Increased Frataxin Expression Induced in Friedreich Ataxia Cells by Platinum TALE-VP64s or Platinum TALE-SunTag
Bibliographic record
Abstract
Frataxin gene ( FXN ) expression is reduced in Friedreich's ataxia patients due to an increase in the number of GAA trinucleotides in intron 1. The frataxin protein, encoded by that gene, plays an important role in mitochondria's iron metabolism. Platinum TALE (plTALE) proteins targeting the regulatory region of the FXN gene, fused with a transcriptional activator (TA) such as VP64 or P300, were used to increase the expression of that gene. Many effectors, plTALE VP64 , plTALE p300 , and plTALE SunTag , targeting 14 sequences of the FXN gene promoter or intron 1 were produced. This permitted selection of 3 plTALE VP64s and 2 plTALE SunTag that increased FXN gene expression by up to 19-fold in different Friedreich ataxia (FRDA) primary fibroblasts. Adeno-associated viruses were used to deliver the best effectors to the YG8R mouse model to validate their efficiencies in vivo . Our results showed that these selected plTALE VP64s or plTALE SunTag induced transcriptional activity of the endogenous FXN gene as well as expression of the frataxin protein in YG8R mouse heart by 10-fold and in skeletal muscles by up to 35-fold. The aconitase activity was positively modulated by the frataxin level in mitochondria, and it was, thus, increased in vitro and in vivo by the increased frataxin 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".