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

OBJECTIVES: To explore the correlation of ELFN1 expression level with prognosis of colorectal cancer and its regulatory role in colorectal cancer cell proliferation and metastasis. METHODS: We analyzed the expression levels of ELFN1 across 33 cancer types using publicly available databases and identified differential genes related to ELFN1 in colorectal cancer. Gene function annotation and enrichment analysis were used to identify the involved signaling pathways. Logistic analysis, Kaplan-Meier analysis and Cox regression analysis were performed to evaluate the correlation between ELFN1 expression and clinicopathological parameters and survival of colorectal cancer patients. qPCR and Western blotting were used to validate the expression levels of ELFN1 in different colorectal cancer cell lines and tissues, and Transwell and EDU experiments were carried out to assess the effect of ELFN1 knockdown on biological behaviors of SW480 cells. RESULTS: ELFN1 was highly expressed in 14 cancers, and its expression was significantly higher in colon cancer tissues than in adjacent tissues. A high expression of ELFN1 mRNA was associated with a poorer overall survival of colorectal cancer patients. Cox regression analysis indicated that ELFN1 expression was an independent prognostic factor for overall survival of the patients. ELFN1 was significantly enriched in tumor metastasis and proliferation and participated in several tumor signaling pathways. The colon cancer cell lines showed significantly higher expression levels of ELFN1 than normal cells, ELFN1 knockdown obviously inhibited proliferation and migration of SW480 cells in vitro. CONCLUSIONS ELFN1 is overexpressed in colorectal cancer and is associated with poor clinical prognosis of the patients. A high ELFN1 expression is associated with malignant phenotypes of colorectal cancer and promotes cancer cell proliferation and metastasis, suggesting its potential as a prognostic biomarker for colorectal cancer.
Humans ; Colorectal Neoplasms/diagnosis* ; Cell Proliferation ; Prognosis ; Cell Line, Tumor ; Biomarkers, Tumor/metabolism* ; Neoplasm Metastasis ; Gene Expression Regulation, Neoplastic ; Nerve Tissue Proteins/metabolism* ; Female ; Male

Objective To discuss the prediction value of the early efficacy of hepatic arterial infusion chemotherapy(HAIC)in treating stage Ⅱ-Ⅲ hepatocellular carcinoma(HCC).Methods The clinical data of 81 patients with stage Ⅱ-Ⅲ HCC,who received at least 3 times of HAIC at the Nanchang Municipal Central Hospital of China from November 2021 to March 2024,were retrospectively analyzed.CT or MRI was used to compare patient's local tumor response after each treatment cycle.Based on modified Response Evaluation Criteria in Solid Tumors(mRECIST),the curative effects of patients after receiving the first,the second,and the last HAIC treatment were compared between each other.The prediction value of the early efficacy of HAIC in treating patients with stage Ⅱ-Ⅲ HCC was analyzed.Results In the 67 patients,the efficacy of the last time HAIC was equal or similar to that of the first time HAIC,and in the remaining 14 patients the efficacy of the last time HAIC was different from that of the first time HAIC,with an efficacy prediction rate of 82.72％.The efficacy of the last time HAIC was equal or similar to that of the second time HAIC in 71 patients,and in the remaining 10 patients the efficacy of the last time HAIC was different from that of the second time HAIC,with an efficacy prediction rate of 87.65％.Conclusion In treating stage Ⅱ-Ⅲ HCC with HAIC,the early efficacy can be used to predict the final efficacy after completion of the total treatment course.

Objective To explore the relationship between PANoptosis and hepatic ischemia-reperfusion injury (HIRI), and to screen the key genes of PANoptosis in HIRI. Methods PANoptosis-related differentially expressed genes (PDG) were obtained through the Gene Expression Omnibus database and GeneCards database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the biological pathways related to PDG. A protein-protein interaction network was constructed. Key genes were selected, and their diagnostic value was assessed and validated in the HIRI mice. Immune cell infiltration analysis was performed based on the cell-type identification by estimating relative subsets of RNA transcripts. Results A total of 16 PDG were identified. GO analysis showed that PDG were closely related to cellular metabolism. KEGG analysis indicated that PDG were mainly enriched in cellular death pathways such as apoptosis and immune-related signaling pathways such as the tumor necrosis factor signaling pathway. GSEA results showed that key genes were mainly enriched in immune-related signaling pathways such as the mitogen-activated protein kinase (MAPK) signaling pathway. Two key genes, DFFB and TNFSF10, were identified with high accuracy in diagnosing HIRI, with areas under the curve of 0.964 and 1.000, respectively. Immune infiltration analysis showed that the control group had more infiltration of resting natural killer cells, M2 macrophages, etc., while the HIRI group had more infiltration of M0 macrophages, neutrophils, and naive B cells. Real-time quantitative polymerase chain reaction results showed that compared with the Sham group, the relative expression of DFFB messenger RNA in liver tissue of HIRI group mice increased, and the relative expression of TNFSF10 messenger RNA decreased. Cibersort analysis showed that the infiltration abundance of naive B cells was positively correlated with DFFB expression (r=0.70, P=0.035), and the infiltration abundance of M2 macrophages was positively correlated with TNFSF10 expression (r=0.68, P=0.045). Conclusions PANoptosis-related genes DFFB and TNFSF10 may be potential biomarkers and therapeutic targets for HIRI.

Objective To evaluate the application of novel oral anticoagulants(NOACs)in the treatment of elderly patients with non-valvular atrial fibrillation(NVAF),and to provide a basis for the rational use of drugs in clinical practice.Methods Based on the Beers criteria(2023 edition),combined with drug instructions and relevant guidelines,the potential inappropriate medication(PIM)evaluation criteria of NOACs in NVAF patients were formulated.The medication PIM of patients aged 80 years or older who were hospitalized in the cardiovascular department from January to December 2023 was analyzed when using NOACs.Results A total of 78 cases were included,and 47 cases of PIM occurred in NOACs,including 1 case of renal function-related PIM(2.13％),and 46 cases of drug interaction related PIM(97.87％).There were 72 patients who do not meet the evaluation criteria of the 2023 version of the Beers standard.Conclusion The updated Beers standard has not yet been widely adopted in clinical practice.The highest incidence of PIM in the use of NOACs in elderly patients with NVAF is due to drug interactions.It is necessary to strengthen drug monitoring in elderly patients with NVAF and promote rational drug use.

The complement component 4 binding protein alpha(C4BPA)gene is the alpha chain of complement binding protein 4.As a plasma protein involved in the complement and coagulation systems,it can influence immune responses and lipid metabolism.In order to study the polymor-phism of C4BPA gene and its correlation with milk quality traits in Chinese Holstein cows,genom-ic DNA was extracted from blood samples of 92 Chinese Holstein cows,and the target fragment of C4BPA gene was amplified by PCR,and the association analysis was performed by using direct se-quencing to obtain the SNP loci and milk quality traits.The results showed that among the four SNPs found at the third intron of the C4BPA gene,I3-11 G＞A was highly significantly correlated with milk protein and urea nitrogen(P＜0.05),I3-291 T＞G was significantly correlated with lac-tose(P＜0.05),I3-374 C＞T was highly significantly correlated with lactose and urea nitrogen(P＜0.05),and I3-375 T＞G was highly significantly correlated with lactose(P＜0.05),milk pro-tein and urea nitrogen.The chi-square test values for each point indicated that the population was in genetic equilibrium.Individuals of haplotype combination H1 H1 had the highest lactose content,and haplotype combination H1H2 can be used as the best haplotype combination in the molecular selection work of dairy cows.

Purpose To explore the feasibility and clinical value of deep learning-based image reconstruction technology in 5.0T MRI for nasopharyngeal carcinoma.Materials and Methods A prospective study was conducted on 50 newly diagnosed nasopharyngeal carcinoma patients from August to December 2024 at Sun Yat-sen University Cancer Center.5.0T MRI was performed to scan the nasopharynx region.Routine scanning protocols included transverse T2WI,transverse T1WI,transverse contrast-enhanced T1WI and coronal fat-suppressed contrast-enhanced T1WI sequences.Based on these standard scanning protocols,DeepRecon deep learning reconstruction technology with different levels(grade 1-5)was applied,generating a total of 24 sets of images.Qualitative evaluation employed a Likert scale(5-point system)for subjective scoring on lesion detection,lesion edge clarity,artifacts and overall image quality.Quantitative evaluation was performed using the signal-to-noise ratio and contrast-to-noise ratio to objectively assess the quality of the 24 image sets.Differences in qualitative and quantitative indicators between different groups were compared,while the Kappa coefficient was used to analyze the consistency of subjective evaluations by two radiologists.Results In the qualitative assessment of 24 image sets from four MRI sequences(with and without DeepRecon reconstruction),DeepRecon images(grade 2-4)significantly outperformed traditional images in all features except for artifact reduction(Z=-12.11--6.23,all P<0.001).Images reconstructed at DeepRecon grade 3 had the highest overall score and the best image quality.Furthermore,compared with traditional images,DeepRecon images(grade 2-5)demonstrated significantly improved signal-to-noise ratio for both lesions and the lateral pterygoid muscle(t=-15.67--3.44,Z=-6.09--4.63,all P<0.01).In addition,in the transverse T2WI,transverse contrast-enhanced T1WI and coronal fat-suppressed contrast-enhanced T1WI images with DeepRecon reconstruction(grade 2-5),the contrast-to-noise ratio(lesion/lateral pterygoid muscle)also showed significant improvement compared to traditional images(t=-12.71--3.19,Z=-6.08--4.47,all P<0.001).The inter-observer agreement for the overall subjective quality score between the two radiologists was good(Kappa=0.75-0.82,all P<0.01).Conclusion DeepRecon deep learning reconstruction technology significantly increases the signal-to-noise ratio and resolution of traditional magnetic resonance images of nasopharyngeal cancer,improving image clarity and bringing more possibilities for the advancement of imaging diagnosis.

A 58-year-old female patient with anti-synthetase syndrome received compound sulfamethoxazole [containing trimethoprim (TMP) 80 mg and sulfamethoxazole (SMZ) 0.4 g, SMZ-TMP] 3 tablets thrice daily orally for the treatment of Pneumocystis jirovecii pneumonia. Before medication, the patient′s blood potassium was 3.3 mmol/L and blood chlorine was 116 mmol/L. Three days after SMZ-TMP treatment, the patient′s blood potassium was 5.7 mmol/L, blood chlorine was 114 mmol/L, blood pH was 7.3, urine pH was <5.5, blood chlorine was 114 mmol/L, and bicarbonate was 15 mmol/L. Hyperkalemia type renal tubular acidosis due to SMZ-TMP was considered. The dosage of SMZ-TMP was reduced to 2 tablets once daily orally. After 1 day of diuretic and potassium excretion treatments, the patient′s blood potassium levels returned to normal; after 2 days of the treatments, her blood chlorine was 109 mmol/L and bicarbonate was 17 mmol/L; after 3 days of the treatments, her chest CT showed emphysema in the neck and mediastinum. The dose of SMZ-TMP was changed to 3 tablets thrice daily orally, and at the same time intravenous infusion of ganciclovir 0.3 g twice daily was given. And again, her blood potassium increased and blood pH decreased. Sodium bicarbonate 1 g thrice daily orally was given to correct the acidosis. After adding SMZ-TMP for 2 days, SMZ-TMP dosage was reduced to 2 tablets once daily orally again. Seven days later, the patient′s vital signs were stable, her mediastinal emphysema was significantly improved, her blood potassium was 4.7 mmol/L, and blood pH was 7.4.

Objective To evaluate the application of novel oral anticoagulants(NOACs)in the treatment of elderly patients with non-valvular atrial fibrillation(NVAF),and to provide a basis for the rational use of drugs in clinical practice.Methods Based on the Beers criteria(2023 edition),combined with drug instructions and relevant guidelines,the potential inappropriate medication(PIM)evaluation criteria of NOACs in NVAF patients were formulated.The medication PIM of patients aged 80 years or older who were hospitalized in the cardiovascular department from January to December 2023 was analyzed when using NOACs.Results A total of 78 cases were included,and 47 cases of PIM occurred in NOACs,including 1 case of renal function-related PIM(2.13％),and 46 cases of drug interaction related PIM(97.87％).There were 72 patients who do not meet the evaluation criteria of the 2023 version of the Beers standard.Conclusion The updated Beers standard has not yet been widely adopted in clinical practice.The highest incidence of PIM in the use of NOACs in elderly patients with NVAF is due to drug interactions.It is necessary to strengthen drug monitoring in elderly patients with NVAF and promote rational drug use.

Purpose To explore the feasibility and clinical value of deep learning-based image reconstruction technology in 5.0T MRI for nasopharyngeal carcinoma.Materials and Methods A prospective study was conducted on 50 newly diagnosed nasopharyngeal carcinoma patients from August to December 2024 at Sun Yat-sen University Cancer Center.5.0T MRI was performed to scan the nasopharynx region.Routine scanning protocols included transverse T2WI,transverse T1WI,transverse contrast-enhanced T1WI and coronal fat-suppressed contrast-enhanced T1WI sequences.Based on these standard scanning protocols,DeepRecon deep learning reconstruction technology with different levels(grade 1-5)was applied,generating a total of 24 sets of images.Qualitative evaluation employed a Likert scale(5-point system)for subjective scoring on lesion detection,lesion edge clarity,artifacts and overall image quality.Quantitative evaluation was performed using the signal-to-noise ratio and contrast-to-noise ratio to objectively assess the quality of the 24 image sets.Differences in qualitative and quantitative indicators between different groups were compared,while the Kappa coefficient was used to analyze the consistency of subjective evaluations by two radiologists.Results In the qualitative assessment of 24 image sets from four MRI sequences(with and without DeepRecon reconstruction),DeepRecon images(grade 2-4)significantly outperformed traditional images in all features except for artifact reduction(Z=-12.11--6.23,all P<0.001).Images reconstructed at DeepRecon grade 3 had the highest overall score and the best image quality.Furthermore,compared with traditional images,DeepRecon images(grade 2-5)demonstrated significantly improved signal-to-noise ratio for both lesions and the lateral pterygoid muscle(t=-15.67--3.44,Z=-6.09--4.63,all P<0.01).In addition,in the transverse T2WI,transverse contrast-enhanced T1WI and coronal fat-suppressed contrast-enhanced T1WI images with DeepRecon reconstruction(grade 2-5),the contrast-to-noise ratio(lesion/lateral pterygoid muscle)also showed significant improvement compared to traditional images(t=-12.71--3.19,Z=-6.08--4.47,all P<0.001).The inter-observer agreement for the overall subjective quality score between the two radiologists was good(Kappa=0.75-0.82,all P<0.01).Conclusion DeepRecon deep learning reconstruction technology significantly increases the signal-to-noise ratio and resolution of traditional magnetic resonance images of nasopharyngeal cancer,improving image clarity and bringing more possibilities for the advancement of imaging diagnosis.