Alterations of white matter integrity in adults with major depressive disorder: a magnetic resonance imaging study
Bibliographic record
Abstract
OBJECTIVE: The purpose of our study was to investigate alterations of white matter integrity in adults with major depressive disorder (MDD) using magnetic resonance imaging (MRI). METHODS: We performed diffusion tensor imaging with a 3T MRI scanner on 45 patients with major depression and 45 healthy controls matched for age, sex and education. Using a voxel-based analysis, we measured the fractional anisotropy (FA), and we investigated the differences between the patient and control groups. We examined the correlations between the microstructure abnormalities of white matter and symptom severity, age of illness onset and cumulative illness duration, respectively. RESULTS: We found a significant decrease in FA in the left hemisphere, including the anterior limb of the internal capsule and the inferior parietal portion of the superior longitudinal fasciculus, in patients with MDD compared with healthy controls. Diffusion tensor imaging measures in the left anterior limb of the internal capsule were negatively related to the severity of depressive symptoms, even after we controlled for age and sex. CONCLUSION: Our findings provide new evidence of microstructural changes of white matter in non-late-onset adult depression. Our results complement those observed in late-life depression and support the hypothesis that the disruption of cortical- subcortical circuit integrity may be involved in the etiology of major depressive disorder.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".