IC‐P‐164: GLUTAMATERGIC CONCENTRATION AS A BIOMARKER OF MEMORY PERFORMANCE IN AGING INDIVIDUALS
Bibliographic record
Abstract
Episodic memory impairment is a predominant symptom of Alzheimer Disease (AD). Glutamatergic transmission mediates a wide range of neural events involved in episodic memory, such as long-term potentiation. In the current study, we aimed to define if glutamatergic concentration in the BA9 region or the hippocampus, as measured with magnetic resonance spectroscopy (MRS), could predict memory variations in the normal aging population. 22 subjects aged between 55-80 years underwent two MRS within a single scanning session, using a Siemens 3T scanner and a 32-Channel head coil. Spectra were acquired separately, using the PRESS sequence with an echo-time of 80ms, from a 20x20x20mm3 voxel in the right BA9 region and a 15x12x25mm3 in the right hippocampus. Analysis was performed using LCModel. Memory was assessed with the Rey Auditory Verbal Learning Test. Linear regressions, using age and education as covariates, were performed to determine if glutamate concentration could accurately predict memory scores (total learning and delayed recall). All 22 scans resulted in a valid estimation (cramer-rao lower bound (CRLB) < 20%) of BA9 glutamatergic concentration. Due to limitations associated with MRS in the hippocampus, a more liberal threshold was used (CRLB < 40%). Using this threshold, 15 scans yielded a valid measure of hippocampal glutamate. A regression analysis showed that hippocampal glutamate concentration and education were significant predictors of both memory scores. Age was not found to be a significant predictor in that model. The overall model fit was of R 2 = 0.76 for the total learning and of R 2 = 0.75 for the delayed recall. A second regression analysis showed that BA9 glutamate and education were also significant predictors of memory performance. Again, age did not significantly contribute to the model. The overall fit was of R 2 = 0.48 for the total learning and of R 2 = 0.59 for the delayed recall. Our results suggest that glutamatergic transmission in the hippocampus and BA9 is a significant predictor of memory performance in aging individuals. This approach should be investigated for its use as a biomarker of cognitive decline in subjects at risk of dementia. Future directions and limitations will be further discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".