RESUMO
Multiple epiphyseal dysplasia (MED) is a congenital disease causing epiphyseal dysplasia in long bones. Herein, we report a case of a middle-aged man with bilateral knee joint locking symptoms who was diagnosed with multiple epiphyseal dysplasia caused by Matrilin-3 (MATN3) pathogenic variants and was successfully treated with arthroscopic loose body removal. A 48-year-old man has had bilateral knee pain since his twenties and underwent loose body removal of both knees in his thirties. He visited our hospital for worsening locking symptoms in both knees. Twenty years ago, his son had been diagnosed with suspected multiple epiphyseal dysplasia. Genetic and imaging testing confirmed his diagnosis of multiple epiphyseal dysplasia due to Matrilin-3 pathogenic variants. Arthroscopic loose body removal was performed, and the locking symptoms disappeared after surgery. Arthroscopic loose body removal was effective for the locking symptoms in a mild adult case of multiple epiphyseal dysplasias caused by Matrilin-3 pathogenic variants.
RESUMO
Meconium, a non-invasive biomaterial reflecting prenatal substance accumulation, could provide valuable insights into neonatal health. However, the comprehensive protein profile of meconium across gestational ages remains unclear. Here, we conducted an extensive proteomic analysis of first meconium from 259 newborns across varied gestational ages to delineate protein composition and elucidate its relevance to neonatal diseases. The first meconium samples were collected, with the majority obtained before feeding, and the mean time for the first meconium passage from the anus was 11.9 ± 9.47 h. Our analysis revealed 5370 host-derived meconium proteins, which varied depending on sex and gestational age. Specifically, meconium from preterm infants exhibited elevated concentrations of proteins associated with the extracellular matrix. Additionally, the protein profiles of meconium also exhibited unique variations depending on both specific diseases, including gastrointestinal diseases, congenital heart diseases, and maternal conditions. Furthermore, we developed a machine learning model to predict gestational ages using meconium proteins. Our model suggests that newborns with gastrointestinal diseases and congenital heart diseases may have immature gastrointestinal systems. These findings highlight the intricate relationship between clinical parameters and meconium protein composition, offering potential for a novel approach to assess neonatal gastrointestinal health.