Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is a chronic autoimmune disease characterised by inflammation of the gastrointestinal tract. The pathogenesis of IBD is not fully understood and curative therapies are lacking. Consequently, development of robust intestine models, representative of the pathogenesis of IBD remains an unmet need. Thus, the overall aims of the studies presented in this thesis were to develop a number of models of small intestine including: genetically engineered murine model, epithelial cell culture models, and an intestinal stem cell organoid model which could reflect or be used to study the pathogenesis of IBD. Interleukin 1 (IL-1) is an important mediator of inflammation and tissue damage in IBD. The balance between IL-1 and IL-1Ra as a natural inhibitor plays a vital role in a variety of diseases. Here, this thesis investigated whether changes seen during IBD could be induced spontaneously by the removal of IL-1Ra in mice that lack a functional IL-1rn gene. Data presented from this thesis highlighted the importance of IL-1 in the pathogenesis of inflammatory bowel disease. In addition, the potential of L-pNIPAM hydrogel scaffolds, which were developed by the research team at Sheffield Hallam University, was utilised to develop long-term 3D co-cultures of layered Caco-2 and HT29-MTX cells under conditions representative of inflammation by treatment with IL-1β, TNFα, and hypoxia (1% O2) for 1 week was investigated. In vitro cell culture studies in this thesis have demonstrated that L-pNIPAM hydrogel supported long-term 3D co-culture model and stimulation with factors seen during inflammation recapitulated features of IBD. Finally, the potential of L-pNIPAM hydrogel scaffolds to develop 3D intestinal stem cell organoid model was investigated. The in vitro study demonstrated the ability of L-pNIPAM hydrogel as scaffold to support organoid formation and cell differentiation in vitro from small intestinal crypts and Lgr5+ stem cells isolated from mice.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".