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Record W2952553905 · doi:10.1172/jci124616

More friend than foe: the emerging role of neutrophils in tissue repair

2019· review· en· W2952553905 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Clinical Investigation · 2019
Typereview
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsUniversity of Calgary
FundersDeutsche ForschungsgemeinschaftCanada Research ChairsHeart and Stroke Foundation of Canada
KeywordsCollateral damageInflammationImmune systemBiologyImmunologyInfiltration (HVAC)Bone marrowCell biology

Abstract

fetched live from OpenAlex

Neutrophils are the most abundant immune cells in humans and serve as first responders to a myriad of host perturbations. Equipped with a plethora of antimicrobial molecules, neutrophils invade sites of inflammation to eradicate pathogens and clear debris. Traditionally, neutrophils were thought to cause collateral tissue damage before dying at the site. However, the presence of neutrophil infiltration into sterile injuries (in the absence of infections) suggests additional roles for these cells. Now, the view of neutrophils as indiscriminate killers seems to be changing as evolving evidence suggests that neutrophils actively orchestrate resolution of inflammation and contribute to tissue repair. Novel concepts include the idea that neutrophils are key to revascularization and subsequently reverse-transmigrate back to the vasculature, actively leaving sites of tissue damage to re-home to functional niches in the lung and bone marrow. This Review scrutinizes the role of neutrophils in tissue damage and repair, discussing recent findings and raising unresolved questions around this intriguing immune cell.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.102
GPT teacher head0.406
Teacher spread0.304 · 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