Subcellular location and colocalization of lipid droplet proteins, ADRP and OXPAT, in resting and stimulated rat soleus
Bibliographic record
Abstract
Skeletal muscle lipid droplet proteins are thought to regulate lipolysis through protein-protein interactions on the lipid droplet surface. In cultured cells ADRP is found only on lipid droplets, while OXPAT (expressed only in oxidative tissues) is found both on and off the lipid droplet, and may be recruited when needed. Our purpose was to determine if OXPAT is recruited to ADRP-coated lipid droplets with contraction, and to investigate the myocellular location and colocalization of OXPAT and ADRP. Rat solei were isolated and assigned one of two groups: 1) a 30 min resting incubation; 2) a 30 min stimulation; 150 ms trains of 0.1ms impulses (60 Hz) at 20 tetani/min for maximal lipid utilization (n=5 each, 25°C). Immunofluorescence microscopy was used to determine subcellular distribution and colocalization. ADRP and OXPAT distribution showed an exponentially higher content from the sarcolemma toward the central region (p<0.001), with no effect of contraction (p=.99). ADRP-OXPAT colocalized at rest and there was no significant difference post stimulation (p=0.11; rest r2=0.64±0.03, stimulated r2=0.71±0.01). There was no difference in either ADRP (p=0.58) or OXPAT (p=0.75) content post stimulation. Contrary to our hypothesis these results show that OXPAT is not recruited to the lipid droplet during contraction and is highly colocalized with ADRP at all times. Supported by NSERC, Canada.
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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) | 0.000 | 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".