Evaluation of the glymphatic system using the DTI-ALPS index in type 2 diabetes mellitus-induced cognitive impairment
Bibliographic record
Abstract
Objectives: The objective of the study is to assess the utility of the perivascular space diffusion tensor imaging - along the perivascular space (DTI-ALPS) index in evaluating the activity of the brain glymphatic system in patients with type 2 diabetes mellitus (T2DM) and cognitive impairment. Material and Methods: This study included 40 T2DM patients with cognitive impairment and 40 healthy controls (HCs). All participants underwent DTI, and the DTI-ALPS index was calculated based on relevant DTI parameters. Statistical analyses were performed using the Statistical Package for the Social Sciences version 26.0, with significance set at P < 0.05. Results: The DTI-ALPS index in T2DM patients with cognitive impairment were significantly lower than that of the HCs. A significant negative correlation was observed between the DTI-ALPS index and glycated hemoglobin levels, while positive correlations were found with vitamin D, Montreal Cognitive Assessment scores, and high-density lipoprotein cholesterol levels. Conclusion: This study confirms glymphatic dysfunction in T2DM patients with cognitive impairment, as indicated by the reduced DTI-ALPS index. Furthermore, it demonstrates the feasibility of utilizing the DTI-ALPS method to assess glymphatic system activity in this patient population.
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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".