Thermal-vacuum test report for the ultraviolet spectrometer thermal model

Early design studies showed that the UV spectrometer thermal design margins were very small so that an experimental confirmation of the analytical model would be desirable. At that time the prototype unit was scheduled too far downstream to be of value, so a separate thermal model was built for use in verifying the analytical model

siRNA-Based Targeting of Cyclin E Overexpression Inhibits Breast Cancer Cell Growth and Suppresses Tumor Development in Breast Cancer Mouse Model

Cyclin E is aberrantly expressed in many types of cancer including breast cancer. High levels of the full length as well as the low molecular weight isoforms of cyclin E are associated with poor prognosis of breast cancer patients. Notably, cyclin E overexpression is also correlated with triple-negative basal-like breast cancers, which lack specific therapeutic targets. In this study, we used siRNA to target cyclin E overexpression and assessed its ability to suppress breast cancer growth in nude mice. Our results revealed that cyclin E siRNA could effectively inhibit overexpression of both full length and low molecular weight isoforms of cyclin E. We found that depletion of cyclin E promoted apoptosis of cyclin E-overexpressing cells and blocked their proliferation and transformation phenotypes. Significantly, we further demonstrated that administration of cyclin E siRNA could inhibit breast tumor growth in nude mice. In addition, we found that cyclin E siRNA synergistically enhanced the cell killing effects of doxorubicin in cell culture and this combination greatly suppressed the tumor growth in mice. In conclusion, our results indicate that cyclin E, which is overexpressed in 30% of breast cancer, may serve as a novel and effective therapeutic target. More importantly, our study clearly demonstrates a very promising therapeutic potential of cyclin E siRNA for treating the cyclin E-overexpressing breast cancers, including the very malignant triple-negative breast cancers

PenQuest Volume 1, Number 2

Table of Contents for this Volume: Untitled by Julie Ambrose Night by Judith Gallo Untitled by Judy Gozdur the shamans by Charles Riddles Untitled by Jerry Connell Untitled by Laura Woods Untitled by LEMA Wicked Bird by Laura Jo Last Untitled by Rick Dentos Untitled by Jeni Moody Untitled by Bettie W. Kwibs Untitled by Joann Stagg The Protector Stood by Laura Jo Last Visions of Salome by Charles Riddles Untitled by Thomas Tutten Kennesaw Line by Don Ova-Dunaway Stone Blood by Mary Ellen C. Wofford Untitled by Roger Whitt Jr. Untitled by C. Wingate Untitled by Doug Dorey Untitled by Karen Blumberg Untitled by Beverly Oviatt Untitled by Virginia Shrader The Crapulous Credo of Charles C. by Charles Riddles the brave and the true by David Reed Untitled by Charles Gutierrez Canoe Creek by Patricia Kraft Untitled by Linda Bobinger The Man in the Iron Lung by Patricia Kraft Untitled by Roger Whitt, Jr. Childish Things by Kathleen Gay Untitled by Joseph Avanzini The Lover by Mary S. Aken Untitled by Ann Harrington And He Taketh Away by David Reed Untitled by Mary Graham Untitled by Melody A. Cummons Untitled by Karen Blumberg To The Poets by Judith Gallo Untitled by Ann Harringto

Chlamydia trachomatis antigens in enteroendocrine cells and macrophages of the small bowel in patients with severe irritable bowel syndrome

<p>Abstract</p> <p>Background</p> <p>Inflammation and immune activation have repeatedly been suggested as pathogentic factors in irritable bowel syndrome (IBS). The driving force for immune activation in IBS remains unknown. The aim of our study was to find out if the obligate intracellular pathogen <it>Chlamydia </it>could be involved in the pathogenesis of IBS.</p> <p>Methods</p> <p>We studied 65 patients (61 females) with IBS and 42 (29 females) healthy controls in which IBS had been excluded. Full thickness biopsies from the jejunum and mucosa biopsies from the duodenum and the jejunum were stained with a monoclonal antibody to <it>Chlamydia </it>lipopolysaccharide (LPS) and species-specific monoclonal antibodies to <it>C. trachomatis </it>and <it>C. pneumoniae</it>. We used polyclonal antibodies to chromogranin A, CD68, CD11c, and CD117 to identify enteroendocrine cells, macrophages, dendritic, and mast cells, respectively.</p> <p>Results</p> <p><it>Chlamydia </it>LPS was present in 89% of patients with IBS, but in only 14% of healthy controls (p < 0.001) and 79% of LPS-positive biopsies were also positive for <it>C. trachomatis </it>major outer membrane protein (MOMP). Staining for <it>C. pneumoniae </it>was negative in both patients and controls. <it>Chlamydia </it>LPS was detected in enteroendocrine cells of the mucosa in 90% of positive biopsies and in subepithelial macrophages in 69% of biopsies. Biopsies taken at different time points in 19 patients revealed persistence of <it>Chlamydia </it>LPS up to 11 years. The odds ratio for the association of <it>Chlamydia </it>LPS with presence of IBS (43.1; 95% CI: 13.2-140.7) is much higher than any previously described pathogenetic marker in IBS.</p> <p>Conclusions</p> <p>We found <it>C. trachomatis </it>antigens in enteroendocrine cells and macrophages in the small bowel mucosa of patients with IBS. Further studies are required to clarify if the presence of such antigens has a role in the pathogenesis of IBS.</p

Classification of Types of Stuttering Symptoms Based on Brain Activity

Among the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT) whole-word repetitions (WWR) should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type

Probabilistic machine learning and artificial intelligence.

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract

Performance related pay: Objectives and application

The stable isotope ratios of atmospheric CO2 (18O/16O and 13C/12C) have been monitored since 1977 to improve our understanding of the global carbon cycle, because biosphere–atmosphere exchange fluxes affect the different atomic masses in a measurable way. Interpreting the 18O/16O variability has proved difficult, however, because oxygen isotopes in CO2 are influenced by both the carbon cycle and the water cycle. Previous attention focused on the decreasing 18O/16O ratio in the 1990s, observed by the global Cooperative Air Sampling Network of the US National Oceanic and Atmospheric Administration Earth System Research Laboratory. This decrease was attributed variously to a number of processes including an increase in Northern Hemisphere soil respiration; a global increase in C4 crops at the expense of C3 forests; and environmental conditions, such as atmospheric turbulence and solar radiation, that affect CO2 exchange between leaves and the atmosphere. Here we present 30 years’ worth of data on 18O/16O in CO2 from the Scripps Institution of Oceanography global flask network and show that the interannual variability is strongly related to the El Niño/Southern Oscillation. We suggest that the redistribution of moisture and rainfall in the tropics during an El Niño increases the 18O/16O ratio of precipitation and plant water, and that this signal is then passed on to atmospheric CO2 by biosphere–atmosphere gas exchange. We show how the decay time of the El Niño anomaly in this data set can be useful in constraining global gross primary production. Our analysis shows a rapid recovery from El Niño events, implying a shorter cycling time of CO2 with respect to the terrestrial biosphere and oceans than previously estimated. Our analysis suggests that current estimates of global gross primary production, of 120 petagrams of carbon per year, may be too low, and that a best guess of 150–175 petagrams of carbon per year better reflects the observed rapid cycling of CO2. Although still tentative, such a revision would present a new benchmark by which to evaluate global biospheric carbon cycling models.