Measurement of Hepatic Protein Fractional Synthetic Rate with Stable Isotope Labeling Technique in Thapsigargin Stressed HepG2 Cells
Bibliographic record
Abstract
Severe burn-induced liver damage and dysfunction is associated with endoplasmic reticulum (ER) stress. ER stress has been shown to regulate global protein synthesis. In the current study, we induced ER stress in vitro and estimated the effect of ER stress on hepatic protein synthesis. The aim was two-fold: (1) to establish an in vitro model to isotopically measure hepatic protein synthesis and (2) to evaluate protein fractional synthetic rate (FSR) in response to ER stress. Human hepatocellular carcinoma cells (HepG2) were cultured in medium supplemented with stable isotopes 1,2-(13)C(2)-glycine and L-[ring-(13)C(6)]phenylalanine. ER stress was induced by exposing the cells to 100 nM of thapsigargin (TG). Cell content was collected from day 0 to 14. Alterations in cytosolic calcium were measured by calcium imaging and ER stress markers were confirmed by Western blotting. The precursor and product enrichments were detected by GC-MS analysis for FSR calculation. We found that the hepatic protein FSR were 0.97 ± 0.02 and 0.99 ± 0.05%/hr calculated from 1,2-(13)C(2)-glycine and L-[ring-(13)C(6)]phenylalanine, respectively. TG depleted ER calcium stores and induced ER stress by upregulating p-IRE-1 and Bip. FSR dramatically decreased to 0.68 ± 0.03 and 0.60 ± 0.06%/hr in the TG treatment group (p<0.05, vs. control). TG-induced ER stress inhibited hepatic protein synthesis. The stable isotope tracer incorporation technique is a useful method for studying the effects of ER stress on hepatic protein synthesis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 0.001 |
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".