Conditional NF-L Transgene Expression in Mice for<i>In Vivo</i>Analysis of Turnover and Transport Rate of Neurofilaments
Bibliographic record
Abstract
We generated mice with doxycycline control of a human neurofilament light (NF-L) transgene in the context of the absence (tTA;hNF-L;NF-L(-/-)) or presence (tTA;hNF-L;NF-L(+/-)) of endogenous mouse NF-L proteins. Doxycycline treatment caused the rapid disappearance of human NF-L (hNF-L) mRNA in tTA;hNF-L mice, but the hNF-L proteins remained with a half-life of 3 weeks in the brain. In the sciatic nerve, the disappearance of hNF-L proteins after doxycycline treatment occurred in synchrony along the sciatic nerve, suggesting a proteolysis of NF proteins along the entire axon. The presence of permanent NF network in tTA;hNF-L;NF-L(+/-) mice further stabilized and extended longevity of hNF-L proteins by several months. Surprisingly, after cessation of doxycycline treatment, there was no evidence of leading front of newly synthesized hNF-L proteins migrating into sciatic nerve axons devoid of NF structures. The hNF-L proteins detected at weekly intervals reappeared and accumulated in synchrony at similar rate along nerve segments, a phenomenon consistent with a fast hNF-L transport into axons. We estimated the hNF-L transport rate to be of approximately 10 mm/d in axons devoid of NF structures based on the use of an adenovirus encoding tet-responsive transcriptional activator to transactivate the hNF-L transgene in hypoglossal motor neurons. These results provide in vivo evidence that the stationary NF network in axons is a key determinant of half-life and transport rate of NF proteins.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".