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Record W4284697827 · doi:10.3390/biom12070942

The Detrimental Role of Intraluminal Thrombus Outweighs Protective Advantage in Abdominal Aortic Aneurysm Pathogenesis: The Implications for the Anti-Platelet Therapy

2022· review· en· W4284697827 on OpenAlexaff
Xiaoying Ma, Shibo Xia, Guangqin Liu, Chao Song

Bibliographic record

VenueBiomolecules · 2022
Typereview
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsSt. Michael's Hospital
FundersNational Natural Science Foundation of China
KeywordsAbdominal aortic aneurysmThrombusMedicinePlateletPathogenesisPlatelet activationAneurysmPathologyImmunologyCardiologySurgery

Abstract

fetched live from OpenAlex

Abdominal aortic aneurysm (AAA) is a common cardiovascular disease resulting in morbidity and mortality in older adults due to rupture. Currently, AAA treatment relies entirely on invasive surgical treatments, including open repair and endovascular, which carry risks for small aneurysms (diameter < 55 mm). There is an increasing need for the development of pharmacological intervention for early AAA. Over the last decade, it has been increasingly recognized that intraluminal thrombus (ILT) is involved in the growth, remodeling, and rupture of AAA. ILT has been described as having both biomechanically protective and biochemically destructive properties. Platelets are the second most abundant cells in blood circulation and play an integral role in the formation, expansion, and proteolytic activity of ILT. However, the role of platelets in the ILT-potentiated AAA progression/rupture remains unclear. Researchers are seeking pharmaceutical treatment strategies (e.g., anti-thrombotic/anti-platelet therapies) to prevent ILT formation or expansion in early AAA. In this review, we mainly focus on the following: (a) the formation/deposition of ILT in the progression of AAA; (b) the dual role of ILT in the progression of AAA (protective or detrimental); (c) the function of platelet activity in ILT formation; (d) the application of anti-platelet drugs in AAA. Herein, we present challenges and future work, which may motivate researchers to better explain the potential role of ILT in the pathogenesis of AAA and develop anti-platelet drugs for early AAA.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.042
GPT teacher head0.353
Teacher spread0.311 · 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

Citations28
Published2022
Admission routes1
Has abstractyes

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