Objective:To explore the mechanism of resveratrol in treatment of sleep disorders in mice based on network pharmacology and experimental verification.Methods:Resveratrol targets were obtained through traditional Chinese medicine systems pharmacology database and analysis platform, Swiss Target Prediction and SuperPred databases. Targets related to sleep disorders were collected from the gene expression omnibus, GeneCards, DrugBank, OMIM, CTD and MalaCards databases. Cytoscape 3.8.0 software was used to identify the core targets of resveratrol in treatment of sleep disorders via protein-protein interaction analysis. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were performed, and AutoDockvina software was used to conduct molecular docking between the top five core targets and resveratrol. Thirty ICR female mice were selected and divided into a control group, a model group, and low-, medium- and high-dose (10, 20, and 30 mg/kg) resveratrol groups according to the random number table method, with 6 mice in each group. Resveratrol was dissolved in 0.9% sodium chloride aqueous solution and 3% dimethyl sulfoxide. For mice in the low-, medium-, and high-dose resveratrol groups, 10, 20, and 30 mg/kg of resveratrol solution were intraperitoneally injected, respectively. The mice in the control group and the model group were intraperitoneally injected with 10 ml/kg of 0.9 % sodium chloride aqueous solution and 3 % dimethyl sulfoxide. Each group was injected once a day for 7 consecutive days. After 7 days of administration, a mouse sleep deprivation model was constructed using an improved multi platform water environment method. The spatial recognition and memory abilities of mice were tested using the Y-maze experiment, and the mRNA and protein relative expression levels of estrogen receptor 1 (ESR1) and B-cell lymphoma-2 (Bcl-2) were detected using real-time reverse transcription-PCR and Western blotting, respectively. Comparisons were made using t-test. Results:There were 47 common targets between resveratrol and sleep disorders, and the top five core targets were ESR1, Bcl-2, cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1), cytochrome P450, family 2, subfamily A, polypeptide 4 (CYP3A4) and cytochrome P450, family 1, subfamily B, polypeptide 1 (CYP1B1). GO enrichment analysis revealed that resveratrol in treatment of sleep disorders was mainly related to the regulation of unsaturated fatty acid metabolic processes, secondary metabolic processes, and responses to exogenous stimuli. KEGG pathway analysis showed that resveratrol acted mainly through pathways involving chemical carcinogenic-DNA adducts, cytochrome P450 metabolism of exogenous substances and estrogen signaling pathways. Molecular docking results indicated that resveratrol had strong binding affinity with ESR1, Bcl-2, CYP1A1, CYP3A4 and CYP1B1, with binding energies of ?31.92, ?27.72, ?34.44, ?34.02 and ?31.92 kJ/mol, respectively. In vivo experiments results demonstrated that the novel arm residence time in the low-, medium- and high-dose resveratrol groups [(52±5, 55±7, and 61±9) s] was higher than that in the model group [(45±4) s] ( P<0.05 or 0.01), and the percentage of spontaneous alternation [(53±4)%, (57±5)%, and (65±7)%] was higher than that in the model group [(47±3)%] ( P<0.05 or 0.01). The relative expression levels of ESR1 mRNA (0.42±0.10, 0.49±0.11, and 0.58±0.10) were higher than those in the model group (0.29±0.06) ( P<0.05 or 0.01). The relative expression levels of Bcl-2 mRNA (0.56±0.07, 0.65±0.10, and 0.77±0.11) were higher than those in the model group (0.44±0.08) ( P<0.05 or 0.01). Similarly, the relative expression levels of ESR1 protein (0.32±0.02, 0.50±0.02, and 0.62±0.02) were higher than those in the model group (0.24±0.01) ( P<0.05 or 0.01). The relative expression levels of Bcl-2 protein (0.45±0.08, 0.69±0.06, and 0.72±0.06) were higher than those in the model group (0.17±0.04) ( P<0.05 or 0.01). Conclusions:Resveratrol exerts therapeutic effects on sleep disorders by acting on ESR1 and Bcl-2.

In order to clarify the effects of drought stress training on the quality and drought resistance of Codonopsis pilosula, this study used PEG to simulate drought stress and employed potting with water control for the drought stress training of C. pilosula plants. The polysaccharide content, secondary metabolites, antioxidant system, and photosynthetic pigment system of C. pilosula after drought stress training were analyzed. The results showed that the content of fructans in the root of C. pilosula increased after two rounds of drought stress treatment, and it was significantly higher than that of the control group. The accumulation of fructans in the root of C. pilosula showed an upward trend during the rehydration treatment. The content of lobetyolin and tangshenoside Ⅰ increased after drought stress treatment compared with that of the control group. The rehydration treatment caused first increasing and then decreasing in the content of lobetyolin, while it had no significant effect on the tangshenoside Ⅰcontent. The content of photosynthetic pigments decreased after drought stress treatment, and it gradually increased during the first round of rehydration and the second round of rehydration. Moreover, the increase was faster in the second round of rehydration than in the first round of rehydration. The content of the peroxidation product malondialdehyde(MDA) and the activities of superoxide dismutase(SOD), peroxidase(POD), and catalase(CAT) increased after drought stress treatment compared with those of the control group, and they showed a tendency of decreasing during rehydration. Moreover, the decrease was faster in the second round of rehydration than in the first round of rehydration. When the plants of C. pilosula after drought stress training were again subjected to severe drought stress, the wilting rate decreased significantly, and the biomass increases significantly. This study showed that the drought stress training could promote the accumulation of polysaccharides and secondary metabolites in the root of C. pilosula. When encountering drought stress again, C. pilosula plants could quickly regulate the antioxidant system and delay the decomposition of chlorophyll to respond to drought stress. The findings provide a theoretical basis for the ecological cultivation of C. pilosula in arid and semi-arid areas.
Codonopsis/growth & development* ; Droughts ; Polysaccharides/metabolism* ; Stress, Physiological ; Water/metabolism* ; Antioxidants/metabolism* ; Photosynthesis ; Drought Resistance

The combination of Aidi Injection(ADI) and doxorubicin(DOX) is a common strategy in the treatment of cancer, which can achieve synergistic anti-tumor effects while attenuating the cardiotoxicity caused by DOX. This study aims to investigate the mechanism of ADI in attenuating DOX-induced cardiotoxicity by multi-omics. DOX was used to induce cardiotoxicity in mice, and the cardioprotective effects of ADI were evaluated based on biochemical indicators and pathological changes. Based on the results, transcriptomics, proteomics, and metabolomics were employed to analyze the changes of endogenous substances in different physiological states. Furthermore, data from multiple omics were integrated to screen key regulatory pathways by which ADI attenuated DOX-induced cardiotoxicity, and important target proteins were selected for measurement by ELISA kits and immunohistochemical analysis. The results showed that ADI significantly reduced the levels of cardiac troponin T(cTnT) and N-terminal pro-B-type natriuretic peptide(NT-proBNP) and effectively ameliorated myocardial fibrosis and intracellular vacuolization, indicating that ADI showed therapeutic effect on DOX-induced cardiotoxicity. The transcriptomics analysis screened out a total of 400 differentially expressed genes(DEGs), which were mainly enriched in inflammatory response, oxidative stress, and myocardial fibrosis. After proteomics analysis, 70 differentially expressed proteins were selected, which were mainly enriched in the inflammatory response, cardiac function, and energy metabolism. A total of 51 differentially expressed metabolites were screened by the metabolomics analysis, and they were mainly enriched in multiple signaling pathways, including the inflammatory response, lipid metabolism, and energy metabolism. The integrated data of multiple omics showed that linoleic acid metabolism, arachidonic acid metabolism, and glycerophosphate metabolism pathways played an important role in DOX-induced cardiotoxicity, and ADI may exert therapeutic effects by modulating these pathways. Target validation experiments suggested that ADI significantly regulated abnormal protein levels of cyclooxygenase-1(COX-1), cyclooxygenase-2(COX-2), prostaglandin H2(PGH2), and prostaglandin D2(PGD2) in the model group. In conclusion, ADI may attenuate DOX-induced cardiotoxicity by regulating linoleic acid metabolism, arachidonic acid metabolism, and glycerophosphate metabolism, thus alleviating inflammation of the body.
Doxorubicin/toxicity* ; Animals ; Mice ; Cardiotoxicity/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Proteomics ; Metabolomics ; Injections ; Humans ; Multiomics

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

The quality of drugs is a crucial premise for ensuring the safety and effectiveness of clinical medication, while quality control during the pharmaceutical process directly affects the quality and consistency of the final product formulation. However, there is a lack of a comprehensive and scientific system for assessing and optimizing the quality control level during the manufacturing process in the field of drug quality control. Therefore, this study proposed the concept of "pharmaceutical process omics", clarified its advantages in guiding drug production, and explored in depth the research approaches, diverse analytical techniques, and broad range of applications in drug quality control. In addition, this study anticipated the broad application prospects of pharmaceutical process omics in the field of drug quality control, aiming to provide a scientific basis for the development of pharmaceutical process quality control standards.
Quality Control ; Humans ; Drugs, Chinese Herbal/chemistry*

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.

Pulpotomy, which belongs to vital pulp therapy, has become a strategy for managing pulpitis in recent decades. This minimally invasive treatment reflects the recognition of preserving healthy dental pulp and optimizing long-term patient-centered outcomes. Pulpotomy is categorized into partial pulpotomy (PP), the removal of a partial segment of the coronal pulp tissue, and full pulpotomy (FP), the removal of whole coronal pulp, which is followed by applying the biomaterials onto the remaining pulp tissue and ultimately restoring the tooth. Procedural decisions for the amount of pulp tissue removal or retention depend on the diagnostic of pulp vitality, the overall treatment plan, the patient's general health status, and pulp inflammation reassessment during operation. This statement represents the consensus of an expert committee convened by the Society of Cariology and Endodontics, Chinese Stomatological Association. It addresses the current evidence to support the application of pulpotomy as a potential alternative to root canal treatment (RCT) on mature permanent teeth with pulpitis from a biological basis, the development of capping biomaterial, and the diagnostic considerations to evidence-based medicine. This expert statement intends to provide a clinical protocol of pulpotomy, which facilitates practitioners in choosing the optimal procedure and increasing their confidence in this rapidly evolving field.
Humans ; Calcium Compounds/therapeutic use* ; Consensus ; Dental Pulp ; Dentition, Permanent ; Oxides/therapeutic use* ; Pulpitis/therapy* ; Pulpotomy/standards*

Curcumae Rhizoma, derived from the rhizome of Curcuma phaeocaulis, Curcuma kwangsiensis and Curcuma wenyujin, was called Ezhu in China. In the past, Curcumae Rhizoma extracts were obtained through water decoction or alternative methods, which showed significant anti-cancer effects. However, the mixed extracts contain various compound components of Curcumae Rhizoma, leading to an ambiguous mechanism of action for Curcumae Rhizoma extracts anti-cancer. Contemporary researchers have extracted the chemical components of Curcumae Rhizoma separately for experimental verification of its active ingredients in the anti-cancer field. Numerous studies demonstrated that curcumol, germacrone, β-elemene, and curcumin in Curcumae Rhizoma extracts have significant governing effects in anti-cancer activities. Pharmacological studies have shown that Curcumae Rhizoma suppresses cancer cell proliferation, invasion, and migration, triggering apoptosis and regulating cellular autophagy to achieve anticancer effects. Here, we summarized the research progress of Curcumae Rhizoma on anti-cancer effects from 2013 to 2022, aiming to explore the deeper molecular mechanisms of Curcumae Rhizoma's active components in cancer treatment.

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged