In vitro reactive nitrating species toxicity in dissociated spinal motor neurons from NFL (−/−) and<i>h</i>NFL (+/+) transgenic mice
Bibliographic record
Abstract
We utilized fetal spinal motor neurons isolated from either NFL (-/-) or hNFL (+/+) transgenic mice to determine whether the loss of the low molecular weight neurofilament protein (NFL) places spinal motor neurons at a greater risk for cell death triggered by reactive nitrating species (RNS). After 21 days in serum-free, antibiotic-free medium, both the NFL (-/-) and hNFL (+/+) motor neurons developed neurofilamentous aggregates. Cultures were then exposed to nitric oxide(100 microM NOC 5, 100 microM NOC 12, or 2 mM sodium nitroprusside) or to peroxynitrite (250 mM SIN-1) forvarying intervals. NFL (-/-) cultures demonstrated extensive numbers of apoptotic neurons within six hours and complete cell loss by 24 hours in response to NOC 5 and NOC 12. In contrast, apoptosis was only observed in the motor neurons derived from control (C57bl/6) or hNLF (+/+) mice at 24 hours. In response to 2 mM sodium nitroprusside, necrosis was induced in all cells within 60 minutes. In response to 250 mM SIN-1, both C57bl/6 and hNFL (+/+) cells survived to six hours with only minimal evidence of degeneration while NFL (-/-) motor neurons were necrotic by 60 minutes. These observations suggest that NFL deficient motor neurons are at an enhanced risk of cell death mediated by RNS.
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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) | 0.001 | 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) | 0.001 | 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".