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Record W4313368026 · doi:10.1016/j.isci.2022.105811

Transcriptomic profiling reveals sex-specific molecular signatures of adipose endothelial cells under obesogenic conditions

2022· article· en· W4313368026 on OpenAlexafffund
Martina Rudnicki, Alexandra Pislaru, Omid Rezvan, Eric Rullman, Aly Fawzy, Emmanuel Nwadozi, Emilie Roudier, Thomas Gustafsson, Tara L. Haas

Bibliographic record

VenueiScience · 2022
Typearticle
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsAdipose tissueTranscriptomeBiologyPhenotypeAngiogenesisAdipose tissue macrophagesEndocrinologyInternal medicineInflammationDownregulation and upregulationWhite adipose tissueGene expression profilingTumor necrosis factor alphaGene expressionGeneCell biologyGeneticsImmunologyMedicine

Abstract

fetched live from OpenAlex

Female mice display greater adipose angiogenesis and maintain healthier adipose tissue than do males upon high-fat diet feeding. Through transcriptome analysis of endothelial cells (EC) from the white adipose tissue of male and female mice high-fat-fed for 7 weeks, we found that adipose EC exhibited pronouncedly sex-distinct transcriptomes. Genes upregulated in female adipose EC were associated with proliferation, oxidative phosphorylation, and chromatin remodeling contrasting the dominant enrichment for genes related to inflammation and a senescence-associated secretory of male EC. Similar sex-biased phenotypes of adipose EC were detectable in a dataset of aged EC. The highly proliferative phenotype of female EC was observed also in culture conditions. In turn, male EC displayed greater inflammatory potential than female EC in culture, based on basal and tumor necrosis factor alpha-stimulated patterns of gene expression. Our study provides insights into molecular programs that distinguish male and female EC responses to pathophysiological conditions.

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 score0.009
Threshold uncertainty score0.517

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 head0.039
GPT teacher head0.308
Teacher spread0.269 · 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

Citations19
Published2022
Admission routes2
Has abstractyes

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