Microbial infections are a prevalent challenge in the prevention and treatment of oral diseases. Antibiotic therapy faces clinical limitations due to its single-target mechanism and tendency to induce resistance with repeated use, necessitating novel antibacterial strategies. Stimuli-responsive antibacterial materials, whose antimicrobial activity can be modulated by external stimuli, offer advantages such as remote controllability, potential for localized precision treatment, and a reduced risk of inducing resistance. Among these materials, mechanical force-triggered piezoelectric materials exhibit significant antibacterial activity in the biomedical field owing to their unique piezoelectric effect, excellent stability, and good biocompatibility. Research has shown that piezoelectric materials can convert mechanical energy into electrical energy in response to external forces, which enables antibacterial effects without requiring an external power source. The underlying mechanisms primarily include direct electric field effects, generation of reactive oxygen species, and immune modulation. Preliminary applications in treating oral infections (e.g., dental caries, periodontitis, and peri-implantitis) have confirmed their stability and biocompatibility, establishing a foundation for clinical translation. However, long-term efficacy and biosafety in the complex oral microenvironment require further validation. Future research should focus on optimizing material preparation protocols to enhance antibacterial efficacy and stability, further investigating the underlying antimicrobial mechanisms, and systematically evaluating their therapeutic outcomes and safety profiles across various types of oral infections. This review summarizes the antibacterial effects, mechanisms, stability, safety, and research progress of piezoelectric materials in the stomatologic field, aiming to provide new insights for further research and application in this area.

Breast cancer is the most common malignant tumor in women worldwide.HER2-positive and HER2-low breast cancers are highly aggressive subtypes with poor prognosis.First-line combination therapies targeting HER2 have significantly improved treatment outcomes for patients with advanced and metastatic breast cancer,but resistance inevitably develops.The emergence of antibody-drug conjugates(ADCs)brings new hope for the treatment of advanced HER2-positive and HER2-low breast cancers.This article analyzes the efficacy and safety of key ADC drugs,including adotrastuzumab emtansine(T-DM1),trastuzumab deruxtecan(DS-8201,T-DXd)and other drugs in the treatment of advanced HER2-positive and HER2-low breast cancers.It also reviews mechanisms of ADC resistance and discusses corres-ponding management strategies,aiming to provide more efficient and personalized treatment options for patients with advanced HER2-pos-itive and HER2-low breast cancers.

Recent progress in the field of breast cancer research was reported at the American Society of Clinical Oncology(ASCO)annual meeting.Research on neoadjuvant therapy for breast cancer represents the current main approach,such as finding different chemothera-peutic regimens to enhance efficacy and improve prognosis,developing treatment strategies for patients who do not achieve pathological complete response(non-pathologic complete response,non-pCR)after neoadjuvant therapy,and exploring predictive biomarkers or tools for efficacy and prognosis.In this article,we report related research progress in neoadjuvant therapy for different subtypes of breast cancer in ASCO 2024 to present the current overall landscape of neoadjuvant therapy and provide a reference for clinical decision-making.

Objective:To understand the status quo of general practice postgraduate researches through visualized analysis of masters′ theses.Methods:The master′s theses in general medicine from January 2007 to December 2022 were retrieved from China Knowledge and Wanfang databases. The number and regional distribution of theses, the degree-granting institutions were analyzed; the performed keywords were visualizde with CiteSpace and VOSviewer softwares.Results:A total of 1 688 master′s theses in general practice were included in the analysis. The highest number of theses ( n=345) were published in 2022. The theses from institutions in the eastern, central and western regions of China accounted for 45.67% (771/1 688), 22.16% (374/1 688) and 32.17% (543/1 688), respectively, and those in Shaanxi Province accounted for the highest proportion at 13.68% (231/1 688). A total of 3 755 keywords were included in the theses, and the top three were diabetes mellitus (115/3 755), risk factors (77/3 755) and clinical efficacy (71/3 755). The results of keyword clustering and timeline mapping showed that the research topics were mainly clustered around five themes: clinical treatment and drug efficacy/safety for diabetes mellitus, training of general practitioners and evaluation of general practice services, risk factors related to common chronic diseases in the community, risk factors and cognitive changes in cerebrovascular diseases, and pathogenic mechanisms of cardiovascular diseases. The results of the emergent words showed that recent research hotspots mainly included obesity, older adults, and cognitive function. Conclusions:The number of general practice master′s theses published in China is increasing rapidly with an uneven regional distribution; and the research topics are diverse, mainly focusing on the diagnosis and treatment of chronic diseases and analysis of related risk factors.

The primary role of transfer RNA(tRNA)is to connect a specific amino acid to its 3' end, use its anticodon to match the codon on messenger RNA(mRNA), and deliver the corresponding amino acid to the ribosome for protein synthesis.tRNA exists in two forms: precursor tRNA and mature tRNA.When acted upon by enzymes like Dicer, elaC ribonuclease Z 2(ELAC2), angiopoietin(ANG), and other ribonucleases, tRNA is broken down into tRNA-derived stress-induced RNA(tiRNA)and tRNA-derived fragments(tRF).Recent advancements in RNA sequencing technology have led to increased interest in tiRNA and tRF, shedding light on their roles in various physiological and pathological processes.tRNA-derived small molecules(tsRNA)function similarly to microRNA(miRNA), influencing gene expression and protein synthesis.They show promise as diagnostic markers and potential therapeutic targets for age-related diseases.This review offers a comprehensive analysis of tsRNA classification, biological functions, research advancements, and clinical applications in age-related conditions.

Grounded in organizational change-complex systems theory,it investigates the pathways and mechanisms for deep integration of Artificial Intelligence(AI)into clinical management.Addressing structural challenges in current clinical management systems,it propose a dynamic three-phase model"unfreezing-changing-refreezing"driven by AI technologies.By deconstructing systemic contradictions arising from technological penetration e.g.,multi-agent coordination,ethical risks,and responsibility ambiguity,a layered governance framework and dynamic regulatory mechanisms are established.Through synergistic evolution of technology,organization,and institution,an adaptive transition in clinical management paradigms can be achieved,ultimately fostering an AI-augmented healthcare ecosystem that balances efficiency with safety.

Objective To establish a Nomogram model based on serum tumor markers to assess the risk of pleural metastasis in patients with stage Ⅲ lung cancer,and to validate the constructed model.Methods A to-tal of 140 patients with stage Ⅲ lung cancer in the hospital from January 2022 to October 2024 were selected as the research subjects.They were divided into the metastasis group(36 cases)and the non-metastasis group(104 cases)based on whether pleural metastasis occurred.Clinical data of patients in the two groups were col-lected,and the levels of serum tumor markers[carcinoembryonic antigen(CEA),cancer antigen(CA)125,CA15-3,CA19-9]of patients in the two groups were detected simultaneously.The risk factors affecting pleural metastasis in patients with stage Ⅲ lung cancer were screened,and the risk of pleural metastasis in patients with stage Ⅲ lung cancer was evaluated by constructing a Nomogram model based on serum tumor markers,and the constructed prediction model was validated.Results The proportion of smoking history,maximum tumor diameter≥4 cm,lymph node metastasis and low differentiation in metastatic group were higher than those in non-metastatic group(P＜0.05).Compared with non-metastatic group,serum CEA,CA125,CA15-3 and CA19-9 levels in metastatic group were higher(P＜0.05).Multiuariate Logistic regression analysis showed that lymph node metastasis,low differentiation and abnormal increase of CEA,CA125,CA15-3 and CA19-9 levels were independent risk factors for pleural metastasis in stage Ⅲ lung cancer patients(P＜0.05).The area under the receiver operating characteristic curve of the Nomogram model constructed based on serum tumor markers was 0.896(95％CI:0.812-0.991),which proved that the model had good predic-tive efficacy.The calibration curve of the model confirmed that there was a good agreement between the pre-dicted risk and the actual risk,and the Hosmer-Lemeshow goodness of fit curve test x2=1.602,P=0.638.The results of the decision curve analysis show that this model could achieve a relatively high net benefit with-in the range of 0％to 80％.Conclusion The Nomogram model based on serum tumor markers can effectively evaluate the risk of pleural metastasis in patients with stage Ⅲ lung cancer,and has good calibration,goodness of fit and clinical practicability.

With the extension of the global population's lifespan and the increasingly severe aging problem,cardio-vascular diseases have become the leading cause of death among the elderly population.Most cardiovascular diseases orig-inate from the formation of atherosclerotic plaques.In addition to common risk factors such as dyslipidemia,diabetes,hy-pertension,smoking,and obesity,circadian rhythm disruption is also regarded as an important but often overlooked risk factor for atherosclerosis.The circadian rhythm is involved in regulating key physiological processes such as inflammation and metabolism,which in turn affect the pathological processes of arteriosclerosis and thrombosis.In this process,the key genes that maintain the stability of the circadian rhythm,namely clock gene,play a crucial role.Clock gene have an important role in the pathological mechanism of atherosclerosis,and they may become potential new targets for the preven-tion and treatment of atherosclerosis.This paper reviews the latest research progress on the mechanism of action of clock gene in the occurrence and development of atherosclerosis.These findings may provide new ideas for the diagnosis and treatment of atherosclerosis.

Objective:To investigate the clinical application effect of Zishen Yutai Pill in patients with repeated implantation failure (RIF) undergoing frozen-thawed embryo transfer (FET) cycles.Methods:A retrospective case-control study was conducted, selecting 744 cycles of patients with RIF at the Department of Female Reproductive Medicine,State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Reproductive Medicine, Institute of Women, Children and Reproductive Health, Shandong University from October 2017 to April 2023. The patients were divided into experimental group (treated with Zishen Yutai Pill, n=279) and control group (treated without Zishen Yutai Pill, n=465) based on whether Zishen Yutai Pill was added to luteal support. The pregnancy outcomes between the two groups were compared. Based on the different endometrial preparation protocols in the FET cycles, the patients were used down-regulation protocol ( n=271) or non-down-regulation protocol ( n=473). The pregnancy outcomes of the two groups in each protocol were compared. Results:There were no statistically significant differences between the two groups in terms of biochemical pregnancy rate, clinical pregnancy rate, embryo implantation rate, early miscarriage rate, late miscarriage rate, and live birth rate (all P>0.05). However, the biochemical pregnancy rate [69.0% (58/84)], clinical pregnancy rate [59.5% (50/84)], and embryo implantation rate [59.4% (57/96)] in the experimental group of the down-regulated protocol were significantly higher than those in control group [56.1% (105/187), P=0.045; 46.5% (87/187), P=0.048; 44.9% (92/205), P=0.019], with statistically significant differences. In the non-down-regulated protocol, there were no statistically significant differences in pregnancy outcomes between the two groups (all P>0.05). Conclusion:In the FET down-regulated protocol, Zishen Yutai Pill can significantly improve the clinical pregnancy rate and the embryo implantation rate in patients with RIF, thereby improving pregnancy outcomes.

Objective:To investigate the risk factors of pediatric sepsis-induced coagulopathy（pSIC），and to construct a nomogram prediction model for early prediction of pSIC.Methods:Using a cross-sectional retrospective cohort design，children with sepsis who were hospitalized in PICU of the Second People's Hospital of Liaocheng Subsidiary to Shandong First Medical University from January 2017 to December 2023 were selected as the study objects，and the diagnosis of sepsis met the diagnostic criteria for childhood sepsis of the 2015 edition.According to the diagnostic criteria of pSIC，the children with sepsis were divided into common sepsis group and pSIC group.The clinical data of both groups were compared，such as general condition，inflammatory indicators，coagulation indicators，sequential organ failure assessment（pSOFA），pSIC score，PICU duration，etc.The risk factors of pSIC were initially screened by Lasso regression analysis，and the independent risk factors were screened by multivariate Logistic regression analysis.R software was used to construct the risk prediction nomogram and evaluate the model.Results:A total of 150 children with sepsis were included in the study，including 121 in the common sepsis group and 29 in the pSIC group.Lasso regression and multivariate Logistic regression analysis showed that pSOFA，prothrombin time（PT），alanine aminotransferase（ALT），blood urea nitrogen（BUN），mean platelet volume/platelet（MPV/PLT）and pediatric critical illness score(PCIS) were independent risk factors for pSIC（all P<0.05）.Since the sources of the pSIC score overlaped with those of pSOFA and PT, only four indicators including ALT，BUN，MPV/PLT and PCIS were used to construct a nomogram model for predicting pSIC.The consistency index of the nomogram model was 0.98，and the area under the receiver operating characteristic curve was 0.975（95% CI 0.952-0.999）.The calibration curve was shown as a straight line with slope close to 1，indicating that the nomogram model had good accuracy in predicting pSIC.The clinical decision curve indicated that the nomogram model had good clinical applicability. Conclusion:pSOFA，PT，ALT，BUN，MPV/PLT and PCIS were all independent risk factors for pSIC.The risk prediction nomogram model of pSIC based on ALT，BUN，MPV/PLT and PCIS can predict the occurrence of pSIC，and provide reference for early clinical recognition and intervention.