BACKGROUND: Disrupted bile secretion leads to @entity409 characterized by @entity32 , @entity82 , eventually @entity82 , and @entity96 . As obstructive @entity1448 often progresses insidiously, markers for the diagnosis and staging of the disease are urgently needed. To this end, we compiled a comprehensive data set of serum markers, histological parameters and transcript profiles at 8 time points of disease progression after bile duct ligation (BDL) in @entity19 , aiming at identifying a set of parameters that could be used as robust biomarkers for transition of different disease progression phases. RESULTS: Statistical analysis of the more than 6,000 data points revealed distinct temporal phases of disease. Time course correlation analysis of biochemical, histochemical and mRNA transcript parameters (=factors) defined 6 clusters for different phases of disease progression. The number of @entity1612 -positive cells provided the most reliable overall measure for disease progression at histological level, @entity648 at biochemical level, and metalloproteinase inhibitor 1 ( @entity5779 ) at transcript level. Prominent molecular events exhibited by strong transcript peaks are found for the transcriptional regulator @entity55778 ( @entity55778 ) and @entity3873 24-hydroxylase ( @entity20593 ) at 6  h. Based on these clusters, we constructed a decision tree of factor combinations potentially useful as markers for different time intervals of disease progression. Best prediction for onset of disease is achieved by fibronectin ( @entity28135 ), for early disease phase by @entity21570 ( @entity21570 ), passage to perpetuation phase by @entity8334 ( @entity8334 ), and transition to the progression phase by @entity636 ( @entity636 ), with early and late progression separated by @entity8334 . Notably, these predictions remained stable even for randomly chosen small sub-sets of factors selected from the clusters. CONCLUSION: Our detailed time-resolved explorative study of liver homogenates following BDL revealed a well-coordinated response, resulting in disease phase dependent parameter modulations at morphological, biochemical, metabolic and gene expression levels. Interestingly, a small set of selected parameters can be used as diagnostic markers to predict disease stages in @entity19 with @entity409 .

Pathobiochemical signatures of @entity409 in bile duct ligated XXXX .

@entity32 :: ('MESH:D007249', 'Disease') :: ['inflammation'] @entity82 :: ('MESH:D005355', 'Disease') :: ['fibrosis', 'cirrhosis'] @entity96 :: ('MESH:D008113', 'Disease') :: ['hepatocellular cancer'] @entity19 :: ('10090', 'Species') :: ['mice'] @entity55778 :: ('23957(Tax:10090)', 'Gene') :: ['Nr0b2', 'Shp'] @entity648 :: ('MESH:D001663', 'Chemical') :: ['bilirubin'] @entity409 :: ('MESH:D008107', 'Disease') :: ['cholestatic liver disease', 'liver damage'] @entity5779 :: ('21857(Tax:10090)', 'Gene') :: ['Timp1'] @entity1612 :: ('14219(Tax:10090)', 'Gene') :: ['CTGF'] @entity3873 :: ('MESH:D002117', 'Chemical') :: ['1,25-dihydroxyvitamin D(3)'] @entity28135 :: ('14268(Tax:10090)', 'Gene') :: ['Fn1'] @entity21570 :: ('13077(Tax:10090)', 'Gene') :: ['Cyp1a2', 'Cytochrome P450 1A2'] @entity8334 :: ('12842(Tax:10090)', 'Gene') :: ['Col1a1', 'collagen1a-1'] @entity1448 :: ('MESH:D002779', 'Disease') :: ['cholestasis'] @entity20593 :: ('13081(Tax:10090)', 'Gene') :: ['Cyp24a1'] @entity636 :: ('16171(Tax:10090)', 'Gene') :: ['Il17a', 'interleukin 17-a']
@entity19 :: (10090,Species) :: ['mice']
