Synthesis and Photoluminescence Properties of Porous Silicon Nanowire Arrays

Herein, we prepare vertical and single crystalline porous silicon nanowires (SiNWs) via a two-step metal-assisted electroless etching method. The porosity of the nanowires is restricted by etchant concentration, etching time and doping lever of the silicon wafer. The diffusion of silver ions could lead to the nucleation of silver nanoparticles on the nanowires and open new etching ways. Like porous silicon (PS), these porous nanowires also show excellent photoluminescence (PL) properties. The PL intensity increases with porosity, with an enhancement of about 100 times observed in our condition experiments. A “red-shift” of the PL peak is also found. Further studies prove that the PL spectrum should be decomposed into two elementary PL bands. The peak at 850 nm is the emission of the localized excitation in the nanoporous structure, while the 750-nm peak should be attributed to the surface-oxidized nanostructure. It could be confirmed from the Fourier transform infrared spectroscopy analyses. These porous SiNW arrays may be useful as the nanoscale optoelectronic devices

Temporal Model Adaptation for Person Re-Identification

Person re-identification is an open and challenging problem in computer vision. Majority of the efforts have been spent either to design the best feature representation or to learn the optimal matching metric. Most approaches have neglected the problem of adapting the selected features or the learned model over time. To address such a problem, we propose a temporal model adaptation scheme with human in the loop. We first introduce a similarity-dissimilarity learning method which can be trained in an incremental fashion by means of a stochastic alternating directions methods of multipliers optimization procedure. Then, to achieve temporal adaptation with limited human effort, we exploit a graph-based approach to present the user only the most informative probe-gallery matches that should be used to update the model. Results on three datasets have shown that our approach performs on par or even better than state-of-the-art approaches while reducing the manual pairwise labeling effort by about 80%

Functional Genomics Unique to Week 20 Post Wounding in the Deep Cone/Fat Dome of the Duroc/Yorkshire Porcine Model of Fibroproliferative Scarring

Background: Hypertrophic scar was first described over 100 years ago; PubMed has more than 1,000 references on the topic. Nevertheless prevention and treatment remains poor, because 1) there has been no validated animal model; 2) human scar tissue, which is impossible to obtain in a controlled manner, has been the only source for study; 3) tissues typically have been homogenized, mixing cell populations; and 4) gene-by-gene studies are incomplete.Methodology/Principal Findings: We have assembled a system that overcomes these barriers and permits the study of genome-wide gene expression in microanatomical locations, in shallow and deep partial-thickness wounds, and pigmented and non-pigmented skin, using the Duroc( pigmented fibroproliferative)/Yorkshire( non-pigmented non-fibroproliferative) porcine model. We used this system to obtain the differential transcriptome at 1, 2, 3, 12 and 20 weeks post wounding. It is not clear when fibroproliferation begins, but it is fully developed in humans and the Duroc breed at 20 weeks. Therefore we obtained the derivative functional genomics unique to 20 weeks post wounding. We also obtained long-term, forty-six week follow-up with the model.Conclusions/Significance: 1) the scars are still thick at forty-six weeks post wounding further validating the model. 2) the differential transcriptome provides new insights into the fibroproliferative process as several genes thought fundamental to fibroproliferation are absent and others differentially expressed are newly implicated. 3) the findings in the derivative functional genomics support old concepts, which further validates the model, and suggests new avenues for reductionist exploration. in the future, these findings will be searched for directed networks likely involved in cutaneous fibroproliferation. These clues may lead to a better understanding of the systems biology of cutaneous fibroproliferation, and ultimately prevention and treatment of hypertrophic scarring.The National Institute on Disability and Rehabilitation ResearchThe National Institutes of HealthThe Washington State Council of Fire Fighters Burn FoundationThe Northwest Burn FoundationUniv Washington, Dept Surg, Div Plast Surg, Seattle, WA 98195 USAIowa State Univ, Dept Anim Sci, Ames, IA USAUniv Washington, Dept Biostat, Seattle, WA 98195 USAMahidol Univ, Ramathibodi Hosp, Dept Surg, Bangkok 10700, ThailandUniv Washington, Dept Environm & Occupat Hlth Sci, Seattle, WA 98195 USAUniversidade Federal de São Paulo, Div Plast Surg, Dept Surg, São Paulo, BrazilUniversidade Federal de São Paulo, Div Plast Surg, Dept Surg, São Paulo, BrazilThe National Institute on Disability and Rehabilitation Research: H133G050022The National Institutes of Health: 1R21GM074673The National Institutes of Health: 5U54GM062119-09Web of Scienc

Estimation of cancer incidence and mortality attributable to alcohol drinking in china

Background. Cancer constitutes a serious burden of disease worldwide and has become the second leading cause of death in China. Alcohol consumption is causally associated with the increased risk of certain cancers. Due to the current lack of data and the imperative need to guide policymakers on issues of cancer prevention and control, we aim to estimate the role of alcohol on the cancer burden in China in 2005. Methods. We calculated the proportion of cancers attributable to alcohol use to estimate the burden of alcohol-related cancer. The population attributable fraction was calculated based on the assumption of no alcohol drinking. Data on alcohol drinking prevalence were from two large-scale national surveys of representative samples of the Chinese population. Data on relative risk were obtained from meta-analyses and large-scale studies. Results. We found that a total of 78,881 cancer deaths were attributable to alcohol drinking in China in 2005, representing 4.40% of all cancers (6.69% in men, 0.42% in women). The corresponding figure for cancer incidence was 93,596 cases (3.63% of all cancer cases). Liver cancer was the main alcohol-related cancer, contributing more than 60% of alcohol-related cancers. Conclusions. Particular attention needs to be paid to the harm of alcohol as well as its potential benefits when making public health recommendations on alcohol drinking. \ua9 2010 Liang et al; licensee BioMed Central Ltd

Equivalence of plasma p-tau217 with cerebrospinal fluid in the diagnosis of Alzheimer's disease

INTRODUCTION: Plasma biomarkers are promising tools for Alzheimer's disease (AD) diagnosis, but comparisons with more established biomarkers are needed. METHODS: We assessed the diagnostic performance of p-tau181, p-tau217, and p-tau231 in plasma and CSF in 174 individuals evaluated by dementia specialists and assessed with amyloid-PET and tau-PET. Receiver operating characteristic (ROC) analyses assessed the performance of plasma and CSF biomarkers to identify amyloid-PET and tau-PET positivity. RESULTS: Plasma p-tau biomarkers had lower dynamic ranges and effect sizes compared to CSF p-tau. Plasma p-tau181 (AUC = 76%) and p-tau231 (AUC = 82%) assessments performed inferior to CSF p-tau181 (AUC = 87%) and p-tau231 (AUC = 95%) for amyloid-PET positivity. However, plasma p-tau217 (AUC = 91%) had diagnostic performance indistinguishable from CSF (AUC = 94%) for amyloid-PET positivity. DISCUSSION: Plasma and CSF p-tau217 had equivalent diagnostic performance for biomarker-defined AD. Our results suggest that plasma p-tau217 may help reduce the need for invasive lumbar punctures without compromising accuracy in the identification of AD. Highlights: p-tau217 in plasma performed equivalent to p-tau217 in CSF for the diagnosis of AD, suggesting the increased accessibility of plasma p-tau217 is not offset by lower accuracy. p-tau biomarkers in plasma had lower mean fold-changes between amyloid-PET negative and positive groups than p-tau biomarkers in CSF. CSF p-tau biomarkers had greater effect sizes than plasma p-tau biomarkers when differentiating between amyloid-PET positive and negative groups. Plasma p-tau181 and plasma p-tau231 performed worse than p-tau181 and p-tau231 in CSF for AD diagnosis

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Immunogenic Comparison of Chimeric Adenovirus 5/35 Vector Carrying Optimized Human Immunodeficiency Virus Clade C Genes and Various Promoters

Adenovirus vector-based vaccine is a promising approach to protect HIV infection. However, a recent phase IIb clinical trial using the vector did not show its protective efficacy against HIV infection. To improve the vaccine, we explored the transgene protein expression and its immunogenicity using optimized codon usage, promoters and adaptors. We compared protein expression and immunogenicity of adenovirus vector vaccines carrying native or codon usage-optimized HIV-1 clade C gag and env genes expression cassettes driven by different promoters (CMV, CMVi, and CA promoters) and adapters (IRES and F2A). The adenovirus vector vaccine containing optimized gag gene produced higher Gag protein expression and induced higher immune responses than the vector containing native gag gene in mice. Furthermore, CA promoter generated higher transgene expression and elicited higher immune responses than other two popularly used promoters (CMV and CMVi). The second gene expression using F2A adaptor resulted in higher protein expression and immunity than that of using IRES and direct fusion protein. Taken together, the adenovirus vector containing the expression cassette with CA promoter, optimized HIV-1 clade C gene and an F2A adaptor produced the best protein expression and elicited the highest transgene-specific immune responses. This finding would be promising for vaccine design and gene therapy

Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new hypotheses. Principal Component Analysis (PCA) is a widely used linear method to define the mapping between the high-dimensional data and its low-dimensional representation. During the last decade, many new nonlinear methods for dimension reduction have been proposed, but it is still unclear how well these methods capture the underlying structure of microarray gene expression data. In this study, we assessed the performance of the PCA approach and of six nonlinear dimension reduction methods, namely Kernel PCA, Locally Linear Embedding, Isomap, Diffusion Maps, Laplacian Eigenmaps and Maximum Variance Unfolding, in terms of visualization of microarray data.</p> <p>Results</p> <p>A systematic benchmark, consisting of Support Vector Machine classification, cluster validation and noise evaluations was applied to ten microarray and several simulated datasets. Significant differences between PCA and most of the nonlinear methods were observed in two and three dimensional target spaces. With an increasing number of dimensions and an increasing number of differentially expressed genes, all methods showed similar performance. PCA and Diffusion Maps responded less sensitive to noise than the other nonlinear methods.</p> <p>Conclusions</p> <p>Locally Linear Embedding and Isomap showed a superior performance on all datasets. In very low-dimensional representations and with few differentially expressed genes, these two methods preserve more of the underlying structure of the data than PCA, and thus are favorable alternatives for the visualization of microarray data.</p