Effect of Mutated Cu, Zn Superoxide Dismutase (SOD1G93A) on Modulation of Transductional Pathway Mediated by M1 Muscarinic Receptor in SK-N-BE and NSC-34 Cells
Bibliographic record
Abstract
The constitutive secretion of antioxidant Cu-Zn Superoxide dismutase (SOD1) has been widely demonstrated in many cellular lines. In addition, we showed that as well as the basal SOD1 secretion, this enzyme is also exported through depolarization of excitable cells by high extracellular K concentration. Recent data showed that SOD1 was able to activate muscarinic M1 receptor producing the activation, via phospholipase C, of ERK1-2 and AKT pathways. It is also known that about 20% of familial amyotrophic lateral sclerosis (fALS) is due to mutations in the gene coding for SOD1. The aim of the present research is to evaluate whether, analogously to wild type SOD1 (SOD1wt), the mutated form of SOD1G93A is able to activate ERK1-2 and AKT through muscarinic M1 receptor in SK-N-BE as well as in motoneuron like NSC-34. Our results demonstrated that in NSC-34 and SK-N-BE cells mutated SOD1G93A carried out a more evident activation of ERK1-2 and AKT and a stronger increase of intracellular calcium levels compared to SOD1WT; we also demonstrated that these effects are mediated by the M1 receptor as shown using pyrenzepine, a specific M1 inhibitor and the calcium chelator BAPTA. Of note, M1 receptor pathway activation by SOD1G93A, but not by SOD1WT, is associated with both an increase of reactive oxygen species and a cytotoxic effect.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
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".