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*

Objective To explore the value of apparent diffusion coefficient(ADC)values of magnetic resonance diffusion weighted imaging(MR-DWI)in predicting the prognosis of primary hepatocellular carcinoma(HCC)treated by radiofrequency ablation(RFA).Methods A prospective study was conducted on 178 patients with HCC.All patients were treated with RFA and followed up for 1 year after treatment.MR-DWI was performed before RFA and one month after RFA,and the changes in ADC value were calculated.These changes of the cancer in patients with different clinicopathological parameters were compared.The factors affecting the prognosis of HCC patients with RFA,and the value of ADC value changes in predicting the prognosis were analyzed.Results The changes of ADC values in patients with high alpha-fetoprotein,Barcelona clinic live cancer(BCLC)stage C,and poorly differentiated were lower than those in patients with low alpha-fetoprotein,BCLC stage B,and moderately well-differentiated(P<0.05).Six cases were lost to follow-up,and 120 of the remaining 172 patients survived.Cox regression analysis showed that the changes in ADC value,tumor stage and degree of differentiation were independent factors affecting the prognosis of HCC patients with RFA(P<0.05).Receiver operating characteristic(ROC)curve results showed that the best cut-off point,sensitivity,specificity and area under the curve(AUC)of ADC value change in predicting the prognosis of HCC patients with RFA were 0.42×10-3 mm2/s,75.00%,78.33%and 0.801.There were 16 deaths in the high change group of ADC value(>0.42)and 36 deaths in the low change group(≤0.42).The overall survival curve of the high change group of ADC value was better than that of the low change group(P<0.05).Conclusion The change in ADC value of MR-DWI sequence before and after short-term RFA treatment in HCC patients is related to the patient's pathology and prognosis,with a good predictive effect.The low change in ADC value has a higher risk of poor prognosis.

Objective To investigate the role of member septin family(SEPT12)in human spermatogenesis and its influence on sperm motility and sperm ultrastructure.Methods Whole exome sequencing(WES)was performed on peripheral blood DNA extracted from 375 patients with asthenoteratozoospermia,and a patient with idiopathic in-fertility carrying compound heterozygous mutation of SEPT12 was screened out.Sanger sequencing was performed to verify the mutation,and co-segregation analysis was performed in the family.The morphological abnormalities of sperm were analyzed by hematoxylin-eosin(HE)staining and scanning electron microscopy(SEM),and the ultra-structural defects of sperm were analyzed by transmission electron microscopy(TEM).Then the effects of the muta-tion on the level and position of the protein and the changes of the location and level of the defect structure markers were analyzed by Western blot and immune-fluorescence(IF).Results The compound heterozygous mutations c.C332A(p.Ti111K)and c.406_416 del TGCTCGTATTG(p.q136 VFS*39)in the SEPT12 gene were screened and identified in a patient with asthenoteratozoospermia.The mutations were verified by Sanger sequencing,which was consistent with the co-segregation genetic pattern of the family.The mutations resulted in loss of protein expres-sion,decreased sperm motility and sperm morphological deformities,mainly including short tail,curly tail and ir-regular sperm head.The ultrastructure of sperm showed that the annulus between the mid-piece and the principle-piece was missing,the acrosome membrane of sperm head fell off and the nucleus contained vacuoles.In the mid-piece of sperm flagella,the arrangement of mitochondrial sheath was disordered,most of flagella axoneme central pair was absent,microtubules doublet was missing or disordered,and some radical spoke was absent.By Western blot and IF,the marker proteins of related structural components were detected,and the results showed that the level of SEPT4 protein decreased,SEPT6 protein unchanged,acrosomal related proteins ACTL7A and ACROSIN protein missing,and the expression levels of mitochondrial and axoneme related proteins TOMM20,SPAG6 and RSPH3 protein significantly decreased.Conclusion The deletion of SEPT12 protein caused by SEPT12 gene mu-tation leads to the deletion of the annulus between the mid-piece and the principle-piece,and the abnormal assem-bly of sperm acrosome,mitochondrial sheath and flagella.

Restless legs syndrome (RLS) is a common sensorimotor disorder. Although it does not pose a threat to life, it seriously affects the quality of life of patients. RLS pathogenesis is still unclear, and its incidence is associated with a variety of risk factors, including genetic factors and non-genetic factors. Genetic factors involve more than 20 risk genes, such as meis homeobox 1 ( MEIS1), BTB domain containing 9 ( BTBD9), mitogen-activated protein kinase kinase 5 ( MAP2K5), and protein tyrosine phosphatase receptor type Db ( PTPRD). Non-genetic factors include regional age, gender, obesity, medical related diseases, neuropsychiatric diseases and drugs. This paper reviews the recent advance in risk factors and related pathogenesis of RLS to provide references for early prevention and treatment of the disease.

Objective:To construct a predictive model for the risk of major adverse cardiovascular events(MACE) after surgery in patients with symptomatic arteriosclerosis obliterans(ASO) .Methods:From Jan 2018 to Dec 2021, 957 patients with symptomatic ASO admitted to Nanjing Drum Tower Hospital were selected and divided into MACE and non-MACE groups according to whether they had a post-op MACE. A risk prediction model was constructed based on a stepwise regression method with multi-factor COX regression analysis. The model was evaluated using the receiver operating characteristic curve (ROC), the calibration curve to assess the model fit, and the Bootstrap method for internal validation.Results:MACE occurred in 143 patients (14.94%). After COX regression analysis, BMI, creatinine clearance, fibrinogen, rivaroxaban and previous history of surgery were enrolled into model constructing. The ROC curve assessed the model with a C-statistic of 0.690 (95% CI: 0.644-0.736), sensitivity and specificity of 49.2% and 80.7% respectively, a Jorden index of 0.299 and an optimal cut-off value of 0.086. Calibration curves showing agreement between predicted and actual observed values. Internally validated C-statistic of 0.689 (95% CI: 0.672-0.700). The population was divided into high and low risk groups based on the best cut-off value and analysed for survival. The difference between the two groups was statistically different. Conclusion:The risk prediction model for the occurrence of MACE based on clinical parameters is simple and convenient, with good predictability and good discriminatory ability, and can provide reference for the assessment and treatment of MACE in ASO patients.

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.

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.