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Abstract Background Leber hereditary optic neuropathy (LHON) is the most common mitochondrial disorder, frequently resulting in acute or subacute severe bilateral central vision loss. Vitamin B12 deficiency is also a known cause of optic neuropathy through mitochondrial dysfunction. Here we evaluated the prevalence and clinical significance of vitamin B12 deficiency in a large cohort of LHON patients and asymptomatic mutation carriers from a tertiary referral center. Methods From the Munich LHON prospective cohort study, participants included all LHON patients and asymptomatic LHON mutation carriers, who were recruited between February 2014 and March 2020 and consented to participate. Neurological, general, and ophthalmological examinations were regularly performed, as were laboratory tests. Vitamin B12 deficiency was diagnosed if serum vitamin B12 was below 201 pg/mL, or if 201–339 pg/mL plus low serum holotranscobalamin or elevated serum methylmalonic acid or elevated total plasma homocysteine. Results We analyzed 244 subjects, including 147 symptomatic LHON patients (74% males) and 97 asymptomatic mutation carriers (31% males). Median age at study baseline was 34 years (range 5–82 years). The prevalence of vitamin B12 deficiency was higher for LHON mutation carriers than for the general population in all age categories. This was statistically significant for the LHON mutation carriers under 65 years (21% vs. 5–7%, p = 0.002). While vitamin B12 deficiency prevalence was not statistically different between LHON patients and asymptomatic mutation carriers, its clinical correlates, e.g., macrocytosis and polyneuropathy, were more frequent in the subgroup of LHON patients. Excessive alcohol consumption was a significant predictor of vitamin B12 deficiency (p

Abstract Background Biallelic pathogenic variants in the neuroblastoma‐amplified sequence (NBAS) gene manifest in a broad spectrum of disorders, including, but not limited to recurrent acute liver failure, skeletal dysmorphism, susceptibility to infections, and SOPH syndrome with its cardinal symptoms of short stature, optic atrophy, and Pelger–Huët anomaly. We aimed to present clinical and genetic characteristics of two sisters (20 and 15 years old) who were diagnosed with optic atrophy and cone dystrophy in childhood. Genome sequencing revealed two novel variants in NBAS in compound heterozygous state in both sisters, namely a 1‐bp deletion predicted to result in a premature termination codon (c.5104del; p.(Met1702*)), and a non‐canonical splice site variant of unclear significance (c.886‐5T>A; p.?). Results Clinical examination and history revealed cone dystrophy, optic atrophy, and Pelger–Huët anomaly, but no short stature, recurrent acute liver failure, or susceptibility to infections. RNA analysis revealed that the c.886‐5T>A variant results in two aberrant transcripts that are predicted to lead to in frame amino acid changes in the β‐propeller region of the protein. Conclusion We hypothesize that the phenotype of our subjects, which appears to be at the end of the spectrum of NBAS‐related disorders, could be explained by residual protein function mediated by the non‐canonical splice site variant c.886‐5T>A. Our study contributes to the existing knowledge on the genotypic and phenotypic spectrum of NBAS‐related disorders.

Music generating computer programs can support jazz musicians and students during performance and practice, for instance by providing accompaniment for solo improvisation. However, such software typically plays sequences of static precomposed snippets and does not react to the user. In that context, it is hardly possible to determine whether such a system has any of its own creative powers. Within the scope of a user study with 20 participants, we evaluate and compare the mobile application iReal Pro to our own system, the evolutionary automatic and reactive system called ‘EAR Drummer’ that generates drum patterns as accompaniment to jazz solo improvisation. It adapts its behaviour in real-time by heuristic rules based on music properties derived from the user’s melodies. The user-based evaluation is performed by following the standardised procedure for evaluating creative systems (SPECS). The analysis of the results is based on a Linear Mixed Effects Model to consider fixed and random effects on the survey data. The model reveals that our system outperforms iReal Pro in all of SPECS’s partial components of creativity and significantly outperforms it for 7 of those 14 components including variety, originality, emotional involvement, and social interaction. Further, it is characterised as “better” and “more interesting” in the user survey. A conflicting observation is that while 70% of the study participants tend to prefer our more “creative” system as support for stage performances, only 40% find it more suitable for practice. Further analysis addresses differences between user groups defined by their played instrument, age, and musical experience.

Multi-objective optimization problems (MOPs) naturally arise in many applications. Since for such problems one can expect an entire set of optimal solutions, a common task in set based multi-objective optimization is to compute N solutions along the Pareto set/front of a given MOP. In this work, we propose and discuss the set based Newton methods for the performance indicators Generational Distance (GD), Inverted Generational Distance (IGD), and the averaged Hausdorff distance Δp for reference set problems for unconstrained MOPs. The methods hence directly utilize the set based scalarization problems that are induced by these indicators and manipulate all N candidate solutions in each iteration. We demonstrate the applicability of the methods on several benchmark problems, and also show how the reference set approach can be used in a bootstrap manner to compute Pareto front approximations in certain cases.

This paper presents an innovative approach for employing surrogate modeling in computer-aided design of sheet metal work pieces. The surrogate models replace expensive finite element analysis and thus shorten development time in the early design stages considerably. We experimentally compare neural networks and Kriging models for the task of predicting the sheet metal thickness after cold forming of B-pillars in automotive engineering. We also discuss some aspects of handling large data-sets and exploiting certain structures in the data.