CSF TNF-α Levels Were Associated with Longitudinal Change in Brain Glucose Metabolism Among Non-Demented Older People
Bibliographic record
Abstract
Pan Fu, Bihong Zhu, Yangping Huang On behalf of Alzheimer’s Disease Neuroimaging InitiativeDepartment of Neurology, Taizhou First People’s Hospital, Taizhou, Zhejiang, People’s Republic of ChinaCorrespondence: Yangping HuangDepartment of Neurology, Taizhou First People’s Hospital, 218 Hengjie Road, Huangyan District, Taizhou City, Zhejiang Province, People’s Republic of ChinaEmail hypnihao@163.comPurpose: Emerging studies have suggested that tumor necrosis factor-alpha (TNF-α) is implicated in the pathogenesis of Alzheimer’s disease (AD), and that cerebral glucose hypometabolism is a key feature of AD. However, the association of CSF TNF-α levels with changes in cerebral glucose metabolism has not been studied among non-demented older people.Patients and Methods: At baseline, there were a total of 214 non-demented older people from Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. We examined the cross-sectional and longitudinal associations of CSF TNF-α with global cognition (as assessed by mini-mental state examination), verbal memory (as assessed by Rey Auditory Verbal Learning Test-total learning score), and cerebral glucose metabolism (as measured by FDF-PET). Linear mixed-effects models were used to examine the longitudinal association of CSF TNF- α with change in each outcome over time with adjustment of age, educational level, gender, and APOE4 status.Results: In the cross-sectional study, CSF TNF-α was negatively associated with MMSE scores, but not verbal memory or FDG-PET. In the longitudinal study, higher CSF TNF- α at baseline was associated with a faster decline in cerebral glucose metabolism, but not MMSE scores or RAVLT total learning scores.Conclusion: Higher CSF TNF-α levels were associated with a steeper decline in cerebral glucose metabolism among non-demented older people.Keywords: mild cognitive impairment, Alzheimer’s disease, TNF-α, cerebral glucose metabolism, FDG-PET
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".