Background Evidence suggests that disrupting prolonged bouts of sitting with short bouts of physical activity can significantly reduce blood glucose and improve insulin sensitivity; however, limited research is available on the impact of such disruptions on inflammation and swelling. The purpose of this study was to determine whether short bouts of exercise performed each hour during a 4 h sitting session were able to negate the effects of prolonged sitting (PS) on several cardiometabolic outcomes. Methods Eligible participants (n = 10) attended two laboratory sessions: PS (uninterrupted sitting for 4 h) and disrupted sitting (DS; 4 h sitting session disrupted by 3 min of exercise each hour (60-s warm-up at 50 W, 5 s of unloaded cycling, 20-s sprint at 5% body weight, and 95-s cool-down at 50 W)). The exercise bouts were performed at minute 60, 120, and 180. Blood and saliva samples, and measures of heart rate and blood pressure were assessed before (T1) and after (T2) each session; leg swell was measured continuously. Results Concentrations of salivary IL-8 increased during PS (T1: 0.19 ± 0.32; T2: 0.50 ± 1.00 pg/μg of protein) but decreased during DS (T1: 0.41 ± 0.23; T2: 0.22 ± 0.11 pg/μg of protein, d: 0.51, p = 0.002). Leg swell increased and plateaued in PS, but was attenuated during DS. Conclusion It appears that short bouts of exercise significantly reduce swelling in the lower leg and IL-8 levels in the saliva, indicating that even among healthy, active, young adults, disrupting prolonged sitting can significantly reduce swelling and systemic inflammation.

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Persistent inward current (PIC) plays a critical role in setting the gain of spinal motor neurons. In humans, most estimates of PIC are made from plantarflexor or dorsiflexor motor units in a seated position. This seated and static posture negates the task-dependent nature of the monoaminergic drive and afferent inhibition that modulate PIC activation. Our purpose was to estimate PIC during both the conventional seated posture and in a more functionally relevant anterior postural sway. We hypothesized that paired motor unit estimates of PIC would be greater when during standing compared with sitting. Soleus motor neuron PIC was estimated via the paired motor unit (PMU) technique. For each motor unit pair, difference in reference unit firing frequency (ΔF) estimates of PIC were made during isometric ramps in plantarflexion force during sitting (conventional approach) and during standing anterior postural sway (new approach). Baseline reciprocal inhibition (RI) was also measured in each posture using the poststimulus time histogram technique. ΔF estimates during standing postural sway were not different [2.64 ± 0.95 pulses/s (pps), P = 0.098] from seated PIC estimates (3.15 ± 1.45 pps) measured from the same motor unit pair. Similarly, reciprocal inhibition at the onset of each task was the same in standing (−0.60 ± 0.32, P = 0.301) and seated (−0.86 ± 0.82) postures. PMU recordings made during standing postural sway met all assumptions that underlay the PMU technique, including rate modulation ≥0.5 pps (3.11 ± 1.90 pps), rate-rate correlation r ≥ 0.7 (0.84 ± 0.13), and time between reference and test unit recruitment ≥1 s (1.83 ± 0.81 s). This study presents a novel, functionally relevant standing method for investigating PIC in humans. NEW & NOTEWORTHY Paired motor unit (PMU) estimates of persistent inward current (PIC) in human soleus motor units are typically made in seated posture. Our study demonstrates that these estimates can be made during standing forward sway, a task that more accurately reflects the postural role of human soleus muscle. PMU recordings made during standing postural sway were validated using all previously published criteria used to test the assumptions of the PMU technique. Standing estimates of PIC did not differ from seated estimates made from the same motor unit pairs.

Transcriptome data holds substantial promise for better interpretation of rare genetic variants in basic research and clinical settings. Here, we introduce ANalysis of Expression VAriation (ANEVA) to quantify genetic variation in gene dosage from allelic expression (AE) data in a population. Application to GTEx data showed that this variance estimate is robust across datasets and is correlated with selective constraint in a gene. We next used ANEVA variance estimates in a Dosage Outlier Test (ANEVA-DOT) to identify genes in an individual that are affected by a rare regulatory variant with an unusually strong effect. Applying ANEVA-DOT to AE data form 70 Mendelian muscular disease patients showed high accuracy in detecting genes with pathogenic variants in previously resolved cases, and lead to one confirmed and several potential new diagnoses in cases previously unresolved. Using our reference estimates from GTEx data, ANEVA-DOT can be readily incorporated in rare disease diagnostic pipelines to better utilize RNA-seq data.Large reference databases of human exomes and genomes have enabled characterization of genomic variation in human populations (1-3). These data have been used to summarize genic intolerance to damaging variants (1,4,5), which has been essential for prioritizing rare and de novo coding variants to achieve genetic diagnosis of Mendelian disease currently for 25-50% patients (6, 7). Yet, a large number of patients remain undiagnosed after exome and/or whole genome sequencing. Despite remarkable advances in DNA sequencing, the search for rare disease-causing variants outside the coding sequence has been hindered by the difficulty of interpreting rare regulatory variants and identifying their target genes. P.M.