The correlation between age ⁃ related white matter changes and number of circulating endothelial progenitor cells and cognitive function
Bibliographic record
Abstract
Objective To explore the pathogenesis of age⁃related white matter changes (ARWMC), and to investigate the correlation between ARWMC and the number of circulating endothelial progenitor cells (EPCs) and cognitive function in order to provide evidence for early prevention and treatment of ARWMC and cognitive impairment in elderly people. Methods Forty patients with ARWMC were confirmed by CT or MRI. The number of circulating EPCs was measured by flow cytometry. The cognitive function was evaluated by Mini ⁃ Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). One way analysis of variance (ANOVA) of completely random design and χ2 test of R × C tabular data were used to select single factor. Logistic regression (backward) was performed to determine the risk factors for ARWMC. Results Flow cytometry showed that the number of circulating EPCs reduced in patients with ARWMC, especially in severe group (29.50 ± 6.26), and there was statistically significant difference compared with control group (70.50 ± 8.71) and mild⁃to⁃moderate group (58.99 ± 7.78; P = 0.000, for all). The number of circulating EPCs was negatively correlated with the severity of ARWMC (r = ⁃ 0.562, P = 0.001). The scores of MMSE (23.85 ± 2.35) and the scores of MoCA (19.80 ± 3.38) in severe group were significantly lower than control group (27.10 ± 1.80, 26.60 ± 1.23, respectively) and mild⁃to⁃moderate group (25.80 ± 2.02, 23.30 ± 2.87, respectively), and there was statistically significant difference between groups (P < 0.05, for all). Cognitive impairment was mainly presented on visuoconstructional and executive functions, delayed recall and orientation. Conclusion The change of the number of circulating EPCs can be a predictive factor for ARWMC, and it is a potential predictor of the severity of ARWMC. The decrease of the circulating EPCs may be an important pathogenesis of ARWMC, and also the important causation of cognitive impairment in elderly people. DOI：10.3969/j.issn.1672-6731.2010.03.015
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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) | 0.002 | 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".