Reaction-Diffusion Degradation Model for Delayed Erosion of Cross-Linked Polyanhydride Biomaterials

We develop a theoretical model to explain the long induction interval of water intake that precedes the onset of erosion due to degradation caused by hydrolysis in the recently synthesized and studied cross-linked polyanhydrides. Various kinetic mechanisms are incorporated in the model in an attempt to explain the experimental data for the mass loss profile. Our key finding is that the observed long induction interval is attributable to the nonlinear dependence of the degradation rate constants on the local water concentration, which essentially amounts to the breakdown of the standard rate-equation approach, potential causes for which are then discussed. Our theoretical results offer physical insights into which microscopic studies will be required to supplement the presently available macroscopic mass-loss data in order to fully understand the origin of the observed behavior

Development Toward a Ground-Based Interferometric Phased Array for Radio Detection of High Energy Neutrinos

The in-ice radio interferometric phased array technique for detection of high energy neutrinos looks for Askaryan emission from neutrinos interacting in large volumes of glacial ice, and is being developed as a way to achieve a low energy threshold and a large effective volume at high energies. The technique is based on coherently summing the impulsive Askaryan signal from multiple antennas, which increases the signal-to-noise ratio for weak signals. We report here on measurements and a simulation of thermal noise correlations between nearby antennas, beamforming of impulsive signals, and a measurement of the expected improvement in trigger efficiency through the phased array technique. We also discuss the noise environment observed with an analog phased array at Summit Station, Greenland, a possible site for an interferometric phased array for radio detection of high energy neutrinos.Comment: 13 Pages, 14 Figure

Evaluating the High School Lunar Research Projects Program

The Center for Lunar Science and Exploration (CLSE), a collaboration between the Lunar and Planetary Institute and NASA s Johnson Space Center, is one of seven member teams of the NASA Lunar Science Institute (NLSI). In addition to research and exploration activities, the CLSE team is deeply invested in education and outreach. In support of NASA s and NLSI s objective to train the next generation of scientists, CLSE s High School Lunar Research Projects program is a conduit through which high school students can actively participate in lunar science and learn about pathways into scientific careers. The objectives of the program are to enhance 1) student views of the nature of science; 2) student attitudes toward science and science careers; and 3) student knowledge of lunar science. In its first three years, approximately 168 students and 28 teachers from across the United States have participated in the program. Before beginning their research, students undertake Moon 101, a guided-inquiry activity designed to familiarize them with lunar science and exploration. Following Moon 101, and guided by a lunar scientist mentor, teams choose a research topic, ask their own research question, and design their own research approach to direct their investigation. At the conclusion of their research, teams present their results to a panel of lunar scientists. This panel selects four posters to be presented at the annual Lunar Science Forum held at NASA Ames. The top scoring team travels to the forum to present their research in person

Elucidating glycosaminoglycan–protein–protein interactions using carbohydrate microarray and computational approaches

Glycosaminoglycan polysaccharides play critical roles in many cellular processes, ranging from viral invasion and angiogenesis to spinal cord injury. Their diverse biological activities are derived from an ability to regulate a remarkable number of proteins. However, few methods exist for the rapid identification of glycosaminoglycan–protein interactions and for studying the potential of glycosaminoglycans to assemble multimeric protein complexes. Here, we report a multidisciplinary approach that combines new carbohydrate microarray and computational modeling methodologies to elucidate glycosaminoglycan–protein interactions. The approach was validated through the study of known protein partners for heparan and chondroitin sulfate, including fibroblast growth factor 2 (FGF2) and its receptor FGFR1, the malarial protein VAR2CSA, and tumor necrosis factor-α (TNF-α). We also applied the approach to identify previously undescribed interactions between a specific sulfated epitope on chondroitin sulfate, CS-E, and the neurotrophins, a critical family of growth factors involved in the development, maintenance, and survival of the vertebrate nervous system. Our studies show for the first time that CS is capable of assembling multimeric signaling complexes and modulating neurotrophin signaling pathways. In addition, we identify a contiguous CS-E-binding site by computational modeling that suggests a potential mechanism to explain how CS may promote neurotrophin-tyrosine receptor kinase (Trk) complex formation and neurotrophin signaling. Together, our combined microarray and computational modeling methodologies provide a general, facile means to identify new glycosaminoglycan–protein–protein interactions, as well as a molecular-level understanding of those complexes

Galectin-1 serum levels reflect tumor burden and adverse clinical features in classical Hodgkin lymphoma

Galectin-1 (Gal1) is a member of a highly conserved family of carbohydrate-binding proteins that modulates innate and adaptive immune responses and fosters tumor-immune escape. Hodgkin lymphoma (HL) Reed-Sternberg (RS) cells overexpress and secrete Gal1, which selectively kills Th1,Th17 and cytotoxic T cells and promotes the immunosuppressive Th2/Treg-predominant HL microenvironment. We developed a sandwich ELISA and assessed serum Gal1 levels in 315 newly diagnosed, previously untreated HL patients enrolled on 3 risk-adapted clinical trials. Serum Gal1 levels were significantly higher in HL patients than in normal controls (p < .0001). Gal1 serum levels also increased with Ann Arbor stage (p < .0001), areas of nodal involvement (p = .0001) and the International Prognostic Score (IPS) (2-7, p = .006). We conclude that Gal1 serum levels are significantly associated with tumor burden and additional adverse clinical characteristics in newly diagnosed HL Patients.Fil: Ouyang, Jing. Dana-Farber Cancer Institute. Department of Medical Oncology; Estados Unidos de América;Fil: Plütschow, Annette. German Hodgkin Study Group; Alemania;Fil: Von Strandmann, Elke Pogge. University Hospital of Cologne. Laboratory for Immunotherapy; Alemania;Fil: Reiners, Katrin S.. University Hospital of Cologne. Laboratory for Immunotherapy; Alemania;Fil: Ponader, Sabine. German Hodgkin Study Group; Alemania;Fil: Rabinovich, Gabriel Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental (i); Argentina;Fil: Neuberg, Donna. Dana-Farber Cancer Institute. Department of Biostatistics; Estados Unidos de América;Fil: Engert, Andreas. German Hodgkin Study Group; Alemania;Fil: Shipp, Margaret A.. Dana-Farber Cancer Institute. Department of Medical Oncology; Estados Unidos de América

Astrobites as a Community-led Model for Education, Science Communication, and Accessibility in Astrophysics

Support for early career astronomers who are just beginning to explore astronomy research is imperative to increase retention of diverse practitioners in the field. Since 2010, Astrobites has played an instrumental role in engaging members of the community -- particularly undergraduate and graduate students -- in research. In this white paper, the Astrobites collaboration outlines our multi-faceted online education platform that both eases the transition into astronomy research and promotes inclusive professional development opportunities. We additionally offer recommendations for how the astronomy community can reduce barriers to entry to astronomy research in the coming decade

Binomial Sampling of Western Flower Thrips Infesting Flowering Greenhouse Crops Using Incidence-Mean Models

Accurate assessments of thrips density are important for effective thrips management programs. Complicating the development of sampling plans for western flower thrips (WFT) Frankliniella occidentalis (Pergande) in greenhouse crops are the facts that they are small, difficult to detect, and attack a variety of crops, which may be grown concurrently within the same greenhouse. Binomial sampling was evaluated as an alternative to sampling plans based on complete enumeration. This work included comparison of incidence-mean models across diverse plant species (impatiens, cucumber, and marigold) to determine the possibility of using a generic model for sampling WFT in mixed crops. Data from laboratory-processed flower samples revealed that infestation rates calculated using a tally threshold of three thrips per flower provided the best estimates of thrips population densities in each tested crop and in the combined crops (composite data set). Distributions of thrips populations were similar across the three plant species, indicating potential for development of a generic sampling plan for mixed floral crops. Practical sampling methods for simple and complex flowers tested in the greenhouse (in situ) were evaluated via construction of binomial count operating characteristic functions. In the case of simple flowers (impatiens), visual inspections provided adequate estimates of thrips infestation rates at a low tally threshold, which ultimately enabled accurate estimation of thrips densities. However, visual inspection and tap-sampling of complex flowers (marigold) provided unreliable results. These findings indicate that use of binomial sampling methods in mixed floral crops will require development of more accurate sampling technique

Flow and retreat of the Late Quaternary Pine Island-Thwaites palaeo-ice stream, West Antarctica

Multibeam swath bathymetry and sub-bottom profiler data are used to establish constraints on the flow and retreat history of a major palaeo-ice stream that carried the combined discharge from the parts of the West Antarctic Ice Sheet now occupied by the Pine Island and Thwaites glacier basins. Sets of highly elongated bedforms show that, at the last glacial maximum, the route of the Pine Island-Thwaites palaeo-ice stream arced north-northeast following a prominent cross-shelf trough. In this area, the grounding line advanced to within similar to 68 km of, and probably reached, the shelf edge. Minimum ice thickness is estimated at 715 m on the outer shelf, and we estimate a minimum ice discharge of similar to 108 km(3) yr(-1) assuming velocities similar to today's Pine Island glacier (similar to 2.5 km yr(-1)). Additional bed forms observed in a trough northwest of Pine Island Bay likely formed via diachronous ice flows across the outer shelf and demonstrate switching ice stream behavior. The "style" of ice retreat is also evident in five grounding zone wedges, which suggest episodic deglaciation characterized by halts in grounding line migration up-trough. Stillstands occurred in association with changes in ice bed gradient, and phases of inferred rapid retreat correlate to higher bed slopes, supporting theoretical studies that show bed geometry as a control on ice margin recession. However, estimates that individual wedges could have formed within several centuries still imply a relatively rapid overall retreat. Our findings show that the ice stream channeled a substantial fraction of West Antarctica's discharge in the past, just as the Pine Island and Thwaites glaciers do today

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites. google.com/site/gaussianbhc