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Record W2412831586

Differential morphometric and ultrastructural remodelling in the left atrium and left ventricle in rapid ventricular pacing-induced heart failure.

2000· article· en· W2412831586 on OpenAlexaff
O'Brien Dw, Yue Fu, Parker Hr, Chan Sy, Halliday Idikio, Scott Pg, Jugdutt Bi

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVentricleMedicineCardiologyHeart failureInternal medicineMuscle hypertrophyEjection fractionUltrastructureCardiomyopathyAnatomy
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Heart failure induced by rapid ventricular pacing (RVP) is associated with left atrial (LA) but not left ventricular (LV) hypertrophy. OBJECTIVE: To determine whether differences in wall tension correlate with the differential ultrastructural remodelling in the LA and LV chambers, changes in ultrastructure, systolic function and wall tension (an index of wall stress) were compared in dogs after RVP (n=7) and with no RVP (n=9). RESULTS: Compared with dogs with no RVP (controls), dogs with RVP had increased collagen volume fraction (5.3% versus 8.3%), myocyte cross-sectional area (245 versus 366 microm(2)) and hydroxyproline (222 versus 323 microg/mg protein) in the LA (all P<0.05), but not in the LV. The increase in systolic wall tension produced by RVP was greater in the LA (five versus 43 units, P<0.0004) than in the LV (227 versus 290 units, P<0.01) chambers and correlated closely with the collagen volume fraction (r=0.87), which in turn correlated with myocyte cross-sectional area (r=0.98). In the left atrium, wall tension correlated with wall stress (r=0.99). CONCLUSIONS: The results suggest that differential wall tension may provide the stimulus for differential ultrastructural remodelling (with more hypertrophy and collagen) between LA and LV chambers in RVP-induced cardiomyopathy.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.211
Teacher spread0.197 · 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

Citations15
Published2000
Admission routes1
Has abstractyes

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