Colorectal cancer stands as a leading cause of cancer-related morbidity and mortality globally,with liver metastases being a significant determinant of patient prognosis.Conventional diagnostic methods,includ-ing imaging studies and biomarker testing,frequently exhibit inadequate sensitivity and specificity,underscoring the necessity for more advanced technologies.Recent advancements in genomics,transcriptomics,proteomics,me-tabolomics,and epigenomics have revolutionized our understanding of the biological mechanisms driving colorectal cancer.These methodologies enable comprehensive analyses of genetic mutations,gene expression profiles,protein modifications,and metabolic reprogramming,all of which are pivotal to the metastatic process.This article high-lights the advanced capabilities of artificial intelligence(AI)technologies in processing complex multi-omics data,thereby enhancing diagnostic accuracy and supporting personalized treatment strategies.It also addresses the challenges AI encounters in multi-omics analyses,such as ensuring data quality,improving model interpretability,and facilitating clinical translation.Additionally,it explores the potential integration of emerging technologies like single-cell sequencing and spatial omics into large-scale,multicenter studies to further enhance the clinical utility of these tools.

Objective:To explore the characteristics of systemic immune microenvironment during the progression of dextran sulfate sodium(DSS)-induced acute ulcerative colitis(UC)induced in mice by Mass cytometry(CyTOF).Methods:Male C57BL/6 mice were randomly divided into control group and model group.The control group was given normal drinking water for 15 d.The mouse in the model group were given 5%DSS in drinking water,which was changed to normal drinking water after 7 days.In the model group,peripheral blood was collected on days 4,9 and 15,respectively.CyTOF was used to detect the expressions of 33 immune cell markers and changes in cell subsets in peripheral blood of mice,and the characteristics of systemic immune microenvironment in mice with acute UC were analyzed.Results:The cluster analysis of 33 kinds of immune cell markers showed that CD45+cells in peripheral blood of mice with DSS induced acute UC were divided into 23 fine subgroups,among which the proportions of B cell subgroup,T cell subgroup and neutrophil subgroup showed significant changes.A further dimensional reduction cluster analysis of T cell subsets found significant differences in the composition and proportion of the 10 identified T cell subsets.Conclusion:The systemic immune micro-environment map of mice with acute UC induced by DSS has been successfully constructed,and heterogeneity has been found in the systemic immune microenvironment of mice with acute UC.The changes and activation degree of T cell subpopulations are closely re-lated to disease progression and inflammation level.The results of this study provide theoretical basis for assisting the diagnosis,moni-toring the risk,progression,treatment and prognosis of acute UC.

Objective To evaluate the recognition capability of AI-enabled Cellsee CS-BM1 automatic cell morphology analyzer for pe-ripheral blood smears and its roles in assisting manual classification,and explore the application value of AI system in the diagnosis network of tiered primary medical units.Methods The blood samples which triggered the re-examination rules were collected from six primary medical units,including the Laboratory Department of Shanghai Jiahui International Hospital,and so on,from March to No-vember 2023.The smears of peripheral blood were prepared and AI analyzer was used for pre-classification to evaluate its recognition performance in identifying the samples with abnormal WBC and RBC.The sensitivity,specificity,and accuracy of WBC classification by six junior and intermediate technicians,both with and without AI assistance,were analyzed.Additionally,the roles of the AI system in tiered diagnosis of primary medical units were also evaluated.Results The sensitivity,specificity,and accuracy of AI system in recognizing malignant primitive cells were 92.86％,95.16％,and 95.10％,respectively.The sensitivities of AI system in recognizing immature granulocytes,reactive lymphocytes,and nucleated RBCs were all greater than 90％.The sensitivity of AI system in identif-ying abnormal morphology of RBCs reached 99.59％,along with rapid quantitative analysis for various anomalous types of RBCs.In AI-assisted mode,the sensitivity of recognition for all cell types was improved to varying degrees by junior and intermediate technicians,and the sensitivity for recognizing malignant primitive cells,reactive lymphocytes,and immature granulocytes increased to 58.24％,53.39％,and 62.37％for junior technicians,and to 92.06％,83.24％,and 83.12％for intermediate technicians,respectively.The improvements for junior technicians were particularly significant,with increases of 12.46％,10.61％,and 3.71％for each cell type,respectively.Both groups achieved higher specificity and accuracy.Through AI pre-classification and manual review,a variety of pe-ripheral blood cell-related diseases were accurately diagnosed in the tiered healthcare practice of primary medical units,including 339 cases(11.13％)of red blood cell diseases,5 cases(0.16％)of platelet diseases,2 343 cases(76.90％)of infection-related disea-ses,and 28 cases(0.92％)of malignant hematological diseases.In addition,332 cases(10.90％)which lacked an obvious related cause or required further examinations were identified as well.Conclusion AI pre-classification has demonstrated strong cell recogni-tion capabilities and may assist technicians in improving the sensitivity,specificity,and accuracy of blood cell classification.AI could en-hance the disease-screening capabilities in the tiered diagnosis network of primary medical units,presenting a broad application prospect.

Digestive system tumors account for more than half of all malignant tumors in terms of incidence and mortality,and thus pose a serious threat to human health.Haptoglobin(Hp)is an acute-phase glycoprotein that is elevated in both plasma and tumor tissues in various clinical conditions,including different types of cancer,such as liver,gastric,colorectal,pancreatic,and gallbladder cancer.Numerous studies have indicated that Hp plays a significant role in the prognosis of cancer patients,highlighting its potential as a prognostic marker for gastrointestinal tumors,with important clinical applications.Despite its demonstrated crucial role in the development of various tumors,however,the specific mechanisms of Hp in gastrointestinal tumors remain controversial.This review considers the differential expression and clinical significance of Hp in the five major types of gastrointestinal tumors,to explore its role in different stages of cancer progression and prognosis.This review thus aims to provide reliable and accurate serum biomarkers for the screening,early diagnosis,treatment,and prognosis monitoring of gastrointestinal tumors,with important implications for predicting the survival and prognosis of cancer patients.

Objective To evaluate the recognition capability of AI-enabled Cellsee CS-BM1 automatic cell morphology analyzer for pe-ripheral blood smears and its roles in assisting manual classification,and explore the application value of AI system in the diagnosis network of tiered primary medical units.Methods The blood samples which triggered the re-examination rules were collected from six primary medical units,including the Laboratory Department of Shanghai Jiahui International Hospital,and so on,from March to No-vember 2023.The smears of peripheral blood were prepared and AI analyzer was used for pre-classification to evaluate its recognition performance in identifying the samples with abnormal WBC and RBC.The sensitivity,specificity,and accuracy of WBC classification by six junior and intermediate technicians,both with and without AI assistance,were analyzed.Additionally,the roles of the AI system in tiered diagnosis of primary medical units were also evaluated.Results The sensitivity,specificity,and accuracy of AI system in recognizing malignant primitive cells were 92.86％,95.16％,and 95.10％,respectively.The sensitivities of AI system in recognizing immature granulocytes,reactive lymphocytes,and nucleated RBCs were all greater than 90％.The sensitivity of AI system in identif-ying abnormal morphology of RBCs reached 99.59％,along with rapid quantitative analysis for various anomalous types of RBCs.In AI-assisted mode,the sensitivity of recognition for all cell types was improved to varying degrees by junior and intermediate technicians,and the sensitivity for recognizing malignant primitive cells,reactive lymphocytes,and immature granulocytes increased to 58.24％,53.39％,and 62.37％for junior technicians,and to 92.06％,83.24％,and 83.12％for intermediate technicians,respectively.The improvements for junior technicians were particularly significant,with increases of 12.46％,10.61％,and 3.71％for each cell type,respectively.Both groups achieved higher specificity and accuracy.Through AI pre-classification and manual review,a variety of pe-ripheral blood cell-related diseases were accurately diagnosed in the tiered healthcare practice of primary medical units,including 339 cases(11.13％)of red blood cell diseases,5 cases(0.16％)of platelet diseases,2 343 cases(76.90％)of infection-related disea-ses,and 28 cases(0.92％)of malignant hematological diseases.In addition,332 cases(10.90％)which lacked an obvious related cause or required further examinations were identified as well.Conclusion AI pre-classification has demonstrated strong cell recogni-tion capabilities and may assist technicians in improving the sensitivity,specificity,and accuracy of blood cell classification.AI could en-hance the disease-screening capabilities in the tiered diagnosis network of primary medical units,presenting a broad application prospect.

Colorectal cancer(CRC)is one of the most common malignant life-threatening tumors,with serious impacts on patient quality of life.Src homology 2 domain-containing protein tyrosine phosphatase(SHP2)has recently become a hot topic in the field of cancer research,and has demonstrated a close relationship with CRC.SHP2,encoded by the PTPN11 gene,is a non-receptor tyrosine kinase commonly present in various tissues and cells of the human body.Existing research shows that SHP2 plays a crucial role in regulating CRC and colitis-associated colon cancer(CAC),and the emergence of SHP2 allosteric inhibitors has identified SHP2 as a potential new therapeutic target for patients with CRC.Here we review the structure of SHP2 and its roles in CRC and CAC.

Colorectal cancer stands as a leading cause of cancer-related morbidity and mortality globally,with liver metastases being a significant determinant of patient prognosis.Conventional diagnostic methods,includ-ing imaging studies and biomarker testing,frequently exhibit inadequate sensitivity and specificity,underscoring the necessity for more advanced technologies.Recent advancements in genomics,transcriptomics,proteomics,me-tabolomics,and epigenomics have revolutionized our understanding of the biological mechanisms driving colorectal cancer.These methodologies enable comprehensive analyses of genetic mutations,gene expression profiles,protein modifications,and metabolic reprogramming,all of which are pivotal to the metastatic process.This article high-lights the advanced capabilities of artificial intelligence(AI)technologies in processing complex multi-omics data,thereby enhancing diagnostic accuracy and supporting personalized treatment strategies.It also addresses the challenges AI encounters in multi-omics analyses,such as ensuring data quality,improving model interpretability,and facilitating clinical translation.Additionally,it explores the potential integration of emerging technologies like single-cell sequencing and spatial omics into large-scale,multicenter studies to further enhance the clinical utility of these tools.

Colorectal cancer(CRC)is one of the most common malignant life-threatening tumors,with serious impacts on patient quality of life.Src homology 2 domain-containing protein tyrosine phosphatase(SHP2)has recently become a hot topic in the field of cancer research,and has demonstrated a close relationship with CRC.SHP2,encoded by the PTPN11 gene,is a non-receptor tyrosine kinase commonly present in various tissues and cells of the human body.Existing research shows that SHP2 plays a crucial role in regulating CRC and colitis-associated colon cancer(CAC),and the emergence of SHP2 allosteric inhibitors has identified SHP2 as a potential new therapeutic target for patients with CRC.Here we review the structure of SHP2 and its roles in CRC and CAC.

Objective:To enhance the understanding of clinical doctors on the concurrence of Sj?gren′s syndrome (SS) and myasthenia gravis (MG), provide reference forclinical diagnosis and treatment.Methods:The medical record of SS、MG patient Taian Central hospital in october 2021 was reviewed and a retrospective analysis was conducted. Based on the key words, the main databases domestic and abroad from Jan 1973 to April 2024. The cases reported in the literature were searched out and merged with our case and analyzed by SPSS 27.0. The measurement data of normal distribution were expressed by mean standard deviation ± s, and the measurement data of abnormal distribution were expressed by M( Q1, Q3). Counting data were expressed as examples and percentages (%) . Results:Twenty-one patients with SS complicated with MG were reviewed. Among them, 19(90.5%) patients were female. The average age was (47.6 ± 3.1) years, and the median time from onset to diagnosis was 24 (11, 78) months. There were 11 patients (52.4%) with myasthenia gravis as the initial presentation. The main clinical manifestations of patients with myasthenia muscle fatigue (80.9%, 17/21), gravis include fatigue ptosis (71.4%, 15/21), diplopia, blurred vision (57.1%, 12/21), dysphagia (33.3%, 7/21), joint pain (33.3%, 7/21), odysarthria, and unclear speech (23.8%, 5/21), hair loss (14.3%, 3/21), and swelling of the excocrine glands(9.5%, 2/21). Eighteen patients (85.7%, 18/21) showed positive anti acetylcholine receptor antibodies. Sixteen patients (76.2%) were positive for ANA, and 14 patients (66.8%) were positive for anti SSA or (and) anti SSB antibodies. Four patients (19.0%) also had other autoimmune diseases (Hashimoto′s thyroiditis, rheumatoid arthritis, optic neuritis). In terms of treatment, cholinesterase inhibitors were the most common treatment measure, applied to 18 patients (85.7%), followed by glucocorticoid therapy, and applied to 14 patients (66.8%). In addition, 7 patients (33.3%) received immunosuppressive agents therapy, 5 patients (23.8%) underwent thymectomy, 2 patients (9.5%) received intravenous human immunoglobulin injection, and 1 patient (4.8%) underwent plasma exchange. All patients showed improvement after treatment.Conclusion:SS and MG are both autoimmune diseases, and their coexistence is rare. Clinicans should be aware of this rare association. Early diagnosis is crucial for the treatment and prognosis of patients,and requiresa comprehensive assessment of clinical symptoms, laboratory tests, and auto-antibody test results.

Objective:To explore the characteristics of systemic immune microenvironment during the progression of dextran sulfate sodium(DSS)-induced acute ulcerative colitis(UC)induced in mice by Mass cytometry(CyTOF).Methods:Male C57BL/6 mice were randomly divided into control group and model group.The control group was given normal drinking water for 15 d.The mouse in the model group were given 5%DSS in drinking water,which was changed to normal drinking water after 7 days.In the model group,peripheral blood was collected on days 4,9 and 15,respectively.CyTOF was used to detect the expressions of 33 immune cell markers and changes in cell subsets in peripheral blood of mice,and the characteristics of systemic immune microenvironment in mice with acute UC were analyzed.Results:The cluster analysis of 33 kinds of immune cell markers showed that CD45+cells in peripheral blood of mice with DSS induced acute UC were divided into 23 fine subgroups,among which the proportions of B cell subgroup,T cell subgroup and neutrophil subgroup showed significant changes.A further dimensional reduction cluster analysis of T cell subsets found significant differences in the composition and proportion of the 10 identified T cell subsets.Conclusion:The systemic immune micro-environment map of mice with acute UC induced by DSS has been successfully constructed,and heterogeneity has been found in the systemic immune microenvironment of mice with acute UC.The changes and activation degree of T cell subpopulations are closely re-lated to disease progression and inflammation level.The results of this study provide theoretical basis for assisting the diagnosis,moni-toring the risk,progression,treatment and prognosis of acute UC.