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A Voluntary Oral Ethanol‐Feeding Rat Model Associated With Necroinflammatory Liver Injury

2008· article· en· W2048278498 on OpenAlexaff
George L. Tipoe, Emily C. Liong, Carol A. Casey, Terrence M. Donohue, Patricia K. Eagon, Henry So, Tung Ming Leung, Franz Fogt, Amin A. Nanji

Bibliographic record

VenueAlcoholism Clinical and Experimental Research · 2008
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsDalhousie University
FundersNational Institute on Alcohol Abuse and AlcoholismNational Institutes of HealthU.S. Department of Veterans Affairs
KeywordsEthanolLiver injuryMedicineInternal medicineChemistryBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: The intragastric (IG) ethanol infusion model results in fatty liver, necrosis, inflammation and fibrosis. This model was utilized to study the pathogenesis of alcoholic liver disease (ALD). Disadvantages of the IG model include maintenance of the animals and equipment expense. To develop a voluntary feeding model for ALD, we took advantage of two important observations in the IG model: (i) female rats demonstrate greater severity of alcohol-induced liver injury than males and (ii) rats fed fish oil as a source of fatty acids develop more severe alcoholic liver injury than rats fed other fatty acids with ethanol. METHODS: Female Wistar rats (205 to 220 g) were fed for 8 weeks a diet containing 8% ethanol, fish oil (30% of calories), protein, and dextrose. Pair-fed controls (FD) received dextrose in amounts isocaloric to ethanol. The following measurements were made: liver pathology [fatty liver (0 to 4), necrosis, inflammation and fibrosis by Sirius Red], endotoxin and alanine aminotransferase (ALT) in plasma, urine ethanol, lipid peroxidation, nuclear factor kappa-B (NF-kappaB) and mRNA levels for tumor necrosis factor-alpha (TNF-alpha), cyclooxygenase-2 (COX-2), and inducible nitric oxide synthase (iNOS). Protein levels for iNOS and nitrotyrosine were evaluated by immunohistochemistry and Western Blot analysis. Liver proteasome and cytochrome P450 2E1 activity and protein levels of asialoglycoprotein receptor (ASGPR) were also evaluated. In addition, mRNA levels of fibrogenic markers were assessed. RESULTS: All animals lost weight for the initial 2 to 3 weeks but then gained weight until killing at 8 weeks. There was, however, a significant difference (p < 0.05) in weight between the ethanol-fed (Etoh) and (FD) groups at the end of the experiment. The mean urine ethanol levels ranged between 190 and 240 mg/dl. The severity of pathological changes was greater (p < 0.01) in Etoh vs. FD: fatty liver, 3.0 +/- 1.2 vs. 1.2 +/- 0.4; necrosis (foci/mm(2)), 3.9 +/- 2.3 vs. 0.4 +/- 0.3; inflammation (cells/mm(2)), 19.0 +/- 6.3 vs. 1.8 +/- 0.6. Centrilobular collagen deposition (% area), assessed by Sirius Red staining, was greater in Etoh vs. FD. Levels of endotoxin, ALT, CYP2E1 and lipid peroxidation markers were also higher (p < 0.01) in Etoh vs. FD. Levels of NF-kappaB and mRNA of pro-inflammatory mediators (TNF-alpha, COX-2, iNOS) and procollagen-I were increased (p < 0.05) in ethanol-fed rats. Immunohistochemical analysis showed more intense staining for both iNOS and nitrotyrosine in the centrilobular areas in the Etoh vs. FD groups. The greater area of positive staining for iNOS and nitrotyrosine in Etoh vs. FD was confirmed by Western Blot analysis. An increase in the expression of mRNA for profibrogenic genes (p < 0.05) was seen in ethanol-fed rats. CONCLUSIONS: A voluntary feeding regimen consisting of fish oil and ethanol in female rats is technically less demanding yet produces pathological and biochemical changes similar to those observed with the IG model. Pathological changes include fatty liver, necrosis and inflammation. Increased NF-kappaB and mRNA and protein levels of the pro-inflammatory mediators TNF-alpha, COX-2 and iNOS, coincided with the presence of necroinflammatory changes. The voluntary feeding regimen is proposed as an alternative to the IG model in the study of alcoholic liver injury.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.407
GPT teacher head0.517
Teacher spread0.110 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations45
Published2008
Admission routes1
Has abstractyes

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