Fatty Acids and Their Lipogenic Enzymes in Anorexia Nervosa Clinical Subtypes
Bibliographic record
Abstract
Disordered eating behavior differs between the restricting subtype (AN-R) and the binging and purging subtype (AN-BP) of anorexia nervosa (AN). Yet, little is known about how these differences impact fatty acid (FA) dysregulation in AN. To address this question, we analyzed 26 FAs and 7 FA lipogenic enzymes (4 desaturases and 3 elongases) in 96 women: 25 AN-R, 25 AN-BP, and 46 healthy control women. Our goal was to assess subtype-specific patterns. Lauric acid was significantly higher in AN-BP than in AN-R at the fasting timepoint (p = 0.038) and displayed significantly different postprandial changes 2 h after eating. AN-R displayed significantly higher levels of n-3 alpha-linolenic acid, stearidonic acid, eicosapentaenoic acid (EPA), docosapentaenoic acid, and n-6 linoleic acid and gamma-linolenic acid compared to controls. AN-BP showed elevated EPA and saturated lauric acid compared to controls. Higher EPA was associated with elevated anxiety in AN-R (p = 0.035) but was linked to lower anxiety in AN-BP (p = 0.043). These findings suggest distinct disordered eating behaviors in AN subtypes contribute to lipid dysregulation and eating disorder comorbidities. A personalized dietary intervention may improve lipid dysregulation and enhance treatment effectiveness for AN.
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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 | 0.001 |
| 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".