Signalling by lysophosphatidate and its health implications
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
Extracellular lysophosphatidate (LPA) signalling is regulated by the balance of LPA formation by autotaxin (ATX) versus LPA degradation by lipid phosphate phosphatases (LPP) and by the relative expressions of six G-protein-coupled LPA receptors. These receptors increase cell proliferation, migration, survival and angiogenesis. Acute inflammation produced by tissue damage stimulates ATX production and LPA signalling as a component of wound healing. If inflammation does not resolve, LPA signalling becomes maladaptive in conditions including arthritis, neurologic pain, obesity and cancers. Furthermore, LPA signalling through LPA1 receptors promotes fibrosis in skin, liver, kidneys and lungs. LPA also promotes the spread of tumours to other organs (metastasis) and the pro-survival properties of LPA explain why LPA counteracts the effects of chemotherapeutic agents and radiotherapy. ATX is secreted in response to radiation-induced DNA damage during cancer treatments and this together with increased LPA1 receptor expression leads to radiation-induced fibrosis. The anti-inflammatory agent, dexamethasone, decreases levels of inflammatory cytokines/chemokines. This is linked to a coordinated decrease in the production of ATX and LPA1/2 receptors and increased LPA degradation through LPP1. These effects explain why dexamethasone attenuates radiation-induced fibrosis. Increased LPA signalling is also associated with cardiovascular disease including atherosclerosis and deranged LPA signalling is associated with pregnancy complications including preeclampsia and intrahepatic cholestasis of pregnancy. LPA contributes to chronic inflammation because it stimulates the secretion of inflammatory cytokines/chemokines, which increase further ATX production and LPA signalling. Attenuating maladaptive LPA signalling provides a novel means of treating inflammatory diseases that underlie so many important medical conditions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it