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Inflammaging and Proteases in Abdominal Aortic Aneurysm

2015· review· en· W2055362790 on OpenAlex
Alon Hendel, Lisa S. Ang, David J. Granville

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Vascular Pharmacology · 2015
Typereview
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsSt. Paul's Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineAbdominal aortic aneurysmProteasesAortic aneurysmAneurysmCardiologyRadiologyInternal medicineBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Abdominal aortic aneurysm (AAA) is an age-related disease resulting in aortic wall weakening and dilatation which may progress to the fatal point of abrupt aortic wall rupture. Chronic inflammation is a driving force in the pathogenesis of AAA and extracellular matrix (ECM) proteases are considered central to aortic wall degradation. Considerable effort is dedicated to identifying the proteases responsible as well as the mechanism by which these proteases contribute to disease progression. As such, they are considered important molecular targets for pharmacological intervention. Along with smoking, male gender and family history, aging is a major risk factor for AAA. Examination of age-related changes of the immune system reveals an interwoven relationship between the processes of aging and chronic inflammation, collectively predisposing to AAA development. The present review explores current evidence as to the role of specific ECM proteases in AAA pathogenesis. The contribution of the aging process to disease pathogenesis is also explored to provide the relevant context and highlight key molecular pathways that should be considered while attempting to develop effective treatment approaches.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.076
GPT teacher head0.422
Teacher spread0.346 · 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