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Record W2718921410 · doi:10.1161/atvbaha.117.309229

Cell Death in the Vessel Wall

2017· review· en· W2718921410 on OpenAlexaff
Katey J. Rayner

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsUniversity of Ottawa
FundersNational Heart, Lung, and Blood Institute
KeywordsVascular wallProgrammed cell deathBlood vesselMedicineAnatomyCell biologyBiologyInternal medicineApoptosisBiochemistry

Abstract

fetched live from OpenAlex

Atherosclerotic vascular disease results from an imbalance of inflammatory and vascular cell accumulation and removal in the neointimal space. When pathways that promote cell recruitment, survival and proliferation are favored over to those that activate cell death, egress and clearance, the plaque expands. In contrast, programmed cell death and the efficient clearance of apoptotic bodies by efferocytosis reduces lesion cellularity and promotes a reparative environment and lesion stability. However, should these carefully balanced pathways become disturbed, lesions can accumulate cell debris, damaged-associated molecular patterns and arrested macrophages, all contributing to the pro-inflammatory environment and lesion instability. Here, we will review the latest understanding of how cell death in the vessel wall directly coordinates the development of atherosclerosis, and what molecular signals are orchestrating these pathways. We will discuss the necessity of cell death, and the ways in which the execution of different forms of cell death can direct different outcomes in the plaque, and how promoting the effective clearance of dead cells from the lesion is looking like a promising therapeutic path forward.

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)0.001
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 score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.085
GPT teacher head0.343
Teacher spread0.258 · 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.

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

Citations66
Published2017
Admission routes1
Has abstractyes

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