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Record W1492637412

Abstract 15623: Angiopoietin Like-2 Knockdown Worsens Pressure Overload-Induced Cardiac Dysfunction Despite Preserving Vascular Endothelial Integrity in Mice

2014· article· en· W1492637412 on OpenAlexaff
Cécile Martel, Adeline Raignault, Carol Yu, Marc‐Antoine Gillis, Natacha Duquette, Nathalie Thorin‐Trescases, Christine Des Rosiers, Éric Thorin

Bibliographic record

VenueCirculation · 2014
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicinePressure overloadEndothelial dysfunctionInternal medicineGene knockdownEndocrinologyCardiac function curveBlood pressureEndotheliumInflammationCardiologyHeart failureApoptosisBiology
DOInot available

Abstract

fetched live from OpenAlex

Background: High circulating levels of angiopoietin-like 2 (angptl2), a pro-inflammatory protein, have been associated with obesity, diabetes and atherosclerosis. In mice, angptl2 induces vascular inflammation and endothelial dysfunction, but the impact of angptl2 on cardiac function is still unknown. Since mechanical stress has been shown to promote angptl2 expression and tissue remodeling, we hypothesized that angptl2 could contribute to cardiac dysfunction and that knocking down angptl2 would be protective against pressure overload. Methods/Results: We investigated both cardiac and vascular endothelial functions in angptl2 knockdown mice (KD) versus wild-type (WT) littermates, in response to a 6-week pressure overload induced by transverse aortic constriction (TAC). While peripheral blood pressure was not affected by TAC, systolic pressure in the right carotid artery was increased by 60 % in WT, but only by 28 % in KD mice (p<0.05 vs. WT, n=8). In WT, but not in KD mice, carotid and posterior cerebral ...

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.245
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2014
Admission routes1
Has abstractyes

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