Manipulating age-related metabolic flexibility: using pharmacological and dietary interventions
Bibliographic record
Abstract
The world’s population is increasing rapidly as a result of reduced child mortality and extended lifespan. However, the elderly of today are not healthier than their parents at the same age. As a result of excessive food intake, physical inactivity and a decline of metabolic flexibility, over 70% of all elderly suffer from at least one chronic disease, such as diabetes. While the mechanisms behind ageing-induced metabolic decline are still poorly understood, several anti-ageing strategies are currently under investigation for their potential to improve metabolic health. In this thesis, we investigated the effectiveness of several anti-ageing strategies when implemented at an advanced age. Recently, fibroblast growth factors (FGFs) have gained interest as a pharmacological intervention for the treatment of metabolic diseases. Administration of FGF21 or FGF19 successfully reduces symptoms of liver diseases, but could not induced anti-diabetic effects. Using a hepatocyte cell model, this thesis investigated the signalling mechanisms involved after administration of FGF21 and different FGF1-analogues. Furthermore, dietary interventions, such as caloric and protein restriction, have a large impact on metabolic health and flexibility. This thesis highlights the significant improvements in glucose and energy homeostasis of aged mice after these dietary interventions. However, when administrated with a high fat diet, the metabolic flexibility, which allow young mice to compensate, is reduced in aged mice, thereby contributing to the development of metabolic syndrome. Overall, this thesis contributes to the idea that the importance of nutritional quality at advanced ages increases to maintain metabolic health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".