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Record W4409228011 · doi:10.1161/atvb.39.suppl_1.375

Abstract 375: Regulation of the Long Non-coding RNA Transcriptome in Endothelial Cells in Response to Shear Stress

2019· article· en· W4409228011 on OpenAlexaff
Aravin N. Sukumar, Haizhong Man, Michelle K. Dubinsky, Paul J. Turgeon, Kyung Ha Ku, Daniel H. Teitelbaum, M. Lee, Philip A. Marsden

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTranscriptomeRNACell biologyBiologyShear stressGene expressionGeneGeneticsPhysicsMechanics

Abstract

fetched live from OpenAlex

Fluid shear stress, the frictional force exerted by blood flow, is a key modulator of the expression of endothelial cell (EC) protein-coding genes. In the absence of laminar (healthy) blood flow, EC gene expression becomes dysfunctional (e.g. reduced eNOS expression) which can predispose the vessel to atherosclerosis. However, the effects of shear stress on the non-coding transcriptome are not fully defined, particularly long non-coding RNAs (lncRNAs), which are transcripts >200 nts that do not encode proteins yet regulate gene expression via diverse epigenetic mechanisms. Previously, we have identified an EC-enriched lncRNA, termed STEEL , that is induced by the absence of laminar flow to promote angiogenesis and vessel maturation in vivo . The objective of this work is to comprehensively study the effects of shear stress on EC lncRNAs to uncover novel genes that contribute to vascular homeostasis. Five independent HUVEC lines were subjected to either static (no flow) or laminar flow conditions (10 dynes/cm 2 ) for 48 hrs using a parallel plate flow chamber. RNA was isolated and analyzed using a custom human lncRNA microarray to profile 30,586 lncRNAs. In brief, 75 (0.25%) and 47 (0.15%) lncRNAs were up-regulated or down-regulated respectively (≥4 fold vs. static, p<.05). Using qRT-PCR, the top 3 highly induced and repressed lncRNAs exhibited responses to flow ranging from 10-1500 fold. HUVECs overexpressing KLF2, a transcription factor activated by laminar flow in ECs, revealed a subset of flow-induced lncRNAs to be regulated by this pathway including one which we termed NIMBUS . The NIMBUS locus is located adjacent to MEF2A, an upstream regulator of KLF2 expression in response to laminar flow. Knockdown of MEF2A using siRNA in either flow or KLF2-overexpressing ECs reduced the expression of NIMBUS confirming that NIMBUS is also regulated by MEF2A. Microarray analysis of NIMBUS KD via siRNA in KLF2-overexpressing ECs revealed several NIMBUS target genes important for vascular homeostasis including eNOS, DKK2, and CNP. These findings demonstrate that lncRNAs are novel regulators in the EC response to shear stress and represent additional gene targets for improved therapeutic and diagnostic modalities for cardiovascular diseases.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.268
Teacher spread0.253 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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