Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

Recently exciting progress has been made on protein contact prediction, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual networks. This deep neural network allows us to model very complex sequence-contact relationship as well as long-range inter-contact correlation. Our method greatly outperforms existing contact prediction methods and leads to much more accurate contact-assisted protein folding. Tested on three datasets of 579 proteins, the average top L long-range prediction accuracy obtained our method, the representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints can yield correct folds (i.e., TMscore>0.6) for 203 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 proteins, respectively. Further, our contact-assisted models have much better quality than template-based models. Using our predicted contacts as restraints, we can (ab initio) fold 208 of the 398 membrane proteins with TMscore>0.5. By contrast, when the training proteins of our method are used as templates, homology modeling can only do so for 10 of them. One interesting finding is that even if we do not train our prediction models with any membrane proteins, our method works very well on membrane protein prediction. Finally, in recent blind CAMEO benchmark our method successfully folded 5 test proteins with a novel fold

Errata for Stochastic calculus for symmetric Markov processes

This erratum corrects the article arXiv:0806.2044 published in Ann. Probab. 36 (2008) 931--970Comment: Published in at http://dx.doi.org/10.1214/11-AOP684 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

Study of the Influence of Brand Image on Consumers\u27 Online Shopping Intention——in the Case of Cosmetics

With the rapid development of science and technology, people’s acceptance of online shopping is increasing. As an important part of online shopping, small and medium-sized cosmetics enterprises have the characteristics of small investment scale and flexible adjustment of brand strategy, but previous research lack sustained and effective methods and tools to analysis brand impact. The paper takes INOHERB as an example, to explore the connotation and feature of brand and brand image from the perspective of the cosmetics online shopping, as well as the relevant theories of online shopping intention. Through literature review, the paper applies the bell brand image measurement model, dividing brand image into corporate image and product or service image, and user image. It also adds the analysis on the consumption characteristics, so as to test result reasonableness of the brand image analysis’s influence on online shopping intention. Data were collected from college female students by print questionnaires and online surveys. The result indicated that corporate image has a strong influence on consumer online shopping intention. Besides, product and service image also have a significant influence on consumer online shopping intention, consumers are more willing to buy cosmetics online above average prices with positive word of mouth and good quality

BH3 mimetic ABT-737 sensitizes colorectal cancer cells to ixazomib through MCL-1 downregulation and autophagy inhibition.

The proteasome inhibitor MLN9708 is an orally administered drug that is hydrolyzed into its active form, MLN2238 (ixazomib). Compared with Bortezomib, MLN2238 has a shorter proteasome dissociation half-life and a lower incidence and severity of peripheral neuropathy, which makes it an attractive candidate for colorectal cancer treatment. In the present study, we observed that MLN2238 induced autophagy, as evidenced by conversion of the autophagosomal marker LC3 from LC3I to LC3II, in colorectal cancer cell lines. Mcl-1, an anti-apoptotic Bcl-2 family protein, was markedly elevated after treating a colorectal cancer cell line with MLN2238. We proved that inhibiting Mcl-1 expression enhances MLN2238 induced apoptosis and negatively regulates autophagy. Co-administration of BH3 mimetic ABT-737 with MLN2238 synergistically kills colorectal cancer cells through MCL-1 neutralization and autophagy inhibition. Furthermore, the synergistic killing effect of the combination therapy is correlated with P53 status in colorectal cancer. These data highlight that the combination of ABT-737 with MLN9708 is a promising therapeutic strategy for human colorectal cancer

Priprava toplinskoizolacijske žbuke s FGD-gipsom

Thermal insulation gypsum plaster was prepared from flue gas desulphurization (FGD) gypsum. K12 is more recommendable as foaming agent, when the mass fraction of K12 is around 0.1 %, the setting time and compressive strength meet the requirements of gypsum-based construction materials. In the meanwhile, the thermal conductivity is 0.18 W m–1 K–1, which can be used as a thermal insulation material. The hemihydrate mixtures obtained, allow the design of a new wall structure, which is more efficient as a thermal insulation system. The wall heat transfer coefficient test was carried out to compare thermal performance of two different thermal insulation systems. Compared with the thermal performance of a conventional system, the heat transfer coefficient of the new system was reduced by 5.6 %. Finally, energy-saving analysis of a building was carried out to compare the energy-saving effect of the conventional and new systems of building. The energy-savings of the building with the new system increased by almost 2 %, thus resulting in low energy consumption of the building.Toplinskoizolacijska gipsana žbuka izrađena je od gipsa nastalog odsumporavanjem dimnog plina (FGD). Uz maseni udjel sredstva za pjenjenje (K12) 0,1 % toplinska provodnost iznosi 0,18 W m–1 K–1 pa se materijal može upotrijebiti za toplinsku izolaciju. Žbuka i sredstvo za pjenjenje uključeni su u novi tip zidne toplinske izolacije. Koeficijent prijenosa topline novog izolacijskog sustava određen je eksperimentalno i iznosi 0,608 W m–2 K–1. Na temelju analize zaključeno je da se s novim sustavom ušteda energije u zgradi može popeti do 66,99 %. Novi materijal može imati velik utjecaj na energijsku učinkovitost zgrade