Mouse Model for Liver Failure (LF) Mus musculus (Mouse) Disease model

Hepatic failure

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Overview
Properties
  • Prototype SpeciesHuman
  • Sourceinduced by carbon tetrachloride
  • Model Animal StrainsBalb/c Mice(SPF), healthy, male, age: 8~10weeks, body weight:30g~35g.
  • Modeling GroupingRandomly divided into six group: Control group, Model group, Positive drug group and Test drug group.
  • Modeling Period12~14 weeks
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  • Mouse Model for Liver Failure (LF) Packages (Simulation)
  • Mouse Model for Liver Failure (LF) Packages (Simulation)
  • DSI556Mu03.jpg Picture
  • Certificate ISO9001: 2008, ISO13485: 2003 Registered

Modeling Method

Modeling method:

Establishment of chronic liver injury model in mice: BALB/ C mice, male, random grouping. Except for normal control group, other mice were intraperitoneally injected 20% CCl4 oil solution (5mL /kg) twice a week for 12 weeks. D-Gal (1g/kg) and LPS (10ug/kg) were intraperitoneally injected after 12 weeks of administration for 3 days.

Intervention administration: TSA (Trichostatin A), sodium n-butyrate, NF-κB inhibitor (PDTC) were administered respectively.

Model evaluation

After modeling, the mice in each group were sacrificed, and the blood was collected and the serum was separated for biochemical detection. Liver and intestinal tissues were collected for pathological examination.

1. Serum biochemical indexes ALT and AST were detected;

2. Liver tissue was taken, fixed, dehydrated and embedded, and paraffin section was prepared.

HE staining and TUNEL fluorescence staining were performed respectively.

3. Intestinal tissue was taken for HE staining.

Intestinal tissue (small intestine) was taken, fixed and embedded, paraffin section prepared, HE staining.

4. Serum was separated and the levels of HMGB1, TNF-α and IL-18 in each group were detected by ELISA.

Pathological results

Cytokines level

The levels of HMGB1, TNF-α and IL-18 in serum samples were detected by ELISA.

Statistical analysis

SPSS software is used for statistical analysis, measurement data to mean ± standard deviation (x ±ｓ), using t test and single factor analysis of variance for group comparison , P<0.05 indicates there was a significant difference, P<0.01 indicates there are very significant differences.

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