The Clock Mechanism Influences Neurobiology and Adaptations to Heart Failure in Clock∆19/∆19 Mice With Implications for Circadian Medicine
Bibliographic record
Abstract
Abstract In this study we investigated the role of the circadian mechanism on cognition-relevant brain regions and neurobiological impairments associated with heart failure (HF), using murine models. We found that the circadian mechanism is an important regulator of healthy cognitive system neurobiology. Normal Clock∆19/∆19 mice had neurons with smaller apical dendrite trees in the medial prefrontal cortex (mPFC), and hippocampus, showed impaired visual-spatial memory, and exhibited lower cerebrovascular myogenic tone, versus wild types (WT). We then used the left anterior descending coronary artery ligation model to investigate adaptations in response to HF. Intriguingly, adaptations to neuron morphology, memory, and cerebrovascular tone occurred in differing magnitude and direction between Clock∆19/∆19 and WT mice, ultimately converging in HF. To investigate this dichotomous response, we performed microarrays and found genes crucial for growth and stress pathways that were altered in Clock∆19/∆19 mPFC and hippocampus. Thus these data demonstrate for the first time that (i) the circadian mechanism plays a role in neuron morphology and function; (ii) there are changes in neuron morphology and function in HF; (iii) CLOCK influences neurobiological gene adaptations to HF at a cellular level. These findings have clinical relevance as patients with HF often present with concurrent neurocognitive impairments. There is no cure for HF, and new understanding is needed to reduce morbidity and improve the quality of life for HF patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".