Basic Research Protocol: Exome Sequencing in Adults With Loin Pain Hematuria Syndrome: A Pilot Study
Bibliographic record
Abstract
Background: Loin pain hematuria syndrome (LPHS) is a poorly understood clinical syndrome characterized by hematuria and either unilateral or bilateral severe kidney pain in the absence of identifiable urological disease. Loin pain hematuria syndrome imposes a significant health and economic impact with a loss of productivity and quality of life in a young population. Owing to an incomplete understanding of its pathophysiology, treatment has been limited to nonspecific pain management. Nearly 60 years after its initial description, we are no further ahead in understanding the molecular pathways involved in LPHS. Objective: To outline the study design for exome sequencing in adults with LPHS and their families. Methods: In this single-center case series, 24 patients with LPHS and 2 additional first-degree family members per participant will be recruited. DNA extracted from venous blood samples will undergo exome sequencing on the Illumina NovaSeq 6000 System at 100× depth and will be assessed for pathogenic variants in genes associated with hematuria (number of genes in: glomerular endothelium [n = 10] and basement membrane [n = 8]), and pain pathways (number of genes in: pain transduction [n = 17], conduction [n = 8], synaptic transmission [n = 37], and modulation [n = 27]). We will further examine identified potentially pathogenic variants that co-segregate with LPHS features among affected families. Conclusions: This pilot study may identify new directions for an investigation into the molecular mechanisms underlying LPHS.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.054 | 0.016 |
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".