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Resolving inflammation by TAM receptor activation

2021· review· en· W3163931645 on OpenAlexfundno aff
Juliana P. Vago, Flávio A. Amaral, Fons A. J. van de Loo

Bibliographic record

VenuePharmacology & Therapeutics · 2021
Typereview
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorArthritis SocietyReumaNederlandDutch Arthritis Society
KeywordsMERTKEfferocytosisInflammationReceptor tyrosine kinaseGAS6Receptor Protein-Tyrosine KinasesReceptorLipid signalingCell biologyImmunologySignal transductionBiologyCancer researchMacrophageBiochemistryIn vitro

Abstract

fetched live from OpenAlex

The control of inflammation is strictly regulated to ensure the adequate intensity and duration of an inflammatory response, enabling the removal of the trigger factors and the restoration of the integrity of the tissues and their functions. This process is coordinated by anti-inflammatory and pro-resolving mediators that regulate the cellular and molecular events necessary to restore homeostasis, and defects in this control are associated with the development of chronic and autoimmune diseases. The TAM family of receptor tyrosine kinases-Tyro3, Axl, and MerTK-plays an essential role in efferocytosis, a key process for the resolution of inflammation. However, new studies have demonstrated that TAM receptor activation not only reduces the synthesis of pro-inflammatory mediators by different cell types in response to some stimuli but also stimulates the production of anti-inflammatory and pro-resolving molecules that control the inflammation. This review provides a comprehensive view of TAM receptor family members as important players in controlling inflammatory responses through anti-inflammatory and pro-resolving actions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.063
GPT teacher head0.362
Teacher spread0.299 · 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

Citations85
Published2021
Admission routes1
Has abstractyes

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