Future change in extreme precipitation in East Asian spring and Mei-yu seasons in two high-resolution AGCMs

Precipitation in the spring and Mei-yu seasons, the main planting and growing period in East Asia, is crucial to water resource management. Changes in spring and Mei-yu extreme precipitation under global warming are evaluated based on two sets of high-resolution simulations with various warming pattern of sea surface temperature (SST'spa). In the spring season, extreme precipitation exhibits larger enhancements over the northern flank of the present-day prevailing rainy region and a tendency of increased occurrence and enhanced intensity in the probability distribution. These changes imply a northward extension of future spring rainband. Although the mean precipitation shows minor change, enhanced precipitation intensity, less total rainfall occurrence, and prolonged consecutive dry days suggest a more challenging water resource management in the warmer climate. The projected enhancement in precipitation intensity is robust compared with the internal variability related to initial conditions (σˆint) and the uncertainty caused by SST'spa (σˆΔSST). In the Mei-yu season, extreme precipitation strengthens and becomes more frequent over the present-day prevailing rainband region. The thermodynamic component of moisture flux predominantly contributes to the changes in the spring season. In the Mei-yu season, both the thermodynamic and dynamic components of moisture flux enhance the moisture transport and intensify the extreme precipitation from southern China to northeast Asia. Compared with spring season, projecting future Mei-yu precipitation is more challenging because of its higher uncertainty associated with 1) the σˆint and σˆΔSST embedded in the projections and 2) the model characteristics of present-day climatology that determines the spatial distribution of precipitation enhancement.publishedVersio

A novel randomly textured phosphor structure for highly efficient white light-emitting diodes

We have successfully demonstrated the enhanced luminous flux and lumen efficiency in white light-emitting diodes by the randomly textured phosphor structure. The textured phosphor structure was fabricated by a simple imprinting technique, which does not need an expensive dry-etching machine or a complex patterned definition. The textured phosphor structure increases luminous flux by 5.4% and 2.5% at a driving current of 120 mA, compared with the flat phosphor and half-spherical lens structures, respectively. The increment was due to the scattering of textured surface and also the phosphor particles, leading to the enhancement of utilization efficiency of blue light. Furthermore, the textured phosphor structure has a larger view angle at the full width at half maximum (87°) than the reference LEDs

EMUlator: An Elementary Metabolite Unit (EMU) Based Isotope Simulator Enabled by Adjacency Matrix

Stable isotope based metabolic flux analysis is currently the unique methodology that allows the experimental study of the integrated responses of metabolic networks. This method primarily relies on isotope labeling and modeling, which could be a challenge in both experimental and computational biology. In particular, the algorithm implementation for isotope simulation is a critical step, limiting extensive usage of this powerful approach. Here, we introduce EMUlator a Python-based isotope simulator which is developed on Elementary Metabolite Unit (EMU) algorithm, an efficient and powerful algorithm for isotope modeling. We propose a novel adjacency matrix method to implement EMU modeling and exemplify it stepwise. This method is intuitively straightforward and can be conveniently mastered for various customized purposes. We apply this arithmetic pipeline to understand the phosphoketolase flux in the metabolic network of an industrial microbe Clostridium acetobutylicum. The resulting design enables a high-throughput and non-invasive approach for estimating phosphoketolase flux in vivo. Our computational insights allow the systematic design and prediction of isotope-based metabolic models and yield a comprehensive understanding of their limitations and potentials

Risk factors for pulmonary tuberculosis in patients with chronic obstructive airway disease in Taiwan: a nationwide cohort study

BACKGROUND: An association between chronic obstructive pulmonary disease (COPD) and tuberculosis (TB) has been described, mainly due to smoking and corticosteroid use. Whether inhaled corticosteroid (ICS) therapy is associated with an increased risk of TB remains unclear. METHODS: We selected COPD cases by using six diagnostic scenarios and control subjects from a nationwide health insurance database, and applied time-dependent Cox regression analysis to identify the risk factors for TB. RESULTS: Among 1,000,000 beneficiaries, 23,594 COPD cases and 47,188 non-COPD control subjects were selected. Cox regression analysis revealed that age, male gender, diabetes mellitus, end-stage renal disease, and cirrhosis, as well as COPD (hazard ratio = 2.468 [2.205–2.762]) were independent risk factors for TB. Among the COPD cases, those who developed TB received more oral corticosteroids and oral β-agonists. Time-dependent Cox regression analysis revealed that age, male gender, diabetes mellitus, low income, oral corticosteroid dose, and oral β-agonist dose, but not ICS dose, were independent risk factors for TB. The identified risk factors and their hazard ratios were similar among the COPD cases selected using different scenarios. CONCLUSION: Keeping a high suspicion and regularly monitoring for the development of pulmonary TB in COPD patients are necessary, especially for those receiving higher doses of oral corticosteroids and other COPD medications. Although ICS therapy has been shown to predispose COPD patients to pneumonia in large randomized clinical trials, it does not increase the risk of TB in real world practice

Gold nanoparticles as high-resolution X-ray imaging contrast agents for the analysis of tumor-related micro-vasculature

<p>Abstract</p> <p>Background</p> <p>Angiogenesis is widely investigated in conjunction with cancer development, in particular because of the possibility of early stage detection and of new therapeutic strategies. However, such studies are negatively affected by the limitations of imaging techniques in the detection of microscopic blood vessels (diameter 3-5 μm) grown under angiogenic stress. We report that synchrotron-based X-ray imaging techniques with very high spatial resolution can overcome this obstacle, provided that suitable contrast agents are used.</p> <p>Results</p> <p>We tested different contrast agents based on gold nanoparticles (AuNPs) for the detection of cancer-related angiogenesis by synchrotron microradiology, microtomography and high resolution X-ray microscopy. Among them only bare-AuNPs in conjunction with heparin injection provided sufficient contrast to allow <it>in vivo </it>detection of small capillary species (the smallest measured lumen diameters were 3-5 μm). The detected vessel density was 3-7 times higher than with other nanoparticles. We also found that bare-AuNPs with heparin allows detecting symptoms of local extravascular nanoparticle diffusion in tumor areas where capillary leakage appeared.</p> <p>Conclusions</p> <p>Although high-Z AuNPs are natural candidates as radiology contrast agents, their success is not guaranteed, in particular when targeting very small blood vessels in tumor-related angiography. We found that AuNPs injected with heparin produced the contrast level needed to reveal--for the first time by X-ray imaging--tumor microvessels with 3-5 μm diameter as well as extravascular diffusion due to basal membrane defenestration. These results open the interesting possibility of functional imaging of the tumor microvasculature, of its development and organization, as well as of the effects of anti-angiogenic drugs.</p

Discovering Chromatin Motifs using FAIRE Sequencing and the Human Diploid Genome

Background: Specific chromatin structures are associated with active or inactive gene transcription. The gene regulatory elements are intrinsically dynamic and alternate between inactive and active states through the recruitment of DNA binding proteins, such as chromatin-remodeling proteins. Results: We developed a unique genome-wide method to discover DNA motifs associated with chromatin accessibility using formaldehyde-assisted isolation of regulatory elements with high-throughput sequencing (FAIRE-seq). We aligned the FAIRE-seq reads to the GM12878 diploid genome and subsequently identified differential chromatin-state regions (DCSRs) using heterozygous SNPs. The DCSR pairs represent the locations of imbalances of chromatin accessibility between alleles and are ideal to reveal chromatin motifs that may directly modulate chromatin accessibility. In this study, we used DNA 6-10mer sequences to interrogate all DCSRs, and subsequently discovered conserved chromatin motifs with significant changes in the occurrence frequency. To investigate their likely roles in biology, we studied the annotated protein associated with each of the top ten chromatin motifs genome-wide, in the intergenic regions and in genes, respectively. As a result, we found that most of these annotated motifs are associated with chromatin remodeling, reflecting their significance in biology. Conclusions: Our method is the first one using fully phased diploid genome and FAIRE-seq to discover motifs associated with chromatin accessibility. Our results were collected to construct the first chromatin motif database (CMD), providing the potential DNA motifs recognized by chromatin-remodeling proteins and is freely available at http://syslab.nchu.edu.tw/chromatin

Genetic and Functional Analysis of the DLG4 Gene Encoding the Post-Synaptic Density Protein 95 in Schizophrenia

Hypofunction of N-methyl-D-aspartate (NMDA) receptor-mediated signal transduction has been implicated in the pathophysiology of schizophrenia. Post-synaptic density protein 95 (PSD95) plays a critical role in regulating the trafficking and activity of the NMDA receptor and altered expression of the PSD95 has been detected in the post-mortem brain of patients with schizophrenia. The study aimed to examine whether the DLG4 gene that encodes the PSD95 may confer genetic susceptibility to schizophrenia. We re-sequenced the core promoter, all the exons, and 3′ untranslated regions (UTR) of the DLG4 gene in 588 Taiwanese schizophrenic patients and conducted an association study with 539 non-psychotic subjects. We did not detect any rare mutations at the protein-coding sequences of the DLG4 gene associated with schizophrenia. Nevertheless, we identified four polymorphic markers at the core promoter and 5′ UTR and one single nucleotide polymorphism (SNP) at the 3′UTR of the DLG4 gene in this sample. Genetic analysis showed an association of a haplotype (C–D) derived from 2 polymorphic markers at the core promoter (odds ratio = 1.26, 95% confidence interval = 1.06–1.51, p = 0.01), and a borderline association of the T allele of the rs13331 at 3′UTR with schizophrenia (odds ratio = 1.19, 95% confidence interval = 0.99–1.43, p = 0.06). Further reporter gene assay showed that the C-D-C-C and the T allele of the rs13331 had significant lower activity than their counter parts. Our data indicate that the expression of the DLG4 gene is subject to regulation by the polymorphic markers at the core promoter region, 5′ and 3′UTR of the gene, and is associated with the susceptibility of schizophrenia

Label-free quantitative proteomics of CD133-positive liver cancer stem cells

Abstract Background CD133-positive liver cancer stem cells, which are characterized by their resistance to conventional chemotherapy and their tumor initiation ability at limited dilutions, have been recognized as a critical target in liver cancer therapeutics. In the current work, we developed a label-free quantitative method to investigate the proteome of CD133-positive liver cancer stem cells for the purpose of identifying unique biomarkers that can be utilized for targeting liver cancer stem cells. Label-free quantitation was performed in combination with ID-based Elution time Alignment by Linear regression Quantitation (IDEAL-Q) and MaxQuant. Results Initially, IDEAL-Q analysis revealed that 151 proteins were differentially expressed in the CD133-positive hepatoma cells when compared with CD133-negative cells. We then analyzed these 151 differentially expressed proteins by MaxQuant software and identified 10 significantly up-regulated proteins. The results were further validated by RT-PCR, western blot, flow cytometry or immunofluorescent staining which revealed that prominin-1, annexin A1, annexin A3, transgelin, creatine kinase B, vimentin, and EpCAM were indeed highly expressed in the CD133-positive hepatoma cells. Conclusions These findings confirmed that mass spectrometry-based label-free quantitative proteomics can be used to gain insights into liver cancer stem cells.http://deepblue.lib.umich.edu/bitstream/2027.42/113089/1/12953_2012_Article_407.pd