Challenges in tackling energy expenditure as obesity therapy: From preclinical models to clinical application
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: A chronic imbalance of energy intake and energy expenditure results in excess fat storage. The obesity often caused by this overweight is detrimental to the health of millions of people. Understanding both sides of the energy balance equation and their counter-regulatory mechanisms is critical to the development of effective therapies to treat this epidemic. SCOPE OF REVIEW: Behaviors surrounding ingestion have been reviewed extensively. This review focuses more specifically on energy expenditure regarding bodyweight control, with a particular emphasis on the organs and attractive metabolic processes known to reduce bodyweight. Moreover, previous and current attempts at anti-obesity strategies focusing on energy expenditure are highlighted. Precise measurements of energy expenditure, which consist of cellular, animal, and human models, as well as measurements of their translatability, are required to provide the most effective therapies. MAJOR CONCLUSIONS: A precise understanding of the components surrounding energy expenditure, including tailored approaches based on genetic, biomarker, or physical characteristics, must be integrated into future anti-obesity treatments. Further comprehensive investigations are required to define suitable treatments, especially because the complex nature of the human perspective remains poorly understood.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it