Subcutaneous adipose tissue metabolism and pharmacology: a new investigative technique
Bibliographic record
Abstract
According to the Fick principle, any metabolic or hormonal exchange through a given tissue depends on the product of blood flow by arteriovenous difference. Because adipose tissue plays dual storage and endocrine roles, regulation of adipose tissue blood flow (ATBF) is of pivotal importance. Monitoring ATBF in humans can be achieved through different methodologies, such as the (133)Xe washout technique, considered to be the "gold standard", as well as microdialysis and other methods that are not well validated as of yet. This report describes a new method, called "adipose tissue microinfusion" or "ATM", which simultaneously quantifies ATBF by combining the (133)Xe washout technique together with variations of ATBF induced by local infusion of vasoactive agents. The most appropriate site for ATM investigation is the subcutaneous adipose tissue of the anterior abdominal wall. This innovative method conveniently enables the direct comparison of the effects on ATBF of any vasoactive compound, drug, or hormone against a contralateral saline control. The ATM method improves the accuracy and feasibility of physiological and pharmacological studies on the regulation of ATBF in vivo in humans.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".