Bibliographic record
Abstract
Since the discovery of leptin in 1994, a considerable amount of research has focused on leptin as a central regulator of body weight. In the animal model, research has demonstrated leptin action through hypothalamic centres altering both satiety and energy expenditure. In contrast to animal studies, it is unlikely that leptin functioning in the human system exerts such a profound role in body weight regulation. Human studies suggest that leptin levels are strongly correlated with both percentage fat mass and body mass index, in accordance with the proposed 'lipostatic theory'. Current research suggests the existence of a unique inter-relationship between dietary fat, leptin expression and leptin action within the peripheral system. More specifically, it has been demonstrated that polyunsaturated fatty acid (PUFA) intake influences adipose tissue expression of leptin, and of several lipogenic enzymes and transcription factors. In addition, leptin stimulates triglyceride depletion in white adipose tissue without increasing free fatty acid release, thus favouring fatty acids versus glucose as a fuel source. Recent studies suggest that the reduction in adipose hypertrophy observed with n-3 PUFA-containing fish oil feeding might involve a leptin-specific process. A large amount of evidence supports direct functioning of leptin in peripheral lipid metabolism in vivo and in vitro. It is possible that PUFAs will maintain an efficient level of circulating leptin, thus preventing leptin insensitivity and weight gain. There has been much recent progress in clinical leptin research, from energy expenditure to leptin analogue efficacy; the purpose of the present review is to summarize our current understanding of leptin functioning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".