MétaCan
Menu
Back to cohort
Record W2119515848 · doi:10.1161/circresaha.116.303805

The Role of Autophagy in Vascular Biology

2015· review· en· W2119515848 on OpenAlexafffund
Samuel C. Nussenzweig, Subodh Verma, Toren Finkel

Bibliographic record

VenueCirculation Research · 2015
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsSt. Michael's Hospital
FundersNational Institutes of HealthFondation LeducqHeart and Stroke Foundation of Canada
KeywordsAutophagyParacrine signallingCell biologyBiologyAngiogenesisVascular smooth muscleEndotheliumAutophagosomeFlux (metallurgy)NeuroscienceCancer researchChemistrySmooth muscleReceptorEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

There is increasing interest in the role of autophagic flux in maintaining normal vessel wall biology and a growing suspicion that autophagic dysregulation may be a common pathway through which vascular aging and associated pathologies develop. Within endothelial and smooth muscle cells, diverse but important triggers that range from oxidized lipids to β-amyloid seem to stimulate autophagosome formation potently. In addition, emerging evidence links autophagy to a wide array of vascular processes ranging from angiogenesis to calcification of the vessel wall. Alterations in autophagic flux are also increasingly being implicated in disease processes that include both atherosclerosis and pulmonary hypertension. Finally, recent insights point toward an important role of autophagy in the paracrine regulation of vasoactive substances from the endothelium. Here, we review the progress in understanding how autophagy can contribute to vascular biology and the emerging strategies to target this process for therapeutic benefit.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.182
GPT teacher head0.506
Teacher spread0.324 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations248
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueCirculation ResearchSame topicAutophagy in Disease and TherapyFrench-language works237,207