Disrupted Glucose Metabolism Covariance Network in Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
AIMS: This study aimed to characterize the topological changes in glucose metabolism covariance networks in amyotrophic lateral sclerosis (ALS). METHODS: F-FDG-PET data to examine topological alterations in individualized glucose metabolism covariance networks in 127 ALS patients compared to 128 healthy controls (HC). RESULTS: Compared to HC, ALS patients showed reduced small-worldness (lower normalized clustering coefficient, higher normalized characteristic path length) and decreased global and local efficiency, suggesting impaired global integration and local segregation. These network metrics correlated with disease progression and motor function. Regionally, altered degree centrality affected motor and default mode networks, and related to GABAa and mGluR5 receptor expression. Transcriptomic associations further linked these changes to immune function, synaptic signaling, and protein regulation. Bidirectional shifts in connectivity strength were observed, with both increased connectivity and disease progression independently predicting reduced survival. CONCLUSION: Our findings may provide valuable biomarkers for monitoring the progression of ALS and suggest potential mechanistic pathways for the development of innovative therapeutic strategies for this disorder.
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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 | 0.001 |
| 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".