Increased Expression of GM1 Detected by Electrospray Mass Spectrometry in Rat Primary Embryonic Cortical Neurons Exposed to Glutamate Toxicity
Bibliographic record
Abstract
Neurons within different brain regions have varying levels of vulnerability to external stress and respond differently to injury. A potential reason to explain this may lie within a key lipid class of the cell's plasma membrane called gangliosides. These glycosphingolipid species have been shown to play various roles in the maintenance of neuronal viability. The purpose of this study is to use electrospray ionization mass spectrometry (ESI-MS) and immunohistochemistry to evaluate the temporal expression profiles of gangliosides during the course of neurodegeneration in rat primary cortical neurons exposed to glutamate toxicity. Primary embryonic (E18) rat cortical neurons were cultured to DIV (days in vitro) 14. Glutamate toxicity was induced for 1, 3, 6, and 24 h to injure and kill neurons. Immunofluorescence was used to stain for GM1 and GM3 species, and ESI-MS was used to quantify the ganglioside species expressed within these injured neurons. ESI-MS data revealed that GM1, GM2, and GM3 were up-regulated in neurons exposed to glutamate. Interestingly, using immunofluorescence, we demonstrated that the GM1 increase following glutamate exposure occurred in viable neurons, possibly indicating a potential intrinsic neuroprotective response. To test this potential neuroprotective property, neurons were pretreated with GM1 for 24 h prior to glutamate exposure. Pretreatment with GM1 conferred significant neuroprotection against glutamate-induced cell death. Overall, work from this study validates the use of ESI-MS for cell-derived gangliosides and supports the further development of lipid based strategies to protect against neuron cell death.
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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) | 0.001 | 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".