Low effective surface recombination in In(Ga)As/GaAs quantum dot diodes

Size dependent current-voltage measurements were performed on InGaAs quantum dot active region mesa diodes and the surface recombination velocity was extracted from current density versus perimeter/area plots using a diffusion model. An effective surface recombination value of 5.5 x 10(4) cm/s was obtained that can be reduced by more than an order of magnitude by selective oxidation of Al(0.9)Ga(0.1)As cladding layers. The values are three times smaller than those obtained for a single quantum well. The effect of p-type doping in the active region was investigated and found to increase the effective surface recombination. (C) 2011 American Institute of Physics. [doi:10.1063/1.3611387

Table 1 and data of some representative samples in Figs 3 and 4.

Supplementary material related to the article: Altyn Tagh Mountain uplift and climate change of Qaidam basin in the northeastern Tibetan Plateau: evidences from grain size records of the sediments during ~40-25 Ma

Table 1 and data of some representative samples in Figs 3 and 4.

Supplementary material related to the article: Altyn Tagh Mountain uplift and climate change of Qaidam basin in the northeastern Tibetan Plateau: evidences from grain size records of the sediments during ~40-25 Ma

Shh coacervate imaging.

<p>Alexa Fluor 488-labeled Shh was incorporated into the coacervate in water and imaged by fluorescence microscopy. (<b>a</b>) 10× magnification. (<b>b</b>) 40× magnification. Scale bars = 100 µm.</p

DataSheet_1_IBI: Identification of Biomarker Genes in Individual Tumor Samples.docx

Individual patient biomarkers have an important role in personalized treatment. Although various high-throughput sequencing technologies are widely used in biological experiments, these are usually conducted only once or a few times for each patient, which makes it a challenging problem to identify biomarkers in individual patients. At present, there is a lack of effective methods to identify biomarkers in individual sample data. Here, we propose a novel method, IBI, to identify biomarkers in individual tumor samples. Experimental results from several tumor data sets showed that the proposed method could effectively find biomarker genes for individual patients, including common biomarkers related to the mechanisms of the development of cancer, which can be used to predict survival and drug response in patients. In summary, these results demonstrate that the proposed method offers a new perspective for analyzing individual samples.</p

DataSheet_1_A Pipeline for Reconstructing Somatic Copy Number Alternation’s Subclonal Population-Based Next-Generation Sequencing Data.pdf

State-of-the-art next-generation sequencing (NGS)-based subclonal reconstruction methods perform poorly on somatic copy number alternations (SCNAs), due to not only it needs to simultaneously estimate the subclonal population frequency and the absolute copy number for each SCNA, but also there exist complex bias and noise in the tumor and its paired normal sequencing data. Both existing NGS-based SCNA detection methods and SCNA’s subclonal population frequency inferring tools use the read count on radio (RCR) of tumor to its paired normal as the key feature of tumor sequencing data; however, the sequencing error and bias have great impact on RCR, which leads to a large number of redundant SCNA segments that make the subsequent process of SCNA’s subclonal population frequency inferring and subclonal reconstruction time-consuming and inaccurate. We perform a mathematical analysis of the solution number of SCNA’s subclonal frequency, and we propose a computational algorithm to reduce the impact of false breakpoints based on it. We construct a new probability model that incorporates the RCR bias correction algorithm, and by stringing it with the false breakpoint filtering algorithm, we construct a whole SCNA’s subclonal population reconstruction pipeline. The experimental result shows that our pipeline outperforms the existing subclonal reconstruction programs both on simulated data and TCGA data. Source code is publicly available as a Python package at https://github.com/dustincys/msphy-SCNAClonal.</p

Galactose Oxidase Model Complexes: Catalytic Reactivities

Galactose Oxidase Model Complexes:  Catalytic Reactivitie

Shh-stimulated cardiac fibroblast signaling.

<p>Near-confluent cardiac fibroblasts were incubated with Shh, free or in the coacervate, and growth factor levels in the conditioned media were assessed after 6, 12, 24, and 48 h. Data is presented as a fold-change from the stimulation media (C). Bars indicate means ± SD. (<b>a</b>) Quantification of Shh concentration in the cardiac fibroblast-conditioned media by western blot. Ponceau-S staining of protein bands near 27 kDa is shown as the loading control. (<b>b</b>) Quantification of VEGF in the cardiac fibroblast-conditioned media by indirect ELISA, *<i>P</i><0.05. (<b>c</b>) Quantification of SDF-1α in the cardiac fibroblast-conditioned media by indirect ELISA. (<b>d</b>) Quantification of IGF-1 in the cardiac fibroblast-conditioned media by indirect ELISA.</p

Shh release profile.

<p><i>In vitro</i> release of Shh from the coacervate into saline over 21 days, quantified by sandwich ELISA. Percent release is relative to total amount loaded. Bars indicate means ± SD.</p

Additional file 1 of Modeling and correct the GC bias of tumor and normal WGS data for SCNA based tumor subclonal population inferring

Modeling and Correct the GC bias of tumor and normal WGS data for SCNA based tumor subclonal population inferring. (PDF 2570 kb