Protocol for assessing mitochondrial cholesterol transport and protein molten globule state in steroidogenic and nonsteroidogenic systems
Bibliographic record
Abstract
Steroid hormones are essential for the survival of all mammals for carbohydrate metabolism, stress management, and sexual reproduction. Here, we present a protocol for assessing mitochondrial cholesterol transport and protein molten globule state via measurement of pregnenolone or progesterone synthesis in steroidogenic and nonsteroidogenic cellular systems. We describe steps for cell culture, transfection, and measurement of steroidogenic activity from nonsteroidogenic cells. We then detail procedures for metabolic conversion. For complete details on the use and execution of this protocol, please refer to Bose, 1 Bose et al., 2 Pawlak et al., 3 and Prasad et al. 4 • Steps to determine steroidogenic activity by overexpression in nonsteroidogenic cells • Instructions for identifying a dry molten globule state in living cells • Assay steroidogenic activity and molten globule state of biosynthetic protein(s) Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Steroid hormones are essential for the survival of all mammals for carbohydrate metabolism, stress management, and sexual reproduction. Here, we present a protocol for assessing mitochondrial cholesterol transport and protein molten globule state via measurement of pregnenolone or progesterone synthesis in steroidogenic and nonsteroidogenic cellular systems. We describe steps for cell culture, transfection, and measurement of steroidogenic activity from nonsteroidogenic cells. We then detail procedures for metabolic conversion.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.045 | 0.030 |
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".