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Record W2045958649 · doi:10.1159/000126878

Effects of Age and Long-Term Ovariectomy on the Estrogen-Receptor Containing Subpopulations of Beta-Endorphin-Immunoreactive Neurons in the Arcuate Nucleus of Female C57BL/6J Mice

2008· article· en· W2045958649 on OpenAlexaff
M.M. Miller, Pierre Tousignant, Ung-Suk Yang, Sydney Pedvis, Reinhart B. Billiar

Bibliographic record

VenueNeuroendocrinology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
FundersNational Institute on Aging
KeywordsInternal medicineEndocrinologyArcuate nucleusbeta-EndorphinEstrogenBETA (programming language)NucleusBiologyReceptorEstrogen receptorHypothalamusMedicineNeuroscience

Abstract

fetched live from OpenAlex

We have reported a decrease in the number of arcuate nucleus (ARC)-immunoreactive β-endorphin neurons in old (24 months) female C57BL/6J mice versus young (5 months) mice. Here, we have tested by immunocytochemistry whether age-related changes in β-endorphin neuron numbers are selective for β-endorphin neurons which do or do not contain estrogen receptors (E2R). We also compared β-endorphin neuron number in mice with short- (S) and long-duration (L) ovariectomy (OVX), since the latter may protect against neuroendocrine aging. Mice were studied at 5 (young), 12 (middle-aged), or 23-24 months (old). When the mean number of neurons per tissue section (15 sections per animal) was examined, there were no significant differences between young and middle-aged S-OVX females for either β-endorphin, E<sub>2</sub>R, or β-endorphin/ E<sub>2</sub>R neuron number. However, there were significant decreases in β-endorphin-containing neurons in the oldest age group versus young females (young S-OVX: 74.4 ± 11 (±SD) immunopositive neurons per tissue section, n = 10 mice; young L-OVX: 61.6 ± 6.9, n = 6; old S-OVX: 45.7 ± 9.9, n = 7; and old L-OVX: 37.5 ± 7.3, n = 7). There were also decreases in β-endorphin neurons which contained E<sub>2</sub>R in the oldest animals (young S-OVX: 16.6 ± 6.4; young L-OVX: 13.7 ± 1.3; old S-OVX: 9.2 ± 1.8; L-OVX: 6.0 ± 1.5) (p < 0.05 ANOVA). Both age (p < 0.001, two-way ANOVA) and ovarian status (p < 0.05) independently affected neuron number for both the β-endorphin and β-endorphin E<sub>2</sub>R populations versus young mice. We tested whether the observed age and/or ovarian-related decreases were proportionally greater in the subpopulation of β-endorphin neurons which contained E<sub>2</sub>R compared to the total β-endorphin neuron population. In the oldest age group, there was no significant difference in the decrease with age in the population of β-endorphin neurons which contained E<sub>2</sub>R and the total β-endorphin population (p = 0.208). When we examined the E<sub>2</sub>R neuron population as compared to the β-endorphin neuron populations, age-related decreases in the β-endorphin neuronal population tended to be greater than the decreases seen in the E<sub>2</sub>R neuron population (p = 0.054 repeated measures ANOVA). The tyrosine hydroxylase (TH) neuron population was studied to test whether there were changes in another ARC neuron population. There was no age-related change in either TH neuron number (young S-OVX: 35.8 ± 6.2, n = 4; middle-aged S-OVX: 33.1 ± 2.8, n = 4; old S-OVX: 33.4 ± 3.4, n = 4) or in the number of TH neurons which contained E<sub>2</sub>R (young S-OVX: 7.6 ± 1.0; middle-aged S-OVX: 7.2 ± 0.8; old S-OVX: 6.9 ± 1.2). These data demonstrate that ARC β-endorphin-containing perikarya are sensitive to alterations associated both with age and ovarian status; these effects are independent of one another. Our findings fail to support the hypothesis that L-OVX has a protective effect on hypothalamic neurons in older females. The subpopulation of β-endorphin neurons that contain E<sub>2</sub>R are not affected to any greater degree by age or ovarian status than the β-endorphin neuron population as a whole in the old animal.

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 score0.367
Threshold uncertainty score0.541

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 studies0.0000.001
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 head0.016
GPT teacher head0.242
Teacher spread0.227 · 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".

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Citations32
Published2008
Admission routes1
Has abstractyes

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