Increased sensitivity of Fancc-deficient hematopoietic cells to nitric oxide and evidence that this species mediates growth inhibition by cytokines
Bibliographic record
Abstract
Fanconi anemia complementation group C (Fancc)-deficient murine bone marrow progenitors demonstrate increased sensitivity to growth inhibition by interferon gamma (IFNgamma), tumor necrosis factor alpha (TNFalpha), and macrophage inflammatory protein 1alpha (MIP-1alpha). This property has been proposed as a possible pathogenic factor in the marrow failure seen in Fanconi anemia. Supporting our hypothesis that nitric oxide (NO) production might be a common effector in this sensitivity, we found that cytokine-mediated growth inhibition of Fancc(-/-) bone marrow cells was prevented by inhibiting NO synthase activity. Interestingly, Fancc(-/-) hematopoietic cells also exhibited increased growth inhibition on exposure to 2 distinct NO-generating agents, S-nitroso-N-acetyl-D, L-penicillamine (SNAP) and diethylenetriamine nitric oxide adduct (DETA/NO). In keeping with the sensitivity of Fancc(-/-) cells to IFNgamma, inducible nitric oxide synthase (iNOS) levels and nitrite release were both increased following stimulation of Fancc(-/-) macrophages with this cytokine, either alone or in combination with bacterial lipopolysaccharide. Suggesting a plausible mechanism for the increased expression of iNOS, IFNgamma-stimulated Fancc(-/-) macrophages generated higher levels of phospho-Stat1, a positive regulator of inos (nos2) gene expression. These observations, while confined to C57BL/6 Fancc(-/-) hematopoietic cells, raise the possibility that nitric oxide has a role in the pathogenesis of Fanconi anemia.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".