IL-10 and IL-10 Receptor Mutations in Very Early Onset Inflammatory Bowel Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Very early onset inflammatory bowel disease (VEO-IBD) is a unique disease entity with a complex genetic susceptibility in affected patients. Next-generation gene sequencing techniques have revealed various monogenetic mutations contributing to the pathogenesis of VEO-IBD, including interleukin 10 (IL-10) and IL-10 receptor (IL-10R) mutations. In this article, we reviewed the features of and effective therapeutic options for VEO-IBD with IL-10 and/or IL-10R mutations. The IL-10 signal pathway inhibits the release of several key cytokines and thereby has a significant anti-inflammatory effect in the gastrointestinal tract. Mutations of the genes encoding IL-10 and/or IL-10R have been detected in VEO-IBD patients among myriad populations throughout the world. VEO-IBD patients with IL-10 or IL-10R mutations often present with repeated bouts of bloody diarrhea, marked weight loss, growth retardation, and recurrent perianal problems, including abscesses, fistulas, and significant fissures. Moreover, some patients may have folliculitis and present with pulmonary infections. While the therapeutic efficacy of immunosuppressants is typically poor in these patients, allogeneic hematopoietic stem cell transplantation (HSCT) has been reported to improve symptoms significantly. However, the long-term prognosis of VEO-IBD patients with IL-10 or IL-10R gene mutations treated with HSCT requires further exploration to verify the efficacy and safety of this treatment. We concluded that clinicians should recognize the clinical phenotype of VEO-IBD, as mutational analysis of the IL-10 pathway can support the diagnosis and prompt early treatment of this complicated 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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it