Recent advances in the detection of brown adipose tissue in adult humans: a review
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
The activation of brown adipose tissue (BAT) is associated with reductions in circulating lipids and glucose in rodents and contributes to energy expenditure in humans indicating the potential therapeutic importance of targetting this tissue for the treatment of a variety of metabolic disorders. In order to evaluate the therapeutic potential of human BAT, a variety of methodologies for assessing the volume and metabolic activity of BAT are utilized. Cold exposure is often utilized to increase BAT activity but inconsistencies in the characteristics of the exposure protocols make it challenging to compare findings. The metabolic activity of BAT in response to cold exposure has most commonly been measured by static positron emission tomography of 18F-fluorodeoxyglucose in combination with computed tomography (18F-FDG PET-CT) imaging, but recent studies suggest that under some conditions this may not always reflect BAT thermogenic activity. Therefore, recent studies have used alternative positron emission tomography and computed tomography (PET-CT) imaging strategies and radiotracers that may offer important insights. In addition to PET-CT, there are numerous emerging techniques that may have utility for assessing BAT metabolic activity including magnetic resonance imaging (MRI), skin temperature measurements, near-infrared spectroscopy (NIRS) and contrast ultrasound (CU). In this review, we discuss and critically evaluate the various methodologies used to measure BAT metabolic activity in humans and provide a contemporary assessment of protocols which may be useful in interpreting research findings and guiding the development of future studies.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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