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

Acute pancreatitis (AP) is a severe inflammatory disease characterized by self-digestion of pancreatic tissue and inflammatory responses. Recent studies have revealed a close connection between gut microbiota and AP. The gut microbiota community, a complex ecosystem composed of trillions of microorganisms, is closely associated with various physiological activities of the host, including metabolic processes, immune system regulation, and intestinal structure maintenance. However, in patients with AP, dysbiosis of the gut microbiota are believed to play a key role in the occurrence and progression of the disease. This dysbiosis not only impairs the integrity of the intestinal barrier, but may also exacerbate inflammatory responses through multiple mechanisms, thereby affecting the severity of the disease and patient' clinical prognosis. This article reviews the mechanisms of action of gut microbiota in AP, explores how gut microbiota dysbiosis affects disease progression, and evaluates current clinical treatment methods to regulate intestinal flora, including probiotic supplementation, fecal microbiota transplantation, antibiotic therapy, and early enteral nutrition. In addition, this article discusses the efficacy and safety of the aforementioned therapeutic approaches, and outlines future research directions, aiming to provide novel perspectives and strategies for the diagnosis, treatment and prognostic evaluation of AP. Through in-depth understanding the interaction between gut microbiota and AP, it is expected that more precise and personalized therapeutic regimens will be developed to improve patients' quality of life and clinical outcomes.
Humans ; Gastrointestinal Microbiome ; Dysbiosis ; Pancreatitis/microbiology* ; Fecal Microbiota Transplantation ; Probiotics/therapeutic use* ; Acute Disease ; Anti-Bacterial Agents/therapeutic use* ; Enteral Nutrition

A novel analytical method was developed in this study by combining online solid phase extraction with ultra performance liquid chromatography-tandem mass spectrometry(Online SPE-UPLC-MS/MS)for simultaneous determination of 50 kinds of steroid hormones in surface water.Specifically,after high-speed centrifugation of 4 mL water samples,the supernatant was directly injected into an Oasis HLB online SPE column for enrichment and purification.Subsequently,the target compounds were transferred to the analytical column via valve switching for separation and analysis.The chromatographic separation was performed on a Thermo Acclaim RSLC C18 column(100 mm×2.1 mm,2.2 μm),using a mobile phase composed of 5 mmol/L ammonium fluoride aqueous solution and acetonitrile.Mass spectrometric detection was conducted in positive ion mode,utilizing multiple reaction monitoring(MRM)with quantification achieved by the internal standard method.The method validation demonstrated that the limits of detection(LOD)for the 50 kinds of steroid hormones ranged from 0.02 to 0.50 ng/L,while the limits of quantification(LOQ)were between 0.08 and 1.67 ng/L.The average recoveries in surface water samples at spiked concentrations of 5,20 and 200 ng/L were between 74.1％and 119％,with relative standard deviations(RSDs)of 0.2％to 9.9％.This method was applied to analyze 11 surface water samples collected from sites surrounding a pharmaceutical and chemical industrial park.A total of 44 kinds of steroid hormones were detected,with concentrations ranging from 0.11 to 88.6 ng/L,revealing the presence of hormone contamination in the environmental waters surrounding industrial areas.Compared with the traditional offline SPE methods,the proposed online SPE technique significantly reduced sample volume requirements and pretreatment time,while minimizing the loss of target compounds during the pretreatment process.Moreover,compared to reported online SPE techniques,this method achieved high-throughput analysis of multiple classes of steroid hormones,with lower detection limits and higher recoveries.Overall,this method provided rapid sample preparation,high sensitivity,and excellent stability,making it suitable for the direct analysis of trace steroid hormones in surface water.

Objective To investigate the self-healing status of children with abnormal tongue root sounds at different age stages of 4 to 12 years old who have not received articulation training,and to provide correct guidance plans for patients.Methods Through retrospective analysis,114 cases of children diagnosed with functional dysar-thria and abnormal root of tongue in Kunming children's hospital from 2019 to 2020 who refused to do rehabilitation training but could receive long-term outpatient follow-up visit,were selected.The follow-up visit was conducted one year later to reevaluate the root of tongue of the children,and the relationship between the self-healing situation of the children's root of tongue and age and wrong form was statistically analyzed.Results Among the 114 children with abnormal root sound,35 cases(30.70％)healed by themselves.The self-healing rates of each age group were as follows:4～5 years old(45.24％),5～6 years old(27.08％),6～7 years old(14.29％),7～12 years old(10.00％).The self-healing rate of all age groups was significant(x2=8.254,P=0.041).There were 287 fre-quency of errors in 114 cases,among which the self-healing rate of consonant loss was the highest(41.46％),fol-lowed by consonant substitution(40.76％),and consonant distortion was the worst(16.67％).The overall differ-ence of the three error forms was statistically significant(x2=10.003,P=0.007).According to different root sounds,the self-healing rate of/h/sound was the highest(31/60.78％),followed by/k/sound(40,32.26％),and/g/sound was the worst(35,31.25％).There was significant difference among the three root sounds(x2=15.172,P＜0.001).There was no significant difference in the self-healing rate between male and female children(x2=1.311,P=0.252).Conclusion The rate of root sound healing in children with functional articulation disor-der was related to age,wrong form and wrong root sound,but not gender.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Objective:To identifying risk factors of postoperative pulmonary infection(POI)in gastric cancer(GC)patients as well as generating an effective nomogram for the POI.Methods:Pa-tients with gastric cancer after surgery from 1st January 2010 to 31st December 2020 were retro-spectively analysed.Their clinical and pathological data were collected.Multiple logistic regression analysis was conducted to identify risk factors for POI and to generate the nomogram prediction model.Predictive accuracy,discriminatory capability,and clinical usefulness were evaluated by cali-bration curves,concordance index(C-index),and decision curve analysis(DCA).Results:Multivari-ate regression analysis revealed that age,smoking,chronic respiratory diseases,laparoscopic surgery,intraoperative blood loss and lung function exercise compliance were independent prognos-tic factors for POI in GC patients.The nomogram had a Cindex of 0.878(95％CI:0.801～0.956).The calibration curves showed good consistency between actual and nomogram-predicted probabilities.The area under the curve(AUC)was 0.878,while the cutoff value was-2.088 with a sensitivity of 80.6％and a specifificity of 82.9％.DCA showed that the nomogram had better clinical usefulness.Conclusions:The present study provides a nomogram developed with perioperative features to predict the incidence of POI in GC patients.

Objective: To investigate the clinical characteristics of children with allergic diseases suffering from SARS-CoV-2 Omicron variant strains. Methods: This was a cross-sectional study. A total of 43 pediatric patients with allergic diseases infected by SARS-CoV-2 from April 25, 2022 to June 8, 2022 in Shanghai Jiao Tong University School of Medicine were selected as the allergic disease group, while 114 cases without underlying diseases and 16 cases with other underlying diseases were selected as control groups diagnosed at the same period. Clinical data including clinical features, laboratory tests, duration of hospitalization, and the time to negative turn of novel coronavirus nucleic acid were collected and analysed. Kruskal-Wallis H test, chi-square test or Fisher exact test were used for comparison among three groups. Results: Among the 43 patients with allergic diseases, 28 were males and 15 were females, with an age of 4.4 (2.1, 8.2) years on admission, including 32 mild cases and 11 common cases. The allergic disease group included 20 cases (46.5%) of atopic dermatitis and eczema, followed by 14 cases (32.6%) of rhinitis, 8 cases (18.6%) of food allergies, 7 cases (16.3%) of asthma, 4 cases (9.3%) of allergic conjunctivitis and 2 cases (4.7%) of drug allergy. Among the 114 cases without underlying diseases, 57 were males and 57 were females, with an age of 2.8 (1.2, 5.6) years on admission, including 93 mild cases and 21 common cases. Among the 16 cases with other underlying diseases, 9 were males and 7 were females, with an age of 3.0 (2.6, 10.8) years on admission, including 13 cases mild and 3 cases common cases. Children with allergic diseases had higher frequency of sore throat and vomiting than those without underlying diseases (10 cases (23.3%) vs.9 cases (7.9%), 14 cases (32.6%) vs. 11 cases (9.6%), χ²=6.93, 12.24, both P<0.05). The lymphocyte count of patients with allergic disease was lower than those without underlying disease (1.1 (0.7,1.7)×10⁹ vs. 1.6 (1.1,2.7)×10⁹/L, H=-28.00,P=0.005). There were no significant differences in age, gender, typing of SARS-CoV-2, the duration of hospitalization, cycle threshold values of SARS-CoV-2 and the time to negative turn of novel coronavirus nucleic acid among the three groups (all P>0.05). Conclusions: Children with allergic diseases may suffer from sore throat and vomiting more frequently when infected with SARS-CoV-2 Omicron variant. The combination of allergic diseases hardly influenced the disease course of SARS-CoV-2 in children.
Male ; Female ; Humans ; Child ; SARS-CoV-2 ; Cross-Sectional Studies ; COVID-19 ; China/epidemiology* ; Food Hypersensitivity ; Pharyngitis

This study explored the feasibility of mineral element content and ratios of nitrogen isotopes to discriminate the cultivation mode of Dendrobium nobile in order to provide theoretical support for the discrimination of the cultivation mode of D. nobile. The content of 11 mineral elements(N, K, Ca, P, Mg, Na, Fe, Cu, Zn, Mn, and B) and nitrogen isotope ratios in D. nobile and its substrate samples in three cultivation methods(greenhouse cultivation, tree-attached cultivation, and stone-attached cultivation) were determined. According to the analysis of variance, principal component analysis, and stepwise discriminant analysis, the samples of different cultivation types were classified. The results showed that the nitrogen isotope ratios and the content of elements except for Zn were significantly different among different cultivation types of D. nobile(P<0.05). The results of correlation analysis showed that the nitrogen isotope ratios, mineral element content, and effective component content in D. nobile were correlated with the nitrogen isotope ratio and mineral element content in the corresponding substrate samples to varying degrees. Principal component analysis can preliminarily classify the samples of D. nobile, but some samples overlapped. Through stepwise discriminant analysis, six indicators, including δ~(15)N, K, Cu, P, Na, and Ca, were screened out, which could be used to establish the discriminant model of D. nobile cultivation methods, and the overall correct discrimination rates after back-substitution test, cross-check, and external validation were all 100%. Therefore, nitrogen isotope ratios and mineral element fingerprints combined with multivariate statistical analysis could effectively discriminate the cultivation types of D. nobile. The results of this study provide a new method for the identification of the cultivation type and production area of D. nobile and an experimental basis for the quality evaluation and quality control of D. nobile.
Dendrobium ; Minerals ; Discriminant Analysis ; Multivariate Analysis ; Nitrogen Isotopes

OBJECTIVE: To investigate the expression of pyruvate kinase M2 (PKM2) in bone marrow mesenchymal stem cells (BMSCs) in myeloma bone disease (MBD) and its effect on osteogenic and adipogenic differentiation of BMSCs. METHODS: BMSCs were isolated from bone marrow of five patients with multiple myeloma (MM) (MM group) and five with iron deficiency anemia (control group) for culture and identification. The expression of PKM2 protein were compared between the two groups. The differences between osteogenic and adipogenic differentiation of BMSCs were assessed by using alkaline phosphatase (ALP) and oil red O staining, and detecting marker genes of osteogenesis and adipogenesis. The effect of MM cell line (RPMI-8226) and BMSCs co-culture on the expression of PKM2 was explored. Functional analysis was performed to investigate the correlations of PKM2 expression of MM-derived BMSCs with osteogenic and adipogenic differentiation by employing PKM2 activator and inhibitor. The role of orlistat was explored in regulating PKM2 expression, osteogenic and adipogenic differentiation of MM-derived BMSCs. RESULTS: Compared with control, MM-originated BMSCs possessed the ability of increased adipogenic and decreased osteogenic differentiation, and higher level of PKM2 protein. Co-culture of MM cells with BMSCs markedly up-regulated the expression of PKM2 of BMSCs. Up-regulation of PKM2 expression could promote adipogenic differentiation and inhibit osteogenic differentiation of MM-derived BMSCs, while down-regulation of PKM2 showed opposite effect. Orlistat significantly promoted osteogenic differentiation in MM-derived BMSCs via inhibiting the expression of PKM2. CONCLUSION The overexpression of PKM2 can induce the inhibition of osteogenic differentiation of BMSCs in MBD. Orlistat can promote the osteogenic differentiation of BMSCs via inhibiting the expression of PKM2, indicating a potential novel agent of anti-MBD therapy.
Humans ; Adipogenesis ; Bone Diseases/metabolism* ; Bone Marrow Cells ; Cell Differentiation ; Cells, Cultured ; Mesenchymal Stem Cells/physiology* ; Multiple Myeloma/metabolism* ; Orlistat/pharmacology* ; Osteogenesis/genetics*

Fermented Chinese medicine has long been used. Amid the advance for preservation of experience, the connotation of fermented Chinese medicine has been enriched and improved. However, fermented Chinese medicine prescriptions generally contain a lot of medicinals. The fermentation process is complicated and the conventional fermentation conditions fail to be strictly controlled. In addition, the judgment of the fermentation end point is highly subjective. As a result, quality of fermented Chinese medicine is of great difference among regions and unstable. At the moment, the quality standards of fermented Chinese medicine are generally outdated and different among regions, with simple quality control methods and lacking objective safe fermentation-specific evaluation indictors. It is difficult to comprehensively evaluate and control the quality of fermented medicine. These problems have aroused concern in the industry and also affected the clinical application of fermented Chinese medicine. This article summarized and analyzed the application, quality standards, and the modernization of fermentation technology and quality control methods of fermented Chinese medicine and proposed suggestions for improving the quality standards of the medicine, with a view to improving the overall quality of it.
Medicine, Chinese Traditional ; Reference Standards ; Quality Control ; Fermentation