Reliability of running gait variability measures calculated from inertial measurement units.

Changes to the variability within biomechanical signals may reflect a change in the health of the human system. However, for running gait variability measures calculated from wearable device data, it is unknown whether a between-day difference reflects a shift in system dynamics reflective of a change in human health or is a result of poor between-day reliability of the measurement device or the biomechanical signal. This study investigated the reliability of stride time and sacral acceleration variability measures calculated from inertial measurement units (IMUs).

Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run.

Human locomotion contains innate variability which may provide health insights. Detrended fluctuation analysis (DFA) has been used to quantify the temporal structure of variability for treadmill running, although it has been less commonly applied to uncontrolled overground running. This study aimed to determine how running gait complexity changes in response to gradient and elapsed exercise duration during uncontrolled overground running.

The repeatability of stride time variability, regularity, and long-range correlations.

Background: Detrended fluctuation analysis (DFA) and sample entropy (SE) measure the long-term correlations and regularity of gait patterns, respectively, having previously been used to identify participants at risk of falling, previous history of injury, or patients with motor diseases. Since these measures are more sensitive to gait impairment than linear measures (e.g.

Pharmacological restriction of genomic binding sites redirects PU.1 pioneer transcription factor activity.

Transcription factor (TF) DNA-binding dynamics govern cell fate and identity. However, our ability to pharmacologically control TF localization is limited. Here we leverage chemically driven binding site restriction leading to robust and DNA-sequence-specific redistribution of PU.

Mechanomemory of pulmonary fibroblasts demonstrates reversibility of transcriptomics and contraction phenotypes.

Fibroblasts are cells responsible for producing extracellular matrix (ECM) components, which provides physical support for organs. Although these mesenchymal cells are responsive to mechanical cues in their environment, the permanence of these mechanophenotypes is not well defined. We investigated the mechanomemory of lung fibroblasts and determined how switching culture conditions modulate cell responses and function.