Integrin Linked Kinase Is Important in Platelet Signalling and Function.
Bibliographic record
Abstract
Abstract Integrin linked kinase (ILK) is a 59 kDa protein that has been previously implicated in both collagen- and thrombin-induced platelet activation. Platelet stimulation results in the transient activation of ILK kinase activity and movement to the plasma membrane where signaling complexes are formed with beta 1 and beta 3 integrins. The change in ILK activity and association with beta 1 and beta 3 integrins that occurs upon stimulation suggests that this protein may be important for the co-ordination of platelet responses. We have successfully developed a conditional ILK knockout mouse model using the Cre-Lox system to enable the study of platelets deficient in this protein. ILK deficient mice appear healthy and have normal platelet levels by day 8 following induction of gene deletion. ILK deficient platelets display reduced aggregation and fibrinogen binding in response to agonists such as collagen and thrombin. This is accompanied by a secretion defect, although early collagen stimulated signaling such as PLCγ2 phosphorylation and calcium mobilization are unaffected. Analysis of blood from ILK deficient mice using an in vitro flow system showed reduced thrombus formation under arterial conditions. Furthermore, extended bleeding times were observed in these mice. The data presented here demonstrates that ILK has a role in platelet regulation and is important for functional haemostasis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".