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Record W3012861332 · doi:10.1073/pnas.1920193117

15-Epi-LXA <sub>4</sub> and 17-epi-RvD1 restore TLR9-mediated impaired neutrophil phagocytosis and accelerate resolution of lung inflammation

2020· article· en· W3012861332 on OpenAlexafffund
Meriem Sekheri, Driss El Kebir, Natalie M. Edner, János G. Filep

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersCanadian Institutes of Health ResearchCanadian HIV Trials Network, Canadian Institutes of Health ResearchGovernment of CanadaYale University
KeywordsPhagocytosisInflammationApoptosisNeutrophil extracellular trapsBiologyGranulocyteImmunologyReceptorInnate immune systemMicrobiologyCell biologyImmune systemBiochemistry

Abstract

fetched live from OpenAlex

Significance Timely resolution of bacterial infections critically depends on phagocytosis of invading pathogens by polymorphonuclear neutrophil granulocytes, followed by neutrophil apoptosis and removal by macrophages. Neutrophils integrate cues from the inflammatory microenvironment. Here we show a Toll-like receptor 9-mediated mechanism, involving regulation of phagocytosis and phagocytosis-induced neutrophil apoptosis, by which bacterial DNA, a pathogen-associated molecular pattern, and the danger signal mitochondrial DNA may impair host defense to bacteria and prolong the inflammatory response. We also report that the proresolution aspirin-triggered lipids 15-epi-lipoxin A 4 and 17-epi-resolvin D1 restore impaired phagocytosis and enhance bacterial clearance and phagocytosis-induced neutrophil apoptosis, thereby facilitating resolution of acute lung inflammation. These findings imply the lipoxin receptor ALX/FPR2 as a potential therapeutic target for combating bacterial infections.

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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.258
Teacher spread0.226 · 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 teacher head, 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

Citations112
Published2020
Admission routes2
Has abstractyes

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