The Pharmacovigilance Guidelines for Clinical Application of Oral Chinese Patent Medicines （hereinafter referred to as the Guidelines） is first specialized in the field of drug safety for oral Chinese patent medicines （OCPMs） in China. Rooted in China's healthcare context， the Guidelines address the unique usage patterns and risk characteristics of OCPMs， filling a regulatory gap in the pharmacovigilance framework specific to this category. To facilitate accurate understanding and effective implementation of the Guidelines， and to promote the standardized development of pharmacovigilance practices for OCPMs， this study offered a systematic interpretation based on its three core components. In the domain of risk monitoring and reporting， the paper analyzed the rationale for multi-source information integration and clarified the criteria for identifying key products and target populations for intensive monitoring. Regarding risk assessment， the Guidelines were examined from three dimensions of formulation components， medication behaviors， and population to address complex safety issues arising from medicinal constituents， irrational use， and individual susceptibility. In the area of risk control， the analysis focused on context-based interventions and dynamic closed-loop management strategies， exploring practical pathways to shift from passive response to proactive risk mitigation. Furthermore， this paper evaluated the applied value of the Guidelines and identified implementation challenges， such as insufficient capacity at the primary-care level and limited digital infrastructure. In response， the study proposed optimization strategies including establishing a dynamic updating mechanism， strengthening training at the grassroots level， and incorporating artificial intelligence to enhance pharmacovigilance capacity. This interpretation aims to provide actionable insights for marketing authorization holders （including manufacturers）， pharmaceutical distributors， healthcare institutions， and research organizations， ultimately supporting the establishment and refinement of a full lifecycle pharmacovigilance system for OCPMs.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective:Acute myocardial infarction (AMI) secondary to acute gastrointestinal bleeding (AGIB) is a common severe condition in emergency department. Currently, there is a lack of sufficient data regarding the use of emergency endoscopy in patients suffering from acute gastrointestinal bleeding (AGIB) complicated with acute myocardial infarction (AMI). The objective of this study is to examine the present status, effectiveness, and safety of emergency endoscopy in such patients, and to determine the factors that influence clinicians' decision-making regarding the use of emergency endoscopy.Methods:Clinical data of AGIB patients complicated with AMI who were admitted to the emergency department of the First Affiliated Hospital of Nanjing Medical University from January 2020 to June 2023 were respectively collected. Based on their survival status at discharge, patients were categorized into survival and non-survival groups. Additionally, according to whether emergency endoscopy was performed, patients were further classified into the emergency endoscopy group and the conventional treatment groupStabilized inverse probability of treatment weighting (SIPTW) and logistic regression analysis were used to explore the correlation between emergency endoscopy and prognosis. A paired wilcoxon test was used to analyze whether emergency endoscopy could worsen myocardial injury. A multiple logistic regression model was used to explore the factors influencing clinicians to make emergency endoscopic decisions.Results:A total of 106 patients with AMI secondary to AGIB were included, and 22 patients underwent emergency endoscopy. After weighing, logistic regression analysis showed that emergency endoscopy was a protective factor for patients' survival after discharge ( OR = 0.808, 95% CI: 0.6755-0.967, P = 0.022). In the emergency endoscopy group, there was no significant change in hypersensitive troponin T before and after emergency endoscopy [ 61.1 (35.4, 164.1) ng/L vs 69.8 (60.1, 159.5) ng/L, P = 0.078]. Previous history of coronary heart disease ( OR = 0.098, 95% CI: 0.015-0.381, P = 0.003) was an independent negative factor for emergency endoscopic decision-making. Glasgow Blatchford Score (GBS) on admission ( OR = 1.217, 95% CI: 1.019-1.482, P = 0.038) was an independent positive factor for emergency endoscopic decision-making. Conclusions:Emergency endoscopy is safe and effective in patients with AMI secondary to AGIB. GBS score and previous history of coronary heart disease were the main factors affecting emergency endoscopic decision-making.

Knee osteoarthritis(KOA)is a common chronic degenerative bone and joint disease characterized by degeneration and wear of knee cartilage.It is commonly found in middle-aged and elderly people and seriously impacts on their lower limb activity and quality of life.At present,the treatment of early and middle stage KOA mainly relies on the conservative methods such as oral medication,joint injection,topical patches and traditional Chinese medicine.Platelet rich plasma(PRP),as an autologous platelet concentrate,is rich in various growth factors and has no risk of immune rejection.In recent years,it has been widely used in the repair of bone,joint,and soft tissue injuries.However,the short biological half-life of growth factors in PRP and the fluidity of injection sites can result in insufficient binding force,short action time,poor target therapy efficacy,and the need for repeated injections in the joint cavity,which will increase the risk of iatrogenic infections.Hydrogels are cross-linked polymer networks containing water,and their high histocompatibility and drug release have attracted much attention.The slow and continuous release of drug is achieved by loading PRP onto hydrogel.Its unique adhesion reduces the flow of drug in the joint,thus extending the local action time of PRP and reducing the need for repeated injection.This article reviews the biological characteristics of PRP and hydrogel,the mechanism of action and clinical application of PRP loaded hydrogel in the treatment of KOA,and analyzes the existing problems and challenges,aiming to provide more effective treatment options for KOA patients through the in-depth discussion of this new treatment method.

Objective:To explore the effect of social cognition and interaction training (SCIT) combined with transcranial magnetic stimulation (TMS) on intrinsic motivation and social cognition in patients with schizophrenia.Methods:Forty-two stable schizophrenia patients were randomly divided into the SCIT + TMS group( n=22) and the SCIT group( n=20). All the subjects received 20 sessions of SCIT treatment, and the SCIT+ TMS group simultaneously received 15 sessions of intermittent theta burst stimulation(iTBS) over the left dorsolateral prefrontal cortex(DLPFC). All the subjects were assessed by intrinsic motivation inventory for schizophrenia research(IMI-SR), Chinese version of the ambiguous intentions hostility questionnaire(AIHQ-C), theory of mind-picture sequencing task(ToM-PST), mentalization scale (MentS), Chinese version of interpersonal reactivity index (IRI-C) and positive and negative syndrome scale (PANSS) before and after intervention. SPSS 26.0 software was used for data analysis.Wilcoxon signed-rank test was used for intra-group comparison before and after treatment, while Mann-Whitney U test and covariance analysis were used for inter-group comparison.Spearman correlation analysis and Logistic regression analyses were used to explore the association between the intrinsic motivation and social cognition. Results:There were no significant differences on IMI-SR scores before and after treatment between the two groups(all P>0.05). In the SCIT+ TMS group, the total score of hostility bias (HB), HB scores in ambiguous scenes, HB scores in intentional scenes, and aggressive bias (AB) scores in ambiguous scenes of AIHQ-C scale after treatment were lower than those befor treatment( Z=-2.044--3.112, all P<0.05), while the total score of ToM-PST(18.50(16.00, 21.00) vs 15.50(11.75, 18.00), Z=-2.598, P=0.009) and IRI-C imagination score (12.18±3.79, 14.41±4.73, t=-2.694, P=0.014) were higher than those before treatment.In the SCIT group, the total score of ToM-PST after treatment was higher than that before treatment(21.00(20.00, 22.00) vs 17.00(14.50, 20.75), Z=-2.518, P=0.012).There was no significant statistical difference in MentS scores between after treatment and before treatment ( P>0.05). The difference in AIHQ-C intentional scenario AB score before and after treatment was higher in the SCIT+ TMS group than in the SCIT group ( Z=-1.996, P=0.046), while there was no statistically significant difference in the difference before and after treatment in social cognitive scores between the two groups (all P>0.05).In the combined two samples, Spearman correlation analysis showed that the total score of IMI-SR before treatment was positively correlated with the primary belief score of ToM-PST understanding, reciprocity score, MentS total score, other person mentalization score, motivation mentalization score, IRI-C total score, viewpoint taking score, and empathy concern score after treatment( r=0.341-0.509, all P<0.05), while negatively correlated with AIHQ-C total score and factor scores ( r=-0.434--0.645, P<0.05).Logistic regression analysis showed that the total score of IMI-SR had negative impact on AIHQ-C total HB score( B=-0.047, OR=0.954, 95% CI=0.917-0.993).The value score had a positive impact on the total score of MentS ( B=0.143, OR=1.154, 95% CI=1.043-1.277), other person mentalization score( B=0.166, OR=1.181, 95% CI=1.058-1.318), motivation mentalization score( B=0.111, OR=1.117, 95% CI=1.021-1.223), IRI-C total score ( B=0.138, OR=1.148, 95% CI=1.038-1.270), and viewpoint taking score( B=0.194, OR=1.214, 95% CI=1.076-1.369). Interest score had a positive impact on IRI-C empathy concern score ( B=0.098, OR=1.103, 95% CI=0.998-1.218) and ToM-PST understanding primary belief score( B=0.130, OR=1.138, 95% CI=1.010-1.283) and reciprocity score( B=0.189, OR=1.208, 95% CI=1.057-1.380). Conclusion:The research results did not confirm the effect of TMS over the DLPFC on enhancing intrinsic motivation, as well as the synergistic effect of SCIT treatment on social cognition. But the correlation results indicates that improving schizophrenia patients' intrinsic motivation level in cognitive training is meaningful for promoting social cognition.

Aim To explore the effect of the classical famous prescription Dahuang Zhechong pill(DHZCP)on relieving liver cirrhosis by regulating the stress fiber remodeling mediated by mechanistic signaling pathway and to explore the underlying mechanism.Methods Mice were randomly divided into the control group,model group,DHZCP low-dose group,DHZCP high-dose group,and Colchicine-positive control group.The liver cirrhosis mouse model was constructed by intrap-eritoneal injection of olive oil-solubilized CCl4.HE staining and serologic markers were used to reflect liver injury.Masson staining was used to evaluate collagen deposition in liver tissue.ELISA was applied to detect vasoactive molecules and cancer indicators.Atomic force microscopy was employed to detect liver tissue stiffness.Color Doppler diagnostic instrument was used to assess portal blood flow velocity.Western blot was utilized to detect ROCK2 expression and phosphoryla-tion of YAP,Cofilin,and MLC.Results The liver tis-sues in the model group had obvious inflammatory cell infiltration and collagen deposition,accompanied by significant elevation of serum transaminases and fibrosis indexes.Similarly,vasoactive molecules and cancer in-dicators were elevated,and the mechanoregulatory pro-tein ROCK2 expression and phosphorylation of Cofilin and MLC were elevated,with YAP being strongly de-phosphorylated.Both low and high doses of DHZCP re-versed the pathological changes,serological indices,and inhibited the activation of the stress fiber(SF)re-modeling mechanistic signaling pathway.Conclusion DHZCP effectively ameliorates liver tissue lesions in mice with liver cirrhosis,and its mechanism may be re-lated to the inhibition of SF remodeling mechanistic signaling pathway.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

OBJECTIVE: To investigate the effect of miR-483-5p on hepatocellular carcinoma (HCC) cells proliferation and stemness, as well as the attenuating effect of Pien Tze Huang (PZH). METHODS: Differentially expressed miRNA between HepG2 cells and hepatic cancer stem-like cells (HCSCs) were identified by a miRNA microarray assay. miR-483-5p mimics were transfected into HepG2 cells to explore the effects of miR-483-5p on cell proliferation and stemness. HepG2 cells and HCSCs were treated with PZH (0, 0.25, 0.50 and 0.75 mg/mL) to explore the effects of PZH on the proliferation and stemness, both in non-induced state and the state induced by miR-483-5p mimics. RESULTS: miR-483-5p was significantly up-regulated in HCSCs and its overexpression increased cell proliferation and stemness in HepG2 cells (P<0.05). PZH not only significantly inhibited proliferation in HepG2 cells, but also significantly suppressed the cell proliferation and self-renewal of HCSCs (P<0.05). The effects of miR-483-5p mimics on proliferation and stemness of HepG2 cells were partially abolished by PZH. CONCLUSIONS miR-483-5p promotes proliferation and enhances stemness of HepG2 cells, which were attenuated by PZH, demonstrating that miR-483-5p is a potential molecular target for the treatment of HCC and provide experimental evidence to support clinical use of PZH for patients with HCC.
Humans ; MicroRNAs/metabolism* ; Cell Proliferation/drug effects* ; Liver Neoplasms/drug therapy* ; Carcinoma, Hepatocellular/drug therapy* ; Hep G2 Cells ; Neoplastic Stem Cells/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Gene Expression Regulation, Neoplastic/drug effects*