Animal models to study acute and chronic intestinal inflammation in mammals
Bibliographic record
Abstract
Acute and chronic inflammatory diseases of the intestine impart a significant and negative impact on the health and well-being of human and non-human mammalian animals. Understanding the underlying mechanisms of inflammatory disease is mandatory to develop effective treatment and prevention strategies. As inflammatory disease etiologies are multifactorial, the use of appropriate animal models and associated metrics of disease are essential. In this regard, animal models used alone or in combination to study acute and chronic inflammatory disease of the mammalian intestine paired with commonly used inflammation-inducing agents are reviewed. This includes both chemical and biological incitants of inflammation, and both non-mammalian (i.e. nematodes, insects, and fish) and mammalian (i.e. rodents, rabbits, pigs, ruminants, dogs, and non-human primates) models of intestinal inflammation including germ-free, gnotobiotic, as well as surgical, and genetically modified animals. Importantly, chemical and biological incitants induce inflammation via a multitude of mechanisms, and intestinal inflammation and injury can vary greatly according to the incitant and animal model used, allowing studies to ascertain both long-term and short-term effects of inflammation. Thus, researchers and clinicians should be aware of the relative strengths and limitations of the various animal models used to study acute and chronic inflammatory diseases of the mammalian intestine, and the scope and relevance of outcomes achievable based on this knowledge. The ability to induce inflammation to mimic common human diseases is an important factor of a successful animal model, however other mechanisms of disease such as the amount of infective agent to induce disease, invasion mechanisms, and the effect various physiologic changes can have on inducing damage are also important features. In many cases, the use of multiple animal models in combination with both chemical and biological incitants is necessary to answer the specific question being addressed regarding intestinal disease. Some incitants can induce acute responses in certain animal models while others can be used to induce chronic responses; this review aims to illustrate the strengths and weaknesses in each animal model and to guide the choice of an appropriate acute or chronic incitant to facilitate intestinal disease.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".