Strategic Modulation of Polarity and Viscosity Sensitivity of Bimane Molecular Rotor-Based Fluorophores for Imaging α-Synuclein.

Molecular rotor-based fluorophores (RBFs) that are target-selective and sensitive to both polarity and viscosity are valuable for diverse biological applications. Here, we have designed next-generation RBFs based on the underexplored bimane fluorophore through either changing in aryl substitution or varying π-linkages between the rotatable electron donors and acceptors to produce red-shifted fluorescence emissions with large Stokes shifts. RBFs exhibit a twisted intramolecular charge transfer mechanism that enables control of polarity and viscosity sensitivity, as well as target selectivity.

Predicting control of cardiovascular disease risk factors in South Asia using machine learning.

A substantial share of patients at risk of developing cardiovascular disease (CVD) fail to achieve control of CVD risk factors, but clinicians lack a structured approach to identify these patients. We applied machine learning to longitudinal data from two completed randomized controlled trials among 1502 individuals with diabetes in urban India and Pakistan. Using commonly available clinical data, we predict each individual's risk of failing to achieve CVD risk factor control goals or meaningful improvements in risk factors at one year after baseline.

Injectable, in-situ forming, tunable, biocompatible gelatin hydrogels for biomedical applications.

Gelatin hydrogels have drawn attention for their diverse biomedical applications due to their flexible physiochemical properties. However, such gelatin hydrogels are made of toxic crosslinkers and photoinitiators, restricting their non-invasive deep tissue application. The in-situ forming chemical crosslinked without such toxic crosslinker and UV light has not been explored under physiological conditions.