Bibliographic record
Abstract
Impairments of learning and memory are among the most salient outcomes of the natural aging process. Particularly among humans who have experienced dramatic increases in lifespan over the last century, age-associated cognitive decline has become especially problematic in our increasingly elderly population. To mitigate the impact of these demographic changes, understanding of the fundamental biology that underlies the aging process is essential. The aim of the research presented in this thesis is to provide a new perspective on the foundational biological processes that contribute to age-related declines in cognitive function. In this regard, mitochondrial dysfunction and resulting oxidative stress have been widely implicated in the cellular and molecular deterioration of aging cells including neurons. Yet, how these phenomena arise and translate to the neuronal and behavioural dysfunction observed in aging animals remains an open question. The research conducted here integrates existing knowledge of biological aging with the novel idea that mechanisms surrounding lipid (dys)homeostasis play a prominent role in cognitive outcomes of aging. Using the gastropod model system Lymnaea stagnalis, the general hypothesis that deregulation of lipid homeostasis contributes to neuronal and behavioural impairment is investigated. Briefly, evidence is provided for the following ideas. 1) Neurons do not generally rely on lipids to meet energy requirements, yet mitochondrial fatty acid metabolism (β-oxidation) is important for the maintenance of metabolic reserve capacity and excess lipid management. In aging neurons, this is compromised as β-oxidation capacity declines. 2) Mitochondria are often considered the “seat of senescence”; however, plasma membrane lipid peroxidation and associated phospholipase A2 activity is involved with producing characteristics of age-related mitochondrial dysfunction, suggesting an extra-mitochondrial origin of biological aging. These changes may arise due to ailing β-oxidation capabilities in old neurons, and subsequent uncoupling of oxidative phosphorylation in a fatty acid-dependent manner. 3) β-oxidation dysfunction has wide-ranging implications for fatty acid-sensitive biological functions, such as ion channel function. The KATP potassium channels are particularly sensitive to activation by fatty acids, and directly translate β-oxidation failures to age-associated declines in neuronal excitability and long-term memory formation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".