"suMus," a novel digital system for arm movement metrics and muscle energy expenditure

OBJECTIVE: In the field of non-treatable muscular dystrophies, promising new gene and cell therapies are being developed and are entering clinical trials. Objective assessment of therapeutic effects on motor function is mandatory for economical and ethical reasons. Main shortcomings of existing measurements are discontinuous data collection in artificial settings as well as a major focus on walking, neglecting the importance of hand and arm movements for patients' independence. We aimed to create a digital tool to measure muscle function with an emphasis on upper limb motility. METHODS: suMus provides a custom-made App running on smartwatches. Movement data are sent to the backend of a suMus web-based platform, from which they can be extracted as CSV data. Fifty patients with neuromuscular diseases assessed the pool of suMus activities in a first orientation phase. suMus performance was hence validated in four upper extremity exercises based on the feedback of the orientation phase. We monitored the arm metrics in a cohort of healthy volunteers using the suMus application, while completing each exercise at low frequency in a metabolic chamber. Collected movement data encompassed average acceleration, rotation rate as well as activity counts. Spearman rank tests correlated movement data with energy expenditure from the metabolic chamber. RESULTS: Our novel application "suMus," sum of muscle activity, collects muscle movement data plus Patient-Related-Outcome-Measures, sends real-time feedback to patients and caregivers and provides, while ensuring data protection, a long-term follow-up of disease course. The application was well received from the patients during the orientation phase. In our pilot study, energy expenditure did not differ between overnight fasted and non-fasted participants. Acceleration ranged from 1.7 ± 0.7 to 3.2 ± 0.5 m/sec(2) with rotation rates between 0.9 ± 0.5 and 2.0 ± 3.4 rad/sec. Acceleration and rotation rate as well as derived activity counts correlated with energy expenditure values measured in the metabolic chamber for one exercise (r = 0.58, p < 0.03). CONCLUSION: In the analysis of slow frequency movements of upper extremities, the integration of the suMus application with smartwatch sensors characterized motion parameters, thus supporting a use in clinical trial outcome measures. Alternative methodologies need to complement indirect calorimetry in validating accelerometer-derived energy expenditure data

Rapid Identification of Plasma DNA Samples with Increased ctDNA Levels by a Modified FAST-SeqS Approach.

Abstract BACKGROUND Recent progress in the analysis of cell-free DNA fragments [cell-free circulating tumor DNA (ctDNA)] now allows monitoring of tumor genomes by noninvasive means. However, previous studies with plasma DNA from patients with cancer demonstrated highly variable allele frequencies of ctDNA. The comprehensive analysis of tumor genomes is greatly facilitated when plasma DNA has increased amounts of ctDNA. Therefore, a fast and cost-effective prescreening method to identify such plasma samples without previous knowledge about alterations in the respective tumor genome could assist in the selection of samples suitable for further extensive qualitative analysis. METHODS We adapted the recently described Fast Aneuploidy Screening Test-Sequencing System (FAST-SeqS) method, which was originally established as a simple, effective, noninvasive screening method for fetal aneuploidy from maternal blood. RESULTS We show that our modified FAST-SeqS method (mFAST-SeqS) can be used as a prescreening tool for an estimation of ctDNA percentage. With a combined evaluation of genome-wide and chromosome arm–specific z-scores from dilution series with cell line DNA and by comparisons of plasma-Seq profiles with data from mFAST-SeqS, we established a detection limit of ≥10% mutant alleles. Plasma samples with an mFAST-SeqS z-score &amp;gt;5 showed results that were highly concordant with those of copy number profiles obtained from our previously described plasma-Seq approach. CONCLUSIONS Advantages of this approach include the speed and cost-effectiveness of the assay and that no prior knowledge about the genetic composition of tumor samples is necessary to identify plasma DNA samples with &amp;gt;10% ctDNA content. </jats:sec