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Estrogen Alters Spine Number and Morphology in Prefrontal Cortex of Aged Female Rhesus Monkeys

2006· article· en· W2104260362 on OpenAlexaff
Jiandong Hao, Peter R. Rapp, Abba E. Leffler, Shoshana R. Leffler, William G.M. Janssen, Wendy Lou, Heather McKay, Jeffrey A. Roberts, Susan L. Wearne, Patrick R. Hof, John H. Morrison

Bibliographic record

VenueJournal of Neuroscience · 2006
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsUniversity of TorontoToronto Public Health
FundersNational Center for Research ResourcesNational Institute of Mental HealthNational Institute on AgingNational Institutes of Health
KeywordsEstrogenPrefrontal cortexNeurosciencePsychologyBiologyAnatomyEndocrinologyCognition

Abstract

fetched live from OpenAlex

Long-term cyclic treatment with 17beta-estradiol reverses age-related impairment in ovariectomized rhesus monkeys on a test of cognitive function mediated by the prefrontal cortex (PFC). Here, we examined potential neurobiological substrates of this effect using intracellular loading and morphometric analyses to test the possibility that the cognitive benefits of hormone treatment are associated with structural plasticity in layer III pyramidal cells in PFC area 46. 17beta-Estradiol did not affect several parameters such as total dendritic length and branching. In contrast, 17beta-estradiol administration increased apical and basal dendritic spine density, and induced a shift toward smaller spines, a response linked to increased spine motility, NMDA receptor-mediated activity, and learning. These results document that, although the aged primate PFC is vulnerable in the absence of factors such as circulating estrogens, it remains responsive to long-term cyclic 17beta-estradiol treatment, and that increased dendritic spine density and altered spine morphology may contribute to the cognitive benefits of such treatment.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.254

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 head0.033
GPT teacher head0.328
Teacher spread0.295 · 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 designObservational
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

Citations261
Published2006
Admission routes1
Has abstractyes

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