Phase-to-pattern inverse design for a fast realization of a functional metasurface by combining a deep neural network and a genetic algorithm.

Metasurface provides an unprecedented means to manipulate electromagnetic waves within a two-dimensional planar structure. Traditionally, the design of meta-atom follows the pattern-to-phase paradigm, which requires a time-consuming brute-forcing process. In this work, we present a fast inverse meta-atom design method for the phase-to-pattern mapping by combining the deep neural network (DNN) and genetic algorithm (GA).

Gut microbiota depletion by antibiotics ameliorates somatic neuropathic pain induced by nerve injury, chemotherapy, and diabetes in mice.

Background: Gut microbiota has been found involved in neuronal functions and neurological disorders. Whether and how gut microbiota impacts chronic somatic pain disorders remain elusive.

Methods: Neuropathic pain was produced by different forms of injury or diseases, the chronic constriction injury (CCI) of the sciatic nerves, oxaliplatin (OXA) chemotherapy, and streptozocin (STZ)-induced diabetes in mice.

Wnt signaling contributes to withdrawal symptoms from opioid receptor activation induced by morphine exposure or chronic inflammation.

Preventing and treating opioid dependence and withdrawal is a major clinical challenge, and the underlying mechanisms of opioid dependence and withdrawal remain elusive. We hypothesized that prolonged morphine exposure or chronic inflammation-induced μ-opioid receptor activity serves as a severe stress that elicits neuronal alterations and recapitulates events during development. Here, we report that Wnt signaling, which is important in developmental processes of the nervous system, plays a critical role in withdrawal symptoms from opioid receptor activation in mice.