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Record W2914524806 · doi:10.1152/physrev.00012.2018

The Neutrophil’s Role During Health and Disease

2019· review· en· W2914524806 on OpenAlexafffund
Pei Xiong Liew, Paul Kubes

Bibliographic record

VenuePhysiological Reviews · 2019
Typereview
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsInnate immune systemImmunologyNeutrophil extracellular trapsImmune systemAcquired immune systemAutoimmunityInflammationBiologyEffectorProinflammatory cytokineImmunityMedicine

Abstract

fetched live from OpenAlex

Neutrophils have always been considered as uncomplicated front-line troopers of the innate immune system equipped with limited proinflammatory duties. Yet recently, the role of the neutrophil has been undergoing a rejuvenation of sorts. Neutrophils are now considered complex cells capable of a significant array of specialized functions, and as an effector of the innate immune response, they are able to regulate many processes such as acute injury and repair, cancer, autoimmunity, and chronic inflammatory processes. Furthermore, evidence exists to indicate that neutrophils also contribute to adaptive immunity by aiding the development of specific adaptive immune responses or guiding the subsequent adaptive immune response. With this revived interest in neutrophils and their many novel functions, it is prudent to review what is currently known about neutrophils and, even more importantly, understand what information is lacking. We discuss the essential features of the neutrophil, from its origins, lifespan, subsets, margination and sequestration of the neutrophil to the death of the neutrophil. We highlight neutrophil recruitment to both infected and injured tissues and outline differences in recruitment of neutrophils between different tissues. Finally, we examine how neutrophils use different mechanisms to either bolster protective immune responses or negatively cause pathological outcomes at different locations.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.096
GPT teacher head0.343
Teacher spread0.246 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1,185
Published2019
Admission routes2
Has abstractyes

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