Study on resting-state fMRI of leukoaraiosis patients with mild cognitive impairment
Bibliographic record
Abstract
Objective To evaluate the changes of resting-state network connection of leukoaraiosis (LA) patients with or without mild cognitive impairment (MCI) by using functional magnetic resonance imaging (fMRI) and to explore the value of resting-state fMRI in the early diagnosis of LA. Methods A total of 49 LA patients were divided into 2 groups: LA with MCI (LA-MCI, N = 34) and LA with non-MCI (LA-NMCI, N = 15) based on Clinical Dementia Rating Scale (CDR). Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Hamilton Depression Rating Scale-17 Items (HAMD-17) and Hamilton Anxiety Rating Scale-14 Items (HAMA-14) were used to evaluate cognitive function, depression and anxiety symptoms of all patients and 33 normal controls. Resting-state fMRI was used to explore the brain network functional connection. Results The age of LA-MCI patients were significantly older than that of normal controls (P = 0.003). The MMSE (P = 0.001, 0.000) and MoCA (P = 0.001, 0.000) scores in LA-MCI group were significantly higher than those in LA-NMCI group and control group. There was decreased functional connection of nuclei within the salience network in LA-MCI group compared with normal control group. Besides, the connection between salience network and default mode network (DMN) was enhanced, while connection between salience network and central executive network (CEN) was weakened. In LA-NMCI group, there was decreased functional connection of nuclei within the salience network compared with normal control group. Besides, the connection between salience network and DMN was enhanced, while the connection between salience network and CEN was weakened. Conclusions There was significant difference in resting-state fMRI brain network functional connection between normal controls and LA patients with or without MCI. Presumably it could account for the pathophysiological mechanism of LA-related cognitive impairment to some extent. DOI: 10.3969/j.issn.1672-6731.2016.05.004
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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 | 0.000 | 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) | 0.001 | 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".