With the rapid advancement of medical technology and the increasing complexity of clinical environments, competence in clinical ethical decision-making has become an indispensable core competency for exemplary physicians. However, traditional medical ethics education has long been confronted with the persistent challenges of theory-practice dissociation and the disconnect between pedagogical settings and clinical realities. Thus, how to construct a "Clinical Ethics" curriculum that aligns with the objectives of training high-caliber medical professionals has emerged as a critical and challenging issue in current medical education reform. To effectively address this challenge, the Office of Education at Peking University Third Hospital, since 2021, has assembled a multidisciplinary "Clinical Ethics" teaching and management team comprising faculty from Peking University School of Humanities and key clinical specialists from the hospital. In 2022, the "Clinical Ethics" elective course was formally launched for fourth-year students in the eight-year MD program who had completed coursework in "Medical Ethics" and organ-system-based curricula, with the aim of exploring and operationalizing a pre-clinical ethics education model tailored for senior medical students. The course employs a modular instructional design encompassing "theoretical review-case-based deliberation-clinical workshop", which effectively facilitates the deep integration of medical humanities with clinical practice.Following four years of iterative refinement through the "plan-act-observe-reflect" cycle, the course has demonstrated positive outcomes in enhancing students' ethical awareness and decision-making capabilities, and has preliminarily established a sustainable collaborative mechanism among the multidisciplinary faculty team. This article systematically delineates the course development background, pedagogical model and methodological innovations, and the multidisciplinary collaborative framework, alongside reflections and summaries based on implementation outcomes, with the intent of providing references for the future development of "Clinical Ethics" curricula.

Drug repurposing offers a promising alternative to traditional drug development and significantly reduces costs and timelines by identifying new therapeutic uses for existing drugs. However, the current approaches often rely on limited data sources and simplistic hypotheses, which restrict their ability to capture the multi-faceted nature of biological systems. This study introduces adaptive multi-view learning (AMVL), a novel methodology that integrates chemical-induced transcriptional profiles (CTPs), knowledge graph (KG) embeddings, and large language model (LLM) representations, to enhance drug repurposing predictions. AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning (MVL), matrix factorization, and ensemble optimization techniques to integrate heterogeneous multi-source data. Comprehensive evaluations on benchmark datasets (Fdataset, Cdataset, and Ydataset) and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art (SOTA) methods, achieving superior accuracy in predicting drug-disease associations across multiple metrics. Literature-based validation further confirmed the model's predictive capabilities, with seven out of the top ten predictions corroborated by post-2011 evidence. To promote transparency and reproducibility, all data and codes used in this study were open-sourced, providing resources for processing CTPs, KG, and LLM-based similarity calculations, along with the complete AMVL algorithm and benchmarking procedures. By unifying diverse data modalities, AMVL offers a robust and scalable solution for accelerating drug discovery, fostering advancements in translational medicine and integrating multi-omics data. We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Tumor is the main lethal type of major diseases that human beings are facing nowadays.Traditional therapies,such as chemotherapy,surgery,radiotherapy,etc,have been the mainstay of tumor treatment for a long time,and still have their own limitations in terms of effectiveness.In recent years,immunotherapy for tumors has attracted much attention with the rise of strategies such as immune checkpoint inhibitors,chimeric antigen receptor T-cell(CAR-T)relay therapy,and anti-tumor vaccines.Among them,CAR-T cell therapy,as a breakthrough tumor immunotherapy method,can precisely target tumors at the cellular and molecular levels by modifying the patient's own T cells to express recombinant antigen receptors targeting specific tumor antigens,breaking the restriction of the major histocompatibility complex(MHC)of the natural T cells themselves.It can precisely target tumors at the cellular and molecular levels,and thus can efficiently and specifically identify and kill cancer cells,providing a new perspective for treatment.Since the approval of the first CAR-T therapy by the US Food and Drug Administration(FDA)in 2017,in addition to still maintaining significant advantages in the field of classical multiple hematologic malignancies,it has also made outstanding progress in the treatment and clinical trials of some solid tumors and autoimmune diseases,among others.This paper will briefly review the current principles,applications,challenges and directions of development of CAR-T technology.

Drug repurposing offers a promising alternative to traditional drug development and significantly re-duces costs and timelines by identifying new therapeutic uses for existing drugs.However,the current approaches often rely on limited data sources and simplistic hypotheses,which restrict their ability to capture the multi-faceted nature of biological systems.This study introduces adaptive multi-view learning(AMVL),a novel methodology that integrates chemical-induced transcriptional profiles(CTPs),knowledge graph(KG)embeddings,and large language model(LLM)representations,to enhance drug repurposing predictions.AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning(MVL),matrix factorization,and ensemble optimization techniques to integrate heterogeneous multi-source data.Comprehensive evaluations on benchmark datasets(Fdata-set,Cdataset,and Ydataset)and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art(SOTA)methods,achieving superior accuracy in predicting drug-disease associations across multiple metrics.Literature-based validation further confirmed the model's predictive capabilities,with seven out of the top ten predictions corroborated by post-2011 evidence.To promote transparency and reproducibility,all data and codes used in this study were open-sourced,providing resources for pro-cessing CTPs,KG,and LLM-based similarity calculations,along with the complete AMVL algorithm and benchmarking procedures.By unifying diverse data modalities,AMVL offers a robust and scalable so-lution for accelerating drug discovery,fostering advancements in translational medicine and integrating multi-omics data.We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Objective To investigate the clinical efficacy and safety of facilitated percutaneous coronary intervention(PCI)with half-dose recombinant staphylokinase(r-SAK)in patients with ST-segment elevation myocardial infarction(STEMI)who are expected to undergo PCI within 120 minutes.Methods From October 2021 to August 2022,a total of 200 STEMI patients in eight centers were included and randomly assigned in a 1﹕1 ratio to either r-SAK group or control group.Patients received loading doses of aspirin and ticagrelor and intravenous heparin and were randomized to receive an intravenous bolus of either 5 mg r-SAK or normal saline prior to PCI.The outcomes were set as ST-segment resolution(STR)at 60-90 minutes after PCI,the proportion and transition of pathological Q waves on the 5th day after PCI,and the proportion of high-sensitivity cardiac troponin T(hs-cTnT)peaking within 12 hours of onset.The safety outcome was major bleeding events defined as Bleeding Academic Research Consortium(BARC)≥type 3 bleeding during hospitalization.Results Compared with the control group,the r-SAK group had a higher proportion of STR≥70%within 60-90 minutes after PCI(58.3%vs.40.3%,P=0.009);a lower proportion of pathological Q waves(59.1%vs.74.1%,P=0.040);a lower rate of Q wave progression(14.8%vs.43.2%,P＜0.001);a higher rate of Q wave disappearance(12.5%vs.3.7%,P=0.027);and a higher proportion of hs-cTnT peaking within 12 hours of symptom onset[31/40(77.5%)vs.17/33(51.5%),P=0.027].Regarding the safety outcome,no significant difference in BARC≥type 3 bleeding was found between the two groups during hospitalization(P＞0.05).Conclusions For STEMI patients who were expected to undergo primary PCI within 120 minutes of symptom onset,the facilitated PCI with half-dose r-SAK significantly increased the proportion of STR≥70%at 60-90 minutes after PCI,reduced the formation of pathological Q waves,and shortened the time to peak hs-cTnT,without increasing the risk of bleeding,which should be an alternative reperfusion strategy worthy of further study.

Objective To investigate the clinical efficacy and safety of facilitated percutaneous coronary intervention(PCI)with half-dose recombinant staphylokinase(r-SAK)in patients with ST-segment elevation myocardial infarction(STEMI)who are expected to undergo PCI within 120 minutes.Methods From October 2021 to August 2022,a total of 200 STEMI patients in eight centers were included and randomly assigned in a 1﹕1 ratio to either r-SAK group or control group.Patients received loading doses of aspirin and ticagrelor and intravenous heparin and were randomized to receive an intravenous bolus of either 5 mg r-SAK or normal saline prior to PCI.The outcomes were set as ST-segment resolution(STR)at 60-90 minutes after PCI,the proportion and transition of pathological Q waves on the 5th day after PCI,and the proportion of high-sensitivity cardiac troponin T(hs-cTnT)peaking within 12 hours of onset.The safety outcome was major bleeding events defined as Bleeding Academic Research Consortium(BARC)≥type 3 bleeding during hospitalization.Results Compared with the control group,the r-SAK group had a higher proportion of STR≥70%within 60-90 minutes after PCI(58.3%vs.40.3%,P=0.009);a lower proportion of pathological Q waves(59.1%vs.74.1%,P=0.040);a lower rate of Q wave progression(14.8%vs.43.2%,P＜0.001);a higher rate of Q wave disappearance(12.5%vs.3.7%,P=0.027);and a higher proportion of hs-cTnT peaking within 12 hours of symptom onset[31/40(77.5%)vs.17/33(51.5%),P=0.027].Regarding the safety outcome,no significant difference in BARC≥type 3 bleeding was found between the two groups during hospitalization(P＞0.05).Conclusions For STEMI patients who were expected to undergo primary PCI within 120 minutes of symptom onset,the facilitated PCI with half-dose r-SAK significantly increased the proportion of STR≥70%at 60-90 minutes after PCI,reduced the formation of pathological Q waves,and shortened the time to peak hs-cTnT,without increasing the risk of bleeding,which should be an alternative reperfusion strategy worthy of further study.

Objective To investigate the differences in blood pressure phenotypes,renal pathological changes,and related pathogenic pathways in genetically diverse hypertensive mice obtained from 13 strains.Methods The genotypes of Cckbr+/+,Cckbr+/-and Cckbr-/-were obtained by hybridization of 13 strains of genetically diverse mice with Cckbr-/-mice.Blood pressure was measured with a noninvasive blood pressure analysis system(BP-2000).The expression of CCKBR protein in mouse kidney tissue was detected by Western Blot,and the pathological changes in mouse kidney tissue were detected by hematoxylin-eosin(HE)staining and immunohistochemistry(IHC).The pathogenic pathways related to essential hypertension were screened by RNA sequencing.Results In three specific mouse strains(A/J,LOT,and FIM),the systolic blood pressure(SBP)was significantly different between the Cckbr-/-and Cckbr+/+groups.HE staining and IHC showed that hypertension caused a certain degree of renal injury in the mice.Gene Ontology(GO)and pathway enrichment analysis showed that differentially expressed genes were enriched in metabolic processes and circadian rhythm regulation.Conclusions Genetically diverse mice can effectively simulate the genetic background of the population and provide a new resource for studying the pathogenic genes related to essential hypertension.

Background: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Methods: The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance. Results: The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05). Conclusion The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.

Objective: To analyze and compare therapy responses, outcomes, and incidence of severe hematologic adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia (CML) . Methods: Data of patients with chronic phase CML diagnosed between January 2006 and November 2022 from 76 centers, aged ≥18 years, and received initial flumatinib or imatinib therapy within 6 months after diagnosis in China were retrospectively interrogated. Propensity score matching (PSM) analysis was performed to reduce the bias of the initial TKI selection, and the therapy responses and outcomes of patients receiving initial flumatinib or imatinib therapy were compared. Results: A total of 4 833 adult patients with CML receiving initial imatinib (n=4 380) or flumatinib (n=453) therapy were included in the study. In the imatinib cohort, the median follow-up time was 54 [interquartile range (IQR), 31-85] months, and the 7-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.2%, 88.4%, 78.3%, and 63.0%, respectively. The 7-year FFS, PFS, and OS rates were 71.8%, 93.0%, and 96.9%, respectively. With the median follow-up of 18 (IQR, 13-25) months in the flumatinib cohort, the 2-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.4%, 86.5%, 58.4%, and 46.6%, respectively. The 2-year FFS, PFS, and OS rates were 80.1%, 95.0%, and 99.5%, respectively. The PSM analysis indicated that patients receiving initial flumatinib therapy had significantly higher cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) and higher probabilities of FFS than those receiving the initial imatinib therapy (all P<0.001), whereas the PFS (P=0.230) and OS (P=0.268) were comparable between the two cohorts. The incidence of severe hematologic adverse events (grade≥Ⅲ) was comparable in the two cohorts. Conclusion: Patients receiving initial flumatinib therapy had higher cumulative incidences of therapy responses and higher probability of FFS than those receiving initial imatinib therapy, whereas the incidence of severe hematologic adverse events was comparable between the two cohorts.
Adult ; Humans ; Adolescent ; Imatinib Mesylate/adverse effects* ; Incidence ; Antineoplastic Agents/adverse effects* ; Retrospective Studies ; Pyrimidines/adverse effects* ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy* ; Treatment Outcome ; Benzamides/adverse effects* ; Leukemia, Myeloid, Chronic-Phase/drug therapy* ; Aminopyridines/therapeutic use* ; Protein Kinase Inhibitors/therapeutic use*

OBJECTIVE: To investigate the effect of Yinlai Decoction (YD) on the microstructure of colon, and activity of D-lactic acid (DLA) and diamine oxidase (DAO) in serum of pneumonia mice model fed with high-calorie and high-protein diet (HCD). METHODS: Sixty male Kunming mice were randomly divided into 6 groups by the random number table method: normal control, pneumonia, HCD, HCD with pneumonia (HCD-P), YD (229.2 mg/mL), and dexamethasone (15.63 mg/mL) groups, with 10 in each group. HCD mice were fed with 52% milk solution by gavage. Pneumonia mice was modeled with lipopolysaccharide inhalation and was fed by gavage with either the corresponding therapeutic drugs or saline water, twice daily, for 3 days. After hematoxylin-eosin staining, the changes in the colon structure were observed under light microscopy and transmission electron microscope, respectively. Enzyme-linked immunosorbent assay was used to detect the protein levels of DLA and DAO in the serum of mice. RESULTS: The colonic mucosal structure and ultrastructure of mice in the normal control group were clear and intact. The colonic mucosal goblet cells in the pneumonia group tended to increase, and the size of the microvilli varied. In the HCD-P group, the mucosal goblet cells showed a marked increase in size with increased secretory activity. Loose mucosal epithelial connections were also observed, as shown by widened intercellular gaps with short sparse microvilli. These pathological changes of intestinal mucosa were significantly reduced in mouse models with YD treatment, while there was no significant improvement after dexamethasone treatment. The serum DLA level was significantly higher in the pneumonia, HCD, and HCD-P groups as compared with the normal control group (P<0.05). Serum DLA was significantly lower in the YD group than HCD-P group (P<0.05). Moreover, serum DLA level significantly increased in the dexamethasone group as compared with the YD group (P<0.01). There was no statistical significance in the serum level of DAO among groups (P>0.05). CONCLUSIONS YD can protect function of intestinal mucosa by improving the tissue morphology of intestinal mucosa and maintaining integrity of cell connections and microvilli structure, thereby reducing permeability of intestinal mucosa to regulate the serum levels of DLA in mice.
Mice ; Male ; Animals ; Lactic Acid/pharmacology* ; Intestinal Mucosa ; Colon/pathology* ; Dexamethasone/pharmacology* ; Diet, High-Protein ; Pneumonia/pathology*