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Primed PMNs in healthy mouse and human circulation are first responders during acute inflammation

2019· article· en· W2947505750 on OpenAlexafffund
Noah Fine, Oriyah Barzilay, Chunxiang Sun, Nimali Chandhema Wellappuli, Farzeen Tanwir, Jeffrey W. Chadwick, Morvarid Oveisi, Nikola Tasevski, David Prescott, Martin Gargan, Dana J. Philpott, Yigal Dror, Michael Glogauer

Bibliographic record

VenueBlood Advances · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsMount Sinai HospitalHospital for Sick ChildrenPrincess Margaret Cancer CentreUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsInflammationMedicineImmunologyCirculation (fluid dynamics)Internal medicine

Abstract

fetched live from OpenAlex

Polymorphonuclear neutrophils (PMNs) are the most abundant circulating leukocytes, and the first cells recruited to sites of tissue inflammation. Using a fixation method to preserve native CD marker expression prior to immunophenotyping, we identified a distinct population of "primed for recruitment" PMNs in healthy mouse and human blood that has high expression of adhesion and activation markers compared with the bulk resting-state PMNs. In response to acute tissue inflammation, primed PMNs (pPMNs) were rapidly depleted from the circulation and recruited to the tissue. One hour after acute peritoneal insult, pPMNs became the dominant PMN population in bone marrow (BM) and blood, returning to baseline levels with resolution of inflammation. PMN priming was induced by the granulopoietic factors granulocyte-macrophage-colony-stimulating factor (GM-CSF) and granulocyte-colony-stimulating factor (G-CSF). High levels of pPMNs were observed in neutropenic mice and in pediatric neutropenic patients who were resistant to infection, highlighting an important role of this population in innate immune function.

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)0.0020.000

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.

Opus teacher head0.008
GPT teacher head0.237
Teacher spread0.229 · 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

Citations50
Published2019
Admission routes2
Has abstractyes

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