Altered calcium responses and antioxidant properties in Friedreich’s ataxia-like cerebellar astrocytes
Bibliographic record
Abstract
ABSTRACT Friedreich’s ataxia (FRDA) is a neurodegenerative disorder characterized by severe neurological signs affecting both the peripheral and central nervous system, caused by reduced levels of the frataxin protein (FXN). While several studies highlight cellular dysfunctions in neurons and various other cell types, there is limited information on the effects of FXN depletion in astrocytes and on the potential non-cell autonomous mechanisms affecting neurons in FRDA. In this study, we generated a model of FRDA cerebellar astrocytes to unveil phenotypic alterations that might contribute to cerebellar atrophy and the degeneration of glutamatergic neurons observed in cerebellar dentate nuclei. We treated primary cerebellar astrocytes with an RNA interference-based approach, to achieve a reduction of FXN comparable to that observed in patients. These FRDA-like astrocytes display some typical features of the disease, such as an increase of oxidative stress, as well as specific functional alterations. Notably, cerebellar astrocytes deplete their reduced glutathione content, becoming more susceptible to oxidative insults. Moreover, FRDA-like astrocytes exhibit alterations of calcium homeostasis, with a reduction in calcium content in the intracellular stores and a corresponding change of calcium responses to purinergic stimuli. Our findings shed light on cellular changes caused by FXN downregulation in cerebellar astrocytes, which can interfere with their physiological and complex interaction with neurons. The potentially impaired ability to provide neuronal cells with glutathione or to release neuromodulators and bioactive molecules in a calcium-dependent manner could impact neuronal function and contribute to neurodegeneration.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".