Bibliographic record
Abstract
Schimke immuno-osseous dysplasia (SIOD) is characterised by autosomal recessive inheritance, spondyloepiphyseal dysplasia causing growth retardation, defective cellular immunity, progressive nephropathy leading to renal failure, hyperpigmented macules, and dysmorphic facial features.1–16 Half of SIOD patients also have hypothyroidism, half episodic cerebral ischaemia, and a tenth bone marrow failure.3 SIOD is caused by mutations in SMARCAL1 (SWI/SNF2 related, matrix associated, actin dependent regulator of chromatin, subfamily a-like 1).17 SNF2 related proteins participate in the DNA nucleosome restructuring which commonly occurs during gene regulation and DNA replication, recombination, methylation, and repair.18,19 Generally SIOD patients surviving past 15-16 years have milder and fewer symptoms than patients dying at younger ages. These older patients do not suffer from hypothyroidism, recurrent infections, bone marrow failure, or central nervous system symptoms such as migraine headaches, transient ischaemic attacks, or strokes but do have spondyloepiphyseal dysplasia, renal disease, and T cell deficiency.3 These older patients have had two SMARCAL1 alleles with missense mutations, whereas most patients dying at younger ages have had at least one null allele.17 Based on this, we had hypothesised that patients surviving into adulthood have two hypomorphic alleles of SMARCAL1 as opposed to null alleles. Here we review the longevity of 38 patients and the causes of death for 22 patients on whom we have collected detailed clinical data. We also describe a 20 year old woman who has had severe clinical symptoms of SIOD and has two SMARCAL1 null alleles; this suggests that prolonged survival of severely affected patients with SMARCAL1 null alleles is possible. ### Human subjects Patients referred to this study gave informed consent approved by the Institutional Review Board of Baylor College of Medicine (Houston, TX, USA) or the Hospital for Sick Children (Toronto, ON, Canada). We isolated DNA from peripheral blood. Clinical data, collected …
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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) | 0.000 | 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".