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Record W3138596015 · doi:10.1111/ejn.15188

An emerging role for microglia in stress‐effects on memory

2021· review· en· W3138596015 on OpenAlexaff
Jeniffer Sanguino‐Gómez, Jacobus C. Buurstede, Oihane Abiega, Carlos P. Fitzsimons, Paul J. Lucassen, Bart J. L. Eggen, Sylvie L. Lesuis, Onno C. Meijer, Harm J. Krugers

Bibliographic record

VenueEuropean Journal of Neuroscience · 2021
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsHospital for Sick Children
FundersFundación Mutua Madrileña
KeywordsMicrogliaNeuroscienceGlutamatergicGlutamate receptorNeurotransmissionKynurenine pathwayEffects of stress on memoryCrosstalkSynaptic plasticityNeuroplasticityMetaplasticityPsychologyPremovement neuronal activityBiologyMemory consolidationReceptorMedicineInflammationHippocampusKynurenineImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Stressful experiences evoke, among others, a rapid increase in brain (nor)epinephrine (NE) levels and a slower increase in glucocorticoid hormones (GCs) in the brain. Microglia are key regulators of neuronal function and contain receptors for NE and GCs. These brain cells may therefore potentially be involved in modulating stress effects on neuronal function and learning and memory. In this review, we discuss that stress induces (1) an increase in microglial numbers as well as (2) a shift toward a pro-inflammatory profile. These microglia have (3) impaired crosstalk with neurons and (4) disrupted glutamate signaling. Moreover, microglial immune responses after stress (5) alter the kynurenine pathway through metabolites that impair glutamatergic transmission. All these effects could be involved in the impairments in memory and in synaptic plasticity caused by (prolonged) stress, implicating microglia as a potential novel target in stress-related memory impairments.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.080
GPT teacher head0.345
Teacher spread0.265 · 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 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

Citations44
Published2021
Admission routes1
Has abstractyes

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