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Record W3011811223 · doi:10.1161/circresaha.119.315708

Deep Phenotyping by Mass Cytometry and Single-Cell RNA-Sequencing Reveals LYN-Regulated Signaling Profiles Underlying Monocyte Subset Heterogeneity and Lifespan

2020· article· en· W3011811223 on OpenAlexafffund
Morgan E. Roberts, Maunish Barvalia, Jessica A.F.D. Silva, Rachel A. Cederberg, William N. Chu, Amanda Wong, Daven C. Tai, Sam Chen, Israel Matos, John J. Priatel, Pieter R. Cullis, Kenneth W. Harder

Bibliographic record

VenueCirculation Research · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsLYNBiologyMonocyteCell biologyImmunologyGene knockdownDownregulation and upregulationSignal transductionTyrosine kinaseGeneticsGene

Abstract

fetched live from OpenAlex

Rationale: Monocytes are key effectors of the mononuclear phagocyte system, playing critical roles in regulating tissue homeostasis and coordinating inflammatory reactions, including those involved in chronic inflammatory diseases such as atherosclerosis. Monocytes have traditionally been divided into 2 major subsets termed conventional monocytes and patrolling monocytes (pMo) but recent systems immunology approaches have identified marked heterogeneity within these cells, and much of what regulates monocyte population homeostasis remains unknown. We and others have previously identified LYN tyrosine kinase as a key negative regulator of myeloid cell biology; however, LYN’s role in regulating specific monocyte subset homeostasis has not been investigated. Objective: We sought to comprehensively profile monocytes to elucidate the underlying heterogeneity within monocytes and dissect how Lyn deficiency affects monocyte subset composition, signaling, and gene expression. We further tested the biological significance of these findings in a model of atherosclerosis. Methods and Results: Mass cytometric analysis of monocyte subsets and signaling pathway activation patterns in conventional monocytes and pMos revealed distinct baseline signaling profiles and far greater heterogeneity than previously described. Lyn deficiency led to a selective expansion of pMos and alterations in specific signaling pathways within these cells, revealing a critical role for LYN in pMo physiology. LYN’s role in regulating pMos was cell-intrinsic and correlated with an increased circulating half-life of Lyn -deficient pMos. Furthermore, single-cell RNA sequencing revealed marked perturbations in the gene expression profiles of Lyn −/− monocytes with upregulation of genes involved in pMo development, survival, and function. Lyn deficiency also led to a significant increase in aorta-associated pMos and protected Ldlr −/− mice from high-fat diet–induced atherosclerosis. Conclusions: Together our data identify LYN as a key regulator of pMo development and a potential therapeutic target in inflammatory diseases regulated by pMos.

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)0.000
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 score0.033
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.139
GPT teacher head0.335
Teacher spread0.197 · 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

Citations31
Published2020
Admission routes2
Has abstractyes

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