Energy Metabolism in Astrocytes and Neurons Treated with Manganese: Relation among Cell-Specific Energy Failure, Glucose Metabolism, and Intercellular Trafficking Using Multinuclear NMR-Spectroscopic Analysis
Bibliographic record
Abstract
A central question in manganese neurotoxicity concerns mitochondrial dysfunction leading to cerebral energy failure. To obtain insight into the underlying mechanism(s), the authors investigated cell-specific pathways of [1-13C]glucose metabolism by high-resolution multinuclear NMR-spectroscopy. Five-day treatment of neurons with 100-micro mol/L MnCl(2) led to 50% and 70% decreases of ATP/ADP and phosphocreatine-creatine ratios, respectively. An impaired flux of [1-13C]glucose through pyruvate dehydrogenase, which was associated with Krebs cycle inhibition and hence depletion of [4-13C]glutamate, [2-13C]GABA, and [13C]glutathione, hindered the ability of neurons to compensate for mitochondrial dysfunction by oxidative glucose metabolism and further aggravated neuronal energy failure. Stimulated glycolysis and oxidative glucose metabolism protected astrocytes against energy failure and oxidative stress, leading to twofold increased de novo synthesis of [3-13C]lactate and fourfold elevated [4-13C]glutamate and [13C]glutathione levels. Manganese, however, inhibited the synthesis and release of glutamine. Comparative NMR data obtained from cocultures showed disturbed astrocytic function and a failure of astrocytes to provide neurons with substrates for energy and neurotransmitter metabolism, leading to deterioration of neuronal antioxidant capacity (decreased glutathione levels) and energy metabolism. The results suggest that, concomitant to impaired neuronal glucose oxidation, changes in astrocytic metabolism may cause a loss of intercellular homeostatic equilibrium, contributing to neuronal dysfunction in manganese neurotoxicity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".