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Contains fulltext : 167862.pdf (publisher's version ) (Open Access), INTRODUCTION: Alpha-1,3-glucosyltransferase congenital disorder of glycosylation (ALG6-CDG) is a congenital disorder of glycosylation. The original patients were described with hypotonia, developmental disability, epilepsy, and increased bleeding tendency. METHODS: Based on Euroglycan database registration, we approached referring clinicians and collected comprehensive data on 41 patients. RESULTS: We found hypotonia and developmental delay in all ALG6-CDG patients and epilepsy, ataxia, proximal muscle weakness, and, in the majority of cases, failure to thrive. Nine patients developed intractable seizures. Coagulation anomalies were present in <50 % of cases, without spontaneous bleedings. Facial dysmorphism was rare, but seven patients showed missing phalanges and brachydactyly. Cyclic behavioral change, with autistic features and depressive episodes, was one of the most significant complaints. Eleven children died before the age of 4 years due to protein losing enteropathy (PLE), sepsis, or seizures. The oldest patient was a 40 year-old Dutch woman. The most common pathogenic protein alterations were p.A333V and p.I299Del, without any clear genotype-phenotype correlation. DISCUSSION: ALG6-CDG has been now described in 89 patients, making it the second most common type of CDG. It has a recognizable phenotype and a primary neurologic presentation.

Contains fulltext : 166204.pdf (publisher's version ) (Closed access), Staphylococcus aureus (S. aureus) is a common bacterium infecting children with cystic fibrosis (CF). Since current detection methods are difficult to perform in children, there is need for an alternative. This proof of concept study investigates whether breath profiles can discriminate between S. aureus infected and non-infected CF patients based on volatile organic compounds (VOCs). We collected exhaled breath of CF patients with and without S. aureus airways infections in which VOCs were identified using gas chromatography-mass spectrometry. We classified these VOC profiles with sparse partial least squares discriminant analysis. Multivariate breath VOC profiles discriminated infected from non-infected CF patients with high sensitivity (100%) and specificity (80%). We identified the nine compounds most important for this discrimination. We successfully detected S. aureus infection in CF patients, using breath VOC profiles. Nine highlighted compounds can be used as a focus point in further biomarker identification research. The results show considerable potential for non-invasive diagnosis of airway infections.