MétaCan
Menu
Back to cohort
Record W3013401843 · doi:10.1038/s41467-020-15267-z

Microglial metabolic flexibility supports immune surveillance of the brain parenchyma

2020· article· en· W3013401843 on OpenAlexafffund
Louis‐Philippe Bernier, Elisa M. York, Alireza Kamyabi, Hyun B. Choi, Nicholas L. Weilinger, Brian A. MacVicar

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of British Columbia HospitalUniversity of British Columbia
FundersInstitute of Neurosciences, Mental Health and AddictionCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaFondation LeducqMichael Smith Health Research BCGovernment of CanadaHeart and Stroke Foundation of Canada
KeywordsParenchymaImmune systemImmune surveillanceMicrogliaFlexibility (engineering)InflammationMedicineImmunologyPathology

Abstract

fetched live from OpenAlex

Microglia are highly motile cells that continuously monitor the brain environment and respond to damage-associated cues. While glucose is the main energy substrate used by neurons in the brain, the nutrients metabolized by microglia to support surveillance of the parenchyma remain unexplored. Here, we use fluorescence lifetime imaging of intracellular NAD(P)H and time-lapse two-photon imaging of microglial dynamics in vivo and in situ, to show unique aspects of the microglial metabolic signature in the brain. Microglia are metabolically flexible and can rapidly adapt to consume glutamine as an alternative metabolic fuel in the absence of glucose. During insulin-induced hypoglycemia in vivo or in aglycemia in acute brain slices, glutaminolysis supports the maintenance of microglial process motility and damage-sensing functions. This metabolic shift sustains mitochondrial metabolism and requires mTOR-dependent signaling. This remarkable plasticity allows microglia to maintain their critical surveillance and phagocytic roles, even after brain neuroenergetic homeostasis is compromised.

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)0.003
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 score0.184
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.048
GPT teacher head0.305
Teacher spread0.257 · 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

Citations297
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207