Conditional recurrent neural networks for broad applications in nonlinear optics.

We present a novel implementation of conditional long short-term memory recurrent neural networks that successfully predict the spectral evolution of a pulse in nonlinear periodically-poled waveguides. The developed networks offer large flexibility by allowing the propagation of optical pulses with ranges of energies and temporal widths in waveguides with different poling periods. The results show very high agreement with the traditional numerical models.

Design, synthesis, molecular modelling and in vitro cytotoxicity analysis of novel carbamate derivatives as inhibitors of Monoacylglycerol lipase.

Monoacylglycerol lipase (MAGL) has an essential role in the catabolic pathway of the endocannabinoid 2-arachidonoylglycerol, which makes it a potential target for highly specific inhibitors for the treatment of a number of diseases. We designed and synthesized a series of carbamate analogues of URB602. We evaluated their inhibitory activity toward human MAGL in vitro both in cell culture and lysates.

Synthesis and characterization of a new fluorogenic substrate for monoacylglycerol lipase and application to inhibition studies.

Human monoacylglycerol lipase (MAGL), a soluble serine hydrolase that belongs to the α/β hydrolase fold superfamily, regulates 2-arachidonoyl glycerol level in the endocannabinoid system, which is implicated in a number of severe diseases, and therefore, inhibition of MAGL activity is crucial in the treatment of these diseases. We have synthesized a red fluorogenic substrate, 7-hydroxyresorufinyl-arachidonate (7-HRA), for a new MAGL assay. This assay is simple, sensitive, and reliable and useful for identifying compounds that modulate MAGL activity.