PB0780 Using Itga2b-creERT2 and Itga2b-creERT2-treml1 Transgenic Mice to Decipher TLT-1's Role in Platelet Interaction with Fibrinogen
Bibliographic record
Abstract
Background: aIIb (CD41), a lineage-specific receptor, plays an important role in hemostasis due to functional interactions with fibrinogen that promote platelet interaction and clot formation.TREM-Like Transcript-1 (TLT-1) is a lineage-specific receptor stored in platelet α-granules, which translocates to the platelet surface following agonist-induced platelet activation.TLT-1 also binds fibrinogen during platelet activation.However, the relevant role of TLT-1 during this process has not been fully elucidated yet.Aims: To elucidate the role of TLT-1 as a fibrinogen receptor by establishing and characterizing a conditional knockout mice model of αIIb (ITGA2B) under the regulation of a tamoxifen-inducible Cre-recombinase (CreER/T2) and subsequently crossing this mouse on to the treml-/-background to study fibrinogen binding.Methods: Tamoxifen was used to induce CRE and remove exons 2-4 of ITGA2b.These mice were crossed into the treml1-/-mouse line to assess TLT-1 binding to fibrinogen and to characterize the phenotype, mice were fed tamoxifen and evaluated by immunological and hematological techniques.Results: We found the 2-week tamoxifen diet-induced repression of GPIIb on Itga2b-creERT2 platelets, but not on other platelet receptors such as GPIb or TLT-1.GPIIIa is expressed intracellularly, but not on the platelet surface.These mice displayed a Glanzmann Thrombasthenia phenotype with severely reduced fibrinogen binding.However, at low-dose thrombin, a distinct binding of fibrinogen is removed in Itga2b-creERT2-treml1-/-mice.We plan to exploit this difference to delineate the differential interactions of αIIbβ2 and TLT-1 with fibrinogen.The current characterization of this model will be shown in this presentation.Conclusion(s): These transgenic mice are likely to be a valuable tool to study the function of platelet TLT-1 involved in immunological response and hemostatic regulation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.007 |
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".