CYP24A1 deficiency causing persistent hypercalciuria in a stone former

Objective: We were comparing the urinary stone risk profiles in stone former subjects group with normal population (non stone-former) group. Material & method: In this study, each group consist of 10 subjects. Urine samples used was a 24-hour-urine. All subjects in this study were previously informed and voluntarily participating. Inclusion criteria in this study were adult, stone free, residing in Jakarta. Measurement was performed in Department of Molecular Biology and Biochemistry Faculty of Medicine Indonesia University. Statistical analysis was performed using SPSS 20 (Chicago, USA) with Student’s t-test or Mann-Whitney (p < 0.05 was considered significant). Results: There was a significant difference in the mean age of two groups with no significant difference in weight and height. Significant difference (p < 0.05) in urinary profile was found in urea, uric acid, chloride, potassium, phosphate, and ammonia. Conversely, we found no significant differences (p > 0.05) in sodium, creatinine, calcium, magnesium, oxalate, and citrate levels. Conclusion: There were no significant differences in urinary stone promoting and inhibiting factors between two groups. Bigger number of sample size with better sampling method must be conducted for future studies.

Download Full-text

Prediction of renal crystalline size distributions in space using a PBE analytic model. 1. Effect of microgravity-induced biochemical alterations

AJP Renal Physiology ◽

10.1152/ajprenal.00401.2015 ◽

2016 ◽

Vol 311 (3) ◽

pp. F520-F530 ◽

Cited By ~ 4

Author(s):

Mohammad Kassemi ◽

David Thompson

Keyword(s):

Size Distribution ◽

Renal Stone ◽

Stone Formation ◽

Absolute Risk ◽

Risk Level ◽

Normal Person ◽

Biochemical Alterations ◽

Numerical Predictions ◽

Stone Former ◽

Recurrent Stone

An analytical Population Balance Equation model is developed and used to assess the risk of critical renal stone formation for astronauts during future space missions. The model uses the renal biochemical profile of the subject as input and predicts the steady-state size distribution of the nucleating, growing, and agglomerating calcium oxalate crystals during their transit through the kidney. The model is verified through comparison with published results of several crystallization experiments. Numerical results indicate that the model is successful in clearly distinguishing between 1-G normal and 1-G recurrent stone-former subjects based solely on their published 24-h urine biochemical profiles. Numerical case studies further show that the predicted renal calculi size distribution for a microgravity astronaut is closer to that of a recurrent stone former on Earth rather than to a normal subject in 1 G. This interestingly implies that the increase in renal stone risk level in microgravity is relatively more significant for a normal person than a stone former. However, numerical predictions still underscore that the stone-former subject carries by far the highest absolute risk of critical stone formation during space travel.

Download Full-text