The expert consensus on the clinical treatment of herpes zoster with fire needling was developed, and the commonly used fire needling treatment scheme verified by clinical research was selected to form a standardized diagnosis and treatment scheme for acute herpes zoster and postherpetic neuralgia (PHN), so as to answer the core problems in clinical application. The consensus focuses on patients with herpes zoster, and forms recommendations for 9 key clinical issues, covering simple fire needling and TCM comprehensive therapy based on fire needling, including fire needling combined with cupping, fire needling combined with Chinese herb, fire needling combined with cupping and Chinese herb, fire needling combined with filiform needling, fire needling combined with moxibustion, and provides specific recommendations and operational guidelines for various therapies.
Humans ; Herpes Zoster/therapy* ; Acupuncture Therapy/instrumentation* ; Consensus ; Clinical Protocols

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Computational modeling is an invaluable tool for mechanism analysis, directed engineering, and rational design of biological parts, metabolic networks, and even cellular systems. It can provide new technological solutions to address biological challenges at different levels and has become a central focus of research in biomanufacturing. In the computational modeling of proteins, which are the key parts in biological systems, the traditional physics-based methods (computer software and mathematical model) have been widely used to study the physical and chemical processes in the functioning of proteins, and have thus been recognized as a powerful tool for understanding complex biological systems and guiding experimental designs. As the scale of computational modeling continues to expand, traditional modeling techniques face difficulties in balancing computational accuracy and speed. In recent years, the explosive growth of biological data has made it possible to construct high-performance artificial intelligence (AI) models, which brings new opportunities to the computational modeling of proteins, and the AI-enhanced physics-based computational modeling technologies have emerged. This combined strategy not only incorporates the chemical knowledge and established physical principles but also is powerful in data processing and pattern recognition, which greatly improves the computational efficiency and prediction accuracy, as well as possesses stronger interpretation ability, transferability, and robustness. The AI-enhanced physics-based computational modeling technologies have already shown great potential and value in biocatalysis, paving a new way for the future development of biomanufacturing.
Artificial Intelligence ; Proteins/chemistry* ; Computer Simulation ; Software ; Computational Biology/methods*

Inhalation of crystalline silicon dioxide particles can induce silicosis, and the development of silicosis is closely related to the occurrence and development of pulmonary inflammation and pulmonary fibrosis. NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome has been established as a major proinflammatory receptor for sensing environmental danger signals. Activation of NLRP3 inflammasomes after phagocytosis of silicon dioxide particles by pulmonary macrophages may be an important mechanism to induce oxidative stress and sustained inflammatory response in the lung. This article summarizes the role of NLRP3 inflammasome in the inflammatory response and pulmonary fibrosis in silicosis, and analyzes it as a potential target for silicosis treatment.

Inhalation of crystalline silicon dioxide particles can induce silicosis, and the development of silicosis is closely related to the occurrence and development of pulmonary inflammation and pulmonary fibrosis. NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome has been established as a major proinflammatory receptor for sensing environmental danger signals. Activation of NLRP3 inflammasomes after phagocytosis of silicon dioxide particles by pulmonary macrophages may be an important mechanism to induce oxidative stress and sustained inflammatory response in the lung. This article summarizes the role of NLRP3 inflammasome in the inflammatory response and pulmonary fibrosis in silicosis, and analyzes it as a potential target for silicosis treatment.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Background The novel coronavirus infection is widespread in the world, resulting in more pneumoconiosis patients complicated with coronavirus disease 2019 (COVID-19). Objective To understand the clinical characteristics and prognosis of hospitalized COVID-19 patients complicated with or without pneumoconiosis. Methods A total of 36 COVID-19 patients admitted to the Shandong Provincial Occupational Disease Hospital from 10 December to 31 December 2022 were selected, including 21 cases in the complication group (pneumoconiosis complicated with COVID-19) and 15 cases in the COVID-19 group without pneumoconiosis. Symptoms, signs, laboratory test results(e.g. routine blood test), imaging findings, treatment plans and prognosis of the two groups were observed and compared. Results Regarding symptoms and signs in the complication group and the COVID-19 group, the proportions of dyspnea (57.14% vs 0.00%), lung wheezing (28.57% vs 0.00%), wet rales (76.19% vs 33.30%), and fever (61.90% vs 93.33%) were significantly different (P<0.05). Compared with the COVID-19 group, the level of D-dimer in the complication group was significantly increased [2.340 (1.0, 6.5) mg·L⁻¹ vs 0.250 (0.2, 0.4) mg·L⁻¹] (P<0.01), the serum sodium level was decreased [(138.10±2.68) mmol·L⁻¹ vs (140.47±2.27) mmol·L⁻¹] (P<0.05). In terms of drug treatment and prognosis, there were statistically significant differences in the proportion of antiviral drugs (19.00% vs 80.00%), glucocorticoids (38.10% vs 80.00%), and anticoagulants (28.60% vs 0.00%) between the complication group and the COVID-19 group (P<0.05). Compared with the COVID-19 group, the cure rate of the complication group (90.50% vs 100.00%) showed no statistical difference. However, there were 2 deaths in the complication group. Conclusion Patients with pneumoconiosis complicated with COVID-19 have less fever and more dyspnea, wheezing, and wet rales. The increase of plasma D-dimer is a potential predictor in patients with pneumoconiosis complicated with COVID-19.

Clinical research is usually aimed at and guided by therapeutic efficacy. Clarifying the placebo effect and the nocebo effect from treatment outcomes is an important issue in clinical research. This paper reviews the meaning of the placebo effect， suggesting that factors that may produce the placebo effect in clinical practice include past experience associations， patient expectations， suggestion， and doctor-patient relationships. It also summarizes the characteristics of the nocebo effect， its influencing factors， and its impact on clinical prognosis. Combining the characteristics of traditional Chinese medicine， this paper explores the design of acupuncture clinical trials that can reflect the measurement of the placebo effect， attempting to provide a clearer interpretation of the placebo effect in the evaluation of acupuncture efficacy in traditional Chinese medicine. Taking primary insomnia as an example， a prospective randomized placebo-controlled trial is designed to observe and evaluate the relationship between the treatment effects of acupuncture and the placebo effect in different patients under the treatment of the same doctor. Group comparisons will help better distinguish clinical effects in different situations. The authors also attempt to explore the responsive population to the placebo effect and the effects of placebos in different populations.

Standardization is the universal language of the world, and standardization of traditional Chinese medicine (TCM) is essential for its communication in China and globally. However, the principles and methods of TCM acupuncture standardization have been unclear and inadequate in the early stages. Based on an investigative approach to understanding the current status, identifying problems, and finding solutions, our team has established basic principles of TCM acupuncture that embody Chinese wisdom, evaluated the international strategic environment systematically, proposed the principle of “importance of harmony and exercise of impartiality”, and established basic working principles. A series of methods for TCM acupuncture standard development and evaluation have been constructed, including general standards for the revision of TCM acupuncture standards, the first TCM acupuncture clinical research management specification, a shared full chain technology platform, a data center, and an evaluation research base for TCM acupuncture clinical research. Evaluation criteria for ancient literature and expert experience, a recommendation method for the “three main and three auxiliaries” TCM guideline for prevention were established, and quantifiable assessment methods of TCM standard applicability were proposed. These findings provide methodological guidance for TCM acupuncture standardization.

The frontier of science and technology has widely entered the era of studying complexity and regulating complex systems.Especially in medicine,research on the complexity of the human system will attract more scholars'and clinicians'attention.Facing the complexity of the human body system directly,this paper applied the definition of complexity,state estimation,and system control models in modern system science to reveal the unique advantages of traditional Chinese medicine(TCM)in understanding human body complexity and regulating human body complex systems.Thus,this paper may not only lay a foundation for dealing with complex diseases in the future but also provides new ideas and methods for forming the future medical model.