Purpose This study aimed to investigate the expression and clinical significance of TLDC2 in colorec-tal adenocarcinoma.Methods Data from the human protein atlas(HPA)and the cancer genome atlas(TCGA)indi-cated that TLDC2 was highly expressed in colorectal adenocarcinoma.We further analyzed the expression of TLDC2 in 400 colorectal adenocarcinomas and 447 other solid tumors using tissue microarrays and immunohistochemical(IHC)staining.Result The positive expression rate of TLDC2 was significantly higher than that of SATB2 in colorectal ade-nocarcinomas(96.5％vs 87.0％,P＜0.000 1).TLDC2 positivity exceeded that of SATB2 in both low-or high-grade colorectal adenocarcinoma(99.4％vs 88.7％,P＜0.000 1;83.3％vs 79.2％,P=0.669 9).In addition,the expression of TLDC2 and SATB2 was evaluated in 447 cases of other types of solid tumors.TLDC2 was expressed in neuroendocrine tumors as well as in gastric and appendiceal adenocarcinomas,whereas SATB2 was detected in a small number of melanomas,ovarian cancers,breast cancers and gallbladder cancers.The positive and specificity of TLDC2 for colorectal adenocarcinoma were 97％(95％CI=0.94-0.98)and 85％(95％CI=0.81-0.88),respectively.Combined detection of TLDC2 and SATB2 yielded a sensitivity of 96％(95％CI=0.93-0.97)and a specificity of 93％(95％CI=0.90-0.95).Conclusion Analysis of large-scale datasets and IHC staining demonstrated that TLDC2 is a highly sensitive and specific biomarker for colorectal adenocarcinoma.

Alzheimer's disease(AD),a neurodegenerative disorder,manifests pathological changes in the brain even during the asymptomatic stage.As the pathological burden intensifies,patients experience functional decline in multiple cognitive domains,including memory,language,spatial perception,executive function,and calculation,and may also exhibit emotional abnormalities.Once AD progresses,treatment becomes extremely chal-lenging.Therefore,early diagnosis and accurate prediction of disease conversion are core tasks in the prevention and treatment of AD,and they are also urgent scientific research challenges to be overcome.Deep learning(DL)models demonstrate considerable advantages in the diagnosis,prediction,classification,and feature extraction of AD,offering new hope for solving this challenging problem.This research commences with a concise introduction to the outcomes of AD and the fundamental knowledge of deep learning.Subsequently,it offers an overview of the imaging studies on the utilization of deep learning for predicting disease transformation from two perspectives.Firstly,it systematically summarizes the existing DL models that have demonstrated innovation in the classification and prediction performance of AD.Secondly,it provides a comprehensive outline of the DL fusion models applied to the diagnosis,classification,and prediction of AD.Finally,this paper expounds upon the impending challenges in the research of this domain.This article demonstrates that deep learning models is cutting-edge trends in the ex-ploration of AD research.

Alzheimer's disease(AD),a neurodegenerative disorder,manifests pathological changes in the brain even during the asymptomatic stage.As the pathological burden intensifies,patients experience functional decline in multiple cognitive domains,including memory,language,spatial perception,executive function,and calculation,and may also exhibit emotional abnormalities.Once AD progresses,treatment becomes extremely chal-lenging.Therefore,early diagnosis and accurate prediction of disease conversion are core tasks in the prevention and treatment of AD,and they are also urgent scientific research challenges to be overcome.Deep learning(DL)models demonstrate considerable advantages in the diagnosis,prediction,classification,and feature extraction of AD,offering new hope for solving this challenging problem.This research commences with a concise introduction to the outcomes of AD and the fundamental knowledge of deep learning.Subsequently,it offers an overview of the imaging studies on the utilization of deep learning for predicting disease transformation from two perspectives.Firstly,it systematically summarizes the existing DL models that have demonstrated innovation in the classification and prediction performance of AD.Secondly,it provides a comprehensive outline of the DL fusion models applied to the diagnosis,classification,and prediction of AD.Finally,this paper expounds upon the impending challenges in the research of this domain.This article demonstrates that deep learning models is cutting-edge trends in the ex-ploration of AD research.

Lipoprotein X(LpX)is an atypical lipoprotein that abnormally accumulates in the plasma of patients with cholestatic liver disease,and it is also a major pathogenic factor for hypercholesterolemia.The formation of LpX is closely associated with the abnormal metabolism of free cholesterol,phospholipids,and other lipid components in bile.LpX cannot be cleared via the low-density lipoprotein receptor pathway and is mainly metabolized by the reticuloendothelial system.The abnormal accumulation of LpX is closely associated with various complications of cholestatic liver disease,including xanthoma and neuropathy.Although there is no significant correlation between the high level of LpX and the risk of atherosclerosis,the role of LpX in cholesterol metabolism disorders cannot be neglected.Due to the similarities in density and characteristics between LpX and low-density lipoprotein cholesterol,clinical testing may result in misdiagnosis and related treatment risks.Current studies mainly focus on the mechanisms of LpX formation,the clinical significance of LpX,related detection methods,and potential therapeutic strategies.Plasma exchange is considered the preferred treatment in the state of high LpX,while traditional lipid-lowering drugs have a limited effect on LpX.This article explores the formation and clearance mechanisms of LpX in cholestatic liver disease,along with its impact of cholestatic liver disease and related detection methods,in order to improve the understanding of the pathophysiology and clinical significance of LpX,provide new strategies for the management of cholestatic liver disease and its complications,and finally improve the prognosis of patients.

The grade of histological severity is a determining factor to evaluate the prognosis and survival rate in primary biliary cholangitis (PBC). However, liver biopsy is limited by sampling error, invasiveness, high cost, and poor compliance. Therefore, in order to overcome the limitations of liver biopsy, some non-invasive evaluation methods have been studied and applied to evaluate the progression of liver fibrosis in PBC. The prognostic score can be calculated using routine laboratory test results obtained at the time of diagnosis, which are characterized by their simplicity, affordability, ease of acquisition, and superior reproducibility. Recent studies have reported that the prognostic score can be employed as a non-invasive liver fibrosis model to diagnose the liver fibrosis stage in PBC and predict the transplant-free survival rate, in addition to being used to evaluate the patient prognosis and transplant-free survival (TFS). This paper reviews, summarizes, and explores the research progress of different prognostic scores as non-invasive liver fibrosis models via their diagnostic performance and predictive accuracy for PBC.

Lipoprotein X(LpX)is an atypical lipoprotein that abnormally accumulates in the plasma of patients with cholestatic liver disease,and it is also a major pathogenic factor for hypercholesterolemia.The formation of LpX is closely associated with the abnormal metabolism of free cholesterol,phospholipids,and other lipid components in bile.LpX cannot be cleared via the low-density lipoprotein receptor pathway and is mainly metabolized by the reticuloendothelial system.The abnormal accumulation of LpX is closely associated with various complications of cholestatic liver disease,including xanthoma and neuropathy.Although there is no significant correlation between the high level of LpX and the risk of atherosclerosis,the role of LpX in cholesterol metabolism disorders cannot be neglected.Due to the similarities in density and characteristics between LpX and low-density lipoprotein cholesterol,clinical testing may result in misdiagnosis and related treatment risks.Current studies mainly focus on the mechanisms of LpX formation,the clinical significance of LpX,related detection methods,and potential therapeutic strategies.Plasma exchange is considered the preferred treatment in the state of high LpX,while traditional lipid-lowering drugs have a limited effect on LpX.This article explores the formation and clearance mechanisms of LpX in cholestatic liver disease,along with its impact of cholestatic liver disease and related detection methods,in order to improve the understanding of the pathophysiology and clinical significance of LpX,provide new strategies for the management of cholestatic liver disease and its complications,and finally improve the prognosis of patients.

Visfatin,also known as nicotinamide phosphoribosyl transferase(NAMPT)or pre-B-cell colony-enhancing factor,is a proinflam-matory adipokine.Its immunomodulatory effects are closely associated with its pro-inflammatory activity,influencing the secretion of vari-ous cytokines and the function of immune cells.Visfatin exerts pro-tumorigenic effects in most cancers.The tumor immune microenviron-ment(TIME)comprises immune cells within the tumor tissue and an array of secreted cytokines.Growing evidence suggests that visfatin plays a regulatory role in the TIME by promoting inflammatory responses and modulating the polarization of immune cells,their secretory functions,surface protein expression,and energy metabolism,thereby influencing cancer progression.These newly discovered mechanisms provide a critical foundation for the application of NAMPT inhibitors(NAMPTi)in cancer immunotherapy.This review summarizes recent ad-vances in understanding the role of visfatin in tumor immunology and explores the therapeutic potential of NAMPTi in oncology.

Purpose This study aimed to investigate the expression and clinical significance of TLDC2 in colorec-tal adenocarcinoma.Methods Data from the human protein atlas(HPA)and the cancer genome atlas(TCGA)indi-cated that TLDC2 was highly expressed in colorectal adenocarcinoma.We further analyzed the expression of TLDC2 in 400 colorectal adenocarcinomas and 447 other solid tumors using tissue microarrays and immunohistochemical(IHC)staining.Result The positive expression rate of TLDC2 was significantly higher than that of SATB2 in colorectal ade-nocarcinomas(96.5％vs 87.0％,P＜0.000 1).TLDC2 positivity exceeded that of SATB2 in both low-or high-grade colorectal adenocarcinoma(99.4％vs 88.7％,P＜0.000 1;83.3％vs 79.2％,P=0.669 9).In addition,the expression of TLDC2 and SATB2 was evaluated in 447 cases of other types of solid tumors.TLDC2 was expressed in neuroendocrine tumors as well as in gastric and appendiceal adenocarcinomas,whereas SATB2 was detected in a small number of melanomas,ovarian cancers,breast cancers and gallbladder cancers.The positive and specificity of TLDC2 for colorectal adenocarcinoma were 97％(95％CI=0.94-0.98)and 85％(95％CI=0.81-0.88),respectively.Combined detection of TLDC2 and SATB2 yielded a sensitivity of 96％(95％CI=0.93-0.97)and a specificity of 93％(95％CI=0.90-0.95).Conclusion Analysis of large-scale datasets and IHC staining demonstrated that TLDC2 is a highly sensitive and specific biomarker for colorectal adenocarcinoma.

Visfatin,also known as nicotinamide phosphoribosyl transferase(NAMPT)or pre-B-cell colony-enhancing factor,is a proinflam-matory adipokine.Its immunomodulatory effects are closely associated with its pro-inflammatory activity,influencing the secretion of vari-ous cytokines and the function of immune cells.Visfatin exerts pro-tumorigenic effects in most cancers.The tumor immune microenviron-ment(TIME)comprises immune cells within the tumor tissue and an array of secreted cytokines.Growing evidence suggests that visfatin plays a regulatory role in the TIME by promoting inflammatory responses and modulating the polarization of immune cells,their secretory functions,surface protein expression,and energy metabolism,thereby influencing cancer progression.These newly discovered mechanisms provide a critical foundation for the application of NAMPT inhibitors(NAMPTi)in cancer immunotherapy.This review summarizes recent ad-vances in understanding the role of visfatin in tumor immunology and explores the therapeutic potential of NAMPTi in oncology.

The grade of histological severity is a determining factor to evaluate the prognosis and survival rate in primary biliary cholangitis (PBC). However, liver biopsy is limited by sampling error, invasiveness, high cost, and poor compliance. Therefore, in order to overcome the limitations of liver biopsy, some non-invasive evaluation methods have been studied and applied to evaluate the progression of liver fibrosis in PBC. The prognostic score can be calculated using routine laboratory test results obtained at the time of diagnosis, which are characterized by their simplicity, affordability, ease of acquisition, and superior reproducibility. Recent studies have reported that the prognostic score can be employed as a non-invasive liver fibrosis model to diagnose the liver fibrosis stage in PBC and predict the transplant-free survival rate, in addition to being used to evaluate the patient prognosis and transplant-free survival (TFS). This paper reviews, summarizes, and explores the research progress of different prognostic scores as non-invasive liver fibrosis models via their diagnostic performance and predictive accuracy for PBC.