Umkodierung des genetischen Codes mit Selenocystein
Bibliographic record
Abstract
Abstract Der Selenocystein(Sec)‐Einbau in Proteine erfolgt in der Natur durch die kotranslationale Umkodierung eines UGA‐Stopp‐Codons. Diese Studie zeigt nun, dass Sec nicht ausschließlich durch UGA, sondern vielmehr durch 58 aller 64 möglichen Codons kodiert werden kann. Hierbei erlauben 15 Codons nicht nur die vollständige Umkodierung von ihrer ursprünglichen Bedeutung als kanonische Aminosäure zu Selenocystein, sondern sie führen zu Proteinausbeuten, die um mehr als das Zehnfache gesteigert sind. Der hoch effiziente Mechanismus zur Selenocystein‐Rekodierung wird anhand zweier Reporterenzyme, der Escherichia‐coli‐Formiatdehydrogenase und der humanen Thioredoxinreduktase, beschrieben. Da der Selenocysteineinbau an der Position eines UGA‐Stopp‐Codons zwangsläufig mit translationaler Termination konkurriert, war es umso erstaunlicher, dass die Selenocystein‐Einbaumaschinerie während der Umkodierung von Sense‐Codons erfolgreich mit den im Überfluss vorhandenen regulären Aminoacyl‐tRNAs konkurriert.
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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 | 0.001 |
| 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) | 0.001 | 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".