Regulation of the peripheral myelin protein-22 gene
Bibliographic record
Abstract
Peripheral Myelin Protein-22 (PMP22) is a relatively major component of peripheral nerve myelin. Either missense mutations or duplication of the PMP22 gene can be the cause of Charcot-Marie-Tooth disease type 1 A (CMT1A). The control of PMP22 expression could be a basis for treatment. The aim of my research is to understand the regulation of the PMP22 gene in a transgenic mouse model. Initially, -8.5 kb 5' flanking sequence of the rat Pmp22 gene was used to drive reporter gene expressed in transgenic mice. This construct confers tissue specificity, weak developmental regulation, weakly detectable levels of expression in the dorsal root ganglia (DRG), but not the expected up-regulation during nerve regeneration. Secondly, I generated transgenic mice using -21 kb 5' Pmp22 flanking sequence. This construct confers robust reporter gene expression in the peripheral nervous system (PNS), and little to the DRGs in one line. The other lines show weak expression in the PNS, and stronger expression in the DRGs. Thirdly, I targeted a 21 kb Pmp22 promoter/reporter transgene to the hypoxanthine phosphorybosyl transferase (Hprt) locus in male embryonic stem cells. Using this methodology, I obtained a line carrying -21 kb of Pmp22 promoter driving beta-galactosidase gene in the hprt locus. This line confers expression similar to the four lines derived by pronuclear injection carrying the same construct. Fourthly, I introduced the LacZ reporter gene at the start codon of Pmp22 in a 100 kb bacterial artificial chromosome (BAC). Six transgenic lines were produced and analyzed, showing embryonic and postnatal developmental regulation, and high level of expression in the PNS similar to endogenous Pmp22 expression. From my results and the literature, I suggest that (1) the stretch of -10.5 to -21 kb could carry repressor(s), (2) there is (a) positive element(s) that lie(s) between -8.5 and -10.5 kb, and (3) 3' element(s) are important for Pmp22 expression.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".