Outdoor Temperature, Age, Sex, Body Mass Index, and Diabetic Status Determine the Prevalence, Mass, and Glucose-Uptake Activity of 18F-FDG-Detected BAT in Humans
Bibliographic record
Abstract
CONTEXT: In humans, the prevalence, mass, and glucose-uptake activity of (18)F-fluorodeoxyglucose ((18)F-FDG)-detected brown adipose tissue (BAT), which are expectedly enhanced by a cold stimulus, also appear modulated by other factors that still have to be disentangled. OBJECTIVE: The objective of the study was to investigate the factors determining the prevalence, mass, and glucose-uptake activity of (18)F-FDG-detected BAT in humans. RESEARCH DESIGN AND METHODS: We retrospectively analyzed all (18)F-FDG positron emission tomography/computed tomography examinations performed between January 2007 and December 2008 at our institution for (18)F-FDG uptake within the cervical/supraclavicular, mediastinal, paravertebral, and perirenal fat areas. The influence of outdoor temperature, sex, age, body mass index (BMI), plasma glucose level, diabetes diagnosis, day length, and cancer status on the prevalence, mass, and glucose-uptake activity of (18)F-FDG-detected BAT depots was investigated. RESULTS: Three hundred twenty-eight of the 4842 patients (6.8%) had (18)F-FDG-detected BAT. The prevalence of (18)F-FDG BAT was negatively associated with outdoor temperature (P < 0.0001), age (P < 0.0001), BMI (P < 0.0001), and diabetes status (P = 0.0003). Moreover, there was a significant age × sex interaction for the prevalence of (18)F-FDG BAT (the younger the subjects, the greater the sex difference). The mass and glucose-uptake activity of (18)F-FDG-detected BAT also decreased with increasing outdoor temperature (P < 0.0001), age (P < 0.0001), and BMI (P < 0.0001). They were lower in men than in women (P < 0.001) and lower in diabetic than in nondiabetic patients (P = 0.0002). CONCLUSIONS: The present study identifies outdoor temperature, age, sex, BMI, and diabetes status as determinants of the prevalence, mass, and glucose-uptake activity of (18)F-FDG-detected BAT.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".