Genomic abnormalities of the murine model of Fabry disease after disease-related perturbation, a systems biology approach
Bibliographic record
Abstract
Fabry disease is a disorder of alpha-D-galactosyl-containing glycolipids resulting from a deficiency of alpha-galactosidase A. Patients have a poorly understood vascular dysregulation. We hypothesized that disease-related perturbation by using enzyme replacement therapy in the murine model of Fabry disease would provide insight into abnormal biological processes in Fabry disease. Gene expression analyses of the heart, aorta, and liver of male alpha-galactosidase A knockout mice 28 weeks of age were compared with that of WT mice. Microarray analyses were performed before and after six weekly injections of alpha-galactosidase A. Alteration of Rpgrip1 ranked highest statistically in all three organs when knockout mice were compared with WT, and its splice variants responded in a unique way to alpha-galactosidase A. Enzyme replacement therapy tended to not only normalize gene expression, e.g., reduce the overexpression of securin, but also specifically modified gene expression in each tissue examined. Following multiple comparison analysis, gene expression correlation graphs were constructed, and a priori hypotheses were examined by using structural equation modeling. This systems biology approach demonstrated multiple and complex parallel cellular abnormalities in Fabry disease. These abnormalities form the basis for informed, in a Bayesian sense, sequential, hypothesis-driven research that can be subsequently tested experimentally.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".