Monocarboxylate transporter 1 and the vulnerability of oligodendrocyte lineage cells to metabolic stresses
Bibliographic record
Abstract
AIMS: Oligodendrocytes, especially oligodendrocyte precursor cells, are known to be sensitive to hypoxic and metabolic stresses. Vulnerability of oligodendrocytes is considered a contributing factor to white matter dysfunction. However, little is known about the energy processing characteristics of oligodendrocyte lineage cells under basal and metabolic stress conditions. The aim of this study was to identify the energy requirements and cellular responses of oligodendrocytes at different developmental stages. METHODS: We compared the metabolic stress responses between myelinating oligodendrocytes (OLs) and oligodendrocyte precursor cells (OPCs). Differential regulation of cellular response was also investigated. RESULTS: We found that, following cerebral ischemia, monocarboxylate transporter 1 (MCT1) expression was upregulated in the peri-infarct striatum but not in the cortex of the brain. In vitro ischemia models were used to induce oligodendrocyte stress as well. An increase in MCT1 expression was detected in OPCs after a mild oxygen-glucose deprivation. Double-labeled immunohistochemical analysis revealed that OPCs and OLs responded differently to metabolic stresses and that the susceptibility to metabolic stresses of OPCs and OLs was associated with their distinct expression profiles of MCT1. CONCLUSION: Taken together, this study shows that MCT1 plays a role in the responses of OPCs and OLs to metabolic and ischemic stresses and suggests that redistribution of energy substrates is a determinant in white matter injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".