Continuum of Bound States in a Non-Hermitian Model.

In a Hermitian system, bound states must have quantized energies, whereas free states can form a continuum. We demonstrate how this principle fails for non-Hermitian systems, by analyzing non-Hermitian continuous Hamiltonians with an imaginary momentum and Landau-type vector potential. The eigenstates, which we call "continuum Landau modes" (CLMs), have Gaussian spatial envelopes and form a continuum filling the complex energy plane. We present experimentally realizable 1D and 2D lattice models that host CLMs; the lattice eigenstates are localized and have other features matching the continuous model. One of these lattices can serve as a rainbow trap, whereby the response to an excitation is concentrated at a position proportional to the frequency. Another lattice can act a wave funnel, concentrating an input excitation onto a boundary over a wide frequency bandwidth. Unlike recent funneling schemes based on the non-Hermitian skin effect, this requires a simple lattice design with reciprocal couplings.

New insights into the alkoxy effects on auxiliary adsorption and inhibiting charge recombination in dye-sensitized solar cells with high open circuit voltage: a theoretical investigation.

Although introducing an alkoxy group is one of the most popular methods to suppress the interfacial charge recombination process of dye-sensitized solar cells, understanding of its effects is still limited and a microscopic picture of the alkoxy effects is lacking. Two ullazine dyes with distinct alkoxy chains at the donor part are used to investigate the effects of the alkoxy group on the adsorption, dye aggregation and charge recombination process in our study. Different from the usual assumption, we find that alkoxy chains can not only play a shielding role, but can also assist dye adsorption and inhibit the charge recombination process more effectively by covering the TiO2 surface. We also find that the existence of alkyl chains can well inhibit the aggregation of dyes and reduce intermolecular electron transfer. Furthermore, an important structural feature at the interface, the Ti-O interaction between the oxygen atom of the alkoxy group and the Ti atom of the surface is also found to contribute substantially to the interface stability. New insights into the effects of the alkoxy group on auxiliary adsorption and inhibiting charge recombination through reducing the recombination sites pave the way for rational design of sensitizers with high performance.

Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications.

Exponential growth in data rate demands has driven efforts to develop novel beamforming techniques for realizing massive multiple-input and multiple-output (MIMO) systems in sixth-generation (6G) terabits per second wireless communications. Existing beamforming techniques rely on conventional optimization algorithms that are too computationally expensive for real-time applications and require complex digital processing yet to be achieved for phased array antennas at terahertz frequencies. Here, we develop an intelligent and self-adaptive beamforming scheme enabled by deep reinforcement learning, which can predict the spatial phase profiles required to produce arbitrary desired radiation patterns in real-time. Our deep learning model adaptively trains an artificial neural network in real-time by comparing the input and predicted intensity patterns via automatic differentiation of the phase-to-intensity function. As a proof of concept, we experimentally demonstrate two-dimensional beamforming by spatially modulating broadband terahertz waves using silicon metasurfaces designed with the aid of the deep learning model. Our work offers an efficient and robust deep learning model for real-time self-adaptive beamforming to enable multi-user massive MIMO systems for 6G terahertz wireless communications, as well as intelligent metasurfaces for other terahertz applications in imaging and sensing.

Long-term outcomes of kidney transplantation from expanded criteria donors with Chinese novel donation policy: donation after citizens' death.

INTRODUCTION: The Chinese Government initiated the Donation after Citizens' Death policy in 2010. To now, it has been a major source of organs for transplant. Since it is still a young policy, corresponding clinical evidence is still urgently needed for its improvement. Compared to kidneys donated by SCD (standard criteria donor), increasing the use of ECD (expanded criteria donor) derived kidneys is a way to expand the donor pool but is also a result of the aging demography of China. This study is based on the data of kidney transplantation in our center with the Donation after Citizens' Death policy, aiming to provide a reference for the clinical use of ECD kidneys. METHOD: A retrospective study enrolled 415 kidney transplants derived from 211 donors performed between October 2011 and October 2019. A total of 311 (74.9%) organs were donated from 159 (75.4%) SCDs, and the remaining 104 (25.1%) were from 52 (24.6%) ECDs. The log-rank test was used to compare the difference in survival and postoperative complications. The Chi-square test was used to compare the occurrence of postoperative complications and postoperative renal function. The Cox regression analysis was used for risk factor screening. RESULT: Analysis showed that grafts from ECD were poorer in survival (P = 0.013), while their recipients had comparable (P = 0.16) survival. Moreover, it also was an independent risk factor for graft loss (HR 2.27, P = 0.044). There were significantly more AR occurrences in the ECD group compared with SCD group (25.0% vs. 15.8%, P = 0.004), but no significant difference was found in infection (51.9% vs. 47.6%, P = 0.497) and DGF (26.0% vs. 21.9%, P = 0.419) between them. Similarly, fewer recipients in the ECD group were free from AR within 1 year after transplantation (P = 0.040), with no statistical difference in all-cause infection prevalence in 1 year (P = 0.168). The eGFR in the ECD group was significantly worse than that in the SCD group at 3 months, 6 months, 1 year, 3 years, and the highest value posttransplant (all < 0.05), but no difference at 5 years posttransplant. Besides, results showed cardiac arrest (uncontrolled vs. controlled, HR 2.49, P = 0.049), HLA mismatch (4-6 loci vs. 0-3 loci, HR 3.61, P = 0.039), and AR occurrence (HR 2.91, P = 0.006) were demonstrated to be independent risk factors for graft loss. CONCLUSION: The ECD-derived kidney was worse than the SCD-derived kidney in terms of graft survival and AR occurrence, and trend to an inferior renal function postoperative. However, the recipient survival, DGF occurrence, and all-cause infection occurrence were similar.

DUSP4 promotes the carcinogenesis of CCRCC via negative regulation of autophagic death.

DUSP4 is considered as an oncogenic gene. However, the effect of DUSP4 on the carcinogenesis of clear cell Renal cell carcinoma (CCRCC) is still unclear. In this study, DUSP4 mRNA levels were significantly increased in CCRCC tissues and cell lines. Furthermore, DUSP4 overexpression promotes the proliferation, migration, and tumorigenicity of CCRCC cells while DUSP4 silencing showed the opposite effects. Importantly, both autophagic activity (LC3 conversion rate and LC3 puncta formation) and total death level promoted by DUSP4 silencing were reversed by treatment with 3-MA in CCRCC cells. Moreover, the proliferation and migration of CCRCC cells inhibited by DUSP4 silencing were also recovered by suppression of autophagy with 3-MA. In conclusion, DUSP4 serves as an oncogenic gene in CCRCC carcinogenesis due to its inhibitory effect on autophagic death, indicating the potential value of DUSP4 in the diagnosis and treatment of CCRCC.

Cell fate regulation by reticulon-4 in human prostate cancers.

Reticulon-4 (RTN4), a reticulon family protein localized in the endoplasmic reticulum, is reported to be involved in multiple physiological processes like neuroendocrine secretion and membrane trafficking in neuroendocrine cells. Previous studies have presented a great potential of RTN4 for the treatment of autoimmune-mediated demyelinating diseases and spinal cord injury regeneration. While interaction with Bcl-2 and Bcl-2-like family in apoptosis modulation implicated its possible role in various human cancers. However, the investigation of this gene in prostate cancer is mainly ignored. Here in our current study, we focused on its role in prostate cancer and found that RTN4 DNA copy numbers were higher in prostate cancer than normal prostate gland while its RNA and protein expressions were relatively lower. Chromosomal neighbor gene EML6 had similar expression patterns with RTN4 in prostate cancer tissues and cell lines, and further research found that they could be both targeted by miR-148a-3p. Lentivirus-mediated RTN4 overexpression potently inhibited DU145 and LNCaP cells proliferation. Cell cycle was blocked in G2/M phase and significant cell senescence was observed in RTN4 overexpressed prostate cancer cells. Finally, interaction networks in the normal prostate gland and cancer tissues further revealed that RTN4 maybe phosphorylated by MAPKAPK2 and FYN at tyrosine 591 and serine 107, respectively. All these results implied that RTN4 might somehow participate in prostate tumor progression, and this elicits possibility to develop or identify selective agents targeting RTN4 for prostate cancer therapy.

Insight into spin-orbital interaction using MCSCF method: A special analysis of the 1 Σg + electronic state in C2 and the linear polyacetylenic C4 and C6.

The symmetry-broken wave function can transform the 1 Σg + state of C2 from the classic double bonding to the quadruple bonding, where the transformed wave functions of ϕ L and ϕ R are singly occupied by two opposite-spinning electrons. In this article, the effective bond order (EBO) contribution of the fourth bond in C2 is assessed through the overlap integral between ϕ L and ϕ R , namely the value (0.60) is the EBO contribution of the fourth bond in the transformed scheme. Hence, the new EBO is 3.36, which is more equitable than the original EBO (2.15) in the traditional scheme. In addition, the singlet diradical character of the linear polyacetylenic C4 and C6 in the 1 Σg + state is addressed for the first time. No spin-polarized bonding exists in other linear C2n clusters, because the ionic interaction in the polyacetylenic 1 Σg + state of C4 is negligible. Moreover, the coupling energy between α and ß single electrons in C4 is only 4.0 kcal mol-1 based on the electron spin-flip energy. © 2019 Wiley Periodicals, Inc.

Squalene monooxygenase facilitates bladder cancer development in part by regulating PCNA.

Bladder cancer (BC) is one of the most common cancers worldwide. Although the treatment and survival rate of BC are being improved, the risk factors and the underlying mechanisms causing BC are incompletely understood. Squalene monooxygenase (SQLE) has been associated with the occurrence and development of multiple cancers but whether it contributes to BC development is unclear. In this study, we performed bioinformatics analysis on paired BC and adjacent non-cancerous tissues and found that SQLE expression is significantly upregulated in BC samples. Knockdown of SQLE impairs viability, induces apoptosis, and inhibits the migration and invasion of BC cells. RNA-seq data reveals that SQLE deficiency leads to dysregulated expression of genes regulating proliferation, migration, and apoptosis. Mass spectrometry-directed interactome screening identifies proliferating cell nuclear antigen (PCNA) as an SQLE-interacting protein and overexpression of PCNA partially rescues the impaired viability, migration, and invasion of BC cells caused by SQLE knockdown. In addition, we performed xenograft assays and confirmed that SQLE deficiency inhibits BC growth in vivo. In conclusion, these data suggest that SQLE promotes BC development and SQLE inhibition may be therapeutically useful in BC treatment.

Fascinating Electrocatalysts with Dispersed Di-Metals in MN3 -M'N4 Moiety as Two Active Sites Separately for N2 and CO2 Reduction Reactions and Jointly for CN Coupling and Urea Production.

The idealized urea electrocatalyst is crucial to boost the CN coupling reaction and simultaneously suppress their isolated reduction process after adsorbing N2 and CO2 molecules. Therefore, the dispersed MN3 -M'N4 moiety is investigated systematically, including 26 homonuclear and 650 heteronuclear di-metal systems. After, 205 stable systems are selected using lowest-energy principle and ab initio molecular dynamics simulations. According to three possible pathways, NCON, CO, and OCOH to produce urea, a five-step high-throughput screening method for excellent catalytic activity and a five-aspect high-throughput screening strategy for outstanding catalytic selectivity are proposed, respectively. The potential determined steps and the limiting potential through three pathways are identified. The data indicates both CO pathway and OCOH pathway are more competitive at lower Gibbs free energy. Significantly, the most favorite RuN3 -CoN4 combination possesses an extremely low limiting potential of -0.80 V for urea production, meanwhile it exists a strong foundation for experimental preparation. This work not only broadens electrocatalytic potentiality of developing di-metals as two active sites, but also provides a feasible high-throughput screening recipe for urea production.

Non-metal boron atoms on a CuB12 monolayer as efficient catalytic sites for urea production.

An electrocatalytic C-N coupling reaction to convert CO2 and N2 into urea under mild conditions has been proposed to be a promising alternative experimentally, but the development of highly stable, low-cost and high-performance non-metal catalytic sites remains rare and challenging. Herein, a global-minimum CuB12 monolayer with superior stability has been identified based on first-principles computations, and the most significant finding is that the CuB12 monolayer possesses the best catalytic activity among the reported urea catalysts thermodynamically and kinetically. All possible reaction pathways to form urea (NH2CONH2) starting from the CO2 molecule and N2 molecule, including the CO2 pathway, OCOH pathway, CO pathway, NCON pathway and mixed pathway, as well as the kinetic energy barriers of six possible C-N coupling reactions are systematically investigated. Non-metal B atoms at the midpoint of the edges of the squares act as excellent catalytic sites with a limiting potential of urea production of 0.23 V through the CO2 pathway and OCOH pathway and the lowest kinetic energy barrier of C-N bond formation (0.54 eV) through the reaction *CO + *NHNH → *NHCONH. Therefore, this study not only identifies the first non-metal B catalytic sites for urea formation, but also perfects the reaction mechanism to convert CO2 and N2 into urea, which could provide great guiding significance to explore other high-performance urea catalysts.

Establishing the Principal Descriptor for Electrochemical Urea Production via the Dispersed Dual-Metals Anchored on the N-Decorated Graphene.

Urea electrosynthesis under mild conditions starting from the adsorption of inert N2 molecules has brought out a promising alternative experimentally to conquer its huge energy consumption in industrial Haber-Bosch process. The most crucial and inevitable reaction is the formation of urea precursor *NCON from *N2 and CO based on the pre-selected reaction pathway, together with the following protonated processes. It is significant to comprehend their intrinsic intercorrelation and explore the principal descriptor from massive reaction data. Hereby, the authors study the dispersed dual-metals (homonuclear MN3 -MN3 moiety and heteronuclear MN3 -M'N3 moiety) anchored on N-doped graphene as electrocatalysts to synthesize urea. Based on the screened out 72 stable systems by ab initio molecular dynamics (AIMD) simulations as the database, six significant linear correlations between the computed Gibbs free energy and other important factors are achieved. Most encouragingly, the principal descriptor (ΔE(*NCONH)) is established because 72% low-performance systems can be filtered out and its effective range (-1.0 eV < ΔEE(*NCONH) < 0.5 eV) is identified by eight optimal systems. This study not only suggests that dispersed dual-metals via MN3 moiety can serve as promising active sites for urea production, but also identifies the principal descriptor and its effective range in high-throughput methods.

Effective CO Migration among Multiabsorbed Sites Achieves the Low-Barrier and High-Selective Conversion to C2 Products on the Ni2B5 Monolayer.

For the electrochemical reduction of CO2, CO is a crucial single-carbon product and a major intermediate to multicarbon products. Direct dimerization of CO is the most charming channel to C2 products, although the corresponding kinetic energy barrier causes a huge gap compared with other alternative pathways. The effective CO migration among multiple catalytic sites is predominant but has not been fully explored during the C-C bond formation and further protonation processes. Herein, the entirely planar global-minimum Ni2B5 monolayer with multikinds of catalytic sites is selected as an appropriate instance, on which CO can effectively migrate among different types of sites with the highest barrier of 0.64 eV. Most importantly, the computed ultralow barrier of direct *CO dimerization (0.17 eV), the limiting potentials for CH2CH2 (-0.13 V), and CH3CH2OH (-0.17 V) reach the optimal value until now, which all happen on the p-p type of dual-CO adsorption configurations after CO migration. Moreover, the hydrogen reduction side reaction is uncompetitive with the CO electrochemical reduction on all possible adsorption sites. This study demonstrates the significance of CO migration and opens a new avenue for CO reduction to high-density multicarbon products on the surface of catalysts possessing multikinds of catalytic sites.

Image reconstruction through a multimode fiber with a simple neural network architecture.

Multimode fibers (MMFs) have the potential to carry complex images for endoscopy and related applications, but decoding the complex speckle patterns produced by mode-mixing and modal dispersion in MMFs is a serious challenge. Several groups have recently shown that convolutional neural networks (CNNs) can be trained to perform high-fidelity MMF image reconstruction. We find that a considerably simpler neural network architecture, the single hidden layer dense neural network, performs at least as well as previously-used CNNs in terms of image reconstruction fidelity, and is superior in terms of training time and computing resources required. The trained networks can accurately reconstruct MMF images collected over a week after the cessation of the training set, with the dense network performing as well as the CNN over the entire period.