OBJECTIVE: To provide the experience and demonstration for the transformation of acupuncture-moxibustion techniques standards from Chinese national standards to international standards. METHODS: Questionnaire research, literature research, semi-structured interviews and expert consultation were used. RESULTS: The safety of acupuncture-moxibustion techniques was evaluated through literature research, and based on the results of the questionnaire survey, expert interviews, and expert consultation, 11 main bodies and structure of the former Chinese national standard, Technical Benchmark of Acupuncture and Moxibustion: General Rules for Drafting, were adjusted and optimized in accordance with the requirements of international standard (including the language, normative references, purpose, scope, applicable environment, target population, work team, terms and definitions, general principles and basic requirements, structural elements and text structure, and compilation process); and the first international standard, World Federation of Acupuncture-Moxibustion Societis (WFAS) Technical Benchmark of Acupuncture and Moxibustion: General Rules for Drafting was formulated to specify the general rules for drafting. CONCLUSION The 3 key questions, "international compatibility", "technical operability" and "safety" should be solved technically on the basis of explicit international requirements. It is the core technical issue during transforming the national standards of technical benchmark of acupuncture and moxibustion into international standards.
Moxibustion/methods* ; Acupuncture Therapy/methods* ; Humans ; Translational Research, Biomedical/standards* ; Surveys and Questionnaires ; China ; Benchmarking/standards*

The guidelines for clinical research on new drugs provide unified standards for drug developers, researchers, and regulatory authorities, playing a crucial role in new drug development. This article systematically reviews the evolution of guidelines for clinical research on new traditional Chinese medicine(TCM) drugs in China, with a focus on analyzing the current status of these guidelines and the problems that exist. It also provides interpretations of three important guidelines. The article points out that with the continuous emergence of new clinical trial design methods, development concepts, and tools, and under the background of the "three combinations" evidence evaluation system for new TCM drugs, it is imperative to revise existing guidelines, formulate new ones, and develop new tools for clinical efficacy evaluation. It is hoped that relevant departments will adopt an open attitude and work together to build a technical system of clinical research guidelines for new TCM drugs that aligns with the characteristics of TCM.
Humans ; Biomedical Research/trends* ; China ; Clinical Trials as Topic ; Drugs, Chinese Herbal/therapeutic use* ; Guidelines as Topic ; Medicine, Chinese Traditional/standards*

The objective of this study is to map the global scientific competitive landscape in the field of artificial intelligence (AI) medical devices using scientific data. A bibliometric analysis was conducted using the Web of Science Core Collection to examine global research trends in AI-based medical devices. As of the end of 2023, a total of 55 147 relevant publications were identified worldwide, with 76.6% published between 2018 and 2024. Research in this field has primarily focused on AI-assisted medical image and physiological signal analysis. At the national level, China (17 991 publications) and the United States (14 032 publications) lead in output. China has shown a rapid increase in publication volume, with its 2023 output exceeding twice that of the U.S.; however, the U.S. maintains a higher average citation per paper (China: 16.29; U.S.: 35.99). At the institutional level, seven Chinese institutions and three U.S. institutions rank among the global top ten in terms of publication volume. At the researcher level, prominent contributors include Acharya U Rajendra, Rueckert Daniel and Tian Jie, who have extensively explored AI-assisted medical imaging. Some researchers have specialized in specific imaging applications, such as Yang Xiaofeng (AI-assisted precision radiotherapy for tumors) and Shen Dinggang (brain imaging analysis). Others, including Gao Xiaorong and Ming Dong, focus on AI-assisted physiological signal analysis. The results confirm the rapid global development of AI in the medical device field, with "AI + imaging" emerging as the most mature direction. China and the U.S. maintain absolute leadership in this area-China slightly leads in publication volume, while the U.S., having started earlier, demonstrates higher research quality. Both countries host a large number of active research teams in this domain.
Artificial Intelligence ; Bibliometrics ; Humans ; China ; Equipment and Supplies ; United States ; Biomedical Research

Biomedical data is surging due to technological innovations and integration of multidisciplinary data, posing challenges to data management. This article summarizes the policies, data collection efforts, platform construction, and applications of biomedical data in China, aiming to identify key issues and needs, enhance the capacity-building of platform construction, unleash the value of data, and leverage the advantages of China's vast amount of data.
China ; Humans ; Biomedical Research ; Data Management ; Data Collection

Biomedical big data, characterized by its massive scale, multi-dimensionality, and heterogeneity, offers novel perspectives for disease research, elucidates biological principles, and simultaneously prompts changes in related research methodologies. Biomedical ontology, as a shared formal conceptual system, not only offers standardized terms for multi-source biomedical data but also provides a solid data foundation and framework for biomedical research. In this review, we summarize enrichment analysis and deep learning for biomedical ontology based on its structure and semantic annotation properties, highlighting how technological advancements are enabling the more comprehensive use of ontology information. Enrichment analysis represents an important application of ontology to elucidate the potential biological significance for a particular molecular list. Deep learning, on the other hand, represents an increasingly powerful analytical tool that can be more widely combined with ontology for analysis and prediction. With the continuous evolution of big data technologies, the integration of these technologies with biomedical ontologies is opening up exciting new possibilities for advancing biomedical research.
Deep Learning ; Biological Ontologies ; Humans ; Big Data ; Biomedical Research

With the rise of data-intensive research, data literacy has become a critical capability for improving scientific data quality and achieving artificial intelligence (AI) readiness. In the biomedical domain, data are characterized by high complexity and privacy sensitivity, calling for robust and systematic data management skills. This paper reviews current trends in scientific data governance and the evolving policy landscape, highlighting persistent challenges such as inconsistent standards, semantic misalignment, and limited awareness of compliance. These issues are largely rooted in the lack of structured training and practical support for researchers. In response, this study builds on existing data literacy frameworks and integrates the specific demands of biomedical research to propose a comprehensive, lifecycle-oriented data literacy competency model with an emphasis on ethics and regulatory awareness. Furthermore, it outlines a tiered training strategy tailored to different research stages-undergraduate, graduate, and professional, offering theoretical foundations and practical pathways for universities and research institutions to advance data literacy education.
Artificial Intelligence ; Humans ; Biomedical Research

The high failure rates in clinical drug development based on animal models highlight the urgent need for more representative human models in biomedical research. In response to this demand, organoids and organ chips were integrated for greater physiological relevance and dynamic, controlled experimental conditions. This innovative platform-the organoids-on-a-chip technology-shows great promise in disease modeling, drug discovery, and personalized medicine, attracting interest from researchers, clinicians, regulatory authorities, and industry stakeholders. This review traces the evolution from organoids to organoids-on-a-chip, driven by the necessity for advanced biological models. We summarize the applications of organoids-on-a-chip in simulating physiological and pathological phenotypes and therapeutic evaluation of this technology. This section highlights how integrating technologies from organ chips, such as microfluidic systems, mechanical stimulation, and sensor integration, optimizes organoid cell types, spatial structure, and physiological functions, thereby expanding their biomedical applications. We conclude by addressing the current challenges in the development of organoids-on-a-chip and offering insights into the prospects. The advancement of organoids-on-a-chip is poised to enhance fidelity, standardization, and scalability. Furthermore, the integration of cutting-edge technologies and interdisciplinary collaborations will be crucial for the progression of organoids-on-a-chip technology.
Organoids/physiology* ; Humans ; Biomedical Research/methods* ; Lab-On-A-Chip Devices ; Animals ; Microphysiological Systems

BACKGROUND: Supporting the mental health of researchers is essential to maintaining human resources and advancing science. This study investigated the association between Japanese medical researchers' perceptions of research evaluation processes and their psychological well-being. METHODS: We performed a web-based self-administered questionnaire survey. The questionnaires were distributed to each academic society through the Japanese Association of Medical Sciences from December 2022 to January 2023. These questionnaires targeted medical researchers. Exposure was the medical researchers' perceptions of quantitative indicators for evaluating medical research and researchers. The outcome was psychological well-being, measured using the Japanese version of the World Health Organization-Five Well-Being Index (WHO-5). Multivariable-adjusted logistic regressions were conducted to investigate the association between individual attitudes toward research evaluation and psychological well-being. Stratified analyses by research fields, i.e., clinical, basic, and social medicine, were also performed. RESULTS: A total of 3,139 valid responses were collected. After excluding 176 responses from research fields of other than clinical, basic, or social medicine, 2,963 researchers (2,185 male, 737 female, and 41 other) were analyzed. Prevalence of poor well-being (WHO-5 score <13) was 28.3% in the researchers. The highest number of medical researchers was in clinical medicine (n = 500) followed by basic medicine (n = 217) and social medicine (n = 121). Medical researchers who considered research funding slightly important/not important for researcher evaluation had poorer psychological well-being than those who considered it especially important (slightly important: adjusted odds ratio (aOR) 1.33, 95% confidence interval (CI) 1.03-1.71; not important: aOR 1.53, 95%CI 1.10-2.12). This tendency was stronger among basic medical researchers than clinical or social medical researchers. The research field significantly modified the relationship between research funding received and interaction with poor psychological well-being both additively (P = 0.030) and multiplicatively (P = 0.024). CONCLUSIONS The discrepancy between medical researchers' attitudes toward research evaluation and the current state of research evaluation in their research community may worsen their psychological well-being. The influence of this discrepancy differs among clinical, basic, and social medicine. Appropriate evaluation of medical research and researchers in each field can facilitate improving their psychological well-being via the resolution of this discrepancy.
Humans ; Japan ; Female ; Male ; Cross-Sectional Studies ; Adult ; Research Personnel/statistics & numerical data* ; Middle Aged ; Biomedical Research ; Surveys and Questionnaires ; Mental Health ; Psychological Well-Being ; East Asian People

As representatives of the third generation of biomedical materials, hydrogels exhibit revolutionary potential in tissue engineering, precision drug delivery, and smart medical devices due to their ability to construct bionic microenvironments. However, the clinical translation of hydrogels is still limited by multidimensional challenges, including biocompatibility, scalable production, and regulatory complexity. This paper systematically reviews the design innovations, functionalization strategies, and translational bottlenecks of hydrogel materials, integrates the latest technological trends, such as 4D printing and AI-driven design, and proposes a collaborative optimization pathway encompassing materials, technology, clinical applications, and policy. By introducing local Chinese innovation cases and monitoring scientific advancements, this study offers solutions that possess both academic significance and practical guidance for the clinical translation of hydrogels.
Hydrogels ; Tissue Engineering ; Translational Research, Biomedical ; Biocompatible Materials ; Humans ; Drug Delivery Systems

OBJECTIVES: Obtaining informed consent from research participants is an ethical and legal obligation for medical researchers in clinical studies. Electronic informed consent (eIC) is increasingly being adopted in clinical research worldwide. However, there is limited data on Chinese medical researchers' knowledge and attitudes toward eIC. This study aims to investigate their knowledge, attitudes, and influencing factors regarding eIC use in clinical research. METHODS: This cross-sectional study was conducted using stratified random sampling. From June to August 2022, medical researchers from 8 tertiary hospitals were surveyed via an online platform (Wenjuanxing). A self-developed eIC knowledge questionnaire and attitude scale were used to assess participants' understanding and perceptions of eIC. Univariate analysis was employed to explore factors influencing attitude scores and the correlation between knowledge and attitudes. A generalized linear model was used to analyze associations between demographic characteristics and attitude scores, including the frequency of difficulties in using smartphones or computers, preferred device for using eIC, and their interaction effects. Stratified analysis was further performed for significant interactions. RESULTS: A total of 399 valid questionnaires were collected. The mean accuracy rate on the eIC knowledge questionnaire was (94.88±15.50)%. Of the respondents, 74.9% had heard of eIC, and 84.5% preferred using mobile devices over computers to access eIC. The median attitude score was 3.41 (3.18, 3.76), indicating generally positive attitudes. Specifically, 81.7% found eIC more convenient than paper-based consent, 79.7% considered it more efficient, and 51.1% believed it could fully replace paper forms. However, 60.7% expressed concerns about data security and privacy, and 89.7% believed that relevant laws and regulations need improvement. Spearman correlation analysis showed a weak positive correlation between knowledge and attitude scores (r=0.171, P=0.001). Univariate analysis indicated that the frequency of difficulty using devices and preferred device for eIC were significantly associated with attitude scores (P<0.05). After adjusting for confounding factors, the generalized linear model demonstrated that participants who occasionally experienced had difficulty using devices had significantly lower attitude scores compared to those who never had difficulty (β=-0.040, 95% CI -0.071 to -0.009, P=0.012). Those who preferred using PCs had significantly lower attitude scores than those who preferred mobile devices (β=-0.066, 95% CI -0.108 to -0.023, P=0.002). Interaction analysis showed a significant interaction analysis showed a significant interaction between age and preferred device (P=0.011), particularly among participants aged ≥45-year (P<0.001). No other interactions were found to be significant (all P>0.05). CONCLUSIONS Medical researchers in China generally have a high level of knowledge and positive attitudes toward eIC, though concerns remain regarding data security and privacy. Future promotion of eIC in Chinese clinical research should be grounded in ethical considerations and address the specific needs of older users and mobile device users, while also enhancing researchers' competencies in using digital tools and eIC systems.
Humans ; Cross-Sectional Studies ; Informed Consent ; Surveys and Questionnaires ; Female ; Male ; Health Knowledge, Attitudes, Practice ; Adult ; Biomedical Research ; Research Personnel/psychology* ; Middle Aged ; China