Measuring mRNA translation in neuronal processes and somata by tRNA-FRET
Bibliographic record
Abstract
In neurons, the specific spatial and temporal localization of protein synthesis is of great importance for function and survival. Here, we visualized tRNA and protein synthesis events in fixed and live mouse primary cortical culture using fluorescently-labeled tRNAs. We were able to characterize the distribution and transport of tRNAs in different neuronal sub-compartments and to study their association with the ribosome. We found that tRNA mobility in neural processes is lower than in somata and corresponds to patterns of slow transport mechanisms, and that larger tRNA puncta co-localize with translational machinery components and are likely the functional fraction. Furthermore, chemical induction of long-term potentiation (LTP) in culture revealed up-regulation of mRNA translation with a similar effect in dendrites and somata, which appeared to be GluR-dependent 6 h post-activation. Importantly, measurement of protein synthesis in neurons with high resolutions offers new insights into neuronal function in health and disease states.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".