Disruption of brain white matter microstructure in women with anorexia nervosa
Bibliographic record
Abstract
BACKGROUND: The etiology of anorexia nervosa is still unknown. Multiple and distributed brain regions have been implicated in its pathophysiology, implying a dysfunction of connected neural circuits. Despite these findings, the role of white matter in anorexia nervosa has been rarely assessed. In this study, we used diffusion tensor imaging (DTI) to characterize alterations of white matter microstructure in a clinically homogeneous sample of patients with anorexia nervosa. METHODS: Women with anorexia nervosa (restricting subtype) and healthy controls underwent brain DTI. We used tract-based spatial statistics to compare fractional anisotropy (FA) and mean diffusivity (MD) maps between the groups. Furthermore, axial (AD) and radial diffusivity (RD) measures were extracted from regions showing group differences in either FA or MD. RESULTS: We enrolled 19 women with anorexia nervosa and 19 healthy controls in our study. Patients with anorexia nervosa showed significant FA decreases in the parietal part of the left superior longitudinal fasciculus (SLF; p(FWE) < 0.05), with increased MD and RD but no differences in AD. Patients with anorexia nervosa also showed significantly increased MD in the fornix (p(FWE) < 0.05), accompanied by decreased FA and increased RD and AD. LIMITATIONS: Limitations include our modest sample size and cross-sectional design. CONCLUSION: Our findings support the presence of white matter pathology in patients with anorexia nervosa. Alterations in the SLF and fornix might be relevant to key symptoms of anorexia nervosa, such as body image distortion or impairments in body-energy-balance and reward processes. The differences found in both areas replicate those found in previous DTI studies and support a role for white matter pathology of specific neural circuits in individuals with anorexia nervosa.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".