Identification of in vivo <i>P</i>‐glycoprotein mRNA decay intermediates in normal liver but not in liver tumors
Bibliographic record
Abstract
Post-transcriptional regulation at the level of mRNA stability is one important mechanism for over-expression of P-glycoprotein (Pgp) genes observed in cultured cells and in animals. A previous study has shown that mRNA half-lives for Pgp genes in normal liver were less than 2 h, in contrast to greater than 12 h measured in a transplantable liver tumor line. This lower turnover rate of Pgp mRNA may, in large part, contribute to the abundance of Pgp mRNA in liver tumors. The current study sought to investigate the underlying mechanism for the lower turnover rate of Pgp2 mRNA previously determined in liver tumors. As a first approach, we set out to understand the Pgp2 mRNA decay in both normal liver and liver tumors by first identifying and characterizing Pgp2 mRNA degradation intermediates. In this study, we showed that the sensitive ligation-mediated polymerase chain reaction (LM-PCR) method can be used to detect a homogenous pool of in vitro transcribed RNA down to 0.4 ng. By employing gene-specific primers in the LM-PCR method, we successfully identified four Pgp2 mRNA decay intermediates in normal liver. All four decay intermediates detected correspond to the 5' coding region of Pgp2 mRNA, and surprisingly no decay intermediates which correspond to 3' untranslated region, 3' coding region or middle coding region were found using LM-PCR. The identified decay intermediates are unique to the normal liver as they were absent or present at very low level in all three liver tumor samples analyzed. This observation supports our previous findings that the Pgp mRNA turnover rate is lower in liver tumors than in normal liver. These findings have implications for our understanding of the regulation of Pgp mRNA turnover in normal and malignant tissues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".