Incorporating a physical model differentiating in-focus and out-of-focus emissions eliminates background fluorescence without affecting genuine signals. With this added to the sparse deconvolution pipeline, we preserve weak signals and minimize artifacts while achieving a sub-70 nm resolution.

A study led by University of Liverpool scientists has revealed a new way of using synthetic biology to improve crop growth, meeting a significant challenge to increase crop productivity in a changing climate with a growing population.

Here, we present Machine learning Assisted, Interferometric Structured Illumination Microscopy, MAI-SIM, as an easy-to-implement method for fast live cell super-resolution imaging in multiple colours.

Triboelectrification excited by breathing continuously replenishes electrostatic charges, endowing the self-charging face mask with an ultralong service lifespan