A pangenome reference of 36 Chinese populations.

Human genomics is witnessing an ongoing paradigm shift from a single reference sequence to a pangenome form, but populations of Asian ancestry are underrepresented. Here we present data from the first phase of the Chinese Pangenome Consortium, including a collection of 116 high-quality and haplotype-phased de novo assemblies based on 58 core samples representing 36 minority Chinese ethnic groups. With an average 30.65× high-fidelity long-read sequence coverage, an average contiguity N50 of more than 35.63 megabases and an average total size of 3.01 gigabases, the CPC core assemblies add 189 million base pairs of euchromatic polymorphic sequences and 1,367 protein-coding gene duplications to GRCh38. We identified 15.9 million small variants and 78,072 structural variants, of which 5.9 million small variants and 34,223 structural variants were not reported in a recently released pangenome reference1. The Chinese Pangenome Consortium data demonstrate a remarkable increase in the discovery of novel and missing sequences when individuals are included from underrepresented minority ethnic groups. The missing reference sequences were enriched with archaic-derived alleles and genes that confer essential functions related to keratinization, response to ultraviolet radiation, DNA repair, immunological responses and lifespan, implying great potential for shedding new light on human evolution and recovering missing heritability in complex disease mapping.

Synthesis and biological evaluations of 8-biaryl-2,2-dimethylbenzopyranamide derivatives against Alzheimer's disease and ischemic stroke.

Alzheimer's disease, the commonest cause of dementia, is a growing global health concern with huge implications for individuals and society. Stroke has still been a significant challenge in clinics for a long time, which is the second leading cause of death in the world, especially ischemic stroke. Both Alzheimer's disease and stroke are closely related to oxidative stress and HIF-1 signaling pathways in nerve cells. Herein, we describe our structure-based design, synthesis, and biological evaluation of a new class of 8-biaryl-2,2-dimethylbenzopyranamide derivatives as natural product derivatives. Our efforts have resulted in the discovery of highly potent neuroprotective agents, as exemplified by compound D13 as a HIF-1α inhibitor, which significant improvement in the behavior of Alzheimer's disease mice and shows great potential improvement of brain infarct volume in pMCAO model rats, improves the increase of blood-brain barrier permeability after cerebral ischemia in rats, neuroprotective effect, reduce the level of apoptotic cells in rats after cerebral ischemia, better than Edaravone.

Multimodal representation learning for tourism recommendation with two-tower architecture.

Personalized recommendation plays an important role in many online service fields. In the field of tourism recommendation, tourist attractions contain rich context and content information. These implicit features include not only text, but also images and videos. In order to make better use of these features, researchers usually introduce richer feature information or more efficient feature representation methods, but the unrestricted introduction of a large amount of feature information will undoubtedly reduce the performance of the recommendation system. We propose a novel heterogeneous multimodal representation learning method for tourism recommendation. The proposed model is based on two-tower architecture, in which the item tower handles multimodal latent features: Bidirectional Long Short-Term Memory (Bi-LSTM) is used to extract the text features of items, and an External Attention Transformer (EANet) is used to extract image features of items, and connect these feature vectors with item IDs to enrich the feature representation of items. In order to increase the expressiveness of the model, we introduce a deep fully connected stack layer to fuse multimodal feature vectors and capture the hidden relationship between them. The model is tested on the three different datasets, our model is better than the baseline models in NDCG and precision.

Multilevel resistive switching memory in lead-free double perovskite La[Formula: see text]NiFeO[Formula: see text] films.

Dense and flat La[Formula: see text]NiFeO[Formula: see text] (LNFO) films were fabricated on the indium tin oxide-coated glass (ITO/glass) substrate by sol-gel method. The bipolar resistive switching behavior (BRS) could be maintained in 100 cycles and remained after 30 days, indicating that the LNFO-based RS device owned good memory stability. Surprisingly, the multilevel RS characteristics were firstly observed in the Au/LNFO/ITO/glass device. The high resistance states (HRSs) and low resistance state (LRS) with the maximum ratio of [Formula: see text] 500 could be remained stably in 900 s and 130 cycles, demonstrating the fine retention and endurance ability of this LNFO-based RS device. The BRS behavior of Au/LNFO/ITO/glass devices primarily obeyed the SCLC mechanism controlled by oxygen vacancies (OVs) dispersed in the LNFO layer. Under the external electric field, injected electrons were captured or discharged by OVs during trapping or detrapping process in the LNFO layer. Thus, the resistive state switched between HRS and LRS reversibly. Moreover, the modulation of Schottky-like barrier formed at the Au/LNFO interface was contributed to the resistive states switchover. It was related to the change in OVs located at the dissipative region near the Au/LNFO interface. The multilevel RS ability of LNFO-based devices in this work provides an opportunity for researching deeply on the high density RS memory in lead-free double perovskite oxides-based devices.

Gram-Scale Synthesis of Graphitic Carbon Nitride Quantum Dots with Ultraviolet Photoluminescence for Fe3+ Ion Detection.

A method for gram-scale synthesis of graphitic carbon nitride quantum dots (g-C3N4QDs) was developed. The weight of the g-C3N4QDs was up to 1.32 g in each run with a yield of 66 wt%, and the purity was 99.96 wt%. The results showed that g-C3N4QDs exhibit a stable and strong ultraviolet photoluminescence at a wavelength of 365 nm. More interestingly, the g-C3N4QDs can be used as a high-efficiency, sensitive, and selective fluorescent probe to detect Fe3+ with a detection limit of 0.259 µM.

Hyperspectral Pansharpening With Deep Priors.

Hyperspectral (HS) image can describe subtle differences in the spectral signatures of materials, but it has low spatial resolution limited by the existing technical and budget constraints. In this paper, we propose a promising HS pansharpening method with deep priors (HPDP) to fuse a low-resolution (LR) HS image with a high-resolution (HR) panchromatic (PAN) image. Different from the existing methods, we redefine the spectral response function (SRF) based on the larger eigenvalue of structure tensor (ST) matrix for the first time that is more in line with the characteristics of HS imaging. Then, we introduce HFNet to capture deep residual mapping of high frequency across the upsampled HS image and the PAN image in a band-by-band manner. Specifically, the learned residual mapping of high frequency is injected into the structural transformed HS images, which are the extracted deep priors served as additional constraint in a Sylvester equation to estimate the final HR HS image. Comparative analyses validate that the proposed HPDP method presents the superior pansharpening performance by ensuring higher quality both in spatial and spectral domains for all types of data sets. In addition, the HFNet is trained in the high-frequency domain based on multispectral (MS) images, which overcomes the sensitivity of deep neural network (DNN) to data sets acquired by different sensors and the difficulty of insufficient training samples for HS pansharpening.

[Size Distribution and Mixing State of Black Carbon Aerosol in Nanjing During a Heavy Winter Pollution Event].

In December 2013,a lasting haze pollution event occurred in the Central and East regions of China.Here in this paper,using a single-particle soot photometer (SP2),we studied mass concentrations,mixing states,and size distributions of black carbon (BC) in this event.The results showed that BC mass concentration in Nanjing during the observation period was in the range of 1.01-14.05 µg·m-3 with an average of 4.39 µg·m-3,showing the characteristics of double peaks for lighter pollution,andhigh in the nighttime and low in the daytime during heavier pollution.Using the relative coating thickness (Dp/Dc) to define mixing state of black carbon,diurnal variations were higher in early morning and noon when slightly polluted,and lower during rush hour,indicating the degree of BC ageing was deeper in the morning and afternoon,with fresher particles near the ground source emissions during rush hour.The relative coating thickness did not vary greatly throughout the day when heavily polluted,which was expected to be linked to regional pollutants and it also showed Gas-solid transformation under high relative humidity.The average mass and number size distribution had single peaking with the same BC volume-equivalent diameter in different degrees of pollution,with the peak diameter at 100 nm for the number distribution when heavily polluted,at 91 nm when slightly polluted,and at 210 nm for the mass distribution regardless of the degree of pollution.We could find regional differences of BC sources by comparing the observed research worldwide.This study has very important reference value for the in-depth understanding of BC pollution in Yangtze River Delta.