Guidelines for Digital Ancient Books of TCM Indexing(T/CIATCM 119-2024)is based on the theoretical knowledge,disciplinary methods,and practical applications of TCM classical cataloging.Taking digital ancient books of TCM as the object,it systematically reveals the content of TCM knowledge,which is an essential indexing processing standard for building an intelligent retrieval system for TCM ancient books,and can provide support for the deep development and innovative utilization of TCM knowledge.It can not only promote the co-construction and sharing of ancient book resources in the TCM industry,but also promote the standardization construction and application of TCM information.This standard specifies the principles,methods,and examples of free indexing of digital ancient books of TCM based on their original content.It is applicable to the indexing and processing of digital ancient books of TCM for TCM professional libraries and related institutions,and to the data processing and construction of various types of TCM ancient book databases.

Guidelines for Digital Ancient Books of TCM Indexing(T/CIATCM 119-2024)is based on the theoretical knowledge,disciplinary methods,and practical applications of TCM classical cataloging.Taking digital ancient books of TCM as the object,it systematically reveals the content of TCM knowledge,which is an essential indexing processing standard for building an intelligent retrieval system for TCM ancient books,and can provide support for the deep development and innovative utilization of TCM knowledge.It can not only promote the co-construction and sharing of ancient book resources in the TCM industry,but also promote the standardization construction and application of TCM information.This standard specifies the principles,methods,and examples of free indexing of digital ancient books of TCM based on their original content.It is applicable to the indexing and processing of digital ancient books of TCM for TCM professional libraries and related institutions,and to the data processing and construction of various types of TCM ancient book databases.

Objective:To explore the diagnostic value of total bilirubin to albumin ratio(B/A ratio)combined with alpha-fetoprotein(AFP)and abnormal prothrombin induced by vitamin K absence-Ⅱ(PIVKA-Ⅱ)for hepatocellular carcinoma(HCC).Methods:35 HCC patients(HCC group),35 cirrhosis patients(cirrhosis group),35 HCC patients post-transcatheter arterial chemoembolization(TACE)(TACE postoperative group),and 35 healthy volunteers(healthy control group)were selected in our hospital from October 2023 to October 2024.The serum B/A ratio,AFP,and PIVKA-Ⅱ levles were measured and compared across the groups.The correlations between serum B/A ratio,AFP,and PIVKA-Ⅱ in the HCC group were analyzed.The B/A ratio,AFP,PIVKA-Ⅱ were compared across different clinical and pathological features in HCC patients.The serum B/A ratio,AFP,and PIVKA-Ⅱ levels were compared pre and post operation in the HCC group.The diagnostic value of B/A ratio,AFP,PIVKA-Ⅱ alone and in combination for HCC were analyzed by receiver operating characteristic(ROC)curves.Results:The serum B/A ratio,AFP,and PIVKA-Ⅱ levels in HCC group and TACE postoperative group were significantly higher than those in the cirrhosis group and healthy control group,and the HCC group was higher than that in the TACE postoperative group(P＜0.05).Pearson correlation analysis results showed that,B/A ratio in the HCC group was positively correlated with AFP(r=0.352,P=0.001),B/A ratio was positively correlated with PIVKA-Ⅱ(r=0.327,P=0.003),and AFP was positively correlated with PIVKA-Ⅱ(r=0.285,P=0.008).Higher TNM stage,larger tumor diameter,presence of vascular invasion,and lower differentiation degree of HCC patients,who had higher B/A ratio,AFP,and PIVKA-Ⅱ levels(P＜0.05).Serum B/A ratio,AFP,and PIVKA-Ⅱ levels in the HCC group post operation were significantly lower than those in pre operation(P＜0.05).ROC curve analysis results showed that,when B/A ratio,AFP,and PIVKA-Ⅱ were detected separately,the area under the curve(AUC)was 0.785,0.756,and 0.802,respectively.The AUC for joint detection was 0.925.The AUC in combination was greater than that of individual detection of each indicator.Conclusion:The combination of B/A ratio,AFP,and PIVKA-Ⅱ testing significantly improves the diagnostic efficiency for HCC,which is worthy of clinical application.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

The increasing prevalence of aging has led to a rising incidence of comorbidity of sarcopenia and obesity, posing significant burdens on socioeconomic and public health. Current research has systematically explored the pathogenesis of each condition; however, the mechanisms underlying their comorbidity remain unclear. This study reviews the current literature on sarcopenia and obesity in the aging population, focusing on their shared biological mechanisms, which include loss of autophagy, abnormal macrophage function, mitochondrial dysfunction, and reduced sex hormone secretion. It also identifies metabolic mechanisms such as insulin resistance, vitamin D metabolism abnormalities, dysregulation of iron metabolism, decreased levels of nicotinamide adenine dinucleotide, and gut microbiota imbalances. Additionally, this study also explores the important role of genetic factors, such as alleles and microRNAs, in the co-occurrence of sarcopenia and obesity. A better understanding of these mechanisms is vital for developing clinical interventions and preventive strategies.
Humans ; Sarcopenia/physiopathology* ; Obesity/physiopathology* ; Aging/physiology* ; Autophagy/physiology* ; Insulin Resistance ; Comorbidity ; Vitamin D/metabolism* ; Gonadal Steroid Hormones/metabolism* ; Gastrointestinal Microbiome ; Mitochondria ; MicroRNAs

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Prostate cancer(PCa) is a common malignant tumor among elderly men, with high incidence and mortality rates worldwide, posing a serious threat to human health. Traditional treatments face limitations, highlighting the urgent need for novel therapeutic strategies. Recent studies on the regulatory mechanisms of micro ribonucleic acid(microRNA, miRNA) in tumor development has identified miRNA as new targets for PCa diagnosis and treatment. Traditional Chinese medicine(TCM), with its multi-mechanism, multi-target, and multi-pathway regulatory properties, shows promising potential in miRNA-based PCa therapy. This review summarized recent findings on miRNA' roles in PCa and research progress of TCM intervention and found that a variety of miRNA played important regulatory roles in cell differentiation, proliferation, apoptosis, invasion, metastasis, immune microenvironment, and drug resistance, and their potential as biomarkers for PCa diagnosis, prognosis, and therapy, indicating the potential to be a biomarker for the diagnosis, prognosis evaluation, and treatment of PCa. The review concluded that the active components of TCM(terpenoids, flavonoids, alkaloids, and others) and compounds(Yishen Tonglong Decoction, Shenhu Decoction, Zhoushi Qiling Decoction, Fuzheng Yiliu Decoction, and Qilan Formula) could regulate the expression of their downstream target genes by acting on specific miRNA and affect the above biological behaviors of PCa cells, thus playing a role in the treatment of PCa. This review aims to provide a theoretical basis for miRNA as potential biomarkers and therapeutic targets for PCa and suggest new avenues for further development of targeted therapy strategies against miRNA.
Humans ; MicroRNAs/metabolism* ; Prostatic Neoplasms/metabolism* ; Male ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Animals ; Gene Expression Regulation, Neoplastic/drug effects*

OBJECTIVE: To investigate the impact of bone mass and volume of low-density zones beneath the tibial plateau on the maximum von Mises stresses experienced by the cartilage and meniscus in the knee joint. METHODS: The study included one healthy adult volunteer, from whom CT scans were obtained, and one patient diagnosed with knee osteoarthrisis (KOA), for whom X-ray films were acquired. A static model of the knee joint featuring a low-density zone was established based on a normal knee model. In the finite element analysis, axial loads of 1 000 N and 1 800 N were applied to the weight-bearing region of the upper surface of the femoral head for model validation and subsequent finite element studies, respectively. The maximum von Mises stresses in the femoral cartilage, as well as the medial and lateral tibial cartilage and menisci, were observed, and the stress percentage of the medial and lateral components were concurrently analyzed. Additionally, HE staining, as well as alkaline magenta staining, were performed on the pathological specimens of patients with KOA in various low-density regions. RESULTS: The results of model validation indicated that the model was consistent with normal anatomical structures and correlated with previous calculations documented in the literature. Static analysis revealed that the maximum von Mises stress in the medial component of the normal knee was the lowest and increased with the advancement of the hypointensity zone. In contrast, the lateral component exhibited an opposing trend, with the maximum von Mises stress in the lateral component being the highest and decreasing as the hypointensity zone progressed. Additionally, the medial component experienced an increasing proportion of stress within the overall knee joint. HE staining demonstrated that the chondrocyte layer progressively deteriorated and may even disappear as the hypointensity zone expanded. Furthermore, alkaline magenta staining indicated that the severity of microfractures in the trabecular bone increased concurrently with the expansion of the hypointensity zone. CONCLUSION The presence of subtalar plateau low-density zone may aggravate joint degeneration. In clinical practice, it is necessary to pay attention to the changes in the subtalar plateau low-density zone and actively take effective measures to strengthen the bone status of the subtalar plateau low-density zone and restore the complete biomechanical function of the knee joint, in order to slow down or reverse the progression of osteoarthritis.
Humans ; Finite Element Analysis ; Knee Joint/physiology* ; Tibia/anatomy & histology* ; Cartilage, Articular/physiology* ; Menisci, Tibial/physiopathology* ; Tomography, X-Ray Computed ; Osteoarthritis, Knee/diagnostic imaging* ; Weight-Bearing ; Bone Density ; Adult ; Stress, Mechanical ; Male ; Middle Aged ; Biomechanical Phenomena ; Female