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Record W2519937856 · doi:10.1177/0271678x16668536

Sex differences of human cortical blood flow and energy metabolism

2016· article· en· W2519937856 on OpenAlexaff
Joel Aanerud, Per Borghammer, Anders Rodell, Kristjana Ýr Jónsdóttir, Albert Gjedde

Bibliographic record

VenueJournal of Cerebral Blood Flow & Metabolism · 2016
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsEnergy metabolismBlood flowBiologyMedicineInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Brain energy metabolism is held to reflect energy demanding processes in neuropil related to the density and activity of synapses. There is recent evidence that men have higher density of synapses in temporal cortex than women. One consequence of these differences would be different rates of cortical energy turnover and blood flow in men and women. To test the hypotheses that rates of oxygen consumption (CMRO 2 ) and cerebral blood flow are higher in men than in women in regions of cerebral cortex, and that the differences persist with aging, we used positron emission tomography to determine cerebral blood flow and cerebral metabolic rate of oxygen as functions of age in healthy volunteers of both sexes. Cerebral metabolic rate of oxygen did not change with age for either sex and there were no differences of mean values of cerebral metabolic rate of oxygen between men and women in cerebral cortex. Women had significant decreases of cerebral blood flow as function of age in frontal and parietal lobes. Young women had significantly higher cerebral blood flow than men in frontal and temporal lobes, but these differences had disappeared at age 65. The absent sex difference of cerebral energy turnover suggests that the known differences of synaptic density between the sexes are counteracted by opposite differences of individual synaptic activity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
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 head0.015
GPT teacher head0.249
Teacher spread0.235 · 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.

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

Citations117
Published2016
Admission routes1
Has abstractyes

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