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*

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

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

In recent years, the research on artificial intelligence medical devices has risen markedly along with the expanding application scenarios, exhibiting prominent interdisciplinary characteristics. From 2000 to 2024, the variety of research in artificial intelligence medical devices has significantly increased, while the balance of disciplines has slightly declined, and Simpson's diversity index has continuously increased. Medicine and biology are the main research themes and supportive disciplines in this field. Knowledge from computer science, engineering technology, and mathematics is widely involved and shows an upward trend, while content from the humanities and social sciences is less involved in the research. Compared to the United States and the United Kingdom, China has relatively less biological and chemical knowledge content in the research of this field, but more content related to computer science, engineering technology and material science is involved. This study analyzes the current state and trends of interdisciplinary on artificial intelligence medical devices from the perspective of macro-categories of disciplines, aiming to provide references for research planning, talent training and interdisciplinary cooperation in the field.
Artificial Intelligence ; Humans ; Equipment and Supplies ; Interdisciplinary 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 development of education and technology, the construction of research public platforms has emerged as a critical initiative for many universities and top-tier public hospitals. The core and most fundamental function of a basic public platform is to aggregate large instruments and specific resources, providing open services for instrumental analysis and sample testing. Optimized management and high-quality, efficient services are essential for such platforms. This article elucidates the construction of a research public platform in West China Hospital, focusing on the adoption of hierarchical management and precise services. The core of the hierarchical management lies in building a multi-level service platform composed of routine support platforms, advanced technology platforms, and specially qualification platforms, while establishing a talent hierarchy that differentiates between core and routine positions. This structure is designed to accurately meet the diverse needs of users and enhance resource efficiency. By implementing user access control with differentiated permissions for internal and external users and a dynamic credit-based review system, the laboratory can ensure safe and efficient operations. The four service modes-instrument usage, in-lab experiments, sample testing, and collaborative projects-are precisely aligned with various research scenarios. Proactive engagement with grant-funded projects, customized services for research groups, and a multidimensional training system further strengthen the platform's support for major scientific research tasks. Through systematic management and service innovation, this model achieves efficient integration and sustainable development of platform resources, providing a valuable reference for the construction of public platforms in similar medical institutions.
China ; Research ; Laboratories/organization & administration*

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

Periodontitis has emerged as one of the most critical oral diseases, and research on this condition holds great importance for the advancement of stomatology. As the most authoritative national scientific research funding institution in China, the National Natural Science Foundation of China (NSFC) has played a pivotal role in driving the progress of periodontal science by supporting research on periodontitis. This article provides a comprehensive review of the research and development progress related to periodontitis in China from 2014 to 2023, highlighting the significant contributions of the NSFC to this field. We have summarized the detailed funding information from the NSFC, including the number of applicant codes, funded programs and the distribution of funded scholars. These data illustrate the efforts of the NSFC in cultivating young scientists and building research groups to address key challenges in national scientific research. This study offers an overview of the current hot topics, recent breakthroughs and future research prospects related to periodontitis in China.
China ; Periodontitis ; Humans ; Foundations ; Research Support as Topic ; Natural Science Disciplines ; Dental Research/economics*

BACKGROUND AND OBJECTIVE

The COVID-19 pandemic has disrupted the sports industry, resulting in the postponement of events worldwide. This posed a significant burden in the mental and emotional well-being of athletes due to uncertainties and diminished training levels. As an adaptation, bubble camps emerged as a new approach to resuming training and tournaments under stringent regulations of the COVID-19 protocols. In the national context, the University Athletic Association of the Philippines (UAAP) has adapted the bubble set-up by implementing antigen testing, RTPCR, and other health protocols as a prerequisite to bubble training. However, uncertainties in the future of sports continue to present as a psychological toll to the well-being of student-athletes despite the sense of normalcy instilled by bubble training. Existing literature on bubble training is grounded heavily on the quantitative assessments of an athlete's well-being in a bubble set-up and its effectiveness in mitigating COVID-19 transmission, thereby lacking insights that may be obtained from qualitative data. This study explored the experiences of UAAP Season 84 studentathletes in a bubble set-up by examining personal and contextual factors that impacted their well-being.

The study employed a qualitative descriptive phenomenological approach based on Seligman's WellBeing Theory. A purposeful sampling technique was used to recruit UAAP student-athletes through online dissemination of Google Forms for recruitment. Only three student-athletes from UAAP fit the eligibility criteria. Data were collected through on-site and online interviews using a semi-structured interview guide to reveal a narrative of the student-athletes' bubble training experiences, common themes, and patterns. The NVivo software program was used for data analysis, utilizing a deductive thematic approach.

The lived experiences of three UAAP studentathletes were classified into six major themes: (1) Availability and Accessibility of Services; (2) Restrictions; (3) Mental Health; (4) Fostering Relationships; (5) Support Systems; and (6) Individual Growth. Accounts of both positive and negative training perceptions and outcomes regarding the bubble set-up were noted from all student-athletes. The set-up provided studentathletes with easy access to training facilities and services, eventual development of mental fortitude and  perseverance, improved interpersonal relationships, and opportunities for individual growth. However, the restrictions, isolation, internal and external pressures, and routinary nature of the set-up contributed to the elevated levels of stress and anxiety, eventually leading to fatigue and burnout.

The study elucidates on the multi-faceted experiences of UAAP student-athletes in bubble training, underpinning the essence of the adequacy of training services and facilities, enhanced support systems, and prompt policy development that caters to improving the holistic well-being of student-athletes amidst adverse changes in the trajectory of sports.