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Vocabulaire en FL2 : utile d’avoir la tête à Papineau ?

2011· article· en· W37239116 on OpenAlexaff
Linda de Serres

Bibliographic record

VenueQuébec français/Québec-français · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsPolitical scienceHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Aging causes alterations in body composition. Specifically, visceral fat mass increases with age and is associated with age-related diseases. The pathogenic potential of visceral fat accumulation has been associated with its anatomical location and metabolic activity. Visceral fat may control systemic metabolism by secreting molecules that act in distal tissues, mainly the liver, through the portal vein. Currently, little is known about age-related changes in visceral fat in humans. Aiming to identify molecular and cellular changes occurring with aging in the visceral fat of humans, we analyzed publicly available transcriptomic data of 355 omentum samples from the Genotype-Tissue Expression portal (GTEx) of 20-79-year-old males and females. We identified the functional enrichment of genes associated with aging, inferred age-related changes in visceral fat cellularity by deconvolution analysis, profiled the senescence-associated secretory phenotype of visceral adipose tissue, and predicted the connectivity of the age-induced visceral fat secretome with the liver. We demonstrate that age induces alterations in visceral fat cellularity, synchronous to changes in metabolic pathways and a shift toward a pro-inflammatory secretory phenotype. Furthermore, our approach identified candidates such as <i>ADIPOQ-ADIPOR1/ADIPOR2, FCN2-LPR1</i>, and <i>TF-TFR2</i> to mediate visceral fat-liver crosstalk in the context of aging. These findings cast light on how alterations in visceral fat with aging contribute to liver dysfunction and age-related disease etiology.

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), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0460.006

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 head0.026
GPT teacher head0.222
Teacher spread0.197 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2011
Admission routes1
Has abstractyes

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