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Record W3096137085 · doi:10.18632/aging.103786

LncRNA-modulated autophagy in plaque cells: a new paradigm of gene regulation in atherosclerosis?

2020· review· en· W3096137085 on OpenAlex
Kun Ren, Xiaodan Xu, Xiao-Hai Yu, Mengqi Li, Mengwen Shi, Qi-Xian Liu, Ting Jiang, Xi‐Long Zheng, Kai Yin, Guo-Jun Zhao

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.

Bibliographic record

VenueAging · 2020
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Fundersnot available
KeywordsAutophagyCell biologyGeneBiologyCancer researchGeneticsApoptosis

Abstract

fetched live from OpenAlex

The development of atherosclerosis is accompanied by the functional deterioration of plaque cells, which leads to the escalation of endothelial inflammation, abnormal vascular smooth muscle cell phenotype switching and the accumulation of lipid-laden macrophages within vascular walls. Autophagy, a highly conserved homeostatic mechanism, is critical for the delivery of cytoplasmic substrates to lysosomes for degradation. Moderate levels of autophagy prevent atherosclerosis by safeguarding plaque cells against apoptosis, preventing inflammation, and limiting the lipid burden, whereas excessive autophagy exacerbates cell damage and inflammation and thereby accelerates the formation of atherosclerotic plaques. Increasing lines of evidence suggest that long noncoding RNAs can be either beneficial or detrimental to atherosclerosis development by regulating the autophagy level. This review summarizes the research progress related to 1) the significant role of autophagy in atherosclerosis and 2) the effects of the lncRNA-mediated modulation of autophagy on the plaque cell fate, inflammation levels, proliferative capacity, and cholesterol metabolism and subsequently on atherogenesis.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.049
GPT teacher head0.329
Teacher spread0.280 · 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