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Record W4396216141 · doi:10.1101/2024.04.26.591395

GABA and astrocytic cholesterol determine the lipid environment of GABA <sub>A</sub> R in cultured cortical neurons

2024· preprint· en· W4396216141 on OpenAlexfundno aff
Zixuan Yuan, Mahmud Arif Pavel, Scott B. Hansen

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsnot available
FundersUniversity of Ottawa
KeywordsCortical neuronsCholesterolLipid accumulationNeuroscienceChemistryInternal medicineBiologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

Abstract The γ-aminobutyric acid (GABA) type A receptor (GABA A R), a GABA activated pentameric chloride channel, mediates fast inhibitory neurotransmission in the brain. The lipid environment is critical for GABA A R function. How lipids regulate the channel in the cell membrane is not fully understood. Here we employed super resolution imaging of lipids to demonstrate that the agonist GABA induces a rapid and reversible membrane translocation of GABA A R to phosphatidylinositol 4,5-bisphosphate (PIP 2 ) clusters in mouse primary cortical neurons. This translocation relies on nanoscopic separation of PIP 2 clusters and lipid rafts (cholesterol-dependent ganglioside clusters). In a resting state, the GABA A R associates with lipid rafts and this colocalization is enhanced by uptake of astrocytic secretions. These astrocytic secretions enhance endocytosis and delay desensitization. Our findings suggest intercellular signaling from astrocytes regulates GABA A R location based on lipid uptake in neurons. The findings have implications for treating mood disorders associated with altered neural excitability.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.261
Teacher spread0.234 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicNeuroscience and Neuropharmacology Research→French-language works237,207→