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Record W2331789769 · doi:10.1115/sbc2010-19249

The Effects of Cell Contraction and Loss of Adhesion on the Apoptosis of Valve Interstitial Cells

2010· article· en· W2331789769 on OpenAlexaff
Ruogang Zhao, Lina Lin, Craig A. Simmons

Bibliographic record

VenueASME 2010 Summer Bioengineering Conference, Parts A and B · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCell biologyMyofibroblastApoptosisInterstitial cellFocal adhesionCellCytoskeletonExtracellular matrixChemistrySignal transductionBiologyPathologyMedicineFibrosisBiochemistryEndocrinology

Abstract

fetched live from OpenAlex

Dystrophic calcification in sclerotic aortic valves is associated with apoptosis of myofibroblasts that differentiate from valve interstitial cells (VICs). The factors that regulate apoptosis in sclerotic valves are not known, but may include mechanical stimuli, as is the case in other fibrotic tissues. In support of this hypothesis, we have observed that VICs on stiff collagen matrices that simulate fibrotic tissue differentiate to myofibroblasts and form calcified aggregates that contain apoptotic cells [1]. However, the mechanisms by which cell aggregation leads to VIC apoptosis are unknown. In other cell types, cell contraction caused by release of matrix tension can induce cell apoptosis, but the mechanical transduction pathway regulating this process is unknown [2]. Similarly, cell rounding caused by disrupting the cytoskeletal network has been found to induce apoptosis [3], indicating the cytoskeletal network may play an important role in the cell shape-change related apoptosis pathways. Loss of adhesion between the cell and its matrix is also a well-documented cause for apoptosis of adherent cell types [4].

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.120
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.255
Teacher spread0.246 · 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.

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

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