62 GHz germanium photodetector with inductive gain peaking electrode for photonic receiving beyond 100 Gbaud

Silicon photonics has attracted a great deal of interest for integrated photonics systems due to its large-scale electronics-photonics integration on a chip by leveraging the fabrication process of the complementary-metal-oxide semiconductor(CMOS)foundries[1−5].Germanium-on-silicon(Ge-on-Si)waveguide photodetector(PD)is an indispensable building block of silicon photonics technology which requires high sensitivity.

塞来昔布联合顺铂对人舌鳞癌Tca8113细胞移植瘤的生长抑制作用(英文)

Objective:The aim of this study was to observe the inhibitory effect of application of COX-2 inhibitor,celecoxib,combined with cisplatin on the growth of human tongue squamous carcinoma Tca8113 cell xenograft by animal experiment.Methods:The nude mice were transplanted subcutaneously with Tca 8113 cells,and then were administrated with celecoxib,cisplatin or celecoxib combined with cisplatin respectively,and were sacrificed after 35 days.The weight of xenograft was measured to calculate the tumor inhibition rate.The histological change was studied under light and electron microscope.The COX-2 protein expression was observed by immunohistological staining.And the COX-2 mRNA expression was determined by RT-PCR.Results:Celecoxib,the COX-2 inhibitor,could not only inhibit the growth of Tca8113 cell xenograft tumor and COX-2 protein expression,but also enhance the inhibitory effect cisplatin on xenograft tumor growth significantly.The tumor inhibition rates of celecoxib group,cisplatin group and celecoxib plus cisplatin group were 15.63%,37.50% and 82.81% respectively that was statistically significant compared to control group(P < 0.01).The combined application of celecoxib and cisplatin could inhibit tumor growth more significantly than that of separated application(P < 0.01).The inhibitory effect of celecoxib on COX-2 mRNA expression of Tca 8113 cell was weaker and not significant(P = 0.073).Conclusion:Celecoxib can not only inhibit xenograft tumor growth in nude mice,but also enhance the inhibitory effect of CDDP on Tca 8113 transplanted tumor growth in nude mice.The mechanism maybe related to inhibition of COX-2 protein expression,which offers beneficial reference to further explore the mechanism between inhibition of COX-2 enzyme activity and prevention of head and neck tumor.

A new method for predicting injection multiples of extreme displacement in waterflood reservoirs

The theoretical relationship between water injection multiple(i.e.injected pore volume)and water saturation is inferred from theoretical concepts of reservoir engineering.A mathematical model based on core displacement tests is established for the entire injection process that satisfies both initial displacement and extreme displacement,simultaneously.The results show that prior to the flooding,the water injection multiple has a linear relationship with the water saturation,and the utilization rate of the injected water is the highest.As water breakthrough at the production end,the water-cut increases,and the injection multiple increases exponentially while the utilization efficiency of the injected water gradually decreases.When the injection multiple approaches infinity,the utilization efficiency of the injected water gradually decreases to 0,by which time the water-cut at the production end is always 1.At this time,the water saturation no longer changes,and the water flooding recovery rate reaches its limit.Based on the experimental test data,a mathematical model of the entire process of injection multiple and water saturation is established,which has high fitting accuracy that can predict the injection multiple in the different stages of development of a mature oil reservoir.The dynamically changing index of the injection water utilization efficiency in reservoir development by reactive water flooding can be obtained through reasonable transformation of the mathematical model.This is of great significance in guiding evaluations of the effects of reservoir development and formulating countermeasures.

Apoptosis and Proinflammatory Cytokine Responses of Primary Mouse Microglia and Astrocytes Induced by Human H1N1 and Avian H5N1 Influenza Viruses

Patients with an influenza virus infection can be complicated by acute encephalopathy and encephalitis. To investigate the immune reactions involved in the neurocomplication, mouse microglia and astrocytes were isolated, infected with human H1N1 and avian H5N1 influenza viruses, and examined for their immune responses. We observed homogeneously distributed viral receptors, sialic acid （SA）-a2,3-Galactose （Gal） and SA-a2,6-Gal, on microglia and astrocytes. Both viruses were replicative and productive in microglia and astrocytes. Virus-induced apoptosis and cytopathy in infected cells were observed at 24 h post-infection （p.i.）. Expression of IL-1β, IL-6 and TNF-a mRNA examined at 6 h and 24 h p.i. was up-regulated, and their expression levels were considerably higher in H5N1 infection. The amounts of secreted proinflammatory IL-1β, IL-6 and TNF-a at 6 h and 24 h p.i. were also induced, with greater induction by H5N1 infection. This study is the first demonstration that both human H1N1 and avian H5N1 influenza viruses can infect mouse microglia and astrocytes and induce apoptosis, cytopathy, and proinflammatory cytokine production in them in vitro. Our results suggest that the direct cellular damage and the consequences of immunopathological injury in the CNS contribute to the influenza viral pathogenesis. Cellular ＆ Molecular Immunology.

Deep Learning and Its Applications in Biomedicine

Advances in biological and medical technologies have been providing us explosive vol- umes of biological and physiological data, such as medical images, electroencephalography, geno- mic and protein sequences. Learning from these data facilitates the understanding of human health and disease. Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data. The aim of this paper is to provide an overview of deep learning techniques and some of the state-of-the-art applications in the biomedical field. We first introduce the development of artificial neural network and deep learning. We then describe two main components of deep learning, i.e., deep learning architectures and model optimization. Subsequently, some examples are demonstrated for deep learning

High-speed and high-power germanium photodetector with a lateral silicon nitride waveguide

Up to now, the light coupling schemes of germanium-on-silicon photodetectors(Ge-on-Si PDs) could be divided into three main categories:(1) vertical(or normal-incidence) illumination, which can be from the top or back of the wafer/chip, and waveguide-integrated coupling including(2) butt coupling and(3) evanescent coupling. In evanescent coupling the input waveguide can be positioned on top, at the bottom, or lateral to the absorber. Here,to the best of our knowledge, we propose the first concept of Ge-on-Si PD with double lateral silicon nitride(Si_(3)N_(4)) waveguides, which can serve as a novel waveguide-integrated coupling configuration: double lateral coupling. The Ge-on-Si PD with double lateral Si_(3)N_(4) waveguides features uniform optical field distribution in the Ge region, which is very beneficial to improving the operation speed for high input power. The proposed Ge-on-Si PD is comprehensively characterized by static and dynamic measurements. The typical internal responsivity is evaluated to be 0.52 A/W at an input power of 25 mW. The equivalent circuit model and theoretical 3 dB optoelectrical(OE) bandwidth investigation of Ge-on-Si PD with lateral coupling are implemented. Based on the small-signal(S21) radio-frequency measurements, under 4 mA photocurrent, a 60 GHz bandwidth operating at-3 V bias voltage is demonstrated. When the photocurrent is up to 12 mA, the 3 dB OE bandwidth still has 36 GHz. With 1 mA photocurrent, the 70, 80, 90, and 100 Gbit/s non-return-to-zero(NRZ) and 100,120, 140, and 150 Gbit/s four-level pulse amplitude modulation clear openings of eye diagrams are experimentally obtained without utilizing any offline digital signal processing at the receiver side. In order to verify the highpower handling performance in high-speed data transmission, we investigate the eye diagram variations with the increase of photocurrents. The clear open electrical eye diagrams of 60 Gbit/s NRZ under 20 mA photocurrent are also obtained. Overall, the proposed lateral Si_(3)N_(4) waveguide structure is flexibly extendable to a light coupling configuration of PDs, which makes it very attractive for developing high-performance silicon photonic integrated circuits in the future.

Rational screenning in combinatorial peptide libraries of protein functional loop

Redesigning the sequences of protein loops is a frequent practice in protein design. Based on the new results of protein loop database analysis, a rational computer simulation strategy is proposed to obtain functional proteins, which exploits a fast and accurate program to calculate the protein loop conformation, and at the same time, combines molecular docking method with combinatorial chemistry strategy to screen the combinatorial peptide library of pro-

GLUE multimodal single cell data

Single cell sequencing can obtain genetic information of largescale cells at a single cell resolution.The technology has revolutionized life science research and accelerated discoveries in gene expression,cell development,immunology,and others.For instance,single cell transcriptomics has promoted our capability in presenting cell types and status.The outcome sequencing data from single cell technologies allows us to build a comprehensive reference atlas for human cells,enabling us to target complex diseases such as cancers.

Effects of NS1 variants of H5N1 influenza virus on interferon induction, TNFa response and p53 activity

Non-structural protein 1(NS1)is an important virulence factor of the highly pathogenic H5N1 avian influenza virus.A five-amino-acid(5 aa)deletion at position 80–84 and an aspartic acid to glutamic acid substitution at position 92(D92E)are two major NS1 mutations that are highly correlated with enhanced virulence.To investigate the effect of these mutations in H5N1 virulence,three H5N1-NS1 variants were constructed:NS51(lacking 5 aa at position 80–84),NS51(I)(carrying a 5-aa insertion at position 80–84)and NS51(IM)(carrying both the 5-aa insertion and the D92E mutation).We examined the effects of these mutations on interferon(IFN)induction,tumor-necrosis factor(TNF)a response,p53 activity and apoptosis.We found that the D92E mutation eliminated NS1’s repressive effect on IFN induction,while the 5-aa deletion resulted in enhanced resistance to TNFa responses.We also observed that all three variants exhibited a similar suppressive effect on p53 transcriptional activity,although none of them significantly influenced apoptosis of host cells.Our findings shed new light on the role of NS1 in the pathogenicity of H5N1 virus.

Gclust:A Parallel Clustering Tool for Microbial Genomic Data

The accelerating growth of the public microbial genomic data imposes substantial burden on the research community that uses such resources.Building databases for non-redundant reference sequences from massive microbial genomic data based on clustering analysis is essential.However,existing clustering algorithms perform poorly on long genomic sequences.In this article,we present Gclust,a parallel program for clustering complete or draft genomic sequences,where clustering is accelerated with a novel parallelization strategy and a fast sequence comparison algorithm using sparse suffix arrays(SSAs).Moreover,genome identity measures between two sequences are calculated based on their maximal exact matches(MEMs).In this paper,we demonstrate the high speed and clustering quality of Gclust by examining four genome sequence datasets.Gclust is freely available for non-commercial use at https://github.com/niu-lab/gclust.We also introduce a web server for clustering user-uploaded genomes at http://niulab.scgrid.cn/gclust.

MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes

Microbes play important roles in human health and disease.The interaction between microbes and hosts is a reciprocal relationship,which remains largely under-explored.Current computational resources lack manually and consistently curated data to connect metagenomic data to pathogenic microbes,microbial core genes,and disease phenotypes.We developed the MicroPhenoDB database by manually curating and consistently integrating microbe-disease association data.MicroPhenoDB provides 5677 non-redundant associations between 1781 microbes and 542 human disease phenotypes across more than 22 human body sites.MicroPhenoDB also provides 696,934 relationships between 27,277 unique clade-specific core genes and 685 microbes.Disease phenotypes are classified and described using the Experimental Factor Ontology(EFO).A refined score model was developed to prioritize the associations based on evidential metrics.The sequence search option in MicroPhenoDB enables rapid identification of existing pathogenic microbes in samples without running the usual metagenomic data processing and assembly.MicroPhenoDB offers data browsing,searching,and visualization through user-friendly web interfaces and web service application programming interfaces.MicroPhenoDB is the first database platform to detail the relationships between pathogenic microbes,core genes,and disease phenotypes.It will accelerate metagenomic data analysis and assist studies in decoding microbes related to human diseases.MicroPhenoDB is available through http://www.liwzlab.cn/microphenodb and http://lilab2.sysu.edu.cn/microphenodb.

Cytokine storm promoting T cell exhaustion in severe COVID-19 revealed by single cell sequencing data analysis

Background:Evidence has suggested that cytokine storms may be associated with T cell exhaustion(TEX)in COVID-19.However,the interaction mechanism between cytokine storms and TEX remains unclear.Methods:With the aim of dissecting the molecular relationship of cytokine storms and TEX through single-cell RNA sequencing data analysis,we identified 14 cell types from bronchoalveolar lavage fluid of COVID-19 patients and healthy people.We observed a novel subset of severely exhausted CD8 T cells(Exh T_CD8)that co-expressed multiple inhibitory receptors,and two macrophage subclasses that were the main source of cytokine storms in bronchoalveolar.Results:Correlation analysis between cytokine storm level and TEX level suggested that cytokine storms likely promoted TEX in severe COVID-19.Cell–cell communication analysis indicated that cytokines(e.g.CXCL10,CXCL11,CXCL2,CCL2,and CCL3)released by macrophages acted as ligands and significantly interacted with inhibitory receptors(e.g.CXCR3,DPP4,CCR1,CCR2,and CCR5)expressed by Exh T_CD8.These interactions formed the cytokine–receptor axes,which were also verified to be significantly correlated with cytokine storms and TEX in lung squamous cell carcinoma.Conclusions:Cytokine storms may promote TEX through cytokine-receptor axes and be associated with poor prognosis in COVID19.Blocking cytokine-receptor axes may reverse TEX.Our finding provides novel insights into TEX in COVID-19 and new clues for cytokine-targeted immunotherapy development.