Tacrolimus prevents von Willebrand factor secretion by allostimulated human glomerular endothelium
Bibliographic record
Abstract
Little is known about the endothelial injury caused directly by circulating donor-specific antibodies (DSAs) during antibody-mediated rejection. von Willebrand factor (vWF) is a highly thrombotic glycoprotein stored in Weibel-Palade bodies in endothelial cells. It has been shown that its secretion is triggered by allostimulation. Calcineurin-like phosphatases regulate pathways involved in vWF secretion. Therefore, we hypothesized that tacrolimus would prevent alloantibody-induced glomerular lesions, in part via inhibition of vWF secretion from endothelial cells. Here, we used a human in vitro model of glomerular endothelium expressing HLA class I and II antigens and demonstrated that anti-HLA class II antibodies elicit a higher endothelial release of vWF than do anti-HLA class I antibodies in cell supernatants. We observed that tacrolimus treatment decreased vWF secretion after stimulation with both classes of anti-HLA antibodies and decreased platelet adhesion on allostimulated endothelial cells in a microfluidic chamber. In kidney recipients, tacrolimus trough levels were negatively associated with vWF blood levels. These results indicate that direct disruption of hemostasis via vWF secretion is a potential mechanism of antibody-mediated injury in patients with DSAs. Our results further suggest that the targeting of microcirculation hemostasis may be beneficial to prevent the development of microangiopathic lesions in antibody-mediated rejection.
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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) | 0.001 | 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 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".