Application of Statistical Analysis and Machine Learning to Identify Infants' Abnormal Suckling Behavior.

Objective: Identify infants with abnormal suckling behavior from simple non-nutritive suckling devices.

Background: While it is well known breastfeeding is beneficial to the health of both mothers and infants, breastfeeding ceases in 75 percent of mother-child dyads by 6 months. The current standard of care lacks objective measurements to screen infant suckling abnormalities within the first few days of life, a critical time to establish milk supply and successful breastfeeding practices.

A Remote Control System for Emergency Ventilators During SARS-CoV-2.

As COVID-19 began to grip healthcare systems worldwide, worst-case models predicted huge demands for ventilators. The global community sprang to action, producing a large number of emergency "makeshift" ventilator designs. This brought about another problem: a gap between the quantity of new mechanical ventilators and the number of skilled physicians to operate them.

Matrix Rigidity-Dependent Regulation of Ca at Plasma Membrane Microdomains by FAK Visualized by Fluorescence Resonance Energy Transfer.

The dynamic regulation of signal transduction at plasma membrane microdomains remains poorly understood due to limitations in current experimental approaches. Genetically encoded biosensors based on fluorescent resonance energy transfer (FRET) can provide high spatiotemporal resolution for imaging cell signaling networks. Here, distinctive regulation of focal adhesion kinase (FAK) and Ca signals are visualized at different membrane microdomains by FRET using membrane-targeting biosensors.