Quantifying mucosal hemodynamics in a murine model of Ulcerative Colitis with diffuse reflectance spectroscopy

Ulcerative colitis (UC) is a gastrointestinal, autoimmune disease that causes ulceration and inflammation of the colon with an incidence 10 out of every 100,000 people in North America and Western Europe. Though the exact etiology is uncertain, a number of studies have shown that inflammatory cells along with environmental factors, genetics, and lifestyle habits can contribute to the sustained inflammatory response. In order to determine the cellular mechanism behind relapse and remission of UC, researchers have frequently employed immunohistochemistry, western blotting and gene sequencing, but these destructive analysis methods require the removal of a sample, necessarily limiting these methods to non-living tissues. There is an emerging interest in using non-invasive techniques to study the in vivo, longitudinal effects of UC on the mucosa in the colon. Here we have developed a mouse model of UC using dextran sulfate sodium and a non-invasive spectroscopy monitoring modality to study the changes in the tissue hemodynamics during active UC

Pilot randomized trial of an electronic symptom monitoring and reporting intervention for hospitalized adults undergoing hematopoietic stem cell transplantation

Purpose: Patients undergoing a hematopoietic stem cell transplantation (HCT) have varied symptoms during their hospitalization. This study examined whether daily symptom reporting (with electronic patient-reported outcomes [PROs]) in an inpatient bone marrow transplant clinic reduced symptom burden on post-transplant days +7, +10, and +14. Methods: A prospective, single-institution1:1 pilot randomized, two-arm study recruited HCT patients. HCT inpatients (N=76) reported daily on 16 common symptoms using the PRO version of the Common Terminology for Adverse Events (PRO-CTCAE). Fisher’s exact test was used to examine differences in the proportion of patients reporting individual symptoms. Multivariable linear regression modeling was used to examine group differences in peak symptom burden, while controlling for symptom burden at baseline, age, comorbidity, and transplantation type (autologous or allogeneic). Results: HCT patients receiving the PRO intervention also experienced lower peak symptom burden (average of 16 symptoms) at days +7, +10, and +14 (10.4 vs 14.5, p =0.03). Conclusions: Daily use of electronic symptom reporting to nurses in an inpatient bone marrow transplant clinic reduced peak symptom burden and improved individual symptoms during the two weeks post-transplant. A multi-site site trial is warranted to demonstrate the generalizability, efficacy, and value of this intervention

Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments

<p>Abstract</p> <p>Background</p> <p>High-throughput sequencing technologies, such as the Illumina Genome Analyzer, are powerful new tools for investigating a wide range of biological and medical questions. Statistical and computational methods are key for drawing meaningful and accurate conclusions from the massive and complex datasets generated by the sequencers. We provide a detailed evaluation of statistical methods for normalization and differential expression (DE) analysis of Illumina transcriptome sequencing (mRNA-Seq) data.</p> <p>Results</p> <p>We compare statistical methods for detecting genes that are significantly DE between two types of biological samples and find that there are substantial differences in how the test statistics handle low-count genes. We evaluate how DE results are affected by features of the sequencing platform, such as, varying gene lengths, base-calling calibration method (with and without phi X control lane), and flow-cell/library preparation effects. We investigate the impact of the read count normalization method on DE results and show that the standard approach of scaling by total lane counts (e.g., RPKM) can bias estimates of DE. We propose more general quantile-based normalization procedures and demonstrate an improvement in DE detection.</p> <p>Conclusions</p> <p>Our results have significant practical and methodological implications for the design and analysis of mRNA-Seq experiments. They highlight the importance of appropriate statistical methods for normalization and DE inference, to account for features of the sequencing platform that could impact the accuracy of results. They also reveal the need for further research in the development of statistical and computational methods for mRNA-Seq.</p

The Arctic in the twenty-first century: changing biogeochemical linkages across a paraglacial landscape of Greenland

The Kangerlussuaq area of southwest Greenland encompasses diverse ecological, geomorphic, and climate gradients that function over a range of spatial and temporal scales. Ecosystems range from the microbial communities on the ice sheet and moisture-stressed terrestrial vegetation (and their associated herbivores) to freshwater and oligosaline lakes. These ecosystems are linked by a dynamic glacio-fluvial-aeolian geomorphic system that transports water, geological material, organic carbon and nutrients from the glacier surface to adjacent terrestrial and aquatic systems. This paraglacial system is now subject to substantial change because of rapid regional warming since 2000. Here, we describe changes in the eco- and geomorphic systems at a range of timescales and explore rapid future change in the links that integrate these systems. We highlight the importance of cross-system subsidies at the landscape scale and, importantly, how these might change in the near future as the Arctic is expected to continue to warm

Identification of field caught Anopheles gambiae s.s. and Anopheles arabiensis by TaqMan single nucleotide polymorphism genotyping

BACKGROUND: Identification of Anopheles gambiae s.s. and Anopheles arabiensis from field-collected Anopheles gambiae s.l. is often necessary in basic and applied research, and in operational control programmes. The currently accepted method involves use of standard polymerase chain reaction amplification of ribosomal DNA (rDNA) from the 3' 28S to 5' intergenic spacer region of the genome, and visual confirmation of amplicons of predicted size on agarose gels, after electrophoresis. This report describes development and evaluation of an automated, quantitative PCR method based upon TaqMan™ single nucleotide polymorphism (SNP) genotyping. METHODS: Standard PCR, and TaqMan SNP genotyping with newly designed primers and fluorophore-labeled probes hybridizing to sequences of complementary rDNA specific for either An. gambiae s.s. or An. arabiensis, were conducted in three experiments involving field-collected An. gambiae s.l. from western Kenya, and defined laboratory strains. DNA extraction was from a single leg, sonicated for five minutes in buffer in wells of 96-well PCR plates. RESULTS: TaqMan SNP genotyping showed a reaction success rate, sensitivity, and species specificity comparable to that of standard PCR. In an extensive field study, only 29 of 3,041 (0.95%) were determined to be hybrids by TaqMan (i.e., having rDNA sequences from both species), however, all but one were An. arabiensis by standard PCR, suggesting an acceptably low (ca. 1%) error rate for TaqMan genotyping in mistakenly identifying species hybrids. CONCLUSION: TaqMan SNP genotyping proved to be a sensitive and rapid method for identification of An. gambiae s.l. and An. arabiensis, with a high success rate, specific results, and congruence with the standard PCR method

Divergence of the Yeast Transcription Factor FZF1 Affects Sulfite Resistance

Changes in gene expression are commonly observed during evolution. However, the phenotypic consequences of expression divergence are frequently unknown and difficult to measure. Transcriptional regulators provide a mechanism by which phenotypic divergence can occur through multiple, coordinated changes in gene expression during development or in response to environmental changes. Yet, some changes in transcriptional regulators may be constrained by their pleiotropic effects on gene expression. Here, we use a genome-wide screen for promoters that are likely to have diverged in function and identify a yeast transcription factor, FZF1, that has evolved substantial differences in its ability to confer resistance to sulfites. Chimeric alleles from four Saccharomyces species show that divergence in FZF1 activity is due to changes in both its coding and upstream noncoding sequence. Between the two closest species, noncoding changes affect the expression of FZF1, whereas coding changes affect the expression of SSU1, a sulfite efflux pump activated by FZF1. Both coding and noncoding changes also affect the expression of many other genes. Our results show how divergence in the coding and promoter region of a transcription factor alters the response to an environmental stress

mRNA-Seq Analysis of the Pseudoperonospora cubensis Transcriptome During Cucumber (Cucumis sativus L.) Infection

Pseudoperonospora cubensis, an oomycete, is the causal agent of cucurbit downy mildew, and is responsible for significant losses on cucurbit crops worldwide. While other oomycete plant pathogens have been extensively studied at the molecular level, Ps. cubensis and the molecular basis of its interaction with cucurbit hosts has not been well examined. Here, we present the first large-scale global gene expression analysis of Ps. cubensis infection of a susceptible Cucumis sativus cultivar, ‘Vlaspik’, and identification of genes with putative roles in infection, growth, and pathogenicity. Using high throughput whole transcriptome sequencing, we captured differential expression of 2383 Ps. cubensis genes in sporangia and at 1, 2, 3, 4, 6, and 8 days post-inoculation (dpi). Additionally, comparison of Ps. cubensis expression profiles with expression profiles from an infection time course of the oomycete pathogen Phytophthora infestans on Solanum tuberosum revealed similarities in expression patterns of 1,576–6,806 orthologous genes suggesting a substantial degree of overlap in molecular events in virulence between the biotrophic Ps. cubensis and the hemi-biotrophic P. infestans. Co-expression analyses identified distinct modules of Ps. cubensis genes that were representative of early, intermediate, and late infection stages. Collectively, these expression data have advanced our understanding of key molecular and genetic events in the virulence of Ps. cubensis and thus, provides a foundation for identifying mechanism(s) by which to engineer or effect resistance in the host

Frequency fluctuations in silicon nanoresonators

Frequency stability is key to performance of nanoresonators. This stability is thought to reach a limit with the resonator's ability to resolve thermally-induced vibrations. Although measurements and predictions of resonator stability usually disregard fluctuations in the mechanical frequency response, these fluctuations have recently attracted considerable theoretical interest. However, their existence is very difficult to demonstrate experimentally. Here, through a literature review, we show that all studies of frequency stability report values several orders of magnitude larger than the limit imposed by thermomechanical noise. We studied a monocrystalline silicon nanoresonator at room temperature, and found a similar discrepancy. We propose a new method to show this was due to the presence of frequency fluctuations, of unexpected level. The fluctuations were not due to the instrumentation system, or to any other of the known sources investigated. These results challenge our current understanding of frequency fluctuations and call for a change in practices