Bibliographic record
Abstract
Objective: HHT pathogenesis strongly relies on an overactivated AKT activity in endothelial cells.Here, we have investigated the therapeutic effects of AKT inhibitors in preclinical models of HHT1. Method:We compared the effects of Perifosine, Uprosertib and VAD044 on angiogenesis focusing on the neonatal retina of Cdh5-Cre ERT2 ; Eng flox/flox mice at P7. Mice received a single dose of 50 lg Tamoxifen at P2 to induce the formation of retinal AVMs and then were treated with AKT inhibitors at P3 and P5.The half maximal concentrations (EC 50) were identified in mice and in human in vivo and in vitro by measuring AKT activity in primary endothelial cells and in platelets isolated from blood samples.Result: VAD044 showed the best efficacy and safety profile.VAD044 at 2.5 mg.kg -1 of body weight strongly inhibited the formation of AVMs in Eng-iKO e mice.The blood exposure of VAD044 free base in the plasma of mouse neonates corresponded to a concentration of 55.1 nM over 48 h dosing interval.VAD044 IC 50 on AKT phosphorylation was measured at 55 nM in control mouse endothelial cells and increased to 93 nM in mouse endothelial cells depleted for Eng.In human primary endothelial cells, VAD044 IC 50 was comparable and measured at 87 nM.The values of those IC 50 were similar to the average plasmatic concentration of VAD044 in mice and in human.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.430 | 0.262 |
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".