Is Matrix Metalloproteinase-9 Associated with Post-Stroke Cognitive Impairment or Dementia?
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Bibliographic record
Abstract
BACKGROUND: Matrix metalloproteinase-9 (MMP-9) is a significant protease required for synaptic plasticity, learning, and memory. Yet, the role of MMP-9 in the occurrence and development of cognitive decline after ischemic stroke is not fully understood. In this study, we used clinical data experiments to further investigate whether MMP-9 and genetic polymorphism are associated with post-stroke cognitive impairment or dementia (PSCID). MATERIALS AND METHODS: A total of 148 patients with PSCID confirmed by the Montreal Cognitive Assessment (MoCA) 3 months after onset (PSCID group) were included in the study. The MMP-9 rs3918242 polymorphisms were analyzed using polymerase chain reaction coupled with restriction fragment length polymorphism, and the serum level of MMP-9 was measured using enzyme-linked immunosorbent assay (ELISA). The same manipulations have been done on 169 ischemic stroke patients without cognitive impairment (NCI group) and 150 normal controls (NC group). RESULTS: < 0.05). Diabetes mellitus, hyperhomocysteinemia, and increased serum MMP-9 levels were the main risk factors of cognitive impairment after ischemic stroke. The serum level of MMP-9 was negatively correlated with the MoCA score, including visual-spatial executive, naming, attention, language, and delayed recall. Genetic polymorphism showed that TC genotype with MMP-9 rs3918242 and CC genotype were associated with a significantly increased risk of PSCID; moreover, the TC genotype significantly increased the risk of cognitive impairment. In the TCCC genotype of MMP-9 rs3918242, diabetes mellitus and hyperhomocysteinemia were associated with the increased risk of PSCID; also, hyperhomocysteinemia could increase the risk of cognitive impairment. CONCLUSIONS: MMP-9 level and MMP-9 rs3918242 polymorphism have an important role in the occurrence and development of post-stroke cognitive impairment or dementia (PSCID).
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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 it