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Record W4225702197 · doi:10.1101/2021.11.01.466743

Platelet generation from circulating megakaryocytes is triggered in the lung vasculature

2021· preprint· en· W4225702197 on OpenAlexaff
Xiaojuan Zhao, Dominic Alibhai, Tony G. Walsh, Nathalie Tarassova, Semra Zuhal Birol, Christopher M. Williams, Chris R. Neil, Elizabeth W. Aitken, Amie K. Waller, José Ballester‐Beltrán, Peter W. Gunning, Edna C. Hardeman, Ejaife O. Agbani, Ingeborg Hers, Cédric Ghevaert, Alastair W. Poole

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of Calgary
FundersUniversity of BristolBritish Heart FoundationWellcome Trust
KeywordsPlateletMegakaryocyteLungEx vivoBone marrowCell biologyBiologyPathologyIn vivoImmunologyMedicineInternal medicineProgenitor cellStem cell

Abstract

fetched live from OpenAlex

Abstract Platelets, small hemostatic blood cells, are derived from megakaryocytes, although the generation process is not clear. Only small numbers of platelets have been produced in systems outside the body, where bone marrow and lung are proposed as sites of platelet generation. Here we show that perfusion of megakaryocytes ex vivo through the mouse lung vasculature generates very large numbers of platelets, up to 3,000 per megakaryocyte. Despite their large size, megakaryocytes were able repeatedly to passage through the lung vasculature, leading to enucleation and fragmentation to generate platelets intravascularly. Using the ex vivo lung and a novel in vitro microfluidic chamber we determined the contributions of oxygenation, ventilation and endothelial cell health to platelet generation, and showed a critical role for the actin regulator TPM4. One-Sentence Summary Megakaryocytes form platelets intravascularly in the lung, dependent upon oxygenation, endothelium and megakaryocyte TPM4

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.019
GPT teacher head0.238
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicPlatelet Disorders and Treatments→French-language works237,207→