MYH9 Mutation, the Hidden Face of Diverse Disease Spectrum - from Renal Perspective. Renal Perspective of MYH9 Mutation
Bibliographic record
Abstract
MYH9 (myosin heavy chain 9)-mutation is a frequent genetic disorder among African-Americans and rare in Caucasians that can lead to dramatic deterioration of renal function and as a consequence, end stage renal disease (ESRD). The clinical presentation of MYH9 mutations includes five syndromes: May-Hegglin anomaly, Sebastian, Fechtner, Epstein syndromes and isolated sensorineural deafness. The diagnosis is challenging to establish due to non-specific presentation that requires exclusion of a vast number of other entities. Renal biopsy is not commonly performed but it may reveal non-specific findings such as mesangial expansion with hypercellularity, focal segmental glomerulosclerosis (FSGS) and/or global glomerulosclerosis usually with no immune complex deposition. The immunostaining study for alpha-smooth muscle actin (SMA) can be valuable to perform in patients suspected to have MYH9 mutations in order to detect early FSGS. Additional studies for patients presenting with thrombocytopenia, decreasing glomerular filtration rate, proteinuria and haematuria are suggested. Here, we report a child with classic clinical picture of MYH9 genetic disorder that presented with early focal segmental glomerulosclerosis with possible concurrent C1q nephropathy. This case highlights the importance of kidney biopsy in optimal management of pediatric patients with MYH9 related diseases.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".