Hippocampal Subfield Integrity and Age‐Driven Neural Correlates of Appetite Loss in Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
ABSTRACT Background Appetite loss is a non‐motor symptom in amyotrophic lateral sclerosis (ALS) linked to poorer prognosis. While the hippocampus regulates “meal memory”, a key cognitive modulator of eating behavior, its structural role in ALS‐related appetite loss is unknown. Purpose To determine if hippocampal subfield integrity influences appetite dysregulation in ALS and to evaluate the strength of neuroanatomical versus demographic factors. Study Type Cross‐sectional secondary analysis. Population Thirty‐two patients with ALS (mean age: 58.97 ± 8.91 years; 24 males) and 22 non‐neurodegenerative controls (NNDc) (mean age: 53.86 ± 9.98 years; 16 males). Field Strength/Sequence 3T; 3D T1‐weighted magnetization‐prepared rapid gradient‐echo (MP2RAGE) and 3D T2‐weighted turbo spin‐echo (T2‐SPACE) sequences. Assessment Appetite was measured using the Council on Nutrition Appetite Questionnaire (CNAQ). Hippocampal subfield volumes (CA1, CA2/3, CA4/DG, stratum radiatum/lacunosum/moleculare [SRLM], subiculum) and asymmetry indices were segmented from T1w and T2w images using the HIPS automated pipeline. Statistical Tests Analysis of Covariance (ANCOVA) (adjusting for age, sex, body mass index (BMI), total intracranial volume (TIV), and subfield volumes/asymmetry) and hierarchical multiple regression analyses were used. Significance was set at p < 0.05. Results Patients with ALS (adjusted mean: 29.51 ± 0.53) had significantly lower adjusted CNAQ scores compared to controls (adjusted mean: 31.98 ± 0.66; mean difference: −2.47, partial η 2 = 0.195). In the ANCOVA model, left SRLM volume was the only significant neuroanatomical covariate ( F [1, 30] = 6.45, partial η 2 = 0.177). However, hierarchical regression revealed that age was the only consistent independent predictor of CNAQ scores ( B = −0.158), explaining the largest variance (Δ R 2 = 0.165). Hippocampal volumes and asymmetry did not remain significant predictors after adjusting for age (left SRLM: p = 0.853; SRLM asymmetry: p = 0.868). Data Conclusion Appetite loss is a non‐motor symptom in ALS. While associated with lower left SRLM volume at the group level, appetite decline is more robustly and independently associated with advancing age. Evidence Level 3. Technical Efficacy 3.
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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 | 0.001 | 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".