Brown Adipose Tissue—A Translational Perspective
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
Brown adipose tissue (BAT) displays the unique capacity to generate heat through uncoupled oxidative phosphorylation that makes it a very attractive therapeutic target for cardiometabolic diseases. Here, we review BAT cellular metabolism, its regulation by the central nervous and endocrine systems and circulating metabolites, the plausible roles of this tissue in human thermoregulation, energy balance, and cardiometabolic disorders, and the current knowledge on its pharmacological stimulation in humans. The current definition and measurement of BAT in human studies relies almost exclusively on BAT glucose uptake from positron emission tomography with 18F-fluorodeoxiglucose, which can be dissociated from BAT thermogenic activity, as for example in insulin-resistant states. The most important energy substrate for BAT thermogenesis is its intracellular fatty acid content mobilized from sympathetic stimulation of intracellular triglyceride lipolysis. This lipolytic BAT response is intertwined with that of white adipose (WAT) and other metabolic tissues, and cannot be independently stimulated with the drugs tested thus far. BAT is an interesting and biologically plausible target that has yet to be fully and selectively activated to increase the body's thermogenic response and shift energy balance. The field of human BAT research is in need of methods able to directly, specifically, and reliably measure BAT thermogenic capacity while also tracking the related thermogenic responses in WAT and other tissues. Until this is achieved, uncertainty will remain about the role played by this fascinating tissue in human cardiometabolic diseases.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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