MétaCan
Menu
Back to cohort
Record W2612307616 · doi:10.1113/jp274134

The impact of age and frailty on ventricular structure and function in C57BL/6J mice

2017· article· en· W2612307616 on OpenAlexafffund
Hirad Feridooni, Alice E. Kane, Omar Ayaz, Ali Boroumandi, Nazari Polidovitch, Robert G. Tsushima, Robert A. Rose, Susan E. Howlett

Bibliographic record

VenueThe Journal of Physiology · 2017
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsYork UniversityDalhousie University
FundersCanadian Institutes of Health ResearchDalhousie University
KeywordsC57BL/6Ventricular functionInternal medicineGerontologyFunction (biology)MedicineCardiologyNeurosciencePsychologyBiologyCell biology

Abstract

fetched live from OpenAlex

Key points Heart size increases with age (called hypertrophy), and its ability to contract declines. However, these reflect average changes that may not be present, or present to the same extent, in all older individuals. That aging happens at different rates is well accepted clinically. People who are aging rapidly are frail and frailty is measured with a ‘frailty index’. We quantified frailty with a validated mouse frailty index tool and evaluated the impacts of age and frailty on cardiac hypertrophy and contractile dysfunction. Hypertrophy increased with age, while contractions, calcium currents and calcium transients declined; these changes were graded by frailty scores. Overall health status, quantified as frailty, may promote maladaptive changes associated with cardiac aging and facilitate the development of diseases such as heart failure. To understand age‐related changes in heart structure and function, it is essential to know both chronological age and the health status of the animal. Abstract On average, cardiac hypertrophy and contractile dysfunction increase with age. Still, individuals age at different rates and their health status varies from fit to frail. We investigated the influence of frailty on age‐dependent ventricular remodelling. Frailty was quantified as deficit accumulation in adult (≈7 months) and aged (≈27 months) C57BL/6J mice by adapting a validated frailty index (FI) tool. Hypertrophy and contractile function were evaluated in Langendorff‐perfused hearts; cellular correlates/mechanisms were investigated in ventricular myocytes. FI scores increased with age. Mean cardiac hypertrophy increased with age, but values in the adult and aged groups overlapped. When plotted as a function of frailty, hypertrophy was graded by FI score (r = 0.67–0.55, P < 0.0003). Myocyte area also correlated positively with FI (r = 0.34, P = 0.03). Left ventricular developed pressure (LVDP) plus rates of pressure development (+dP/dt) and decay (−dP/dt) declined with age and this was graded by frailty (r = −0.51, P = 0.0007; r = −0.48, P = 0.002; r = −0.56, P = 0.0002 for LVDP, +dP/dt and −dP/dt). Smaller, slower contractions graded by FI score were also seen in ventricular myocytes. Contractile dysfunction in cardiomyocytes isolated from frail mice was attributable to parallel changes in underlying Ca2+ transients. These changes were not due to reduced sarcoplasmic reticulum stores, but were graded by smaller Ca2+ currents (r = −0.40, P = 0.008), lower gain (r = −0.37, P = 0.02) and reduced expression of Cav1.2 protein (r = −0.68, P = 0.003). These results show that cardiac hypertrophy and contractile dysfunction in naturally aging mice are graded by overall health and suggest that frailty, in addition to chronological age, can help explain heterogeneity in cardiac aging.

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)0.001
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.019
GPT teacher head0.305
Teacher spread0.286 · 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".

Quick stats

Citations56
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of PhysiologySame topicFrailty in Older AdultsFrench-language works237,207