Realization of a three-dimensional photonic topological insulator

Confining photons in a finite volume is in high demand in modern photonic devices. This motivated decades ago the invention of photonic crystals, featured with a photonic bandgap forbidding light propagation in all directions. Recently, inspired by the discoveries of topological insulators (TIs), the confinement of photons with topological protection has been demonstrated in two-dimensional (2D) photonic structures known as photonic TIs, with promising applications in topological lasers and robust optical delay lines. However, a fully three-dimensional (3D) topological photonic bandgap has never before been achieved. Here, we experimentally demonstrate a 3D photonic TI with an extremely wide (> 25% bandwidth) 3D topological bandgap. The sample consists of split-ring resonators (SRRs) with strong magneto-electric coupling and behaves as a 'weak TI', or a stack of 2D quantum spin Hall insulators. Using direct field measurements, we map out both the gapped bulk bandstructure and the Dirac-like dispersion of the photonic surface states, and demonstrate robust photonic propagation along a non-planar surface. Our work extends the family of 3D TIs from fermions to bosons and paves the way for applications in topological photonic cavities, circuits, and lasers in 3D geometries

Protective effect of delayed remote limb ischemic postconditioning: role of mitochondrial KATP channels in a rat model of focal cerebral ischemic reperfusion injury

Delayed remote ischemic postconditioning (DRIPost) has been shown to protect the rat brain from ischemic injury. However, extremely short therapeutic time windows hinder its translational use and the mechanism of action remains elusive. Because opening of the mitochondria KATP channel is crucial for cell apoptosis, we hypothesized that the neuroprotective effect of DRIPost may be associated with KATP channels. In the present study, the neuroprotective effects of DRIPost were investigated using adult male Sprague-Dawley rats. Rats were exposed to 90 minutes of middle cerebral artery occlusion followed by 72 hours of reperfusion. Delayed remote ischemic postconditioning was performed with three cycles of bilateral femoral artery occlusion/reperfusion for 5 minutes at 3 or 6 hours after reperfusion. Neurologic deficit scores and infarct volumes were assessed, and cellular apoptosis was monitored by terminal deoxynucleotidyl transferase nick-end labeling. Our results showed that DRIPost applied at 6 hours after reperfusion exerted neuroprotective effects. The KATP opener, diazoxide, protected rat brains from ischemic injury, while the KATP blocker, 5-hydroxydecanote, reversed the neuroprotective effects of DRIPost. These findings indicate that DRIPost reduces focal cerebral ischemic injury and that the neuroprotective effects of DRIPost may be achieved through opening of KATP channels

Masson pine pollen aqueous extract ameliorates cadmium-induced kidney damage in rats

Introduction: Cadmium (Cd) is a hazardous environmental pollutant present in soil, water, and food. Accumulation of Cd in organisms can cause systematic injury and damage to the kidney. The Masson pine pollen aqueous extract (MPPAE) has attracted increasing attention due to its antioxidant activity and ability to enhance immunity.Methods: In this study, we investigated the potential of MPPAE to protect against Cd-induced kidney damage in rats and the underlying mechanism. The transcriptome and metabolome of rats with Cd-induced kidney damage, following treatment with MPPAE, were explored.Results: The concentrations of superoxide dismutase (SOD) and malondialdehyde (MDA) were both significantly altered after treatment with MPPAE. Furthermore, sequencing and analysis of the transcriptome and metabolome of rats with Cd-induced kidney damage, following treatment with MPPAE, revealed differential expression of numerous genes and metabolites compared with the untreated control rats. These differentially expressed genes (DEGs) included detoxification-related genes such as cytochrome P450 and the transporter. The differentially expressed metabolites (DEMs) included 4-hydroxybenzoic acid, L-ascorbate, and ciliatine. Conjoint transcriptome and metabolome analysis showed that several DEGs were correlated with DEMs.Conclusion: These preliminary findings indicate the potential of MPPAE for the treatment of toxic metal poisoning

Topologically-protected refraction of robust kink states in valley photonic crystals

Recently discovered valley photonic crystals (VPCs) mimic many of the unusual properties of two-dimensional gapped valleytronic materials such as bilayer graphene or MoS2. Of the utmost interest to optical communications is their ability to support topologically protected chiral edge (kink) states at the internal domain wall between two VPCs with spectrally overlapping bandgap zones and opposite half-integer valley-Chern indices. We experimentally demonstrate the robustness of the kink states in VPCs that support degenerate transverse-electric-like (TE) and transverse-magnetic-like (TM) topological phases, thus enabling polarization multiplexing in a single topological waveguide. The propagation direction of the kink states is locked to the valleys of the reverse Brave lattice and, therefore, cannot be reversed in the absence of inter-valley scattering. At the intersection between the internal domain wall and the external edge separating the VPCs from free space, the kink states are shown to exhibit >97% out-coupling efficiency into directional free-space beams. This constitutes the first experimental demonstration of meron-like valley-projected topological phases with half-integer valley-Chern indices.Comment: 19 pages, 4 figure

Individual tree-based forest species diversity estimation by classification and clustering methods using UAV data

Monitoring forest species diversity is essential for biodiversity conservation and ecological management. Currently, unmanned aerial vehicle (UAV) remote sensing technology has been increasingly used in biodiversity monitoring due to its flexibility and low cost. In this study, we compared two methods for estimating forest species diversity indices, namely the spectral angle mapper (SAM) classification approach based on the established species-spectral library, and the self-adaptive Fuzzy C-Means (FCM) clustering algorithm by selected biochemical and structural features. We conducted this study in two complex subtropical forest areas, Mazongling (MZL) and Gonggashan (GGS) National Nature Forest Reserves using UAV-borne hyperspectral and LiDAR data. The results showed that the classification method performed better with higher values of R2 than the clustering algorithm for predicting both species richness (0.62 > 0.46 for MZL and 0.55 > 0.46 for GGS) and Shannon-Wiener index (0.64 > 0.58 for MZL, 0.52 > 0.47 for GGS). However, the Simpson index estimated by the classification method correlated less with the field measurements than the clustering algorithm (R2 = 0.44 and 0.83 for MZL and R2 = 0.44 and 0.62 for GGS). Our study demonstrated that the classification method could provide more accurate monitoring of forest diversity indices but requires spectral information of all dominant tree species at individual canopy scale. By comparison, the clustering method might introduce uncertainties due to the amounts of biochemical and structural inputs derived from the hyperspectral and LiDAR data, but it could acquire forest diversity patterns rapidly without distinguishing the specific tree species. Our findings underlined the advantages of UAV remote sensing for monitoring the species diversity in complex forest ecosystems and discussed the applicability of classification and clustering methods for estimating different individual tree-based species diversity indices

Correction of UAV LiDAR-derived grassland canopy height based on scan angle

Grassland canopy height is a crucial trait for indicating functional diversity or monitoring species diversity. Compared with traditional field sampling, light detection and ranging (LiDAR) provides new technology for mapping the regional grassland canopy height in a time-saving and cost-effective way. However, the grassland canopy height based on unmanned aerial vehicle (UAV) LiDAR is usually underestimated with height information loss due to the complex structure of grassland and the relatively small size of individual plants. We developed canopy height correction methods based on scan angle to improve the accuracy of height estimation by compensating the loss of grassland height. Our method established the relationships between scan angle and two height loss indicators (height loss and height loss ratio) using the ground-measured canopy height of sample plots with 1×1m and LiDAR-derived heigh. We found that the height loss ratio considering the plant own height had a better performance (R2 = 0.71). We further compared the relationships between scan angle and height loss ratio according to holistic (25–65cm) and segmented (25–40cm, 40–50cm and 50–65cm) height ranges, and applied to correct the estimated grassland canopy height, respectively. Our results showed that the accuracy of grassland height estimation based on UAV LiDAR was significantly improved with R2 from 0.23 to 0.68 for holistic correction and from 0.23 to 0.82 for segmented correction. We highlight the importance of considering the effects of scan angle in LiDAR data preprocessing for estimating grassland canopy height with high accuracy, which also help for monitoring height-related grassland structural and functional parameters by remote sensing

EGFR Tyrosine Kinase Inhibitors Activate Autophagy as a Cytoprotective Response in Human Lung Cancer Cells

Epidermal growth factor receptor tyrosine kinase inhibitors gefitinib and erlotinib have been widely used in patients with non-small-cell lung cancer. Unfortunately, the efficacy of EGFR-TKIs is limited because of natural and acquired resistance. As a novel cytoprotective mechanism for tumor cell to survive under unfavorable conditions, autophagy has been proposed to play a role in drug resistance of tumor cells. Whether autophagy can be activated by gefitinib or erlotinib and thereby impair the sensitivity of targeted therapy to lung cancer cells remains unknown. Here, we first report that gefitinib or erlotinib can induce a high level of autophagy, which was accompanied by the inhibition of the PI3K/Akt/mTOR signaling pathway. Moreover, cytotoxicity induced by gefitinib or erlotinib was greatly enhanced after autophagy inhibition by the pharmacological inhibitor chloroquine (CQ) and siRNAs targeting ATG5 and ATG7, the most important components for the formation of autophagosome. Interestingly, EGFR-TKIs can still induce cell autophagy even after EGFR expression was reduced by EGFR specific siRNAs. In conclusion, we found that autophagy can be activated by EGFR-TKIs in lung cancer cells and inhibition of autophagy augmented the growth inhibitory effect of EGFR-TKIs. Autophagy inhibition thus represents a promising approach to improve the efficacy of EGFR-TKIs in the treatment of patients with advanced non-small-cell lung cancer

Impostor Resilient Multimodal Metric Learning for Person Reidentification

In person reidentification distance metric learning suffers a great challenge from impostor persons. Mostly, distance metrics are learned by maximizing the similarity between positive pair against impostors that lie on different transform modals. In addition, these impostors are obtained from Gallery view for query sample only, while the Gallery sample is totally ignored. In real world, a given pair of query and Gallery experience different changes in pose, viewpoint, and lighting. Thus, impostors only from Gallery view can not optimally maximize their similarity. Therefore, to resolve these issues we have proposed an impostor resilient multimodal metric (IRM3). IRM3 is learned for each modal transform in the image space and uses impostors from both Probe and Gallery views to effectively restrict large number of impostors. Learned IRM3 is then evaluated on three benchmark datasets, VIPeR, CUHK01, and CUHK03, and shows significant improvement in performance compared to many previous approaches