Performance of CLEAN & MEM-NJIT on synthetic STIX and RHESSI data

Results from initial comparison of CLEAN and MEM-NJIT on synthetic STIX and RHESSI visibility dat

Additional file 1: Table S1. of Puberty-specific promotion of mammary tumorigenesis by a high animal fat diet

Compositions of the diets. (PDF 118 kb

SunPy: Python for Solar Physics Data Analysis

<p>Python has seen widespread adoption among the scientific community in recent years resulting in a wide range of software being written for everything from numerical computation and machine learning to spectral analysis and visualization. SunPy is a free and open-source software library for working with solar and heliospheric datasets, written in the Python programming language. It provides an alternative to the IDL-based SolarSoft (SSW) solar data analysis environment.</p> <p> </p> <p>SunPy has map objects that allow simple overplotting of data from multiple two-dimensional image FITS files; time-series objects that allow overplotting of multiple lightcurves, and integration with online services such as The Virtual Solar Observatory (VSO) and The Heliophysics Event Knowledgebase (HEK). SunPy also provides functionality that is not currently available in SSW such as advanced time series manipulation routines and support for working with solar data stored using JPEG 2000. We give some examples of what can be done in SunPy, and show how Python-based solar data-analysis can take advantage of many different data analysis tools not readily available in SSWIDL.</p> <p> </p> <p>We also discuss future goals for the project and ways for interested users can become involved in the planning and development of SunPy.</p> <p><br>(Presented at AAS SPD 2012 Meeting in Anchorage, AK)</p

Additional file 3: Table S3. of Puberty-specific promotion of mammary tumorigenesis by a high animal fat diet

Ontology analysis of short-latency tumors that cluster together. (PDF 38 kb

Additional file 5: Figure S2. of Puberty-specific promotion of mammary tumorigenesis by a high animal fat diet

Effects of diet treatments on blood levels of glucose and insulin. BALB/c mice started on HFD or LFD at 3 weeks of age were switched to LFD or HFD, respectively, at 9 weeks of age. Blood levels of glucose (a, c) and insulin (b, d) were measured at 4 weeks post diet switches (a, b) or in tumor-bearing mice (c, d). The bars represent mean ± SEM for samples at 4 weeks after diet switches and from tumor-bearing mice (n = 5 for all groups). No significant differences were detected. (PDF 653 kb

DNA Priming for Seasonal Influenza Vaccine: A Phase 1b Double-Blind Randomized Clinical Trial

<div><p>Background</p><p>The efficacy of current influenza vaccines is limited in vulnerable populations. DNA vaccines can be produced rapidly, and may offer a potential strategy to improve vaccine immunogenicity, indicated by studies with H5 influenza DNA vaccine prime followed by inactivated vaccine boost.</p><p>Methods</p><p>Four sites enrolled healthy adults, randomized to receive 2011/12 seasonal influenza DNA vaccine prime (n=65) or phosphate buffered saline (PBS) (n=66) administered intramuscularly with Biojector. All subjects received the 2012/13 seasonal inactivated influenza vaccine, trivalent (IIV3) 36 weeks after the priming injection. Vaccine safety and tolerability was the primary objective and measurement of antibody response by hemagglutination inhibition (HAI) was the secondary objective.</p><p>Results</p><p>The DNA vaccine prime-IIV3 boost regimen was safe and well tolerated. Significant differences in HAI responses between the DNA vaccine prime and the PBS prime groups were not detected in this study.</p><p>Conclusion</p><p>While DNA priming significantly improved the response to a conventional monovalent H5 vaccine in a previous study, it was not effective in adults using seasonal influenza strains, possibly due to pre-existing immunity to the prime, unmatched prime and boost antigens, or the lengthy 36 week boost interval. Careful optimization of the DNA prime-IIV3 boost regimen as related to antigen matching, interval between vaccinations, and pre-existing immune responses to influenza is likely to be needed in further evaluations of this vaccine strategy. In particular, testing this concept in younger age groups with less prior exposure to seasonal influenza strains may be informative.</p><p>Trial Registration</p><p>ClinicalTrials.gov <a href="http://clinicaltrials.gov/ct2/show/NCT01498718" target="_blank">NCT01498718</a></p></div

VRC 701 Consort diagram of subject disposition.

<p>VRC 701 Consort diagram of subject disposition.</p

Frequency of previous seasonal influenza vaccinations.

<p>*All subjects received 2011/2012 IIV3 at least 8 weeks prior to enrollment in the trial.</p><p>Frequency of previous seasonal influenza vaccinations.</p

Influenza strains included in DNA vaccine prime and IIV3 boost.

<p>The trial was conducted at 4 clinical sites in the United States: Center for Vaccine Development, Saint Louis University, Saint Louis, Missouri; Cincinnati Children’s Hospital Medical Center Cincinnati, Ohio; Hope Clinic of the Emory Vaccine Center, Atlanta, Georgia; and Baylor College of Medicine, Houston, Texas. The first subject was screened for recruitment on December 20, 2011, study vaccinations began on January 10, 2012 and study follow-up continued through April 17, 2013.</p><p>Influenza strains included in DNA vaccine prime and IIV3 boost.</p

GMT 4 weeks Post-Boost for Study Groups by Baseline Immune Response: GMT (95% CI).

<p>GMT 4 weeks Post-Boost for Study Groups by Baseline Immune Response: GMT (95% CI).</p