Brief exposure of neuronal cells to levels of short chain fatty acids observed in human systemic circulation impair the cell lipid metabolism resulting in associated cell death by apoptosis
Bibliographic record
Abstract
Abstract Communication between gut microbiota and the brain is an enigma. Alterations in the gut microbial community affects enteric metabolite levels, such as SCFAs. SCFAs have been proposed as a possible mechanism through which the gut microbiome modulate brain health and function. This study analyzed for the first time the effects of SCFAs at levels reported in human systemic circulation on human neuronal cell energy metabolism, viability, survival and the brain lipidome. Cell and rat brain lipidomics was done using UHPLC-HESI-HRAMS/MS. Neuronal cells viability, survival and energy metabolism were analyzed via flow cytometer, immunofluorescence, and SeahorseXF platform. Lipidomics analysis demonstrated that SCFAs significantly remodeled the brain lipidome in vivo and in vitro. The most notable remodulation was observed in the metabolism of phosphatidylethanolamine plasmalogens, and mitochondrial lipids carnitine and cardiolipin. Increased mitochondrial mass, fragmentation, and hyperfusion occurred concomitant with the altered mitochondrial lipid metabolism resulting in decreased neuronal cell respiration, ATP production, and increased cell death. This suggests SCFAs at levels observed in human systemic circulation can adversely alter the brain lipidome and neuronal cell function potentially negatively impacting brain health outcomes.
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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) | 0.003 | 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".