Lifelong high-fat, high-sucrose diet causes sex-specific heart dysfunction in mouse offspring
Bibliographic record
Abstract
Maternal obesity and high-fat, high-sucrose (HFHS) diets during development increase cardiometabolic risk in offspring, but long-term, sex-specific cardiac effects remain underexplored. This study examined how continuous HFHS exposure impacts cardiac function in male and female mice. Female dams were fed a control standard chow (CON) diet or HFHS diet for 8 weeks before pregnancy, continuing through gestation and lactation. Offspring were maintained on their dam’s diet until 29–32 weeks of age. Body composition and cardiac function were assessed using pressure–volume (P–V) loop analysis. HFHS offspring exhibited increased body weight and fat mass, with males showing greater adiposity. Lean mass was higher in males, but relative lean mass decreased in both sexes by 22 weeks in response to the HFHS diet. Cardiac assessments revealed load-dependent and load-independent impairments. HFHS exposure increased end-diastolic and end-systolic volumes, reduced ejection fraction, and lowered end-systolic elastance, indicating systolic dysfunction in both sexes. Diastolic function showed sex-specific alterations; HFHS exposure in males led to slower myocardial relaxation (less negative dP/dt min), while in females it increased end-diastolic elastance (Eed), suggesting greater ventricular stiffness. Ventricular–arterial coupling (Ees/Ea) was reduced in HFHS-exposed animals of both sexes, with females showing more pronounced impairments. Our results highlight sex-specific cardiac dysfunction in HFHS-exposed offspring, with females more susceptible to myocardial stiffness and coupling deficits. This underscores the need for sex-tailored interventions to mitigate long-term cardiovascular risks from early-life HFHS exposure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".