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Excessive vascular smooth muscle and macrophage proliferation underlies impaired coronary collateral growth in the metabolic syndrome

2013· article· en· W3175369128 on OpenAlexaff
Rebecca Hutcheson, Jennifer A. Chaplin, Erika Smith, Rashmi Jadhav, James C. Russell, Petra Ročić

Bibliographic record

VenueThe FASEB Journal · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiomarkers in Disease Mechanisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProliferating cell nuclear antigenCell growthInternal medicineMetabolic syndromeEndocrinologyMedicineImmunohistochemistryBiologyPathologyBiochemistry

Abstract

fetched live from OpenAlex

Rationale Coronary collateral growth (CCG) is impaired in the metabolic syndrome. It is thought that inadequate cell proliferation is a causative factor. Pro‐angiogenic growth factors (GFs) stimulate cell proliferation. Metabolic syndrome patients and animal models exhibit elevated GF levels, but administration of GFs does not promote CCG in the metabolic syndrome. Objective To determine whether temporally inappropriate excessive cell proliferation underlies impaired CCG in the metabolic syndrome. Methods and Results Normal (SD) and metabolic syndrome (JCR) rats underwent transient, repetitive coronary artery occlusion (RI). We have previously shown that CCG was maximal at day 9 of RI in SD rats but did not occur in JCR rats. Cell proliferation was evaluated by immunohistochemistry (PCNA, Ki‐67) and Western blotting (PCNA). The increase in cell proliferation was transient in SD but greater and sustained in JCR rats. Assessment of cell cycle progression confirmed early and transient cell proliferation in SD vs. sustained proliferation in JCR rats. This was associated with accumulation of proliferating cells in the lumen of small arterioles in JCR rats, which failed to undergo outward expansion. Conclusions Excessive cell proliferation in the later stages of collateral remodeling underlies impaired CCG in the metabolic syndrome. R01 HL093052

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.207
Teacher spread0.198 · 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 designObservational
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
Published2013
Admission routes1
Has abstractyes

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