Dysregulations of C1QA, C1QB, C1QC and C5AR1 as candidate biomarkers of vascular dementia
Bibliographic record
Abstract
Vascular dementia (VaD) is the second most common cause of dementia. Few bioinformatic analysis has been done to explore its biomarkers. This study aimed to excavate potential biomarkers for VaD using bioinformatic analysis and validate them at both animal and patient levels. Based on microarray data of GSE122063, bioinformatic analysis revealed 502 DEGs in the frontal and 674 DEGs in the temporal cortex of VaD patients. Afterward, the hub genes between two regions, including C1QA, C1QB, C1QC, and C5AR1, were dugout. Interestingly, compared with sham mice or controls, the above four complements were highly expressed in the cortices of VaD animals and in the peripheral serum of VaD patients. Moreover, receiver operating characteristic curve analysis conformed to good diagnostic powers of these complements, with C1QB having the most prominent capacity (AUC = 0.799, 95%CI 0.722-0.875). That means the complements, especially subunits of C1Q, might be used as specific early VaD diagnostic biomarkers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".