Investigation of temporal contrast effects in femtosecond pulse laser micromachining of metals.

Femtosecond pulse laser drilling has evolved to become a preferred process for selective (maskless) micromachining in a variety of materials, including metals, polymers, semiconductors, ceramics, and living tissue. Manufacturers of state-of-the-art femtosecond laser systems advertise the inherent advantage of micromachining with ultra short pulses: the absence of a heat affected zone. In the ideal case, this leads to micro and nano scale features without distortion due to melt or recast. However, recent studies have shown that this is limited to the low fluence regime in many cases. High dynamic range autocorrelation studies were performed on two commercial Ti:sapphire femtosecond laser systems to investigate the possible presence of a nanosecond pedestal in the femtosecond pulse produced by chirped pulse amplification. If confirmed, nanosecond temporal phenomena may explain many of the thermal effects witnessed in high fluence micromachining. The material removal rate was measured in addition to feature morphology observations for percussion micro drilling of metal substrates in vacuum and ambient environments. Trials were repeated with proposed corrective optics installed, including a variable aperture and a nonlinear frequency doubling crystal. Results were compared. Although the investigation of nanosecond temporal phenomena is ongoing, early results have confirmed published accounts of higher removal rates in a vacuum environment

Survival After Lung Transplantation of Cystic Fibrosis Patients Infected with Burkholderia cepacia Complex

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71603/1/j.1600-6143.2008.02186.x.pd

Evaluating the Quality of Research into a Single Prognostic Biomarker: A Systematic Review and Meta-analysis of 83 Studies of C-Reactive Protein in Stable Coronary Artery Disease

Background Systematic evaluations of the quality of research on a single prognostic biomarker are rare. We sought to evaluate the quality of prognostic research evidence for the association of C-reactive protein (CRP) with fatal and nonfatal events among patients with stable coronary disease. Methods and Findings We searched MEDLINE (1966 to 2009) and EMBASE (1980 to 2009) and selected prospective studies of patients with stable coronary disease, reporting a relative risk for the association of CRP with death and nonfatal cardiovascular events. We included 83 studies, reporting 61,684 patients and 6,485 outcome events. No study reported a prespecified statistical analysis protocol; only two studies reported the time elapsed (in months or years) between initial presentation of symptomatic coronary disease and inclusion in the study. Studies reported a median of seven items (of 17) from the REMARK reporting guidelines, with no evidence of change over time. The pooled relative risk for the top versus bottom third of CRP distribution was 1.97 (95% confidence interval [CI] 1.78–2.17), with substantial heterogeneity (I2 = 79.5). Only 13 studies adjusted for conventional risk factors (age, sex, smoking, obesity, diabetes, and low-density lipoprotein [LDL] cholesterol) and these had a relative risk of 1.65 (95% CI 1.39–1.96), I2 = 33.7. Studies reported ten different ways of comparing CRP values, with weaker relative risks for those based on continuous measures. Adjusting for publication bias (for which there was strong evidence, Egger's p<0.001) using a validated method reduced the relative risk to 1.19 (95% CI 1.13–1.25). Only two studies reported a measure of discrimination (c-statistic). In 20 studies the detection rate for subsequent events could be calculated and was 31% for a 10% false positive rate, and the calculated pooled c-statistic was 0.61 (0.57–0.66). Conclusion Multiple types of reporting bias, and publication bias, make the magnitude of any independent association between CRP and prognosis among patients with stable coronary disease sufficiently uncertain that no clinical practice recommendations can be made. Publication of prespecified statistical analytic protocols and prospective registration of studies, among other measures, might help improve the quality of prognostic biomarker research

The Nrf2 inhibitor brusatol is a potent antitumour agent in an orthotopic mouse model of colorectal cancer

© Evans et al. Nrf2 is a transcription factor that regulates cellular stress response and irinotecan-metabolising pathways. Its aberrant activity has been reported in a number of cancers, although relatively few studies have explored a role for Nrf2 in colorectal cancer (CRC). This study assessed the expression of Nrf2 in patient CRC tissues and explored the effect of Nrf2 modulation alone, or in combination with irinotecan, in human (HCT116) and murine (CT26) cell lines in vitro and in an orthotopic syngeneic mouse model utilising bioluminescent imaging. Using a tissue microarray, Nrf2 was found to be overexpressed (p < 0.01) in primary CRC and metastatic tissue relative to normal colon, with a positive correlation between Nrf2 expression in matched primary and metastatic samples. In vitro experiments in CRC cell lines revealed that Nrf2 siRNA and brusatol, which is known to inhibit Nrf2, decreased viability and sensitised cells to irinotecan toxicity. Furthermore, brusatol effectively abrogated CRC tumour growth in subcutaneously and orthotopicallyallografted mice, resulting in an average 8-fold reduction in luminescence at the study end-point (p=0.02). Our results highlight Nrf2 as a promising drug target in the treatment of CRC

SimHap GUI: An intuitive graphical user interface for genetic association analysis

<p>Abstract</p> <p>Background</p> <p>Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the <it>SimHap </it>package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool.</p> <p>Results</p> <p>We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the <it>SimHap </it>R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress.</p> <p>Conclusion</p> <p>SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis.</p

Application of pharmacogenomics and bioinformatics to exemplify the utility of human <i>ex vivo</i> organoculture models in the field of precision medicine

Here we describe a collaboration between industry, the National Health Service (NHS) and academia that sought to demonstrate how early understanding of both pharmacology and genomics can improve strategies for the development of precision medicines. Diseased tissue ethically acquired from patients suffering from chronic obstructive pulmonary disease (COPD), was used to investigate inter-patient variability in drug efficacy using ex vivo organocultures of fresh lung tissue as the test system. The reduction in inflammatory cytokines in the presence of various test drugs was used as the measure of drug efficacy and the individual patient responses were then matched against genotype and microRNA profiles in an attempt to identify unique predictors of drug responsiveness. Our findings suggest that genetic variation in CYP2E1 and SMAD3 genes may partly explain the observed variation in drug response

DADA: data assimilation for the detection and attribution of weather and climate-related events

A new nudging method for data assimilation, delay‐coordinate nudging, is presented. Delay‐coordinate nudging makes explicit use of present and past observations in the formulation of the forcing driving the model evolution at each time step. Numerical experiments with a low‐order chaotic system show that the new method systematically outperforms standard nudging in different model and observational scenarios, also when using an unoptimized formulation of the delay‐nudging coefficients. A connection between the optimal delay and the dominant Lyapunov exponent of the dynamics is found based on heuristic arguments and is confirmed by the numerical results, providing a guideline for the practical implementation of the algorithm. Delay‐coordinate nudging preserves the easiness of implementation, the intuitive functioning and the reduced computational cost of the standard nudging, making it a potential alternative especially in the field of seasonal‐to‐decadal predictions with large Earth system models that limit the use of more sophisticated data assimilation procedures