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Adult muscle carnitine palmitoyltransferase (CPT) II deficiency is a rare autosomal recessive disorder of long-chain fatty acid metabolism. It is typically associated with recurrent episodes of exercise-induced rhabdomyolysis and myoglobinuria, in most cases caused by a c.338C > T mutation in the CPT2 gene. Here we present the pedigree of one of the largest family studies of CPT II deficiency caused by the c.338C > T mutation, documented so far. The pedigree comprises 24 blood relatives
of the index patient, a 32 year old female with genetically proven CPT II deficiency. In total, the mutation was detected in 20 family members, among them five homozygotes and 15 heterozygotes. Among all homozygotes, first symptoms of CPT II deficiency occurred during childhood. Additionally, two already deceased relatives of the index patient were carriers of at least one copy of the genetic variant, revealing a remarkably high prevalence of the c.338C > T mutation within the tested family. Beside the index patient, only one individual had been diagnosed with CPT II deficiency prior to this study and three cases of CPT II deficiency were newly detected by this family study, pointing
to a general underdiagnosis of the disease. Therefore, this study emphasizes the need to raise awareness of CPT II deficiency for correct diagnosis and accurate management of the disease.
Varying mindsets in Design Thinking. Why they change during the process and how to nudge them
(2019)
Modeling the dynamic of breath methane concentration profiles during exercise on an ergometer
(2015)
The importance of Agent-Based Simulation (ABS) as scientific method to generate data for scientific models in general and for informed policy decisions in particular has been widely recognised. However, the important technique of code testing of implementations like unit testing has not generated much research interested so far. As a possible solution, in previous work we have explored the conceptual use of property-based testing. In this code testing method, model specifications and invariants are expressed directly in code and tested through automated and randomised test data generation. This paper expands on our previous work and explores how to use property-based testing on a technical level to encode and test specifications of ABS. As use case the simple agent-based SIR model is used, where it is shown how to test agent behaviour, transition probabilities and model invariants. The outcome are specifications expressed directly in code, which relate whole classes of random input to expected classes of output. During test execution, random test data is generated automatically, potentially covering the equivalent of thousands of unit tests, run within seconds on modern hardware. This makes property-based testing in the context of ABS strictly more powerful than unit testing, as it is a much more natural fit due to its stochastic nature.