The role of mouse strain differences in the susceptibility to fibrosis: a systematic review
Bibliographic record
Abstract
In humans, a number of genetic factors have been linked to the development of fibrosis in a variety of different organs. Seeking a wider understanding of this observation in man is ethically important. There is mounting evidence suggesting that inbred mouse strains with different genetic backgrounds demonstrate variable susceptibility to a fibrotic injury. We performed a systematic review of the literature describing strain and organ specific response to injury in order to determine whether genetic susceptibility plays a role in fibrogenesis. Data were collected from studies that were deemed eligible for analysis based on set inclusion criteria, and findings were assessed in relation to strain of mouse, type of injury and organ of investigation. A total of 44 studies were included covering 21 mouse strains and focusing on fibrosis in the lung, liver, kidney, intestine and heart. There is evidence that mouse strain differences influence susceptibility to fibrosis and this appears to be organ specific. For instance, C57BL/6J mice are resistant to hepatic, renal and cardiac fibrosis but susceptible to pulmonary and intestinal fibrosis. However, BALB/c mice are resistant to pulmonary fibrosis but susceptible to hepatic fibrosis. Few studies have assessed the effect of the same injury stimulus in different organ systems using the same strains of mouse. Such mouse strain studies may prove useful in elucidating the genetic as well as epigenetic factors in humans that could help determine why some people are more susceptible to the development of certain organ specific fibrosis than others.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".