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Cognitive impairment in mice over-expressing γ-aminobutyric acid transporter I (GAT1)

2003· article· en· W2087605748 on OpenAlexaff
Jia-Hua Hu, Ying-Hua Ma, Jie Jiang, Na Yang, Shu-hui Duan, Zhi-Hua Jiang, Zhen-Tong Mei, Jian Fei, Li-He Guo

Bibliographic record

VenueNeuroreport · 2003
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsGABAergicGABA transporterCognitionNeuroscienceNMDA receptorGenetically modified mouseTransportergamma-Aminobutyric acidTransgeneBiologyPharmacologyEndocrinologyInternal medicineReceptorMedicineBiochemistryInhibitory postsynaptic potentialGene

Abstract

fetched live from OpenAlex

There is increasing evidence that GABAergic system plays an important role in the neural control of learning and memory processes. GAT1 over-expressing mice (NA) were generated, in which GAT1 is under the control of a neuron-specific enolase (NSE) promoter, to investigate effects of GABA transporter on cognitive function. Our results revealed that NA mice displayed cognitive deterioration in associative learning ability and new object recognition retention, compared with the wild-type littermates (WT2). However, the impaired cognitive function of transgenic mice could be rescued after chronic administration of GAT1 selective inhibitor for 6 days. In addition, there was no change of the expression of NMDA receptors in NA mice. Taken together, we show a potentially important role for GAT1 in the neural control of cognitive processes, and indicate great potential for GAT1 as a clinical target of cognitive disorders.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.060
GPT teacher head0.353
Teacher spread0.294 · 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

Citations27
Published2003
Admission routes1
Has abstractyes

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