Association between diffusion tensor imaging analysis along the perivascular space (DTI-ALPS)-based glial-lymphatic dysfunction and cognitive impairment in non-small cell lung cancer
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To investigate the correlation of glial-lymphatic (glymphatic) system function with cognitive deficits in non-small cell lung cancer (NSCLC). METHODS: Data (demographic, clinical, and magnetic resonance imaging [MRI] information) from 83 NSCLC cases and 96 healthy controls were retrospectively analyzed. We evaluated glymphatic activity by using the diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index and cognitive function with the Montreal Cognitive Assessment (MoCA). Medial Temporal Atrophy (MTA) and Fazekas scores were also rated. Statistical analyses included inter-group comparisons, partial correlation assessments, mediation modeling, and regression to identify predictors of cognitive impairment. RESULTS: NSCLC patients had higher MTA and Fazekas scores but lower MoCA and ALPS index scores than controls (all P < 0.05). The ALPS index was symmetrically reduced in both hemispheres, correlating positively with MoCA (r = 0.276, P = 0.012). In the mediation model, the ALPS index exhibited a partial mediating role (4.6%) in the NSCLC-MoCA association. Older age was an independent predictor of cognitive impairment (odds ratio [OR]: 1.229; 95% confidence interval [CI]: 1.111-1.360). CONCLUSION: In NSCLC patients, glymphatic dysfunction was associated with cognitive impairment, and the DTI-ALPS index may facilitate early detection of these deficits. Advanced age remains a major contributing risk factor.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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