Deoxynucleoside Therapy for Thymidine Kinase 2-Deficient Myopathy.

OBJECTIVE: Thymidine kinase 2, encoded by the nuclear gene TK2, is required for mitochondrial DNA maintenance. Autosomal recessive TK2 mutations cause depletion and multiple deletions of mtDNA that manifest predominantly as a myopathy usually beginning in childhood and progressing relentlessly. We investigated the safety and efficacy of deoxynucleoside monophosphate and deoxynucleoside therapies. METHODS: We administered deoxynucleoside monophosphates and deoxynucleoside to 16 TK2-deficient patients under a compassionate use program. RESULTS: In 5 patients with early onset and severe disease, survival and motor functions were better than historically untreated patients. In 11 childhood and adult onset patients, clinical measures stabilized or improved. Three of 8 patients who were nonambulatory at baseline gained the ability to walk on therapy; 4 of 5 patients who required enteric nutrition were able to discontinue feeding tube use; and 1 of 9 patients who required mechanical ventilation became able to breathe independently. In motor functional scales, improvements were observed in the 6-minute walk test performance in 7 of 8 subjects, Egen Klassifikation in 2 of 3, and North Star Ambulatory Assessment in all 5 tested. Baseline elevated serum growth differentiation factor 15 levels decreased with treatment in all 7 patients tested. A side effect observed in 8 of the 16 patients was dose-dependent diarrhea, which did not require withdrawal of treatment. Among 12 other TK2 patients treated with deoxynucleoside, 2 adults developed elevated liver enzymes that normalized following discontinuation of therapy. INTERPRETATION: This open-label study indicates favorable side effect profiles and clinical efficacy of deoxynucleoside monophosphate and deoxynucleoside therapies for TK2 deficiency. ANN NEUROL 2019;86:293-303.

Parametric and non-parametric Poisson regression for modelling of the arterial input function in positron emission tomography.

Full quantification of Positron Emission Tomography (PET) requires an arterial input function (AIF) for measurement of certain targets, or using particular radiotracers, or for the quantification of specific outcome measures. The AIF represents the measurement of radiotracer concentrations in the arterial blood plasma over the course of the PET examination. Measurement of the AIF is prone to error as it is a composite measure created from the combination of multiple measurements of different samples with different equipment, each of which can be sources of measurement error. Moreover, its measurement requires a high degree of temporal granularity for early time points, which necessitates a compromise between quality and quantity of recorded samples. For these reasons, it is often desirable to fit models to this data in order to improve its quality before using it for quantification of radiotracer binding in the tissue. The raw observations of radioactivity in arterial blood and plasma samples are derived from radioactive decay, which is measured as a number of recorded counts. Count data have several specific properties, including the fact that they cannot be negative as well as a particular mean-variance relationship. Poisson regression is the most principled modelling strategy for working with count data, as it both incorporates and exploits these properties. However, no previous studies to our knowledge have taken this approach, despite the advantages of greater efficiency and accuracy which result from using the appropriate distributional assumptions. Here, we implement a Poisson regression modelling approach for the AIF as proof-of-concept of its application. We applied both parametric and non-parametric models for the input function curve. We show that a negative binomial distribution is a more appropriate error distribution for handling overdispersion. Furthermore, we extend this approach to a hierarchical non-parametric model which is shown to be highly resilient to missing data. We thus demonstrate that Poisson regression is both feasible and effective when applied to AIF data, and propose that this is a promising strategy for modelling blood count data for PET in future.

Obsessive passion, opportunity recognition, and entrepreneurial performance: The dual moderating effect of the fear of failure.

A strong inclination toward an important or preferred activity is a critical factor that drives individual to engage in corresponding activities. This study focuses on how entrepreneurs, influenced by obsessive passion, are motivated to put great effort into taking advantage of business opportunities and accomplishing entrepreneurial goals. By using SPSS and AMOS tools to analyze the multi-source questionnaire of 208 entrepreneurs, the research results show that obsessive passion can promote entrepreneurial performance and opportunity recognition plays a mediating role. In addition, endogenous and exogenous fear of failure play different moderating roles in the effect of obsessive passion on opportunity recognition. The research conclusion deepens the theoretical understanding of entrepreneurial passion, opportunity recognition, and fear of failure at a more subtle level.