Dataset 1. The following raw data sets are provided as comma separated values (.csv) files:
Bibliographic record
Abstract
Background : Intestinal fibrosis represents a serious complication of inflammatory bowel diseases (IBD), often necessitating surgical resections. Myofibroblasts are primarily responsible for interstitial matrix accumulation in fibrotic diseases. However intestinal myofibroblasts (IMF) remain inadequately characterized. The aim was to examine fibroblast markers and fibrosis-associated gene expression in IMF isolated from resected intestine from IBD and control patients. As well as determining the effect of the fibrogenic cytokine TGFβ. Methods: Intestinal resections were obtained (n =35) from consenting patients undergoing elective surgery (2014-16). Primary cultures of IMF were isolated using DTT and EDTA and cultured. Viability and phenotypic characterization of IMF was carried out by flow cytometry and fluorescence microscopy. IMF (passages 3-8) were treated for 24 hours. Cytokines were quantified in IMF by real time PCR and in supernatants using the human pro-inflammatory cytokine panel Results : All markers and most fibrosis mediators studied were preferentially expressed by IMF compared to mucosal tissue. Metalloproteinases (MMP) 2 and 3, as well as their inhibitor TIMP1, are highly expressed by IMF. They also highly expressed inflammatory mediators, including IL-6, IL-8, CCL2 and PTGS2. Whereas mucosal expression of pro-inflammatory cytokines such as TNFα and IL-17 is increased in IBD, that of fibrosis mediators was not different. Fibrosis-related gene expression in IMF from IBD patients and controls was similar, but IMF from IBD expressed higher levels of several inflammatory genes. IMF from CD and UC had mostly similar expression profiles. TGFβ induced expression of fibrogenic genes αSMA, COL1A1, CTGF, FN1 and LOX. TGFβ-stimulated IMF released increased levels of IL-6, whereas IL-6, IL-8, as well as small amounts of IFN-γ and IL12p70 were produced following stimulation with IL-1β+IL-23. Conclusions : This study extends knowledge about the pathogenesis of fibrosis in IBD. Further research in the identification of mechanisms involved in IMF activation and fibrogenesis are required.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.084 | 0.115 |
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".