Because of the unclear active substances, metabolic pathways, and targets of new drugs of traditional Chinese medicine(TCM), non-clinical safety evaluation often fails to accurately locate the target organs and tissue exposed to medicinal toxicity. The human use experience(HUE) contains important safety information of TCM, while the clinical safety data in the past HUE are few and have not been effectively applied. Standardized prospective HUE studies should be carried out to collect the clinical safety data, in which appropriate physical and chemical indicators(including blood, urine, and stool routine), liver biochemical indicators, kidney biochemical indicators, and cardiovascular biochemical indicators should be selected for safety evaluation, and the detection time point and sample size should be rationally designed. Importance should be attached to the observation of symptoms and signs of adverse events/reactions in patients as well as the safety information of special groups such as the elderly, children, and pregnant women. The adverse events of TCM should be observed, judged, and treated according to the theory and the diagnosis and treatment mode of TCM. The clinical safety information about the HUE should be comprehensively collected for new drugs of TCM to make up for the lack of extrapolation of toxicological test results to humans. The unique advantages of clinical origin of new drugs of TCM should be given full play for cross-reference of the results of toxicological research and the conclusions of HUE safety evaluation. In addition, benefit-risk assessment should be conducted based on HUE, and a panoramic safety evaluation system characterized by macro and micro combination and in line with the characteristics of TCM should be established to improve the success rate in the research and development of new drugs of TCM.
Humans ; Drugs, Chinese Herbal/adverse effects* ; Medicine, Chinese Traditional/adverse effects* ; Drug-Related Side Effects and Adverse Reactions ; Female

In the development of traditional Chinese medicine(TCM), the concept of "preventive treatment of disease" has a long history and plays a crucial role in bridging the past and the future. With the continuous growth of public health needs and the ongoing transformation of the registration management of TCM, its position in the research and development of new drugs has become increasingly significant. As one of the important sources of new drug innovation, the new TCM for "preventive treatment of diseases" represents a new thinking proposed based on the current routine registration and research and development. The research and development of TCM for "preventive treatment of diseases" mainly cover four stages: prevention(before the onset of disease), early intervention(when the disease is about to occur), interruption and reversal(when the disease has already occurred), and prevention of recurrence after recovery(after the disease). This study aims to comprehensively analyze the positioning, key points, and difficulties in the research and development of TCM for "preventive treatment of diseases" and explore effective paths to promote the innovative development of TCM through relevant cases. The research and development of new TCM for "preventive treatment of disease" require researchers to seize the opportunities for innovation before the start of the research and development, accurately grasp the key issues at different stages, and pay attention to the full lifecycle evaluation of the drugs. Meanwhile, in the design of the research plan, the optimal effectiveness evaluation indicators should be explored; key and difficult areas such as chronic diseases and rare diseases should be taken seriously, and the limitations of new drug development only based on the diagnosed diseases should be broken, so as to cater to more patients. In addition, through relevant representative cases in China and abroad, the unique advantages of TCM for "preventive treatment of diseases" should be fully leveraged. By learning from the past, all aspects of key points in the evaluation of new drug research and development should be strengthened. Finally, this study proposed that TCM for "preventive treatment of diseases" can employ novel methods and advanced technologies such as new biomarkers and innovative clinical design protocols, as well as new perspectives on disease research and health management. This can provide new paths for the innovation of TCM and public health management.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional/methods* ; Pharmacy Research

Extensive epigenetic reprogramming involves in memory CD8+ T-cell differentiation. The elaborate epigenetic rewiring underlying the heterogeneous functional states of CD8+ T cells remains hidden. Here, we profile single-cell chromatin accessibility and map enhancer-promoter interactomes to characterize the differentiation trajectory of memory CD8+ T cells. We reveal that under distinct epigenetic regulations, the early activated CD8+ T cells divergently originated for short-lived effector and memory precursor effector cells. We also uncover a defined epigenetic rewiring leading to the conversion from effector memory to central memory cells during memory formation. Additionally, we illustrate chromatin regulatory mechanisms underlying long-lasting versus transient transcription regulation during memory differentiation. Finally, we confirm the essential roles of Sox4 and Nrf2 in developing memory precursor effector and effector memory cells, respectively, and validate cell state-specific enhancers in regulating Il7r using CRISPR-Cas9. Our data pave the way for understanding the mechanism underlying epigenetic memory formation in CD8+ T-cell differentiation.
CD8-Positive T-Lymphocytes/metabolism* ; Cell Differentiation ; Chromatin/immunology* ; Animals ; Mice ; Immunologic Memory ; Epigenesis, Genetic ; SOXC Transcription Factors/immunology* ; NF-E2-Related Factor 2/immunology* ; Mice, Inbred C57BL ; Gene Regulatory Networks ; Enhancer Elements, Genetic

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective To develop a risk prediction model for ischemic stroke in symptomatic intracranial atherosclerotic stenosis(ICAS)patients based on high-resolution magnetic resonance imaging(HR-MRI)and arterial spin labeling(ASL)imaging.Methods A total of 142 patients were included and divided into acute ischemic stroke(AIS)and transient ischemic attack(TIA)groups based on stroke occurrence.Clinical risk factors,plaque characteristics,and arterial transit artifact(ATA)presence on ASL images were compared between the two groups.Multivariate logistic regression analysis was performed,incorporating clinical risk factors,plaque characteristics,and double post labeling delay(PLD)ATA presence.The predictive value of different models was compared using receiver operating characteristic(ROC)curve and DeLong tests.Results Hypertension,positive lumen remodeling,plaque enhance-ment rate,1.5 s-ATA presence,and 2.5 s-ATA presence were independent risk factors for AIS(P＜0.05).The combination of HR-MRI and ASL imaging predicted AIS most effectively[area under the curve(AUC)=0.908;95％ confidence interval(CI)0.862-0.954].No significant difference was found between the prediction performances of HR-MRI and ASL(95％CI-0.041-0.082,Z=0.659,P=0.509).Conclusion ASL is more convenient than HR-MRI for predicting ischemic stroke in ICAS patients.A model combining plaque characteristics and ATA presence effectively predicts AIS occurrence.

Objective To analyze the research hotspots and trends of invasive fungal infections(IFIs)in China over the past 24 years,and provide references and suggestions for future research.Methods Literatures on IFIs re-search in China from 2000 to 2024 were retrieved from China National Knowledge Infrastructure(CNKI)and Web of Science(WOS).CiteSpace software was employed to conduct collaboration network analysis on authors' institu-tions,and co-occurrence,clustering,and burst analyses were conducted on key words.Results A total of 2 479 li-teratures retrieved from CNKI and 1 149 from WOS were included in the analysis,involving 295 research institu-tions,with no core research team identified having a intermediary centrality＞0.1.Institutions with intermediary centrality＞0.1 included Chinese Academy of Sciences,Peking University,Fudan University,Sun Yat-sen Univer-sity and Zhejiang University.Key words with high centrality included"diagnosis""risk factor""voriconazole"and"Candida albicans".Clustering analysis grouped the co-occurrence network of key words into 6 clusters,mainly covering fungal diagnosis,treatment,and susceptible factors.Since 2020,focuses on the safety of antifungal treat-ment agents and primary prevention have emerged,with hot topics including pharmacokinetics,children,clinical features,and risk factors.Conclusion Currently,research teams are dispersed with insufficient interdisciplinary collaboration.Research topics are relatively simple.It is necessary to strengthen research on fungal resistance and healthcare-associated infection prevention and control.Risk factors and prevention measures for IFIs may be the fo-cus of future research.

Objective To analyze the imaging features of cerebral small vessel disease in patients with type 2 diabetes mellitus by multimodal MRI.Methods The clinical data of 160 patients with cerebral small vessel disease admitted to our hospital from January to December 2020 were retrospectively analyzed.According to whether they were complicated with type 2 diabetes mellitus,they were divided into the diabetic group and the non-diabetic group,with 80 cases in each group.Both groups underwent multimodal MRI scans.And the severity of lacunar infarction,the severity of subcortical and periventricular white matter lesions,white matter integral and cerebral microbleeds of patients in the two groups were compared.Results The severity of lacunar infarction(χ2=34.076,P=0.001),subcortical white matter lesions(χ2=25.000,P=0.001),periventricular white matter lesions(χ2=22.895,P=0.001)and white matter integral(t=12.370,P=0.001)of patients in the diabetic group were significantly higher than those in the non-diabetic group.No cerebral microbleeds were detected in either group of patients.Conclusion Patients with cerebral small vessel disease and type 2 diabetes mellitus show characteristic multimodal MRI changes.The increase in the number of lacunar infarction lesions and the aggravation of white matter lesions can be used as the characteristic imaging basis for the diagnosis of type 2 diabetes mellitus related cerebral small vessel disease.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.