Estrogen Deficiency Potentiates Thioacetamide-Induced Hepatic Fibrosis in Sprague-Dawley Rats
Bibliographic record
Abstract
Hepatic fibrosis is characterized by persistent deposition of extracellular matrix proteins and occurs in chronic liver diseases. The aim of the present study is to investigate whether estrogen deficiency (ED) potentiates hepatic fibrosis in a thioacetamide (TAA)-treated rat model. Fibrosis was induced via intraperitoneal injection (i.p.) of TAA (150 mg/kg/day) for four weeks in ovariectomized (OVX) female, sham-operated female, or male rats. In TAA-treated OVX rats, the activities of serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and γ-glutamyl transferase (GGT) were significantly increased compared to those in TAA-treated sham-operated OVX rats or TAA-treated male rats. Furthermore, α-smooth muscle actin (α-SMA) expression was significantly increased compared to that in TAA-treated sham-operated rats. This was accompanied by the appearance of fibrosis biomarkers including vimentin, collagen-I, and hydroxyproline, in the liver of TAA-treated OVX rats. In addition, ED markedly reduced total glutathione (GSH) levels, as well as catalase (CAT) and superoxide dismutase (SOD) activity in TAA-treated OVX rats. In contrast, hepatic malondialdehyde (MDA) levels were elevated in TAA-treated OVX rats. Apoptosis significantly increased in TAA-treated OVX rats, as reflected by elevated p53, Bcl-2, and cleaved caspase 3 levels. Significant increases in interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) concentrations were exhibited in TAA-treated OVX rats, and this further aggravated fibrosis through the transforming growth factor-β (TGF-β)/Smad pathway. Our data suggest that ED potentiates TAA-induced oxidative damage in the liver, suggesting that ED may enhance the severity of hepatic fibrosis in menopausal women.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".