Brain morphometric and metabolic changes in Subjective Cognitive Decline individuals
Bibliographic record
Abstract
Abstract Background Subjective cognitive decline (SCD) is defined as a memory complaint in individuals without an objective measure of cognitive impairment. In this study, we investigated the morphometric and metabolic brain changes in individuals presenting with SCD. Method Age and sex matched structural MRI and [18F]FDG PET images from SCD and CU (n = 101, per group) were extracted from the ADNI database. We built general linear models corrected for multiple comparisons with 10,000 Monte‐Carlo simulations to verify differences in cortical thickness between groups, using age as a covariate (Freesurfer’s v7.1.1). Metabolic analysis was performed using voxel‐wise general linear models comparing the SUVR of the FDG signal, correcting for age and APOE4 allele carrying status, using the MINC toolkit and the R statistical program. Result SCD and CU groups presented similar age, sex, years of education, CSF AD‐related protein levels (amyloid beta 1‐42, p‐tau and tau), and Clinical Dementia Rating – Sum of Boxes score (Table 1). Compared to CU individuals, SCD subjects showed increased cortical thickness in the right hemisphere rostral middle frontal gyrus (Figure 1), while glucose metabolism was increased in the right medial temporal lobe, including the hippocampus, and right occipital cortex (Figure 2). Conclusion Individuals with SCD present cortical hypertrophy in the rostral middle frontal gyrus and glucose hypermetabolism in the medial temporal lobe and occipital cortex, all in the right hemisphere. Previous studies suggest that these areas play a role in personality and humor, and may be altering self‐perception of cognitive decline. At the biological level, given the high concentration of astrocytes in these areas, such changes may suggest a scenario of astrocyte reactivity. More specifically, astrocyte hypertrophy may account for increased cortical thickness and glucose uptake. In summary, we provide neuroimaging evidence of structural and functional changes in individuals with SCD, suggesting early astrocyte reactivity.
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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 | 0.001 | 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".