Irritable bowel syndrome with diarrhea （IBS-D）， as a prototypical disorder involving the microbiota-gut-brain axis， remains poorly understood in terms of its pathogenesis， posing ongoing challenges for clinical diagnosis. Omics technologies， leveraging their high-throughput detection and systematic analysis advantages， has emerged as a critical tool for deciphering the complex mechanisms underlying traditional Chinese medicine （TCM） treatment of IBS-D. This systematic review summarizes the research progress of transcriptomics， proteomics， metabolomics， microbiomics， and multi-omics integration techniques in TCM interventions for IBS-D. In single-omics studies， transcriptomics using techniques like RNA-seq， reveals the regulatory mechanisms of TCM on IBS-related signaling pathways. Proteomics， leveraging quantitative technologies such as 2D-difference gel electrophoresis and tandem mass tag， identifies differentially expressed proteins and elucidates the action targets of TCM in treating IBS-D. Metabolomics， employing methods like UPLC-Q-TOF-MS and LC-MS/MS， discovers metabolic pathways regulated by TCM to improve metabolic disturbances in IBS-D. Microbiomics， based on 16S rRNA sequencing， confirms that TCM can reshape the gut microbiota structure and restore the intestinal microecological balance， thereby improving IBS-D. Multi-omics integration further overcomes the limitations of single-omics approaches by synthesizing information from transcriptomics， proteomics， metabolomics， and microbiomics， enabling a more comprehensive and systematic elucidation of the complex mechanisms underlying TCM treatment for IBS-D. In the future， research related to IBS-D should be advanced from three aspects： stratified clinical research based on TCM syndrome types， multi-omics integration verification mechanisms， and emerging omics to explore new mechanisms， providing more innovative ideas for the precise diagnosis and treatment of this disease.

Metabolic dysfunction-associated fatty liver disease （MAFLD） is a chronic liver disease closely related to metabolic dysfunction. Its global prevalence is increasing year by year and shows a trend toward younger onset. It is closely associated with cardiovascular and cerebrovascular diseases， chronic kidney disease， and extrahepatic malignant tumors， and has become a major public health problem affecting the health of the Chinese population. At present， the treatment of MAFLD mainly focuses on lifestyle intervention. When metabolic cardiovascular risk factors and liver injury are present， pharmacological intervention is required. However， there is still no specific drug therapy for MAFLD. In recent years， many studies have found that the pathogenesis of MAFLD involves interactions among multiple factors， including insulin resistance， oxidative stress， endoplasmic reticulum stress， programmed cell death， immune dysregulation， inflammasomes， gut microbiota imbalance， and bile acid metabolism. Traditional Chinese medicine （TCM） has advantages in integrated regulation with multiple components and multiple targets， and shows significant efficacy in the treatment of MAFLD. Active components of Chinese medicinal herbs and Chinese medicine compound formulas exert definite therapeutic effects by regulating multiple signaling pathways to improve lipid metabolism disorders， inhibit inflammatory responses， and regulate the gut microbiota， thereby effectively improving clinical symptoms and delaying the occurrence and development of MAFLD. Therefore， strengthening research on the mechanisms of action of TCM in MAFLD is of crucial importance and significance for its treatment. This article summarizes the mechanisms by which Chinese medicine monomers and compound formulas intervene in MAFLD through the regulation of related signaling pathways， based on the retrieval and analysis of relevant literature from multiple databases， with the aim of providing theoretical support and a reference basis for the clinical application of TCM in the treatment of MAFLD.

Objective To provide precise,effective,and intuitive nutritional and dietary recommendations for different population groups,a multi-modal nutritional knowledge graph was constructed,which includes entities such as food,nutrition,population,and diseases.Methods Data sets in the field of nutrition were obtained using web crawling and other technical means.The OneRel model was referenced to complete the joint extraction of Chinese entity relationships and construct a text library.The RoBERTa-ResNet model were used to learn the features of text and image data separately,to align images with text,and to construct a multi-modal knowledge graph.Results The F1 value of the joint entity relationship extraction model was 0.703.The constructed multi-modal knowledge graph contains 3312 textual entities,11 259 relationships,and 1000 image entities.Conclusion The algorithms used in this study to construct the multi-modal nutritional knowledge graph achieve good results.This knowledge graph not only systematically integrates multi-modal knowledge in the field of nutrition and enables good visual query capabilities,but also serves as the underlying support for downstream tasks such as intelligent question answering and nutritional recommendation systems.

Objective To explore the value of dynamic contrast-enhanced(DCE)-MRI quantitative parameters based on differential sub-sampling with Cartesian ordering(DISCO)technology for differentiating high-and low-grade breast cancer.Methods A total of 80 patients with single breast cancer confirmed by biopsy pathology were retrospectively enrolled,including 40 cases of low-grade(L group)and 40 cases of high-grade breast cancer(H group).Then quantitative parameters obtained from DISCO-DCE-MRI before treatment were compared between groups,including extravascular extracellular volume fraction(Ve),rate constant(Kep),contrast enhancement ratio(CER),maximum slope(MaxSlope)and volume transfer constant(Ktrans),and their correlations with histological grade were analyzed.Receiver operating characteristic(ROC)curves of DISCO-DCE-MRI quantitative parameters being significantly different between groups were plotted,and the area under the curves(AUC)were calculated to evaluate their efficacy for differentiating high-and low-grade breast cancer.Results Ve(0.91[0.59,0.99]),CER(2.76±0.54)and MaxSlope(0.02[0.01,0.03])in L group were all higher than those in H group(0.52[0.34,0.73],[2.31±0.74],0.01[0.01,0.02],all P＜0.05),and no significant difference of Kep nor Ktrans was found between groups(both P＞0.05).Ve,CER and MaxSlope of breast cancer were all negatively correlated with histological grade(rs=-0.43,-0.39,-0.35,all P＜0.05),while Kep andKtranshad no significant correlation with histological grade(both P＞0.05).The AUC of Ve,CER and MaxSlope for differentiating high-and low-grade breast cancer was 0.749,0.725 and 0.700,respectively.Conclusion Among DISCO-DCE-MRI quantitative parameters,Ve,CER and MaxSlope could be used for differentiating high-and low-grade breast cancer.

OBJECTIVE: To report the clinical experience of using Ilizarov wrist joint distraction technique in the treatment of a case of rheumatoid arthritis of the wrist. METHODS: In January 2019, a 49-year-old female patient with rheumatoid arthritis of the left wrist, complicated by ulnar impaction syndrome, was admitted for treatment. Preoperatively, the active range of motion of the left wrist was as follows: extension 0°-flexion 0°, pronation 65°-supination 35°, and grip strength of 4.0 kg. The visual analogue scale (VAS) score was 9, and the Cooney wrist function score was 15, indicating poor function. As conservative treatment failed to achieve symptom relief, Ilizarov wrist joint distraction surgery was performed. Postoperatively, joint distraction was applied at 2 mm increments on postoperative days 2 and 7, in 4 separate sessions. RESULTS: Postoperative X-ray film examination at 7 days revealed a distraction of 3.6 mm in the affected wrist joint compared to the contralateral side. The external fixator was removed 2.5 months postoperatively. At 22 months postoperatively, X-ray film and MRI examinations revealed that the joint space of the left wrist had returned to near-normal, with significant reduction in joint effusion and synovial proliferation. The active range of motion of the left wrist improved to extension 15°- flexion 30°, pronation 90°-supination 90°, with a grip strength of 18.0 kg. The wrist pain VAS score decreased to 0, and the Cooney wrist function score improved to 90, indicating excellent function. At 50 months postoperatively, follow-up X-ray film, MRI, and functional assessments showed the results similar to those at 22 months. CONCLUSION Ilizarov wrist joint distraction may be a viable treatment option for rheumatoid arthritis of the wrist.
Humans ; Female ; Middle Aged ; Wrist Joint/physiopathology* ; Arthritis, Rheumatoid/physiopathology* ; Range of Motion, Articular ; Ilizarov Technique ; Treatment Outcome ; Osteogenesis, Distraction/methods*

Objective To provide precise,effective,and intuitive nutritional and dietary recommendations for different population groups,a multi-modal nutritional knowledge graph was constructed,which includes entities such as food,nutrition,population,and diseases.Methods Data sets in the field of nutrition were obtained using web crawling and other technical means.The OneRel model was referenced to complete the joint extraction of Chinese entity relationships and construct a text library.The RoBERTa-ResNet model were used to learn the features of text and image data separately,to align images with text,and to construct a multi-modal knowledge graph.Results The F1 value of the joint entity relationship extraction model was 0.703.The constructed multi-modal knowledge graph contains 3312 textual entities,11 259 relationships,and 1000 image entities.Conclusion The algorithms used in this study to construct the multi-modal nutritional knowledge graph achieve good results.This knowledge graph not only systematically integrates multi-modal knowledge in the field of nutrition and enables good visual query capabilities,but also serves as the underlying support for downstream tasks such as intelligent question answering and nutritional recommendation systems.

Laparoscopic right hemicolectomy is the standard surgical procedure for treating right-sided colon cancer,yet its complex anatomical layers and technically demanding operations pose significant challenges to surgeons'expertise.Currently,surgical skill assessment in clinical practice still predominantly relies on subjective expert evaluation,an approach inherently limited by low efficiency and inconsistent standards.With the rapid advancement of artificial intelligence(AI)technologies(particularly breakthroughs in computer vision and deep learning algorithms),a revolutionary technical foundation has been established for developing objective and precise automated surgical evaluation systems.This article comprehensively reviewed the current clinical application status of right hemicolectomy in China,thoroughly examined the clinical necessity and technical feasibility of constructing an intelligent surgical assessment system,and systematically presented our center's cutting-edge research achievements in this field.Looking ahead,AI-driven intelligent evaluation systems are expected to standardize and quantify surgical skill assessment.Such innovation will not only transform surgical training programs and enhance the quality of multicenter clinical research,but also promote the standardization of precision surgical protocols.This advancement holds significant clinical value and societal importance by improving long-term patient outcomes and fostering more equitable distribution of medical resources.

In recent years, significant progress has been made in the field of colorectal cancer surgery in China. With innovations in techniques such as transanal total mesorectal excision and robotic surgery, as well as the exploration of comprehensive neoadjuvant therapy and neoadjuvant immunotherapy, the application of watch-and-wait and local resection strategies, colorectal surgery is gradually evolving a characteristic of minimally invasive operations, more effective tumor treatments, and individualized organ preservation. In light of these hotspots and innovations, many high-quality evidence-based medical studies have emerged in recent years. This article will review and summarize these developments.

Porcine reproductive and respiratory syndrome virus(PRRSV)mainly causes sow abor-tion,stillbirth,mummified fetus and respiratory symptoms in piglets.Since first reported in China in 1996,the virus complexity has increased significantly in more than 20 years of genetic evolution,bringing huge economic losses to the pig industry.In recent years,with the emergence of various PRRSV recombinant virus strains,preventing and controlling this epidemic became increasingly difficult.The purpose of this article is to comprehensively review the genome structure and func-tion of PRRSV,RNA virus recombination mechanism,main types of recombination,and the epi-demic status and recombination for the dominant epidemic PRRSV strains,in order to provide clues for in-depth research on gene recombination of PRRSV,thus providing the theoretical sup-port for formulating scientific prevention and control strategies.

In recent years, with continuous advancements in molecular biology and gene testing technologies, the diagnosis and treatment of colorectal cancer have been rapidly transitioning toward precision medicine. The application of molecular classification, target detection, and liquid biopsy technologies has driven ongoing updates to clinical guidelines. Multidisciplinary team colla-boration, innovations in precision surgical techniques, and the widespread adoption of neoadjuvant combination therapies have collectively promoted more individualized and scientific management of colorectal cancer. Looking ahead,the authors believe that as multi-omics biomarkers, organoid models, and artificial intelligence are increasingly integrated into clinical practice, precision diagnosis and treatment of colorectal cancer will deepen further, offering patients more efficient and personalized therapeutic options.