Beyond vacuolar pathology: Multiomic profiling of Danon disease reveals dysfunctional mitochondrial homeostasis
Bibliographic record
Abstract
Figure S1: Visual representation of the interaction network of dysregulated proteins. String analysis was carried out separately for increased and decreased proteins. Increased proteins (left panel) show a strong functional interdependence for mitochondrial proteins, whereas decreased proteins (right) form a cluster of proteins involved in protein translation and degradation. The interaction network was built with String 10 DB. Figure S2: (A) Protein investigation: DD-patients (n=2) versus Controls (n=3) => 1,606 unique proteins included from which on average 2 or more peptides were identified in the DD-patient as well as in the control group. Rows are centered; unit variance scaling is applied to rows. Both rows and columns are clustered using correlation distance and average linkage. For all proteins an average of at least 2 peptides had to be identified in each sample. 184 rows, 5 columns, T-test between DD-patients and Controls p<0.05 (B) mRNA investigation: DD-patients (n=2) versus Controls (n=4) => 14,334 mRNA species included. Rows are centered; unit variance scaling is applied to rows. Both rows and columns are clustered using correlation distance and average linkage. 543 rows, 6 columns. FPKM>0.1, T-test between DD-patients and Controls p<0.001. Figure S3: Co-localization of mitochondria with the activated p62-pathway. Immunofluorescence with co-localization (yellow) of mitochondrial protein COX-II (red) and p62 (SQSTM1; green). DAPI staining of nuclei in blue (magnification x400). Table S1. Supporting Information Table S2. Supporting Information Table S3. Supporting Information Table S4. Supporting Information Table S5. Supporting Information Table S6. Supporting Information Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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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 | 0.001 |
| 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".