Thiamine deficiency results in metabolic acidosis and energy failure in cerebellar granule cells: An in vitro model for the study of cell death mechanisms in Wernicke's encephalopathy
Bibliographic record
Abstract
Thiamine deficiency (TD) in both humans and experimental animals results in severe compromise of mitochondrial function and leads to selective neuronal cell death in diencephalic and cerebellar structures. To examine further the influence of TD on neuronal survival in relation to metabolic changes, primary cultures of rat cerebellar granule cells were exposed to thiamine-deficient medium for up to 7 days in the absence or presence of the central thiamine antagonist pyrithiamine (Py). Exposure of cells for 7 days to thiamine-deficient medium alone resulted in no detectable cell death. On the other hand, 50 microM Py treatment led to reductions of thiamine phosphate esters, decreased activities of the thiamine-dependent enzymes alpha-ketoglutarate dehydrogenase and transketolase, a twofold increase in lactate release (P < 0.001), a lowering of pH, and significant (58%, P < 0.001) cell death. DNA fragmentation studies did not reveal evidence of apoptotic cell death. Addition of 50 microM alpha-tocopherol (vitamin E) or 100 microM of butylated hydroxyanisole (BHA) to Py-treated cells resulted in significant neuroprotection. On the other hand, addition of 10 microM MK-801, an NMDA receptor antagonist, was not neuroprotective. These results suggest that reactive oxygen species (ROS) play a major role in thiamine deficiency-induced neuronal cell death. Insofar as this experimental model recapitulates the metabolic and mitochondrial changes characteristic of thiamine deficiency in the intact animal, it might be useful in the elucidation of mechanisms involved in the neuronal cell death cascade resulting from thiamine deficiency.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".