Investigating the effects of expressing APE1 human population variants in cellular systems.
Bibliographic record
Abstract
Apurinic/apyrimidinic endonuclease 1 (APE1) is a multi-functional mammalian protein which has recently been shown to possess the ability to endonucleolytically cleave single-stranded RNA and abasic RNA. Several population variants of APE1 (L104R, E126D and D148E) are known to exist in the human population. L104R and E126D have been linked to Amyotrophic Lateral Sclerosis while D148E has been linked to various cancers. The exact molecular mechanisms which correlate these variants with human disease are currently unknown. Recent evidence has shown that the in vitro endoribonuclease activities of these variants are different from the wild-type APE1 protein. Here, we hypothesize that the altered endoribonuclease activity of APE1 population variants may be associated with phenotype changes leading to disease pathogenesis. The goal of this thesis was to determine whether APE1 population variants can cause an altered phenotype when expressed in prokaryotic (Origami™ (DE3) cells) and eukaryotic systems (HeLa cervical cancer and HepG2 hepatoma cancer cell lines). Subsequently, these changes were to be linked to altered endoribonuclease activity of these variants. Using two separate assays, it was shown that the L104R and E126D variants possess enhanced cytotoxicity to Origami™ (DE3) cells. This correlates with their distinct endoribonuclease activity demonstrated in vitro. The D148E variant, which had lost endoribonuclease activity, had no effect on colony formation and growth of Origami™(DE3) cells. Interestingly, this study also showed that, when over-expressed, the L104R and E126D variants are capable of causing enhanced growth in the mammalian HepG2 cells. Preliminary microarray and quantitative real time polymerase chain reaction experiments were conducted in an attempt to understand the mechanism for the L104R-induced cell growth in HepG2 cells. Unfortunately, the results were inconclusive. In summary, this thesis has demonstrated a solid correlation between having distinct endoribonuclease act
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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 | 0.001 |
| 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".