Study on Effects of salt stress on the Suberin Lamella of grapevine roots

Grape is one of the oldest tree species in the world which have a relatively high tolerance to salt stress. The function of Suberin Lamella is to control the transport of water and ions, which has a positive effect on salt tolerance. However, whether the suberin lamella of grape root is related to its salt-tolerance has not been revealed. In this study, suberin lamella in roots of two grape varieties, "Crimson seedless" and "1103p", were stained by FY0888. Results showed that salt stress induced the appearance and thickening of suberin lamella of grape root cortex. The induction effect was very obvious in salt-toerant "Crimson seedless", while the effect was weak in "1103P", indicating that the suberin lamella of grape was indeed involved in the salt tolerance of grape

From Static to Dynamic Structures: Improving Binding Affinity Prediction with a Graph-Based Deep Learning Model

Accurate prediction of the protein-ligand binding affinities is an essential challenge in the structure-based drug design. Despite recent advance in data-driven methods in affinity prediction, their accuracy is still limited, partially because they only take advantage of static crystal structures while the actual binding affinities are generally depicted by the thermodynamic ensembles between proteins and ligands. One effective way to approximate such a thermodynamic ensemble is to use molecular dynamics (MD) simulation. Here, we curated an MD dataset containing 3,218 different protein-ligand complexes, and further developed Dynaformer, which is a graph-based deep learning model. Dynaformer was able to accurately predict the binding affinities by learning the geometric characteristics of the protein-ligand interactions from the MD trajectories. In silico experiments demonstrated that our model exhibits state-of-the-art scoring and ranking power on the CASF-2016 benchmark dataset, outperforming the methods hitherto reported. Moreover, we performed a virtual screening on the heat shock protein 90 (HSP90) using Dynaformer that identified 20 candidates and further experimentally validated their binding affinities. We demonstrated that our approach is more efficient, which can identify 12 hit compounds (two were in the submicromolar range), including several newly discovered scaffolds. We anticipate this new synergy between large-scale MD datasets and deep learning models will provide a new route toward accelerating the early drug discovery process.Comment: totally reorganize the texts and figure

Investigation into the microstructure and dynamic compressive properties of selective laser melted Ti–6Al–4V alloy with different heating treatments

As a commonly used engineering material, the mechanical properties of titanium alloy under dynamic loads are closely related to their microstructure. In this work, the effects of solution treatment (ST) and solution and aging treatment (SAT) on the microstructure and dynamic compressive properties of Ti–6Al–4V alloy manufactured by selective laser melting were studied. The results showed that the microstructure of selective laser melted Ti–6Al–4V consisted of nearly full acicular α′ martensite, then the acicular α′ martensite was decomposed into α+β phase with basket-weave morphology with solution treatment. Clusters of α2 particles with size of several hundred nanometers were precipitated in the α plates further with solution and aging treatment. The ultimate compressive strength (UCS) of selective laser melted TC4 alloy was increased with the increasing strain rate, showing strong strain rate hardening effect. Stress collapse happened once the strain exceeded 1500/s, which is the dominant failure model of selective laser melted TC4 under impacting load. As expected, the UCS of the ST sample decreased, but the ductility increased compared with the as-built sample; however, both the UCS and ductility of the SAT samples were enhanced synergistically due to the widely distributed α2 precipitates. Besides, the SAT samples had the highest energy absorption compared with the as-built and ST counterparts under the same conditions, indicating that the SAT samples had better load-bearing capacities

Concept for a Future Super Proton-Proton Collider

Following the discovery of the Higgs boson at LHC, new large colliders are being studied by the international high-energy community to explore Higgs physics in detail and new physics beyond the Standard Model. In China, a two-stage circular collider project CEPC-SPPC is proposed, with the first stage CEPC (Circular Electron Positron Collier, a so-called Higgs factory) focused on Higgs physics, and the second stage SPPC (Super Proton-Proton Collider) focused on new physics beyond the Standard Model. This paper discusses this second stage.Comment: 34 pages, 8 figures, 5 table

The Local Origin of the Tibetan Pig and Additional Insights into the Origin of Asian Pigs

BACKGROUND: The domestic pig currently indigenous to the Tibetan highlands is supposed to have been introduced during a continuous period of colonization by the ancestors of modern Tibetans. However, there is no direct genetic evidence of either the local origin or exotic migration of the Tibetan pig. METHODS AND FINDINGS: We analyzed mtDNA hypervariable segment I (HVI) variation of 218 individuals from seven Tibetan pig populations and 1,737 reported mtDNA sequences from domestic pigs and wild boars across Asia. The Bayesian consensus tree revealed a main haplogroup M and twelve minor haplogroups, which suggested a large number of small scale in situ domestication episodes. In particular, haplogroups D1 and D6 represented two highly divergent lineages in the Tibetan highlands and Island Southeastern Asia, respectively. Network analysis of haplogroup M further revealed one main subhaplogroup M1 and two minor subhaplogroups M2 and M3. Intriguingly, M2 was mainly distributed in Southeastern Asia, suggesting for a local origin. Similar with haplogroup D6, M3 was mainly restricted in Island Southeastern Asia. This pattern suggested that Island Southeastern Asia, but not Southeastern Asia, might be the center of domestication of the so-called Pacific clade (M3 and D6 here) described in previous studies. Diversity gradient analysis of major subhaplogroup M1 suggested three local origins in Southeastern Asia, the middle and downstream regions of the Yangtze River, and the Tibetan highlands, respectively. CONCLUSIONS: We identified two new origin centers for domestic pigs in the Tibetan highlands and in the Island Southeastern Asian region

A survey on heterogeneous face recognition: Sketch, infra-red, 3D and low-resolution

Heterogeneous face recognition (HFR) refers to matching face imagery across different domains. It has received much interest from the research community as a result of its profound implications in law enforcement. A wide variety of new invariant features, cross-modality matching models and heterogeneous datasets are being established in recent years. This survey provides a comprehensive review of established techniques and recent developments in HFR. Moreover, we offer a detailed account of datasets and benchmarks commonly used for evaluation. We finish by assessing the state of the field and discussing promising directions for future research

Index construction and application of digital transformation in the insurance industry: Evidence from China.

In the context of digitization, the insurance industry's value chain is undergoing significant shifts. However, the existing research on its comprehension and measurement remains relatively limited. This study constructs an index system for digital transformation in the insurance industry (DTII) on three components: digital infrastructure, digital platform, and digital applications. Utilizing data from 31 provinces in China, this study employs the entropy weight method, analytic hierarchy process method and minimum relative entropy method to measure the weights of indicators, empirically applying this index system. The results show that DTII in China experiences rapid advancement with an average annual growth rate of 20.46% from 2014 to 2020 and there exists strong regional convergence. In addition, the spatial agglomeration and spatial effects of DTII are mainly concentrated in the life insurance industry and the eastern region. This study provides an index system and empirical evidence for evaluating the DTII, providing policy insights for exploring the sustainable development path of the insurance industry in the digital era

PREDICTIVE GREY MARKOV CHAIN MODEL FOR PITTING CORROSION IN PIPLINES

Based on the Grey theory and Markov Chain theory,two prediction models were built,they are Grey Markov Chain prediction model based on absolute distribution（ GMCAD） and Grey Markov Chain prediction model based on probability summation（ GMCPS）. These two models were used to predict the corrosion life of the oil-gas pipeline. Firstly,the calculation method of pit depth was built by the Grey theory. Secondly,test of Markov property was done to verify its feasibility. At last,GMCAD and GMCPS were used,respectively,to predict the corrosion state of the pipeline and results were compared. It indicates that both two models can give a correct prediction and the result from GMCPS is more accurate

A multimodal hybrid parallel network intrusion detection model

With the rapid growth of Internet data traffic, the means of malicious attack become more diversified. The single modal intrusion detection model cannot fully exploit the rich feature information in the massive network traffic data, resulting in unsatisfactory detection results. To address this issue, this paper proposes a multimodal hybrid parallel network intrusion detection model (MHPN). The proposed model extracts network traffic features from two modalities: the statistical information of network traffic and the original load of traffic, and constructs appropriate neural network models for each modal information. Firstly, a two-branch convolutional neural network is combined with Long Short-Term Memory (LSTM) network to extract the spatio-temporal feature information of network traffic from the original load mode of traffic, and a convolutional neural network is used to extract the feature information of traffic statistics. Then, the feature information extracted from the two modalities is fused and fed to the CosMargin classifier for network traffic classification. The experimental results on the ISCX-IDS 2012 and CIC-IDS-2017 datasets show that the MHPN model outperforms the single-modal models and achieves an average accuracy of 99.98 $\%$ . The model also demonstrates strong robustness and a positive sample recognition rate

Mechanism of Vitamin D Receptor Inhibition of Cholesterol 7α-Hydroxylase Gene Transcription in Human HepatocytesS⃞

Lithocholic acid (LCA) is a potent endogenous vitamin D receptor (VDR) ligand. In cholestasis, LCA levels increase in the liver and intestine. The objective of this study is to test the hypothesis that VDR plays a role in inhibiting cholesterol 7α-hydroxylase (CYP7A1) gene expression and bile acid synthesis in human hepatocytes. Immunoblot analysis has detected VDR proteins in the nucleus of the human hepatoma cell line HepG2 and human primary hepatocytes. 1α, 25-Dihydroxy-vitamin D3 or LCA acetate-activated VDR inhibited CYP7A1 mRNA expression and bile acid synthesis, whereas small interfering RNA to VDR completely abrogated VDR inhibition of CYP7A1 mRNA expression in HepG2 cells. Electrophoretic mobility shift assay and mutagenesis analyses have identified the negative VDR response elements that bind VDR/retinoid X receptor α in the human CYP7A1 promoter. Mammalian two-hybrid, coimmunoprecipitation, glutathione S-transferase pull-down, and chromatin immunoprecipitation assays show that ligand-activated VDR specifically interacts with hepatocyte nuclear factor 4α (HNF4α) to block HNF4α interaction with coactivators or to compete with HNF4α for coactivators or to compete for binding to CYP7A1 chromatin, which results in the inhibition of CYP7A1 gene transcription. This study shows that VDR is expressed in human hepatocytes and may play a critical role in the inhibition of bile acid synthesis, thus protecting liver cells during cholestasis