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Record W4396892961 · doi:10.3390/biomedicines12051089

Senescent Macrophages Release Inflammatory Cytokines and RNA-Loaded Extracellular Vesicles to Circumvent Fibroblast Senescence

2024· article· en· W4396892961 on OpenAlexafffund
Camille Laliberté, Bianca Bossé, Véronique Bourdeau, Luis I. Prieto, Genève Perron-Deshaies, Nhung Vuong, Sebastian Igelmann, Lisbeth C. Aguilar, Marlene Oeffinger, Darren J. Baker, Luc DesGroseillers, Gerardo Ferbeyre

Bibliographic record

VenueBiomedicines · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsCentre Hospitalier de l’Université de MontréalMontreal Clinical Research InstituteUniversité de Montréal
FundersInstitute of Cancer ResearchNatural Sciences and Engineering Research Council of CanadaCancer Research Society
KeywordsSenescenceCell biologySecretionBiologyFibroblastInflammationMacrophageProinflammatory cytokineTranscriptomeMicrovesiclesDownregulation and upregulationmicroRNAIn vitroGene expressionImmunologyBiochemistryGene

Abstract

fetched live from OpenAlex

Senescent cells, which accumulate with age, exhibit a pro-inflammatory senescence-associated secretory phenotype (SASP) that includes the secretion of cytokines, lipids, and extracellular vesicles (EVs). Here, we established an in vitro model of senescence induced by Raf-1 oncogene in RAW 264.7 murine macrophages (MΦ) and compared them to senescent MΦ found in mouse lung tumors or primary macrophages treated with hydrogen peroxide. The transcriptomic analysis of senescent MΦ revealed an important inflammatory signature regulated by NFkB. We observed an increased secretion of EVs in senescent MΦ, and these EVs presented an enrichment for ribosomal proteins, major vault protein, pro-inflammatory miRNAs, including miR-21a, miR-155, and miR-132, and several mRNAs. The secretion of senescent MΦ allowed senescent murine embryonic fibroblasts to restart cell proliferation. This antisenescence function of the macrophage secretome may explain their pro-tumorigenic activity and suggest that senolytic treatment to eliminate senescent MΦ could potentially prevent these deleterious effects.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.103
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.244
Teacher spread0.236 · 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.

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

Citations11
Published2024
Admission routes2
Has abstractyes

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