Long Term Preservation of Data Analysis Software at the NASA/IPAC Infrared Science Archive

The NASA/IPAC Infrared Science Archive (IRSA) curates both data and analysis tools from NASA's infrared missions. As part of our primary goal, we provide long term access to mission-specific software from projects such as IRAS and Spitzer. We will review the efforts by IRSA (and within the greater IPAC before that) to keep the IRAS and Spitzer software tools current and available. Data analysis tools are a vital part of the Spitzer Heritage Archive. The IRAS tools HIRES and SCANPI have been in continual use since the 1980's. Scanpi offers a factor of 2 to 5 gain in sensitivity over the IRAS Point Source Catalog by performing 1D scan averaging of raw survey data at specified arbitrary position. In 2007 SCANPI was completely modernized, with major code revisions. HIRES returns IRAS survey images with higher resolution than the IRAS Sky Survey Atlas (ISSA). We are currently undertaking a modest revision to the tool to ensure continued reliability. In the next two years, the US Planck Data Center plans to adapt both tools for use with Planck data, and deliver them to IRSA for long term curation

Hairy Black Holes in String Theory

Solutions of bosonic string theory are constructed which correspond to four-dimensional black holes with axionic quantum hair. The basic building blocks are the renormalization group flows of the CP1 model with a theta term and the SU(1,1)/U(1) WZW coset conformal field theory. However the solutions are also found to have negative energy excitations, and are accordingly expected to decay to the vacuum.Comment: 14 pages (References added

Phase 1 trial of rituximab, lenalidomide, and ibrutinib in previously untreated follicular lymphoma: Alliance A051103

Chemoimmunotherapy in follicular lymphoma is associated with significant toxicity. Targeted therapies are being investigated as potentially more efficacious and tolerable alternatives for this multiply-relapsing disease. Based on promising activity with rituximab and lenalidomide in previously untreated follicular lymphoma (overall response rate [ORR] 90%-96%) and ibrutinib in relapsed disease (ORR 30%-55%), the Alliance for Clinical Trials in Oncology conducted a phase 1 trial of rituximab, lenalidomide, and ibrutinib. Previously untreated patients with follicular lymphoma received rituximab 375 mg/m 2 on days 1, 8, 15, and 22 of cycle 1 and day 1 of cycles 4, 6, 8, and 10; lenalidomide as per cohort dose on days 1 to 21 of 28 for 18 cycles; and ibrutinib as per cohort dose daily until progression. Dose escalation used a 3+3 design from a starting dose level (DL) of lenalidomide 15 mg and ibrutinib 420 mg (DL0) to DL2 (lenalidomide 20 mg, ibrutinib 560 mg). Twenty-two patients were enrolled; DL2 was determined to be the recommended phase II dose. Although no protocol-defined dose-limiting toxicities were reported, a high incidence of rash was observed (all grades 82%, grade 3 36%). Eleven patients (50%) required dose reduction, 7 because of rash. The ORR for the entire cohort was 95%, and the 12-month progression-free survival was 80% (95% confidence interval, 57%-92%). Five patients developed new malignancies; 3 had known risk factors before enrollment. Given the increased toxicity and required dose modifications, as well as the apparent lack of additional clinical benefit to the rituximab-lenalidomide doublet, further investigation of the regimen in this setting seems unwarranted. The study was registered with www.ClinicalTrials.gov as #NCT01829568

Chemotaxis: a feedback-based computational model robustly predicts multiple aspects of real cell behaviour

The mechanism of eukaryotic chemotaxis remains unclear despite intensive study. The most frequently described mechanism acts through attractants causing actin polymerization, in turn leading to pseudopod formation and cell movement. We recently proposed an alternative mechanism, supported by several lines of data, in which pseudopods are made by a self-generated cycle. If chemoattractants are present, they modulate the cycle rather than directly causing actin polymerization. The aim of this work is to test the explanatory and predictive powers of such pseudopod-based models to predict the complex behaviour of cells in chemotaxis. We have now tested the effectiveness of this mechanism using a computational model of cell movement and chemotaxis based on pseudopod autocatalysis. The model reproduces a surprisingly wide range of existing data about cell movement and chemotaxis. It simulates cell polarization and persistence without stimuli and selection of accurate pseudopods when chemoattractant gradients are present. It predicts both bias of pseudopod position in low chemoattractant gradients and-unexpectedly-lateral pseudopod initiation in high gradients. To test the predictive ability of the model, we looked for untested and novel predictions. One prediction from the model is that the angle between successive pseudopods at the front of the cell will increase in proportion to the difference between the cell's direction and the direction of the gradient. We measured the angles between pseudopods in chemotaxing Dictyostelium cells under different conditions and found the results agreed with the model extremely well. Our model and data together suggest that in rapidly moving cells like Dictyostelium and neutrophils an intrinsic pseudopod cycle lies at the heart of cell motility. This implies that the mechanism behind chemotaxis relies on modification of intrinsic pseudopod behaviour, more than generation of new pseudopods or actin polymerization by chemoattractant

Overcoming real-world obstacles in 21 cm power spectrum estimation: A method demonstration and results from early Murchison Widefield Array data

We present techniques for bridging the gap between idealized inverse covariance weighted quadratic estimation of 21 cm power spectra and the real-world challenges presented universally by interferometric observation. By carefully evaluating various estimators and adapting our techniques for large but incomplete data sets, we develop a robust power spectrum estimation framework that preserves the so-called "Epoch of Reionization (EoR) window" and keeps track of estimator errors and covariances. We apply our method to observations from the 32-tile prototype of the Murchinson Widefield Array to demonstrate the importance of a judicious analysis technique. Lastly, we apply our method to investigate the dependence of the clean EoR window on frequency—especially the frequency dependence of the so-called “wedge" feature—and establish upper limits on the power spectrum from z ¼ 6.2 to z ¼ 11:7. Our lowest limit is ?ðkÞ < 0.3 Kelvin at 95% confidence at a comoving scale k ¼ 0.046 Mpc-1 and z ¼ 9.5

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Polymorphisms in CYP1B1, GSTM1, GSTT1 and GSTP1, and susceptibility to breast cancer

Polymorphisms in the cytochrome P450 1B1 (CYP1B1) and glutathione S-transferase (GST) drug metabolic enzymes, which are responsible for metabolic activation/detoxification of estrogen and environmental carcinogens, were analyzed for their association with breast cancer risk in 541 cases and 635 controls from a North Carolina population. Each polymorphism, altering the catalytic function of their respective enzymes, was analyzed in Caucasian and African-American women. As reported in previous studies, individual polymorphisms did not significantly impact breast cancer risk in either Caucasian or African-American women. However, African-American women exhibited a trend towards a protective effect when they had at least one CYP1B1 119S allele (OR=0.53; 95% CI=0.20–1.40) and increased risk for those women harboring at least one CYP1B1 432V allele (OR=5.52; 95% CI=0.50–61.37). Stratified analyses demonstrated significant interactions in younger (age ≤60) Caucasian women with the CYP1B1 119SS genotype (OR=3.09; 95% CI=1.22–7.84) and younger African-American women with the GSTT1 null genotype (OR=4.07; 95% CI=1.12–14.80). A notable trend was also found in Caucasian women with a history of smoking and at least one valine allele at GSTP1 114 (OR=2.12; 95% CI=1.02–4.41). In Caucasian women, the combined GSTP1 105IV/VV and CYP1B1 119AA genotypes resulted in a near 2-fold increase in risk (OR=1.96; 95% CI=1.04–3.72) and the three way combination of GSTP1 105IV/VV, CYP1B1 119AS/SS and GSTT1 null genotypes resulted in an almost 4-fold increase in risk (OR=3.97; 95% CI=1.27–12.40). These results suggest the importance of estrogen/carcinogen metabolic enzymes in the etiology of breast cancer, especially in women before the age of 60, as well as preventative measures such as smoking cessation

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts