Death of Rat Sympathetic Ganglion Cells <i>In Vitro</i> Caused by Neurite Transection: Effect of Extracellular Calcium
Bibliographic record
Abstract
Calcium entry into neurons secondary to excitotoxic insults is believed to cause neuronal death after trauma and ischemia, but the role of calcium influx in neuronal death after neurite transection independent of excitotoxicity has not been clearly defined. This study assesses the effect of variations in extracellular calcium concentration ([Ca2+]e) from 50 nM to 5 mM on cell death, in 14-day-old cultures of dissociated sympathetic neurons from the superior cervical ganglia of newborn rats. The neurites were transected with a custom-made injury device, and cell death was assessed with propidium iodide and fluorescence microscopy. We found that neurite transection caused a significant increase (p < 0.05) in cell death at all [Ca2+]e studies, but there was no significant difference in mortality at the various [Ca2+]e. Cell death significantly increased between 2 and 24 h postinjury at all three [Ca2+]e. Cell death increased with decreasing distance between the cell body and the transection site, and there was a significant decrease in mortality at distances greater than 0.66 mm, irrespective of the [Ca2+]e. These results suggest that influx of extracellular calcium is not responsible for posttransection cell death, suggesting that calcium release from internal stores or calcium-independent cell death mechanisms are triggered by neurite transection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| 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 | 0.000 |
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".