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Record W4386256584 · doi:10.24908/iqurcp16748

Optimizing a Novel Fate-Mapping Strategy to Assess Tissue Resident Macrophages in Muscle Regeneration

2023· article· en· W4386256584 on OpenAlexaffvenue
Jiarui Che, Sarah Dick

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsQueen's University
Fundersnot available
KeywordsBiologyRegeneration (biology)Skeletal muscleFate mappingProgenitor cellMuscle tissueCell biologyCX3CR1Reporter geneMonocyteImmune systemImmunologyStem cellEndocrinologyChemokineGene expressionChemokine receptorGene

Abstract

fetched live from OpenAlex

Tissue resident macrophages (TRMs) are heterogenous innate immune cells involved in tissue homeostasis and repair, yet their role in muscle regeneration is currently unknown. TRMs differ from classical monocyte-derived macrophages (MDMs) in both ontogeny and function. Our inability to differentiate TRMs from MDMs has limited the development of subset specific immunotherapies. The novel Cx3cr1CreER/+:RosaTd/+ fate-mapping mouse model employs tamoxifen inducible labeling of MDMs and TRMs with a TdTomato reporter (Td) that persists only in self-renewing TRMs, while MDMs are replaced by Td- monocyte progenitors over a 4-week period. This strategy has been successfully used in adult mice heart and brain tissue. However, in the skeletal muscle, expression level of the Cx3cr1 reporter gene is unknown. We assessed muscle TRM Cx3cr1 expression in neonate (P3), young (P21), and adult (10wk) mice to optimize a pulse/chase strategy to label muscle TRMs with the Td reporter. Like heart and brain tissue, we found muscle TRMs express high levels of Cx3cr1 throughout development and adulthood suggesting viability of this strategy. We performed a single injection of tamoxifen in adult Cx3cr1CreER/+:RosaTd/+ mice and showed ~20% induction in blood monocytes and muscle TRMs. Although Td induction was poor, levels were similar between the blood and muscle, suggesting accuracy of the model. The next step is to optimize tamoxifen administration to achieve >90% labelling in blood and muscle. To assess spatial localization of TRMs with muscle resident stem cells (satellite cells) we optimized immunofluorescence staining on tissue sections. We found a statistically significant increase in colocalization of macrophages with satellite cells in healthy and injured gastrocnemius tissue, consistent with their predicted role in satellite cell proliferation. Once complete, our fate-mapping approach will allow for the labelling of muscle TRM subsets and reveal their role in the regeneration process.

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)0.001
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
Metaresearch0.0010.000
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.202
GPT teacher head0.401
Teacher spread0.200 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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