Digital wearable insole-based identification of knee arthropathies and gait signatures using machine learning.

Gait is impaired in musculoskeletal conditions, such as knee arthropathy. Gait analysis is used in clinical practice to inform diagnosis and monitor disease progression or intervention response. However, clinical gait analysis relies on subjective visual observation of walking as objective gait analysis has not been possible within clinical settings due to the expensive equipment, large-scale facilities, and highly trained staff required.

magpie: A power evaluation method for differential RNA methylation analysis in N6-methyladenosine sequencing.

Recently, novel biotechnologies to quantify RNA modifications became an increasingly popular choice for researchers who study epitranscriptome. When studying RNA methylations such as N6-methyladenosine (m6A), researchers need to make several decisions in its experimental design, especially the sample size and a proper statistical power. Due to the complexity and high-throughput nature of m6A sequencing measurements, methods for power calculation and study design are still currently unavailable.

Evaluation of epitranscriptome-wide N6-methyladenosine differential analysis methods.

RNA methylation has emerged recently as an active research domain to study post-transcriptional alteration in gene expression regulation. Various types of RNA methylation, including N6-methyladenosine (m6A), are involved in human disease development. As a newly developed sequencing biotechnology to quantify the m6A level on a transcriptome-wide scale, MeRIP-seq expands RNA epigenetics study in both basic and clinical applications, with an upward trend.

NeuCA web server: a neural network-based cell annotation tool with web-app and GUI.

Summary: Correctly annotating individual cell's type is an important initial step in single-cell RNA sequencing (scRNA-seq) data analysis. Here, we present NeuCA web server, a neural network-based scRNA-seq cell annotation tool with web-app portal and graphical user interface, for automatically assigning cell labels. NeuCA algorithm is accurate and exhaustive, maximizing the usage of measured cells for downstream analysis.

Considerations for Soluble Protein Biomarker Blood Sample Matrix Selection.

Blood-based soluble protein biomarkers provide invaluable clinical information about patients and are used as diagnostic, prognostic, and pharmacodynamic markers. The most commonly used blood sample matrices are serum and different types of plasma. In drug development research, the impact of sample matrix selection on successful protein biomarker quantification is sometimes overlooked.