P5375A default in acetyl-CoA carboxylase phosphorylation increases thrombus growth in vitro and in vivo, and in a collagen-dependent manner
Bibliographic record
Abstract
Background: We have previously shown that AMPKα1 is activated in thrombin- or collagen-stimulated murine platelets. Accordingly, acetyl-CoA carboxylase (ACC), the bona-fide substrate of AMPK, is phosphorylated/inhibited upon platelet stimulation but its role in platelets has never been investigated. ACC is a central regulator of lipid metabolism. Given the primary roles of lipids in platelets, namely structural, energy storage and signaling, we hypothesize that acute ACC phosphorylation could affect platelet functions. Aims: To determine the impact of acute ACC phosphorylation on platelet functions and investigate its contribution to haemostasis and thrombosis. Methods: Platelets were isolated from a knock-in mouse model (KI) expressing a genetically modified ACC that can no longer be phosphorylated/inhibited by AMPK. In vitro, platelet adhesion and thrombus formation were measured using a flow chamber-based assay. Haemostasis was assessed via the measurement of bleeding time. Thrombosis was studied upon ferric chloride-induced carotid artery injury. Results: ACC phosphorylation was unchanged in non-stimulated KI relative to control (WT) platelets. Thrombin or collagen stimulation led to a rapid and significant increase in ACC phosphorylation in WT, but not in KI platelets. This effect was accompanied by a prolonged presence of calcium in the cytosol of stimulated KI platelets. Most importantly, thrombus formation on collagen-coated surface was effectively augmented under flow, in the absence of ACC phosphorylation. Accordingly, KI mice had a subsequent shorter bleeding time. They also showed increased thrombus growth reflected by a higher increment in thrombus surface area over a 10-minute time interval, compared to WT mice (7242μm2 ± 1265 versus 2520μm2 ± 1219 for WT mice).
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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) | 0.004 | 0.001 |
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".