Single-cell profiling of alveolar rhabdomyosarcoma reveals RAS pathway inhibitors as cell-fate hijackers with therapeutic relevance

Rhabdomyosarcoma (RMS) is a group of pediatric cancers with features of developing skeletal muscle. The cellular hierarchy and mechanisms leading to developmental arrest remain elusive. Here, we combined single-cell RNA sequencing, mass cytometry, and high-content imaging to resolve intratumoral heterogeneity of patient-derived primary RMS cultures. We show that the aggressive alveolar RMS (aRMS) subtype contains plastic muscle stem-like cells and cycling progenitors that drive tumor growth, and a subpopulation of differentiated cells that lost its proliferative potential and correlates with better outcomes. While chemotherapy eliminates cycling progenitors, it enriches aRMS for muscle stem-like cells. We screened for drugs hijacking aRMS toward clinically favorable subpopulations and identified a combination of RAF and MEK inhibitors that potently induces myogenic differentiation and inhibits tumor growth. Overall, our work provides insights into the developmental states underlying aRMS aggressiveness, chemoresistance, and progression and identifies the RAS pathway as a promising therapeutic target

Assessing dose rate distributions in VMAT plans

Dose rate is an essential factor in radiobiology. As modern radiotherapy delivery techniques such as volumetric modulated arc therapy (VMAT) introduce dynamic modulation of the dose rate, it is important to assess the changes in dose rate. Both the rate of monitor units per minute (MU rate) and collimation are varied over the course of a fraction, leading to different dose rates in every voxel of the calculation volume at any point in time during dose delivery. Given the radiotherapy plan and machine specific limitations, a VMAT treatment plan can be split into arc sectors between Digital Imaging and Communications in Medicine control points (CPs) of constant and known MU rate. By calculating dose distributions in each of these arc sectors independently and multiplying them with the MU rate, the dose rate in every single voxel at every time point during the fraction can be calculated. Independently calculated and then summed dose distributions per arc sector were compared to the whole arc dose calculation for validation. Dose measurements and video analysis were performed to validate the calculated datasets. A clinical head and neck, cranial and liver case were analyzed using the tool developed. Measurement validation of synthetic test cases showed linac agreement to precalculated arc sector times within ±0.4 s and doses ±0.1 MU (one standard deviation). Two methods for the visualization of dose rate datasets were developed: the first method plots a two-dimensional (2D) histogram of the number of voxels receiving a given dose rate over the course of the arc treatment delivery. In similarity to treatment planning system display of dose, the second method displays the dose rate as color wash on top of the corresponding computed tomography image, allowing the user to scroll through the variation over time. Examining clinical cases showed dose rates spread over a continuous spectrum, with mean dose rates hardly exceeding 100 cGy min(-1) for conventional fractionation. A tool to analyze dose rate distributions in VMAT plans with sub-second accuracy was successfully developed and validated. Dose rates encountered in clinical VMAT test cases show a continuous spectrum with a mean less than or near 100 cGy min(-1) for conventional fractionation

Pflegeauszeit und deren beeinflussenden Faktoren aus der Perspektive der Familienmitglieder, die eine ältere Person zu Hause betreuen und pflegen : eine Querschnittsstudie

Die Studie hatte zum Ziel die Inanspruchnahme einer Pflegeauszeit von Familienmitgliedern zu beschreiben, die eine ältere Person zu Hause betreuen und pflegen, und mittels einer logistischen Regressionsanalyse zu untersuchen. Von insgesamt 243 Familienmitgliedern nahmen 158 eine, 68 keine Auszeit und 17 machten keine Angaben. Rund 30 % der Varianz der Auszeit konnte mit Hilfe der Prädiktoren wie demographischen Angaben, Pflegebereitschaft, Zusammengehörigkeitsgefühl und Involviert sein in die professionelle Pflege erklärt werden. Familienmitglieder, die eine Frau pflegten, und die meistgenannten Aktivitäten während einer Auszeit wie Ferien und Hobby erwiesen sich neben dem sich vom Schlafmangel erholen als signifikante Prädiktoren im Modell

Hermitian curve interpolation for CT-data re-sampling

Purpose: Development of an interpolation algorithm for re‐sampling spatially distributed CT‐data with the following features: global and local integral conservation, avoidance of negative interpolation values for positively defined datasets and the ability to control re‐sampling artifacts. Method and Materials: The interpolation can be separated into two steps: first, the discrete CT‐data has to be continuously distributed by an analytic function considering the boundary conditions. Generally, this function is determined by piecewise interpolation. Instead of using linear or high order polynomialinterpolations, which do not fulfill all the above mentioned features, a special form of Hermitian curve interpolation is used to solve the interpolation problem with respect to the required boundary conditions. A single parameter is determined, by which the behavior of the interpolation function is controlled. Second, the interpolated data have to be re‐distributed with respect to the requested grid. Results: The new algorithm was compared with commonly used interpolation functions based on linear and second order polynomial. It is demonstrated that these interpolation functions may over‐ or underestimate the source data by about 10%–20% while the parameter of the new algorithm can be adjusted in order to significantly reduce these interpolation errors. Finally, the performance and accuracy of the algorithm was tested by re‐gridding a series of X‐ray CT‐images. Conclusion: Inaccurate sampling values may occur due to the lack of integral conservation. Re‐sampling algorithms using high order polynomialinterpolation functions may result in significant artifacts of the re‐sampled data. Such artifacts can be avoided by using the new algorithm based on Hermitian curve interpolatio