Bibliographic record
Abstract
Background: Nail-patella syndrome (NPS) is an inherited autosomal dominant disease, with an incidence of approximately 1 in 50,000. It ischaracterized by nail dysplasia, hypoplastic patellae, other bone deformities and open angle glaucoma. The phenotype is variable. Methods: Case report Results: A 66 year old male presented with complaints of mild loss of sensation in both feet with gradual proximal spread to his knees over the past decade. There was no history of pain, paresthesias, autonomic dysfunction or weakness. Examination showed pectus excavatum with symmetrically dystrophic fingernails. Sensation to crude touch, pain and temperature were reduced up to mid shin, and vibration sense was diminished till the malleoli symmetrically. Electrophysiologic studies revealed a mild to moderate length-dependent polyneuropathy of axonal type. Detailed blood screening studies were negative. Genetic testing revealed the diagnosis of nail-patella syndrome with LMX1B gene mutation on chromosome 9q34. The lack of an identifiable acquired cause and the symmetric, slowly progressive and “painless” nature of the patient’s peripheral neuropathy point toward an inherited etiology. Conclusion: We present a case of slowly progressive sensorimotor axonal polyneuropathy in a patient with a diagnosis of NPS, which has not been previously reported. Peripheral nervous system disorder may be a variable phenotypic manifestation of LMX1B gene mutation.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".