Dorsolateral prefrontal cortex metabolites and their relationship with plasticity in Alzheimer’s disease
Bibliographic record
Abstract
Abstract Background Previous studies have shown that patients with Alzheimer’s disease (AD) present with deficits in neuroplasticity of their dorsolateral prefrontal cortex (DLPFC); and decreased N‐acetyl aspartate (NAA) and increased myo‐inositol (mI) concentrations in the cingulate cortex and hippocampus. In this study, we examined the relationship between these metabolites and neuroplasticity in the DLPFC of patients with AD and healthy older adults. Method Patients meeting the core clinical criteria for probable AD and older healthy controls (HC) were recruited. Left DLPFC plasticity was assessed using paired associative stimulation (PAS) combined with EEG. NAA and mI concentrations were assessed in the DLPFC using 3T proton Magnetic Resonance Spectroscopy (point‐resolved spectroscopy, echo time = 35 ms). Result 48 AD participants (mean (SD) age: 75.4 (6.9) years; mean (SD) Mini Mental State Examination (MMSE) score (SD): 23.1 (3.1)) were compared with 27 HC (mean (SD) age: 72.3 (7.0) years; mean (SD) MMSE: 29.5 (0.6)): participants with AD had impaired DLPFC plasticity (t = 2.8, df = 69, p = 0.006) and decreased NAA concentration in the DLPFC (t = 2.4, df = 64, p = 0.02). In the combined group of AD and HC participants, after correcting for multiple comparisons, mI concentration in the DLPFC was negatively correlated with DLPFC plasticity (Pearson’s r = ‐ 0.4, n = 62, p corrected = 0.002). Conclusion Deficits in neuroplasticity in the DLPFC of patients with AD are associated with abnormalities of a metabolite indicative of neuronal injury. These findings advance our understanding of potential mechanisms underlying deficits in DLPFC plasticity in 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 | 0.001 |
| 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".