The Role of Leptin and Adiponectin in Obesity-Associated Cognitive Decline and Alzheimer’s Disease
Bibliographic record
Abstract
Cross-talk between adipose tissue and central nervous system (CNS) underlies the increased risk of obese people to develop brain diseases such as cognitive and mood disorders. Detailed mechanisms for how peripheral changes caused by adipose tissue accumulation in obesity impact the CNS to cause brain dysfunction are poorly understood. Adipokines are a large group of substances secreted by the white adipose tissue to regulate a wide range of homeostatic processes including, but not limited to, energy metabolism and immunity. Obesity is characterized by a generalized change in the levels of circulating adipokines due to abnormal accumulation and dysfunction of adipose tissue. Altered adipokine levels underlie complications of obesity as well as the increased risk for the development of obesity-related comorbidities such as type 2 diabetes, cardiovascular and neurodegenerative diseases. Here, we review the literature for the role of adipokines as key mediators of the communication between periphery and CNS in health and disease. We will focus on the actions of leptin and adiponectin, two of the most abundant and well studied adipokines, in the brain, with particular emphasis on how altered signaling of these adipokines in obesity may lead to cognitive dysfunction and augmented risk for Alzheimer's disease. A better understanding of adipokine biology in brain disorders may prove of major relevance to diagnostic, prevention and therapy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".