Investigating Changes in the Serum Inflammatory Factors in Alzheimer’s Disease and Their Correlation with Cognitive Function
Bibliographic record
Abstract
BACKGROUND: Serum levels of inflammatory factors, such as C3, C4, C-reactive protein (CRP), immunoglobulin (Ig) G, IgA, and IgM, in patients with Alzheimer's disease (AD) and their correlation with cognitive function remain unexplored. OBJECTIVE: To investigate the expression of serum inflammatory factors in patients with AD and its correlation with cognitive function. METHODS: Serum levels of C3, C4, CRP, IgG, IgA, and IgM in 200 patients with AD (mild, moderate, and severe) and those in 174 normal controls were assessed. Spearman's rank correlation analysis was used to explore the relationships among biomarker levels, cognitive function, and activities of daily living (ADL). RESULTS: Among these inflammatory factors, C3 and CRP levels were significantly lower, and IgG and IgA levels were significantly higher in the AD group than in the control group (p < 0.05). There were no significant differences in C4 and IgM levels between the two groups (p > 0.05). In all participants, CRP level was positively correlated with the Mini-Mental State Examination and Montreal Cognitive Assessment scores (p < 0.05). In the AD group, IgA level was negatively associated with ADL scores (p < 0.05). No significant correlation was detected between the other factors and different cognitive scores (p > 0.05). CONCLUSION: Inflammatory factors C3, CRP, IgG, and IgA have the potential to serve as biomarkers for AD. Furthermore, serum IgA was not only correlated with AD but also with ADL. These results support the hypothesis that inflammation is involved in the occurrence and development of 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 | 0.001 | 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 | 0.000 |
| 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".