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Microglial Transcriptional Signatures in the Central Nervous System: Toward A Future of Unraveling Their Function in Health and Disease

2023· review· en· W4382520301 on OpenAlexaff
Haley A. Vecchiarelli, Marie‐Ève Tremblay

Bibliographic record

VenueAnnual Review of Genetics · 2023
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsCentre hospitalier de l'Université LavalMcGill UniversityUniversity of British ColumbiaUniversity of Victoria
Fundersnot available
KeywordsBiologyMicrogliaContext (archaeology)NeuroscienceCentral nervous systemDiseaseTranscriptomeImmune systemNeurodegenerationEmbryonic stem cellFunction (biology)Gene expressionGeneImmunologyCell biologyGeneticsInflammationPathologyMedicine

Abstract

fetched live from OpenAlex

Microglia, the resident immune cells of the central nervous system (CNS), are primarily derived from the embryonic yolk sac and make their way to the CNS during early development. They play key physiological and immunological roles across the life span, throughout health, injury, and disease. Recent transcriptomic studies have identified gene transcript signatures expressed by microglia that may provide the foundation for unprecedented insights into their functions. Microglial gene expression signatures can help distinguish them from macrophage cell types to a reasonable degree of certainty, depending on the context. Microglial expression patterns further suggest a heterogeneous population comprised of many states that vary according to the spatiotemporal context. Microglial diversity is most pronounced during development, when extensive CNS remodeling takes place, and following disease or injury. A next step of importance for the field will be to identify the functional roles performed by these various microglial states, with the perspective of targeting them therapeutically.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.899
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.062
GPT teacher head0.321
Teacher spread0.259 · 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 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

Citations25
Published2023
Admission routes1
Has abstractyes

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