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

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

BACKGROUND: Pancreatic cancer is a lethal malignancy prone to gemcitabine resistance. The single-strand selective monofunctional uracil DNA glycosylase (SMUG1), which is responsible for initiating base excision repair, has been reported to predict the outcomes of different cancer types. However, the function of SMUG1 in pancreatic cancer is still unclear. METHODS: Gene and protein expression of SMUG1 as well as survival outcomes were assessed by bioinformatic analysis and verified in a cohort from Fudan University Shanghai Cancer Center. Subsequently, the effect of SMUG1 on proliferation, cell cycle, and migration abilities of SMUG1 cells were detected in vitro . DNA damage repair, apoptosis, and gemcitabine resistance were also tested. RNA sequencing was performed to determine the differentially expressed genes and signaling pathways, followed by quantitative real-time polymerase chain reaction and Western blotting verification. The cancer-promoting effect of forkhead box Q1 (FOXQ1) and SMUG1 on the ubiquitylation of myelocytomatosis oncogene (c-Myc) was also evaluated. Finally, a xenograft model was established to verify the results. RESULTS: SMUG1 was highly expressed in pancreatic tumor tissues and cells, which also predicted a poor prognosis. Downregulation of SMUG1 inhibited the proliferation, G1 to S transition, migration, and DNA damage repair ability against gemcitabine in pancreatic cancer cells. SMUG1 exerted its function by binding with FOXQ1 to activate the Protein Kinase B (AKT)/p21 and p27 pathway. Moreover, SMUG1 also stabilized the c-Myc protein via AKT signaling in pancreatic cancer cells. CONCLUSIONS SMUG1 promotes proliferation, migration, gemcitabine resistance, and c-Myc protein stability in pancreatic cancer via protein kinase B signaling through binding with FOXQ1. Furthermore, SMUG1 may be a new potential prognostic and gemcitabine resistance predictor in pancreatic ductal adenocarcinoma.
Humans ; Pancreatic Neoplasms/pathology* ; Forkhead Transcription Factors/genetics* ; Signal Transduction/genetics* ; Animals ; Cell Line, Tumor ; Proto-Oncogene Proteins c-akt/metabolism* ; Cell Proliferation/physiology* ; Mice ; Uracil-DNA Glycosidase/genetics* ; Female ; Male ; Gemcitabine ; Mice, Nude ; Apoptosis/physiology* ; Deoxycytidine/analogs & derivatives* ; Cell Movement/genetics*

Background Kurtosis reflecting noise's temporal structure is an effective metric for evaluating noise-induced hearing loss (NIHL), and its threshold is still unclear. Objective To explore the energy range of kurtosis and the threshold of NIHL induced by kurtosis in this energy rangeMethods Using cross-sectional design, 4631 noise-exposed workers in manufacturing industry were selected. The hearing loss and noise exposure data of each worker were collected. Logistic regression model was used to establish the dose-response relationship between noise exposure and hearing loss and estimate the range of energy effects. Restricted cubic spline model was utilized to analyze the dose-response relationship curves of kurtosis to noise-induced hearing loss (NIHI) and high-frequency noise-induced hearing loss (HFNIHL) under different 8 h equivalent sound levels (L_{EX,8 h}), as well as to estimate the kurtosis effect threshold. Results The logistic regression model analysis showed that the prevalence of NIHI and HFNIHL increased significantly with increase of L_{EX,8 h} for steady noise; when L_{EX,8 h} of non-steady noise was 80-100 dB(A), the risk of hearing loss increased with an increase in kurtosis (P<0.05). The restricted cubic spline model showed that when L_{EX,8 h} of non-steady noise was 0-80 dB(A) or >100 dB(A), there was no significant relationship between kurtosis and NIHI or HFNIHL. When L_{EX,8 h} was 80-100 dB(A), there was a significant nonlinear dose-response relationship between kurtosis and NIHL or HFNIHL (P <0.001), and kurtosis > 28.08 exerted effect in elevating NIHI or HFNIHL. Conclusion The effect threshold of kurtosis on NIHL is 28.08 when non-steady noise levels are in the range of 80-100 dB(A). The effect threshold of kurtosis needs further verification.

T7 RNA polymerase (T7 RNAP) is one of the simplest known RNA polymerases. Its unique structural features make it a critical model for studying the mechanisms of RNA synthesis. This review systematically examines the static crystal structure of T7 RNAP, beginning with an in-depth examination of its characteristic “thumb”, “palm”, and “finger” domains, which form the classic “right-hand-like” architecture. By detailing these structural elements, this review establishes a foundation for understanding the overall organization of T7 RNAP. This review systematically maps the functional roles of secondary structural elements and their subdomains in transcriptional catalysis, progressively elucidating the fundamental relationships between structure and function. Further, the intrinsic flexibility of T7 RNAP and its applications in research are also discussed. Additionally, the review presents the structural diagrams of the enzyme at different stages of the transcription process, and through these diagrams, it provides a detailed description of the complete transcription process of T7 RNAP. By integrating structural dynamics and kinetics analyses, the review constructs a comprehensive framework that bridges static structure to dynamic processes. Despite its advantages, T7 RNAP has a notable limitation: it generates double-stranded RNA (dsRNA) as a byproduct. The presence of dsRNA not only compromises the purity of mRNA products but also elicits nonspecific immune responses, which pose significant challenges for biotechnological and therapeutic applications. The review provides a detailed exploration of the mechanisms underlying dsRNA formation during T7 RNAP catalysis, reviews current strategies to mitigate this issue, and highlights recent progress in the field. A key focus is the semi-rational design of T7 RNAP mutants engineered to minimize dsRNA generation and enhance catalytic performance. Beyond its role in transcription, T7 RNAP exhibits rapid development and extensive application in fields, including gene editing, biosensing, and mRNA vaccines. This review systematically examines the structure-function relationships of T7 RNAP, elucidates the mechanisms of dsRNA formation, and discusses engineering strategies to optimize its performance. It further explores the engineering optimization and functional expansion of T7 RNAP. Furthermore, this review also addresses the pressing issues that currently need resolution, discusses the major challenges in the practical application of T7 RNAP, and provides an outlook on potential future research directions. In summary, this review provides a comprehensive analysis of T7 RNAP, ranging from its structural architecture to cutting-edge applications. We systematically examine: (1) the characteristic right-hand domains (thumb, palm, fingers) that define its minimalistic structure; (2) the structure-function relationships underlying transcriptional catalysis; and (3) the dynamic transitions during the complete transcription cycle. While highlighting T7 RNAP’s versatility in gene editing, biosensing, and mRNA vaccine production, we critically address its major limitation—dsRNA byproduct formation—and evaluate engineering solutions including semi-rationally designed mutants. By synthesizing current knowledge and identifying key challenges, this work aims to provide novel insights for the development and application of T7 RNAP and to foster further thought and progress in related fields.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

AIM To study the chemical constituents from the roots of Siraitia grosvenorii(Swingle)C.Jeffrey and their α-glucosidase inhibitory activities.METHODS The 95％ethanol extract was isolated and purified by silica gel,MCI,ODS and HSCCC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The α-glucosidase inhibitory activities were evaluated by PNPG method,after which molecular docking was performed.RESULTS Twenty-one compounds were isolated and identified as vanillin(1),siraitic acid B(2),cucurbitacin B(3),salicylic acid(4),ferulic acid(5),p-hydroxybenzaldehyde(6),(+)-lariciresinol(7),(+)-isolariciresinol(8),liballinol(9),3-(hydroxyacetyl)indole(10),2E-4-hydroxy-nonenoic acid(11),vomifolilol(12),vanillic acid(13),indole-3-carboxylic acid(14),ω-hydroxypropioguaiacone(15),p-hydroxybenzoic acid(16),p-coumaric acid(17),dehydrodipinocarpine(18),secoisolariciresinol(19),sesquimarocanol A(20),threo-guaiacylglycerol-β-O-4-lariciresinol ether(21).IC50 values of compounds 4,10,18 and 21 were(0.42±0.060)-(0.89±0.037)mg/mL.CONCLUSION Compounds 4,10-12,15,16,18,and 21 are isolated from the roots of this plant for the first time.Compounds 4,10,18,21 have α-glucosidase inhibitory activities,and 18 has the strongest activity.

AIM To study the protective effect of Gynura divaricate polysaccharide on gouty nephropathy(GN)induced by dry yeast combined with adenine in rats.METHODS Sixty male SD rats were randomly divided into the normal group,the model group,the allopurinol group(42 mg/kg),and the low-dose,medium-dose and high-dose G.divaricate polysaccharide groups(140,280,560 mg/kg).All the rats except those of the normal group were induced into GN models by intragastrical dosing of yeast(5 g/kg)and adenine(100 mg/kg)and intervened with corresponding drug administration simultaneously.After 35 days,the rats had their levels of creatinine(Cr)and uric acid(UA)in serum and urine detected and their fraction excretion of uric acid(FEUA)value determined;their kidney mass and volume measured and their levels of kidney index and density calculated;their renal pathological changes checked by HE staining;their renal GLUT9,URAT1,ABCG2 and OAT1 mRNA expressions dectected by RT-qPCR;and their renal GLUT9,URAT1,ABCG2 and OAT1 protein expressions dectected by Western blot.RESULTS Compared with the model group,each dose of G.divaricate polysaccharide group displayed decreased levels of kidney mass,kidney volume and kidney index(P＜0.01);increased levels of kidney density(P＜0.05,P＜0.01);decreased serum levels of UA and Cr(P＜0.01);increased urine levels of UA and Cr(P＜0.01);increased FEUA value(P＜0.01);decreased GLUT9,URAT1 mRNA and protein expressions(P＜0.05,P＜0.01);and increased ABCG2,OAT1 mRNA and protein expressions(P＜0.05,P＜0.01);and more alleviated renal histological aberrations.CONCLUSION G.divaricate polysaccharide exerts good protective effects against yeast/adenine-induced GN in rats probably through down-regulating protein expression of GLUT9,URAT1 and up-regulating ABCG2 and OAT1.