ObjectiveBased on ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）， the combination of serum pharmacochemistry， response profile of absorbed components in serum， network pharmacology and drug-likeness prediction was used to screen the potential active ingredients of Yanghetang against breast cancer. MethodsUPLC-Q-TOF-MS/MS was used to identify the main components in different solvent extracts of Yanghetang， and serum pharmacochemistry was applied to analyze the absorbed components from the serum of female SD rats after 0.5， 1， 2 h of administration. Combined with the response characteristic values of serum drug components obtained from UNIFI 1.8.2， the absorbed prototype components and metabolites were screened to get the absorbed components of Yanghetang with a significant patterns of elimination and growth. Network pharmacology was applied to construct a drug-component-pathway-target-disease network， and molecular docking was performed between absorbed components and key targets of breast cancer， and the drug similarity was analyzed by SwissADME. ResultsForty-two compounds were identified in Yanghetang samples extracted with different solvents， of which 16 compounds were common to the three different extraction solvents（methanol， 50% methanol and water）. The results of drug-containing serum analysis showed that there were 16 absorbed components in serum， including 5 prototypes and 11 metabolites. Network pharmacology results showed that Yanghetang against breast cancer involved 15 key targets such as proto-oncogene tyrosine-protein kinase Src（SRC）， epidermal growth factor receptor（EGFR） and phosphoinositide 3 kinase catalytic alpha polypeptide（PIK3CA）. Molecular docking results showed that 16 potential active ingredients were well combined with the predicted targets. Combined with drug likenesses， 12 compounds in the absorbed components of Yanghetang were considered to have potential for anti-breast cancer activity， mainly including α-pinene and γ-eudesmol and their metabolites， of which one was from Ephedrae Herba， one was from Rehmanniae Radix， and eight were from Cinnamomi Cortex. ConclusionThe chemical components of Yanghetang mainly include polysaccharides， monoterpene glycosides and coumarins， and its prototype components mainly undergo oxidation， hydrolysis and acetylation after entering the blood. Its anti-breast cancer mechanism may be related to the regulation of signaling pathways such as the mitogen-activated protein kinase（MAPK） and phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt）. The results of this study can lay a foundation for further exploration of Yanghetang in the treatment of breast cancer.

ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

Non-small cell lung cancer is one of the cancers with the highest incidence and mortality rate in the world, and precise prognostic models can guide clinical treatment plans. With the continuous upgrading of computer technology, deep learning as a breakthrough technology of artificial intelligence has shown good performance and great potential in the application of non-small cell lung cancer prognosis model. The research on the application of deep learning in survival and recurrence prediction, efficacy prediction, distant metastasis prediction, and complication prediction of non-small cell lung cancer has made some progress, and it shows a trend of multi-omics and multi-modal joint, but there are still shortcomings, which should be further explored in the future to strengthen model verification and solve practical problems in clinical practice.

ObjectiveTo investigate the effect of modified Weijingtang on the pyroptosis of RAW264.7 macrophages via the cysteinyl aspartate-specific protease-1 （Caspase-1）/gasdermin D （GSDMD） pathway. MethodLipopolysaccharide （LPS） was used to induce pyroptosis of RAW264.7 cells. The blank group was treated with the blank serum， and the intervention groups were treated with the sera containing different doses of modified Weijingtang. After 24 h， the viability of cells in different groups was examined by the cell counting kit-8 （CCK-8）. The pyroptosis and morphology of cells in each group were observed by a scanning electron microscope and a phase-contrast microscope， respectively. The mRNA and protein levels of nucleotide-binding oligomerization domain-like receptor protein 3 （NLRP3）， Caspase-1， and GSDMD in each group were determined by real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot， respectively. The levels of interleukin （IL）-18 and IL-1β in each group were measured by enzyme-linked immunosorbent assay. ResultUnder the electron microscope， RAW264.7 cells presented the best morphology and structure in the blank group and obvious pyroptosis and leakage of cell contents in the model （LPS） group. Compared with the model group， the intervention groups showed reduced pyroptosis to varying degrees， and the high-dose group had the closest cell morphology and structure to the blank group. Under the optical microscope， RAW264.7 cells were spherical in the blank group and irregular with protrusions in the model group. Compared with the model group， the intervention groups showed improved cell morphology， and the cell morphology in the group with the dose of 20% was the closest to that in the blank group. The mRNA and protein levels of NLRP3， Caspase-1， and GSDMD in the model group were higher than those in the blank group （P<0.05）. Compared with the model group， each intervention group showed down-regulated expression of the above indicators （P<0.05）. Compared with the blank group， the model group presented elevated levels of IL-18 and IL-1β （P<0.05）， which were lowered in the intervention （10%， 20%） groups （P<0.01）. ConclusionModified Weijingtang inhibits the pyroptosis of macrophages by down-regulating the Caspase-1/GSDMD pathway and reducing the release of proinflammatory cytokines.

The traditional Chinese medicine （TCM） in pediatric care has a long history，proven efficacy，and distinctive characteristics.The China Association of Chinese Medicine has organized a series of youth salons to discuss the clinical advantages of treating diseases.Experts at this seminar proposed that the superior disease categories in pediatric TCM are significant for showcasing the unique strengths and advantages of TCM in the treatment of pediatric diseases，enhancing diagnostic and treatment levels，inheriting TCM knowledge，promoting the integration of TCM and Western medicine，and meeting patients' needs.The strengths of pediatric TCM are summed up as "having what others do not，excelling at what others have，being special in what others excel at，and ensuring safety in what others specialize in." The scope of superiority in pediatric TCM covers multiple systems，including respiratory，digestive，endocrine，psychological，and dermatological systems.This article summarized the advantages of TCM in treating 13 diseases discussed in the salon，such as upper respiratory tract infections，coughs，pneumonia，allergic rhinitis，bronchial asthma，atopic dermatitis，functional dyspepsia，functional constipation，enuresis，marginal short stature，simple obesity，attention deficit hyperactivity disorder，and tic disorders.The overall advantages were reflected in three aspects：First，the holistic concept and treatment based on syndrome differentiation in TCM highlight the advantage of treating the root causes of diseases，making the treatment methodical and precise.Second，most traditional Chinese herbs are natural and have strong safety profiles.Third，TCM treatment methods are abundant，especially the external treatment methods，which are widely used in pediatrics，highly accepted by parents，and have definite efficacy，as well as good safety and compliance.

Clinical trial is the gold standard for evaluating the efficacy and safety of interventions; however, it is limited by high costs and long time. Real-world data (RWD) can provide a robust data basis for comparative research, but the quality is uneven. This review introduces the target trial emulation, in which researchers, using RWD and following the design of clinical trials, define exposure and outcome in advance, set eligibility criteria, determine the time zero, estimate sample size, and plan statistical analysis, to enhance the quality of evidence for observational studies. This review preliminarily discusses the standard of evidence quality evaluation in target trial emulation. Then, the target trial emulation is shown through case interpretation.

Objective To explore the prognostic value of hs-cTnⅠ in patients with suspected acute coronary syndrome(ACS)in emergency department.Methods A large-scale,prospective observa-tional study was conducted on totally 966 patients with suspected ACS admitted in Fuwai Hospi-tal from January 2017 to October 2020.Their baseline serum/plasma hs-cTnⅠ level was detected at admission,conventional treatment was performed,and relevant data were collected.Logistic regression analysis was used to predict the risk of primary and secondary endpoint events within 30 d by hs-TnⅠ concentration,and subgroup analysis was performed.Results Among the 966 patients,the time from chest pain to visit was 5.0(2.5,13.0)h,and 284 patients had primary end-point events within 30 d,including 283 cases of myocardial infarction(99.6％)at the first visit,1 case of recurrent myocardial infarction(0.4％),5 cases of cardiovascular death(1.8％),and 1 case of unplanned revascularization(0.4％).When hs-cTnⅠ was at the minimum detection limit of 2 ng/L,the incidence of adverse events was 5.8％,when the limit of 70 ng/L,the incidence was 49.2％,and when of 316 ng/L,the incidence reached 100％.The model could correctly classify 92.3％of the patients.Conclusion The hs-cTn sequence has a good predictive effect for the risk of short-term cardiovascular adverse events in Chinese population.

Objective: This study aimed to determine the predictive performance of non-contrast CT (NCCT) signs for hemorrhagic growth after intracerebral hemorrhage (ICH) when stratified by onset-to-imaging time (OIT). Materials and Methods: 1488 supratentorial ICH within 6 h of onset were consecutively recruited from six centers between January 2018 and August 2022. NCCT signs were classified according to density (hypodensities, swirl sign, black hole sign, blend sign, fluid level, and heterogeneous density) and shape (island sign, satellite sign, and irregular shape) features. Multivariable logistic regression was used to evaluate the association between NCCT signs and three types of hemorrhagic growth: hematoma expansion (HE), intraventricular hemorrhage growth (IVHG), and revised HE (RHE). The performance of the NCCT signs was evaluated using the positive predictive value (PPV) stratified by OIT. Results: Multivariable analysis showed that hypodensities were an independent predictor of HE (adjusted odds ratio [95% confidence interval] of 7.99 [4.87–13.40]), IVHG (3.64 [2.15–6.24]), and RHE (7.90 [4.93–12.90]). Similarly, OIT (for a 1-h increase) was an independent inverse predictor of HE (0.59 [0.52–0.66]), IVHG (0.72 [0.64–0.81]), and RHE (0.61 [0.54– 0.67]). Blend and island signs were independently associated with HE and RHE (10.60 [7.36–15.30] and 10.10 [7.10–14.60], respectively, for the blend sign and 2.75 [1.64–4.67] and 2.62 [1.60–4.30], respectively, for the island sign). Hypodensities demonstrated low PPVs of 0.41 (110/269) or lower for IVHG when stratified by OIT. When OIT was ≤ 2 h, the PPVs of hypodensities, blend sign, and island sign for RHE were 0.80 (215/269), 0.90 (142/157), and 0.83 (103/124), respectively. Conclusion Hypodensities, blend sign, and island sign were the best NCCT predictors of RHE when OIT was ≤ 2 h. NCCT signs may assist in earlier recognition of the risk of hemorrhagic growth and guide early intervention to prevent neurological deterioration resulting from hemorrhagic growth.

Objective To evaluate the effect of preoperative pulmonary artery pressure on perioperative prognosis of the recipients with end-stage heart failure undergoing heart transplantation. Methods Clinical data of 105 recipients receiving heart transplantation were retrospectively analyzed. The mean pulmonary artery pressure (mPAP) was used as the diagnostic criterion. The optimal cut-off value of mPAP for predicting perioperative prognosis of heart transplant recipients was determined. According to the optimal cut-off value of mPAP, all recipients were divided into the low mPAP group (n=66) and high mPAP group (n=39). Intraoperative indexes (cardiopulmonary bypass time, aortic occlusion time, assisted circulation time and cold ischemia time of donor heart) and postoperative indexes [intra-aortic balloon pump (IABP) support rate, IABP support time, extracorporeal membrane oxygenation (ECMO) support rate, ECMO support time, mechanical ventilation time, length of ICU stay, incidence of moderate and severe tricuspid regurgitation and perioperative mortality rate] were compared between the low and high mPAP groups. The prognosis of the two groups was compared. Results The optimal cut-off value of mPAP in predicting clinical prognosis of heart transplant recipients was 30.5 mmHg. In the high mPAP group, the ECMO support rate and perioperative mortality rate were higher than those in the low mPAP group (both P < 0.05). No significant differences were observed in the cardiopulmonary bypass time, aortic occlusion time, assisted circulation time, cold ischemia time of donor heart, IABP support rate, IABP support time, ECMO support time, mechanical ventilation time, length of ICU stay and incidence of moderate and severe tricuspid regurgitation between two groups (all P > 0.05). No significant differences were noted in the 1-, 2-, 3- and 4- survival rates between two groups (all P > 0.05). Conclusions Preoperative mPAP in patients with end-stage heart failure is intimately correlated with perioperative prognosis of heart transplant recipients. The optimal cut-off value of mPAP in predicting perioperative prognosis of heart transplant recipients is 30.5 mmHg. In the high mPAP group, perioperative ECMO support rate and perioperative mortality rate are high, which do not affect the medium and long-term prognosis of the recipients undergoing heart transplantation.