Transient von Willebrand factor‐mediated platelet influx stimulates liver regeneration after partial hepatectomy in mice
Bibliographic record
Abstract
BACKGROUND & AIMS: In addition to their function in thrombosis and haemostasis, platelets play an important role in the stimulation of liver regeneration. It has been suggested that platelets deliver mitogenic cargo to the regenerating liver, and accumulation of platelets in the regenerating liver has been demonstrated. We studied kinetics of platelet influx in the regenerating liver and investigated the signal that initiates platelet influx. METHODS: We visualized platelets in the liver remnant after partial hepatectomy in mice using intravital microscopy and assessed liver regeneration by examination of liver/body weight ratio and the number of proliferating hepatocytes examined by immunohistochemistry. RESULTS: We demonstrated rapid but transient platelet influx into the liver remnant after a partial liver resection. Liver regeneration in thrombocytopenic mice was substantially impaired as evidenced by a reduced liver-to-body weight ratio and decreased numbers of proliferating hepatocytes at day 3 compared to mice with normal platelet counts. In contrast, liver regeneration was only mildly impaired when thrombocytopaenia was induced 2 hours after partial liver resection. Platelet influx into the liver remnant was virtually absent in the presence of an antibody to von Willebrand factor (VWF) suggesting that VWF release from liver sinusoidal endothelial cells mediates platelet influx. Additionally, liver regeneration in mice deficient in VWF was markedly impaired. CONCLUSIONS: A rapid but transient VWF-dependent platelet influx into the liver remnant drives platelet-mediated liver regeneration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".