Evidence from Computer Simulations for Alterations in the Membrane Biophysical Properties and Dendritic Processing of Synaptic Inputs in Mutant Superoxide Dismutase-1 Motoneurons
Bibliographic record
Abstract
A critical step in improving our understanding of the development of amyotrophic lateral sclerosis (ALS) is to identify the factors contributing to the alterations in the excitability of motoneurons and assess their individual contributions. Here we investigated the early alterations in the passive electrical and morphological properties of neonatal spinal motoneurons that occur by 10 d after birth, long before disease onset. We identified some of the factors contributing to these alterations, and estimated their individual contributions. To achieve this goal, we undertook a computer simulation analysis using realistic morphologies of reconstructed wild-type (WT) and mutant superoxide dismutase-1 (mSOD1) motoneurons. Ion channel parameters of these models were then tuned to match the experimental data on electrical properties obtained from these same motoneurons. We found that the reduced excitability of mSOD1 models was accompanied with decreased specific membrane resistance by approximately 25% and efficacy of synaptic inputs (slow and fast) by 12-22%. Linearity of summation of synaptic currents was similar to WT. We also assessed the contribution of the alteration in dendritic morphology alone to this decreased excitability and found that it reduced the input resistance by 10% and the efficacy of synaptic inputs by 7-15%. Our results were also confirmed in models with dendritic active conductances. Our simulations indicated that the alteration in passive electrical properties of mSOD1 models resulted from concurrent alterations in their morphology and membrane biophysical properties, and consequently altered the motoneuronal dendritic processing of synaptic inputs. These results clarify new aspects of spinal motoneurons malfunction in ALS.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".