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Record W4389685509 · doi:10.1038/s41467-023-43579-3

DPPIV+ fibro-adipogenic progenitors form the niche of adult skeletal muscle self-renewing resident macrophages

2023· article· en· W4389685509 on OpenAlexafffund
Farshad Babaeijandaghi, Nasim Kajabadi, Reece Long, Lin Tung, Chun Wai Cheung, Morten Ritso, Chih-Kai Chang, Ryan Cheng, Tiffany Huang, Elena Groppa, Jean X. Jiang, Fábio Rossi

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsUniversity of British Columbia HospitalUniversity of British Columbia
FundersCIHR Skin Research Training CentreCanadian Institutes of Health ResearchCentre for Blood Research, University of British ColumbiaU.S. Department of Health and Human ServicesGovernment of CanadaNational Institutes of HealthUniversity of British ColumbiaNational Institute on AgingWelch Foundation
KeywordsSkeletal muscleProgenitor cellBiologyMacrophageNicheCell biologyMonocyteFunction (biology)ParabiosisImmunologyStem cellEndocrinologyIn vitroGeneticsEcology

Abstract

fetched live from OpenAlex

Abstract Adult tissue-resident macrophages (RMs) are either maintained by blood monocytes or through self-renewal. While the presence of a nurturing niche is likely crucial to support the survival and function of self-renewing RMs, evidence regarding its nature is limited. Here, we identify fibro-adipogenic progenitors (FAPs) as the main source of colony-stimulating factor 1 (CSF1) in resting skeletal muscle. Using parabiosis in combination with FAP-deficient transgenic mice ( Pdgfrα CreERT2 × DTA) or mice lacking FAP-derived CSF1 ( Pdgfrα CreERT2 × Csf1 flox/null ), we show that local CSF1 from FAPs is required for the survival of both TIM4 - monocyte-derived and TIM4 + self-renewing RMs in adult skeletal muscle. The spatial distribution and number of TIM4 + RMs coincide with those of dipeptidyl peptidase IV (DPPIV) + FAPs, suggesting their role as CSF1-producing niche cells for self-renewing RMs. This finding identifies opportunities to precisely manipulate the function of self-renewing RMs in situ to further unravel their role in health and disease.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.282
Teacher spread0.269 · 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 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

Citations34
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueNature Communications→Same topicImmune cells in cancer→French-language works237,207→