Bibliographic record
Abstract
BACKGROUND: Sarcoidosis is a systemic granulomatous disorder of unknown origin. Lymphocytic inflammation is dominated by expression of Th1 type cytokines such as tumour necrosis factor alpha (TNFalpha). Interleukin 13 (IL-13) is a Th2 cytokine which is expressed by CD4+ T cells and has been shown to suppress TNFalpha in human blood monocytes. The role of IL-13 as a possible anti-inflammatory cytokine in sarcoidosis was investigated. METHODS: mRNA expression of IL-13, IL-4, IL-10, and TNFalpha in bronchoalveolar lavage (BAL) fluid cells and peripheral mononuclear blood cells (PBM) of 18 patients with sarcoidosis and nine healthy controls was assessed using RT-PCR. In addition, IL-13 protein levels in BAL cell culture supernatants from 12 patients and all controls were measured and immunocytochemistry of IL-13 protein was performed in BAL fluid cells of eight patients. TNFalpha concentrations were measured with and without stimulation with recombinant human (rh) IL-13, rhIL-10, and lipopolysaccharide (LPS). RESULTS: IL-13 mRNA expression was significantly increased in BAL cells and PBM of patients compared with controls (p<0.05). No significant difference was found in IL-4 mRNA or IL-10 mRNA expression in BAL fluid cells or PBM between the two groups. TNFalpha mRNA expression was significantly higher in BAL fluid cells of patients than controls (p<0.05). IL-13 protein levels in BAL cell culture supernatants were slightly raised in half the patients investigated but in only two controls. Immunocytochemistry detected IL-13 protein in alveolar macrophages of patients. IL-13 led to decreased TNFalpha concentrations (p<0.05). CONCLUSIONS: IL-13 expression is increased in BAL cells and PBM in sarcoidosis and IL-13 is secreted from BAL cells. Alveolar macrophages may be the cellular source. These data suggest that IL-13 might have an anti-inflammatory effect by acting on TNFalpha.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".