The role of SHIP1 in macrophage programming and activation
Bibliographic record
Abstract
The SHIP1 (SH2-containing inositol-5'-phosphatase 1) acts as a negative regulator of proliferation, survival and end cell activation in haemopoietic cells. It does so, at least in part, by translocating to membranes after extracellular stimulation and hydrolysing the phosphoinositide 3-kinase-generated second messenger, PtdIns(3,4,5)P(3) to PtdIns(3,4)P(2). SHIP1(-/-) mice have, as a result, an increased number of neutrophils and monocyte/macrophages because their progenitors display enhanced survival and proliferation. These mice also suffer from osteoporosis because of an increased number of hyperactive osteoclasts and a significant neutrophil infiltration of the lungs. Interestingly, SHIP1(-/-) mice do not display endotoxin tolerance and we have found that lipopolysaccharide-induced endotoxin tolerance is contingent on up-regulating SHIP1, through the production of autocrine-acting transforming growth factor-beta, in bone-marrow-derived macrophages and mast cells. Intriguingly, unlike bone-marrow-derived macrophages, SHIP1(-/-) peritoneal and alveolar macrophages produce 10-fold less NO than wild-type macrophages because these in vivo-generated macrophages have very high arginase I levels and this enzyme competes with inducible nitric oxide synthase for the substrate L-arginine. It is probable that, in the face of chronically increased PtdIns(3,4,5)P(3) levels in their myeloid progenitors, SHIP1(-/-) mice display a skewed development away from M1 (killer) macrophages (which have high inducible nitric oxide synthase levels and produce NO to kill microorganisms and tumour cells), towards M2 (healing) macrophages (which have high arginase levels and produce ornithine to promote host-cell growth and collagen formation). This skewing probably occurs to avoid septic shock and suggests that the phosphoinositide 3-kinase pathway plays a critical role in programming macrophages.
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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 | 0.001 |
| 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".