Building resilient health systems in Africa beyond the COVID-19 pandemic response
Bibliographic record
Abstract
The inflammatory effects of IL-1α/β are controlled by IL-1R antagonist (IL-1Ra). One IL-1Ra isoform is secreted, whereas three other isoforms (intracellular IL-1Ra [icIL-1Ra] 1, 2, and 3) are supposed to remain intracellular because of the absence of a signal peptide. In contrast to the well-characterized function of the secreted isoform, the biological role of the intracellular isoforms remains largely unclear. icIL-1Ra1 represents the major isoform in keratinocytes. We created icIL-1Ra1−/− mice and investigated the role of icIL-1Ra1 in Aldara (5% imiquimod)-induced psoriasis-like skin inflammation. Naive icIL-1Ra1−/− mice bred habitually and exhibited a normal phenotype. icIL-1Ra1 deficiency aggravated Aldara-induced skin inflammation, as demonstrated by increased ear thickness and increased mRNA levels of key proinflammatory cytokines. No intracellular effect of icIL-1Ra1 could be detected in isolated keratinocytes using RNA-sequencing analysis; however, Aldara treatment led to caspase 1/11-, caspase 8-, and RIPK3-independent keratinocyte cell death accompanied by the release of both icIL-1Ra1 and IL-1α. Furthermore, blocking IL-1α attenuated the clinical severity of Aldara-induced ear thickening in icIL-1Ra1−/− mice. Our data suggest that upon keratinocyte damage icIL-1Ra1 acts extracellularly as an antagonist of the alarmin IL-1α to immediately counteract its inflammatory effects.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".