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Record W2014592695 · doi:10.1186/1756-6606-4-33

Impaired spatial and contextual memory formation in galectin-1 deficient mice

2011· article· en· W2014592695 on OpenAlexafffund
Masanori Sakaguchi, Maithé Arruda-Carvalho, Na Kang, Yoichi Imaizumi, Françoise Poirier, Hideyuki Okano, Paul W. Frankland

Bibliographic record

VenueMolecular Brain · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicGalectins and Cancer Biology
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsNeuroscienceGalectinHippocampal formationHippocampusPsychologySubgranular zoneWater mazeBiologyImmunologyNeural stem cellCell biology

Abstract

fetched live from OpenAlex

Galectins are a 15 member family of carbohydrate-binding proteins that have been implicated in cancer, immunity, inflammation and development. While galectins are expressed in the central nervous system, little is known about their function in the adult brain. Previously we have shown that galectin-1 (gal-1) is expressed in the adult hippocampus, and, in particular, in putative neural stem cells in the subgranular zone. To evaluate how gal-1 might contribute to hippocampal memory function here we studied galectin-1 null mutant (gal-1-/-) mice. Compared to their wildtype littermate controls, gal-1-/- mice exhibited impaired spatial learning in the water maze and contextual fear learning. Interestingly, tone fear conditioning was normal in gal-1-/- mice suggesting that loss of gal-1 might especially impact hippocampal learning and memory. Furthermore, gal-1-/- mice exhibited normal motor function, emotion and sensory processing in a battery of other behavioral tests, suggesting that non-mnemonic performance deficits are unlikely to account for the spatial and contextual learning deficits. Together, these data reveal a role for galectin-carbohydrate signalling in hippocampal memory function.

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)0.000
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 score0.030
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.213
Teacher spread0.201 · 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

Citations24
Published2011
Admission routes2
Has abstractyes

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