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Record W2943120746 · doi:10.1242/dev.156000

The origins and non-canonical functions of macrophages in development and regeneration

2019· review· en· W2943120746 on OpenAlexafffund
Marine Théret, Rémi Mounier, Fábio Rossi

Bibliographic record

VenueDevelopment · 2019
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchFondation pour la Recherche MédicaleEuropean Molecular Biology Organization
KeywordsBiologyRegeneration (biology)MacrophageInnate immune systemHomeostasisImmune systemPathogenesisDiseaseImmunologyCell biologyNeuroscienceSkeletal musclePathologyGeneticsAnatomy

Abstract

fetched live from OpenAlex

The discovery of new non-canonical (i.e. non-innate immune) functions of macrophages has been a recurring theme over the past 20 years. Indeed, it has emerged that macrophages can influence the development, homeostasis, maintenance and regeneration of many tissues and organs, including skeletal muscle, cardiac muscle, the brain and the liver, in part by acting directly on tissue-resident stem cells. In addition, macrophages play crucial roles in diseases such as obesity-associated diabetes or cancers. Increased knowledge of their regulatory roles within each tissue will therefore help us to better understand the full extent of their functions and could highlight new mechanisms modulating disease pathogenesis. In this Review, we discuss recent studies that have elucidated the developmental origins of various macrophage populations and summarize our knowledge of the non-canonical functions of macrophages in development, regeneration and tissue repair.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.033
GPT teacher head0.291
Teacher spread0.258 · 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

Citations87
Published2019
Admission routes2
Has abstractyes

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