The relationship between oxidative stress and imaging markers of brain tissue injury and clinical scores in patients with mild cognitive impairment of the Alzheimer’s type
Bibliographic record
Abstract
There is compelling evidence that oxidative stress, a process which contributes to neuronaldamage and loss, is an early neuropathological event in Alzheimer’s disease. It is thereforeimportant to measure this process in vivo and establish the extent to which it is associated withcognitive deficit and markers of brain tissue injury such as total N-acetylaspartate (tNA) level,whole-brain volume, hippocampal volume, and white matter hyperintensities volume onmagnetic resonance imaging (MRI). Glutathione (GSH), the major antioxidant in the brain, canbe measured in vivo using specialized proton magnetic resonance spectroscopy (MRS)techniques, and decreased GSH can serve as a marker of oxidative stress. We measured GSH,both as a ratio, using intravoxel creatine (Cr) as an internal standard, and using internal waterreferencing to obtain absolute concentrations (in mmol/L) in a group of patients with mildcognitive impairment (MCI) of the Alzheimer’s type. GSH levels were then correlated withestablished imaging markers of injury and cognitive scores. We report significant positivecorrelation between water-referenced GSH and tNA concentrations in both posterior cingulatecortex (PCC) and frontal white matter (FWM) regions and between GSH/Cr and tNA/Cr, inFWM only. No correlation, however, was found with Montreal Cognitive Assessment (MoCA)scores or measures of brain tissue injury. These novel findings suggest that oxidative stress in theMCI stage of Alzheimer’s disease is associated with neuronal metabolic changes but may not yetbe marked enough to be associated with brain or hippocampal volume changes or cognitiveimpairment
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".