Palmitate and ceramide induce human monocytic cell toxicity towards neuronal cells
Bibliographic record
Abstract
Obesity is associated with increased risk of Alzheimer's disease (AD) but the mechanisms linking these conditions are poorly understood. Levels of saturated fatty acids and their metabolites (e.g., ceramides) are elevated in obesity and can induce inflammation in peripheral immune cells. Brain inflammation, which is mediated by activation of glial cells, is increased in AD. Our aim was to determine if elevated levels of saturated fatty acids or ceramides could induce inflammation and cause neurotoxin secretion from glial cells. Human THP‐1 monocytes and U‐ 373MG astrocytoma cell lines were used to model microglia and astroctyes, respectively. Incubation of THP‐1 cells, but not U‐ 373MG cells, with 125–250 μM palmitate for 48 h increased secretion of the pro‐inflammatory cytokines MCP‐1 and IL‐8 ( p <0.001). Transfer of conditioned media from palmitate‐treated THP‐1 cells to SH‐SY5Y neuroblastoma cells caused a significant increase in neuronal cell death ( p <0.001). Palmitate had no effect on U‐373 MG cell‐mediated neurotoxicity ( p >0.05). Similar to palmitate, treatment of THP‐1 cells with C2 ceramide significantly increased neurotoxicity ( p <0.001). These results indicate that increased circulating levels of palmitate or ceramides in obesity may contribute to neurodegeneration through inflammatory pathways involving microglia. Supported by the NSERC
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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) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".