Activating KIR genes act as risk factors for Crohn’s Disease (93.34)
Bibliographic record
Abstract
Abstract Activating Killer-cell Immunoglobulin-like Receptor (KIR) genes constitute a subset of KIR family. The genes are expressed as activating receptors on the surface of NK cells as well as on a subset of T cells. The receptors interact with poorly defined ligands and decrease the activation threshold of these cells. Overall, they increase immune reactivity of the individuals. The activating KIR genes, like other KIR genes, are highly polymorphic. Furthermore, KIR haplotypes differ from each other with respect to the number of activating genes. Some haplotypes have no activating genes while others may carry upto seven such genes. Consequently, humans differ from each other with respect to the number of inherited activating KIR genes. Activating KIR genes have been associated with autoimmune diseases. However, little is known about their association with Crohn’s Disease. We have investigated the potential association of these genes with this disease in Canadian children of the French origin. Our results show that these genes act as risk factors for developing CD in these children. An increased number of inherited activating KIR genes correspondingly increased the risk for the disease. These results were also replicated in the Canadian (Caucasian) children of non-French origin. Collectively, our results suggest that activating KIR genes act as risk factors in developing CD in humans. The study was supported by the Crohn’s and Colitis Foundation of Canada (CCFC)
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".