Adipose tissue depot specific differences of PLIN protein content in endurance trained rats
Bibliographic record
Abstract
Adipose tissue is classified as either white (WAT) or brown (BAT) and differs not only by anatomical location but also in function. WAT is the main source of stored energy and releases fatty acids in times of energy demand, whereas BAT plays a role in regulating non-shivering thermogenesis and oxidizes fatty acids released from the lipid droplet. The PLIN family of proteins has recently emerged as being integral in the regulation of fatty acid storage and release in adipose tissue. Previous work has demonstrated that PLIN protein content varies among adipose tissue depots, however an examination of endurance training-induced depot specific changes in PLIN protein expression has yet to be done. Male Sprague-dawley rats (n = 10) underwent 8-weeks of progressive treadmill training (18-25 m/min for 30-60 min at 10% incline) or remained sedentary as control. Following training, under isoflurane induced anesthesia epidydmal (eWAT), inguinal subcutaneous (iWAT) and intrascapular brown adipose tissue (BAT) was excised, and plasma was collected. Endurance training resulted in an increase in BAT PLIN5 and iWAT PLIN3 content, while there was no difference in PLIN protein content in endurance trained eWAT. Interestingly, endurance training resulted in a robust increase in ATGL and CGI-58 in eWAT alone. Together these results suggest the potential of a depot specific function of PLIN3 and PLIN5 in adipose tissue in response to endurance training.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".