Stearoyl‐CoA desaturase inhibition leads to fatty acids normalization and improves dendritic spine density in the hippocampus of 5xFAD mouse model
Bibliographic record
Abstract
BACKGROUND: Alterations in brain lipids are a central feature of Alzheimer's disease (AD), nevertheless therapeutic strategies targeting brain lipid metabolism are still lacking. Our lab recently reported that a pharmacological inhibitor of the fatty acid enzyme, stearoyl-CoA desaturase (SCD), led to recovery of hippocampal synapses with associated improvements in learning and memory in the slow-progressing 3xTg-AD mouse model. Here, we used the 5xFAD rapidly progressing AD model to further delve into lipid metabolism disruptions in AD, and into the effect of the SCD inhibitor (SCDi) on fatty acid (FA) alterations and synapse loss. METHOD: Hippocampi from 5xFAD and non-carrier control mice were collected at 5 and 8 months old (MO) for FA profiling by gas chromatography-flame ion detection (GC-FID) and for IHC for b-amyloid, GFAP (astrocytes) and Iba-1 (microglia). SCDi or vehicle was infused via intracerebroventricular osmotic pumps for 28 days in 5 MO 5xFAD and NC mice, and their hippocampi were processed for GC-FID and Golgi staining for dendritic spine quantification. RESULT: FA alterations were apparent in female hippocampus at 5 MO (together with plaque pathology and gliosis) and worsened by the age at 8 MO, while males first showed FA alterations at 8MO (Figure 1). The C16:1/C16:0 desaturation index, parameter associated to SCD enzymatic activity, showed a significant increase in 5xFAD mice at 8 MO, but starting at 5MO in females. Treating 5xFAD females' mice with SCDi improved dendritic spine density and normalized FA levels (Figures 2 and 3). CONCLUSION: These data demonstrate that SCD inhibitor treatment in a second AD mouse model, the more aggressive 5xFAD model, has beneficial effects on FA alterations and hippocampal dendritic spines. These findings add to accumulating data supporting SCD inhibition as a promising novel therapeutic target for AD.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".