Redox profiles of amyotrophic lateral sclerosis lymphoblasts with or without known SOD1 mutations
Bibliographic record
Abstract
BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly progressing neurodegenerative disease that affects motor neurons. This disease is associated with oxidative stress especially in mutant superoxide dismutase 1 (mutSOD1) patients. However, less is known for the most prevalent sporadic ALS form, due to a lack of disease models. Here, we studied oxidative stress profiles in lymphoblasts from ALS patients with mutSOD1 or unknown (undSOD1) mutations. METHODS: mutSOD1 and undSOD1 lymphoblasts, as well as sex/age-matched controls (3/group) were obtained from Coriell and divided into 46 years-old-men (C1), 46 years-old-women (C2) or 26/27 years-old-men (C3) cohorts. Growth curves were performed, and several parameters associated with redox homeostasis were evaluated, including SOD activity and expression, general oxidative stress levels, lipid peroxidation, response to oxidative stimulus, glutathione redox cycle, catalase expression, and activity, and Nrf2 transcripts. Pooled (all cohorts) and paired (intra-cohort) statistical analyses were performed, followed by clustering and principal component analyses (PCA). RESULTS: Although a high heterogeneity among lymphoblast redox profiles was found between cohorts, clustering analysis based on 7 parameters with high chi-square ranking (total SOD activity, oxidative stress levels, catalase transcripts, SOD1 protein levels, metabolic response to mM concentrations of tert-butyl hydroperoxide, glutathione reductase activity, and Nrf2 transcript levels) provided a perfect cluster segregation between samples from healthy controls and ALS (undSOD1 and mutSOD1), also visualized in the PCA. CONCLUSIONS: Our results show distinct redox signatures in lymphoblasts from mutSOD1, undSOD1 and healthy controls that can be used as therapeutic targets for ALS drug development.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".