Background: s/Aims: Anti-mitochondrial M2 antibody (AMA-M2) is a specific marker for primary biliary cholangitis (PBC) and it could be also present in non-PBC individuals. Methods: A total of 72,173 Chinese health check-up individuals tested AMA-M2, of which non-PBC AMA-M2 positive individuals were performed follow-up. Baseline data of both clinical characteristics and laboratory examinations were collected in all AMA-M2-positive individuals. Least absolute shrinkage and selection operator (LASSO) regression was performed to investigate the potential variables for developing PBC. Results: A total of 2,333 individuals were positive with AMA-M2. Eighty-two individuals had a medical history of PBC or fulfilled the diagnostic criteria of PBC at baseline, and 2,076 individuals were non-PBC. After a median follow-up of 6.6 years, 0.6% developed PBC, with an accumulative 5-year incidence rate of 0.5%. LASSO regression showed that levels of alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), immunoglobulin M (IgM), eosinophilia proportion (EOS%), gamma globulin percentage, and hemoglobin (HGB) were potential variables for developing PBC. Multivariate Cox regression is used to construct a predictive model based on 7 selected variables, and time-dependent receiver operating characteristic analysis showed that the area under the curve of the prediction model at 3, 5, and 10 years were, respectively, 1.000, 0.875, and 0.917. Conclusions This study offers insights into the onset of PBC among individuals who tested positive for AMA-M2 during routine health check-ups. The prediction model based on ALP, GGT, IgM, EOS%, gamma globulin percentage, HGB, and sex has a certain predictive ability for the occurrence of PBC in this population.

Background: s/Aims: Anti-mitochondrial M2 antibody (AMA-M2) is a specific marker for primary biliary cholangitis (PBC) and it could be also present in non-PBC individuals. Methods: A total of 72,173 Chinese health check-up individuals tested AMA-M2, of which non-PBC AMA-M2 positive individuals were performed follow-up. Baseline data of both clinical characteristics and laboratory examinations were collected in all AMA-M2-positive individuals. Least absolute shrinkage and selection operator (LASSO) regression was performed to investigate the potential variables for developing PBC. Results: A total of 2,333 individuals were positive with AMA-M2. Eighty-two individuals had a medical history of PBC or fulfilled the diagnostic criteria of PBC at baseline, and 2,076 individuals were non-PBC. After a median follow-up of 6.6 years, 0.6% developed PBC, with an accumulative 5-year incidence rate of 0.5%. LASSO regression showed that levels of alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), immunoglobulin M (IgM), eosinophilia proportion (EOS%), gamma globulin percentage, and hemoglobin (HGB) were potential variables for developing PBC. Multivariate Cox regression is used to construct a predictive model based on 7 selected variables, and time-dependent receiver operating characteristic analysis showed that the area under the curve of the prediction model at 3, 5, and 10 years were, respectively, 1.000, 0.875, and 0.917. Conclusions This study offers insights into the onset of PBC among individuals who tested positive for AMA-M2 during routine health check-ups. The prediction model based on ALP, GGT, IgM, EOS%, gamma globulin percentage, HGB, and sex has a certain predictive ability for the occurrence of PBC in this population.

Background: s/Aims: Anti-mitochondrial M2 antibody (AMA-M2) is a specific marker for primary biliary cholangitis (PBC) and it could be also present in non-PBC individuals. Methods: A total of 72,173 Chinese health check-up individuals tested AMA-M2, of which non-PBC AMA-M2 positive individuals were performed follow-up. Baseline data of both clinical characteristics and laboratory examinations were collected in all AMA-M2-positive individuals. Least absolute shrinkage and selection operator (LASSO) regression was performed to investigate the potential variables for developing PBC. Results: A total of 2,333 individuals were positive with AMA-M2. Eighty-two individuals had a medical history of PBC or fulfilled the diagnostic criteria of PBC at baseline, and 2,076 individuals were non-PBC. After a median follow-up of 6.6 years, 0.6% developed PBC, with an accumulative 5-year incidence rate of 0.5%. LASSO regression showed that levels of alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), immunoglobulin M (IgM), eosinophilia proportion (EOS%), gamma globulin percentage, and hemoglobin (HGB) were potential variables for developing PBC. Multivariate Cox regression is used to construct a predictive model based on 7 selected variables, and time-dependent receiver operating characteristic analysis showed that the area under the curve of the prediction model at 3, 5, and 10 years were, respectively, 1.000, 0.875, and 0.917. Conclusions This study offers insights into the onset of PBC among individuals who tested positive for AMA-M2 during routine health check-ups. The prediction model based on ALP, GGT, IgM, EOS%, gamma globulin percentage, HGB, and sex has a certain predictive ability for the occurrence of PBC in this population.

Immune thrombocytopenia (ITP) is a disease characterized by an imbalance between immune-mediated platelet destruction and production. Its clinical management has long been confronted with core challenges such as insufficient diagnostic specificity, significant individual differences in treatment response, and difficulties in prognosis assessment. In recent years, researches have systematically revealed the multi-dimensional pathological mechanisms of this disease: in terms of immunology, autoantibodies mediate platelet clearance, and the imbalance of T cell subsets exacerbates the disorder of immune homeostasis. Proteomic techniques have identified plasma markers such as matrix metallopeptidase 9 and CXCL11. Genomic studies have revealed that miR-199a-5p, lncRNA MALAT1, etc., are involved in the pathogenesis by regulating the immune-thrombopoiesis axis. Metabolism research has shown features such as lipid metabolism disorders, abnormal tryptophan pathways in the bone marrow, and excessive T cell glycolysis. Although multi-omics techniques have promoted the progress of biomarker research, the clinical translation of biomarkers is still limited by high heterogeneity, insufficient validation, and lack of standardization. In the future, it is expected that through the integration of multi-omics data and the development of artificial intelligence algorithms, combined with single-cell technologies to analyze the heterogeneity of the immune microenvironment, and multi-dimensional prediction models can be constructed to optimize precision diagnosis and treatment strategies.

Immune thrombocytopenia (ITP) is a disease characterized by an imbalance between immune-mediated platelet destruction and production. Its clinical management has long been confronted with core challenges such as insufficient diagnostic specificity, significant individual differences in treatment response, and difficulties in prognosis assessment. In recent years, researches have systematically revealed the multi-dimensional pathological mechanisms of this disease: in terms of immunology, autoantibodies mediate platelet clearance, and the imbalance of T cell subsets exacerbates the disorder of immune homeostasis. Proteomic techniques have identified plasma markers such as matrix metallopeptidase 9 and CXCL11. Genomic studies have revealed that miR-199a-5p, lncRNA MALAT1, etc., are involved in the pathogenesis by regulating the immune-thrombopoiesis axis. Metabolism research has shown features such as lipid metabolism disorders, abnormal tryptophan pathways in the bone marrow, and excessive T cell glycolysis. Although multi-omics techniques have promoted the progress of biomarker research, the clinical translation of biomarkers is still limited by high heterogeneity, insufficient validation, and lack of standardization. In the future, it is expected that through the integration of multi-omics data and the development of artificial intelligence algorithms, combined with single-cell technologies to analyze the heterogeneity of the immune microenvironment, and multi-dimensional prediction models can be constructed to optimize precision diagnosis and treatment strategies.

Objective To investigate the role of the renin-angiotensin system(RAS)in the pathogenesis of acute kidney injury(AKI)after laparoscopic radical nephrectomy(LRN)and the predictive value of RAS activation status for AKI.Methods Eighty-two patients undergoing LRN at the Third Medical Center of General Hospital of PLA from December,2023 to March,2024 were enrolled,including 57 with postoperative AKI and 25 without AKI according to KDIGO criteria.Blood and urine samples were collected from the patients before and at 24 h after the operation for analyzing the correlation of urinary aldosterone,plasma ACE2,Ang1-7,Nrf-2,and IL-10 levels with postoperative AKI.Univariate and multivariate logistic regression analyses and ROC curve were employed to identify the risk factors for postoperative AKI and their predictive value for AKI.Results Compared with those without postoperative AKI,the patients with AKI had significantly higher postoperative urinary aldosterone levels and lower plasma ACE 2,Ang 1-7,Nrf-2,and IL-10 levels(P<0.05).Postoperative urinary aldosterone level was positively correlated with AKI and negatively with estimated glomerular filtration rate(eGFR)(P<0.05);plasma levels of ACE 2,Nrf-2,and IL-10 were all negatively correlated with AKI and positively with eGFR.Urinary aldosterone was a risk factor and plasma ACE 2,Ang 1-7,Nrf-2 and IL-10 were protective factors for AKI,and among them urinary aldosterone was an independent risk factor(AUC=0.651)and plasma Nrf-2 was an independent protective factor(AUC=0.679).The unconventional RAS pathway indices had an AUC of 0.758,and aldosterone combined with the unconventional pathway indices had an AUC of 0.788 for predicting postoperative AKI.Conclusion Activation of the conventional RAS pathway and suppression of the unconventional pathway contribute to AKI following LRA possibly by affecting eGFR.Aldosterone combined with the unconventional pathway indicators can predict the occurrence of AKI after LRN.

Objective To investigate the role of the renin-angiotensin system(RAS)in the pathogenesis of acute kidney injury(AKI)after laparoscopic radical nephrectomy(LRN)and the predictive value of RAS activation status for AKI.Methods Eighty-two patients undergoing LRN at the Third Medical Center of General Hospital of PLA from December,2023 to March,2024 were enrolled,including 57 with postoperative AKI and 25 without AKI according to KDIGO criteria.Blood and urine samples were collected from the patients before and at 24 h after the operation for analyzing the correlation of urinary aldosterone,plasma ACE2,Ang1-7,Nrf-2,and IL-10 levels with postoperative AKI.Univariate and multivariate logistic regression analyses and ROC curve were employed to identify the risk factors for postoperative AKI and their predictive value for AKI.Results Compared with those without postoperative AKI,the patients with AKI had significantly higher postoperative urinary aldosterone levels and lower plasma ACE 2,Ang 1-7,Nrf-2,and IL-10 levels(P<0.05).Postoperative urinary aldosterone level was positively correlated with AKI and negatively with estimated glomerular filtration rate(eGFR)(P<0.05);plasma levels of ACE 2,Nrf-2,and IL-10 were all negatively correlated with AKI and positively with eGFR.Urinary aldosterone was a risk factor and plasma ACE 2,Ang 1-7,Nrf-2 and IL-10 were protective factors for AKI,and among them urinary aldosterone was an independent risk factor(AUC=0.651)and plasma Nrf-2 was an independent protective factor(AUC=0.679).The unconventional RAS pathway indices had an AUC of 0.758,and aldosterone combined with the unconventional pathway indices had an AUC of 0.788 for predicting postoperative AKI.Conclusion Activation of the conventional RAS pathway and suppression of the unconventional pathway contribute to AKI following LRA possibly by affecting eGFR.Aldosterone combined with the unconventional pathway indicators can predict the occurrence of AKI after LRN.