pressure in 5 cases and epilepsy in 1 case. The lesion sites were cerebellum (2 cases), frontal lobe (2 cases), parietal lobe (1 case), and cranioorbital communication (1 case). The radiological features mainly showed solid or cystic components, with obvious annular enhancement on MRI. The histopathological features showed a wide spectrum of morphology, clear boundaries and fibrous pseudocapsule. The tumor cells were arranged in a lamellar or nodular pattern, and some in cord or loose network. The tumor cells were spindle, oval, epithelioid or stellate. The stroma was collagenous or mucin-rich, and accompanied by abundant lymphocytes and plasma cells infiltration. By immunohistochemical staining, desmin, CD99 and EMA were expressed in 6 cases, CD68 in 1 case, MUC4 in 1 case, synaptophysin in 2 cases, and ALK in 1 case. The Ki-67 proliferation index was between 1%-15%. Molecular analysis showed EWSR1::ATF1 fusion in 3 cases, EWSR1::CREB1 fusion in 2 cases, and EWSR1::CREM fusion in 1 case.Conclusions:Intracranial mesenchymal tumors with FET::CREB fusion are relatively rare and typically occur in children and younger adults. These tumors have a broad morphological spectrum and often express desmin, CD99 and EMA. The molecular characteristics are the gene fusions of FET family (mainly EWSR1, FUS) with CREB family transcription factors (ATF1, CREB1 or CREM). It is necessary to distinguish these tumors from meningiomas and solitary fibrous tumors, and the combination of immunohistochemical staining and molecular genetic testing can effectively help identify these tumors.

Objective To retrospectively analyze the correlation between inflammatory markers in complete blood counts(CBC)and influenza A virus infection in patients visited the outpatient department of Nanjing First Hospital.Methods The suspected influenza A virus infection patients visited the outpatient department of Nanjing First Hospital from February to March 2023 were collected and di-vided into the positive and negative groups based on the detection results of influenza A virus antigen.The differences in inflammatory markers in CBC between the two groups were compared.The Logistic regression analysis was used to evaluate the correlation between inflammatory markers and influenza A virus infection.Meanwhile,the restricted cubic spline(RCS)and age subgroup(≤6 years,7-12 years,13-17 years,and ≥18 years)analysis were also performed.Results A total of 1 487 outpatients were included,of which 404(27.2％)were positive for influenza A virus antigen.The Logistic regression analysis showed that white blood cell count(WBC),lymphocyte percentage(LY％),and lymphocyte count(LYM)were significantly negatively correlated with influenza A virus infection(P＜0.01),while the neutrophil percentage(NE％),monocyte/lymphocyte ratio(MLR),and neutrophil/lymphocyte ratio(NLR)were significantly positively correlated with influenza A virus infection(P＜0.01).The RCS analysis exhibited the same trend.The age subgroup analysis showed that when the age was greater than 6 years,LYM was significantly negatively correlated with influenza A virus infection(P＜0.01).When the age was greater than 12 years,MLR was significantly positively correlated with influenza A virus infec-tion(P＜0.01).Conclusion The WBC,LY％,LYM,NE％,MLR,and NLR in CBC parameters are important indicators associated with the occurrence of Influenza A virus infection,especially LYM in patients aged over 6 years and MLR in patients aged over 12 years,which may serve as biomarkers for the diagnosis and differential diagnosis of influenza A virus infection.

Cardiotoxicity is a critical issue in drug development that poses serious health risks, including potentially fatal arrhythmias. The human ether-à-go-go related gene (hERG) potassium channel, as one of the primary targets of cardiotoxicity, has garnered widespread attention. Traditional cardiotoxicity testing methods are expensive and time-consuming, making computational virtual screening a suitable alternative. In this study, we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds, with the aim of improving prediction accuracy and efficiency. We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. Our models demonstrated advanced predictive performance. The best machine learning model, XGBoost Morgan, achieved an accuracy (ACC) value of 0.84, and the deep learning model, Transformer_Morgan, achieved the best ACC value of 0.85, showing a high ability to distinguish between toxic and non-toxic compounds. On an external independent validation set, it achieved the best area under the curve (AUC) value of 0.93, surpassing ADMETlab3.0, Cardpred, and CardioDPi. In addition, we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods, such as voting and stacking, provided slight improvements in model stability. Furthermore, the SHapley Additive exPlanations (SHAP) explanations revealed the relationship between benzene rings, fluorine-containing groups, NH groups, oxygen in ether groups, and cardiotoxicity, highlighting the importance of these features. This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment. Using computational methods, this study facilitates a more efficient drug development process, reduces costs, and improves the safety of new drug candidates, ultimately benefiting medical and public health.

Objective:To investigate the effect of nuclear receptor subfamily 2 group F member 2(NR2F2)on the biological behaviors of human ovarian cancer SKOV3 cells,and to clarify its molecular mechauism and provide the new idea for treatment of ovarian cancer.Methods:Gene Expression Profiling Interactive Analysis(GEPIA)Database analyse the expression level of NR2F2 gene in ovarian tissue,and analyse its correlation with clinical prognosis of ovarian cancer patients.The human ovarian cancer SKOV3 cells were divided into control group and NR2F2 over-expression(NR2F2 OE)group,which were transfected with mCherry control virus and NR2F2 OE over-expression virus,respectively,when the cell deusity reached 70％,and the stable transfection SKOV3 cell lines were screened with puromycin(puro)48h lafter.Real-time fluorescence quantitative PCR(RT-qPCR)and Western blotting methods were used to detect the transfection efficiencies of the cells;RT-qPCR method was used to detect the expression levels of NR2F2 and sex-determining region Y-box 2(SOX2)mRNA in the cells in two groups;Western blotting method was used to detect the expression levels of NR2F2,ATP-binding cassette superfamily G member 2(ABCG2),and programmed cell death 1-ligand 1(PD-L1)protcins in the cells in two groups.CCK-8 assay was used to detect the proliferation activities of the cells in two groups;Wound assay was used to detect the migration rates of the cells in two groups;Transwell chamber assay was used to detect the number of transmembrane cells;Spheroidization assay was used to detect the numbers of spheroids in the cells;peripheral blood mononuclear cells(PBMCs)-mediated tumor cell killing assay was used to detect the relative densities of surviving tumor cells;CCK-8 assay was used to detect the half maximal inhibitory concentration(IC50)of paclitaxel(PTX)and carboplatin(CBP).Results:Compared with normal ovarian tissue,the expression level of NR2F2 gene in ovarian tumor tissue was decreased(P＜0.05),and decreased with the improvement of clinical pathological grading of ovarian tumor.The patients with higher expression level of NR2F2 gene had better clincal prognosis.The SKOV3 cells with NR2F2 over-expresson were successfully constructed,and the expression levels of NR2F2 mRNA and protein in the cells in NR2F2 OE group were increased compared with control group(P＜0.001).The CCK-8 assay results showed that compared with control group,the proliferation activities of the cells in NR2F2 OE group were decreased at different time points(1,2,3,and 4 d)(P＜0.05 or P＜0.01).The cell wound assay results showed that compared with control group,the migration rate of the cells in NR2F2 OE group was decreased(P＜0.001).The Transwell assay results showed that compared with control group,the number of transmembrane cells in NR2F2 OE group was decreased(P＜0.01).Compared with control group,the number of the spheroids in NR2F2 OE group was decreased(P＜0.05),and the expression levels of SOX2 mRNA(P＜0.01)and protein(P＜0.001)were increased.Compared with control group,the relative density of surviving tumor cells in NR2F2 OE group was decreased,but the difference was not significant(P＜0.05),and the expression level of PD-L1 protein was decreased(P＜0.05).Compared with control group,the proliferation activities of cells in NR2F2 OE group were decreased(P＜0.05),and the drug sensitivities of the cells to PTX and CBP were enhanced(P＜0.05);the IC50 of PTX was significantly reduced,while the IC50of CBP could not be calculated due to excessively high drug concentration;the expression level of ABCG2 protein was decreased(P＜0.05).Conclusion:The over-expression of NR2F2 may inhibit the proliferation,migration,and invasion of the human ovarian cancer SKOV3 cells,decrease the expression levels of SOX2,PD-L1 and ABCG2 proteins,suppress the stemness and immune evasion ability of the SKOV3 cells,and enhance the sensitivities of the SKOV3 cells to PTX and CBP.