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Recent advances in upconversion technology have enabled optogenetic neural stimulation using remotely applied optical signals, but limited success has been demonstrated for neural inhibition by using this method, primarily due to the much higher optical power and more redshifted excitation spectrum that are required to work with the appropriate inhibitory opsin proteins. To overcome these limitations, core−shell−shell upconversion nanoparticles (UCNPs) with a hexagonal phase are synthesized to optimize the doping contents of ytterbium ions (Yb 3+ ) and to mitigate Yb-associated concentration quenching. Such UCNPs' emission contains an almost three-fold enhanced peak around 540−570 nm, matching the excitation spectrum of a commonly used inhibitory opsin protein, halorhodopsin. The enhanced UCNPs are utilized as optical transducers to develop a fully implantable upconversion-based device for in vivo tetherless optogenetic inhibition, which is actuated by near-infrared (NIR) light irradiation without any electronics. When the device is implanted into targeted sites deep in the rat brain, the electrical activity of the neurons is reliably inhibited with NIR irradiation and restores to normal level upon switching off the NIR light. The system is further used to perform tetherless unilateral inhibition of the secondary motor cortex in behaving mice, achieving control of their motor functions. This study provides an important and useful supplement to the upconversion-based optogenetic toolset, which is beneficial for both basic and translational neuroscience investigations.

Theranostic nanomedicine is capable of diagnosis, therapy, and monitoring the delivery and distribution of drug molecules and has received growing interest. Herein, a self-monitored and self-delivered photosensitizer-doped FRET nanoparticle (NP) drug delivery system (DDS) is designed for this purpose. During preparation, a donor/acceptor pair of perylene and 5,10,15,20-tetro (4-pyridyl) porphyrin (H2TPyP) is co-doped into a chemotherapeutic anticancer drug curcumin (Cur) matrix. In the system, Cur works as a chemotherapeutic agent. In the meantime, the green fluorescence of Cur molecules is quenched (OFF) in the form of NPs and can be subsequently recovered (ON) upon release in tumor cells, which enables additional imaging and real-time self-monitoring capabilities. H2TPyP is employed as a photodynamic therapeutic drug, but it also emits efficient NIR fluorescence for diagnosis via FRET from perylene. By exploiting the emission characteristics of these two emitters, the combinatorial drugs provide a real-time dual-fluorescent imaging/tracking system in vitro and in vivo, and this has not been reported before in self-delivered DDS which simultaneously shows a high drug loading capacity (77.6%Cur). Overall, our carrier-free DDS is able to achieve chemotherapy (Cur), photodynamic therapy (H2TPyP), and real-time self-monitoring of the release and distribution of the nanomedicine (Cur and H2TPyP). More importantly, the as-prepared NPs show high cancer therapeutic efficiency both in vitro and in vivo. We expect that the present real-time self-monitored and self-delivered DDS with multiple-therapeutic and multiple-fluorescent ability will have broad applications in future cancer therapy.

Motion has shown to be useful for video understanding, where motion is typically represented by optical flow. However, computing flow from video frames is very timeconsuming. Recent works directly leverage the motion vectors and residuals readily available in the compressed video to represent motion at no cost. While this avoids flow computation, it also hurts accuracy since the motion vector is noisy and has substantially reduced resolution, which makes it a less discriminative motion representation. To remedy these issues, we propose a lightweight generator network, which reduces noises in motion vectors and captures fine motion details, achieving a more Discriminative Motion Cue (DMC) representation. Since optical flow is a more accurate motion representation, we train the DMC generator to approximate flow using a reconstruction loss and an adversarial loss, jointly with the downstream action classification task. Extensive evaluations on three action recognition benchmarks (HMDB-51, UCF-101, and a subset of Kinetics) confirm the effectiveness of our method. Our full system, consisting of the generator and the classifier, is coined as DMC-Net which obtains high accuracy close to that of using flow and runs two orders of magnitude faster than using optical flow at inference time.

During the evolution of SARS-CoV-2 in humans a D614G substitution in the spike (S) protein emerged and became the predominant circulating variant (S-614G) of the COVID-19 pandemic. However, whether the increasing prevalence of the S-614G variant represents a fitness advantage that improves replication and/or transmission in humans or is merely due to founder effects remains elusive. Here, we generated isogenic SARS-CoV-2 variants and demonstrate that the S-614G variant has (i) enhanced binding to human ACE2, (ii) increased replication in primary human bronchial and nasal airway epithelial cultures as well as in a novel human ACE2 knock-in mouse model, and (iii) markedly increased replication and transmissibility in hamster and ferret models of SARS-CoV-2 infection. Collectively, our data show that while the S-614G substitution results in subtle increases in binding and replication in vitro, it provides a real competitive advantage in vivo, particularly during the transmission bottle neck, providing an explanation for the global predominance of S-614G variant among the SARS-CoV-2 viruses currently circulating.