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At least 109 records · Page 6

A Meta-Analysis of the Protein Components in Rattlesnake Venom

The specificity and potency of venom components give them a unique advantage in developing various pharmaceutical drugs. Though venom is a cocktail of proteins, rarely are the synergy and association between various venom components studied. Understanding the relationship between various components of venom is critical in medical research. Using meta-analysis, we observed underlying patterns and associations in the appearance of the toxin families. For Crotalus, Dis has the most associations with the following toxins: PDE; BPP; CRL; CRiSP; LAAO; SVMP P-I and LAAO; SVMP P-III and LAAO. In Sistrurus venom, CTL and NGF have the most associations. These associations can predict the presence of proteins in novel venom and understand synergies between venom components for enhanced bioactivity. Using this approach, the need to revisit the classification of proteins as major components or minor components is highlighted. The revised classification of venom components is based on ubiquity, bioactivity, the number of associations, and synergies. The revised classification can be expected to trigger increased research on venom components, such as NGF, which have high biomedical significance. Using hierarchical clustering, we observed that the genera’s venom compositions were similar, based on functional characteristics rather than phylogenetic relationships.

60 APPLIED LIFE SCIENCES↗

Antibiotic tigecycline inhibits cell proliferation, migration and invasion via down‐regulating CCNE2 in pancreatic ductal adenocarcinoma

Abstract Recently, many researches have reported that antibiotic tigecycline has significant effect on cancer treatment. However, biomedical functions and molecular mechanisms of tigecycline in human pancreatic ductal adenocarcinoma (PDAC) remain unclear. In the current study, we tried to assess the effect of tigecycline in PDAC cells. AsPC‐1 and HPAC cells were treated with indicated concentrations of tigecycline for indicated time, and then, MTT, BrdU and soft agar assay were used to test cell proliferation. The effect of tigecycline on cell cycle and cellular apoptosis was tested by cytometry. Migration and invasion were detected by wound healing assay and transwell migration/invasion assay. Expressions of cell cycle‐related and migration/invasion‐related protein were determined by using Western blot. The results revealed that tigecycline observably suppressed cell proliferation by inducing cell cycle arrest at G0/G1 phase and blocked cell migration/invasion via holding back the epithelial‐mesenchymal transition (EMT) process in PDAC. In addition, tigecycline also remarkably blocked tumorigenecity in vivo. Furthermore, the effects of tigecycline alone or combined with gemcitabine in vitro or on PDAC xenografts were also performed. The results showed that tigecycline enhanced the chemosensitivity of PDAC cells to gemcitabine. Interestingly, we found CCNE2 expression was declined distinctly after tigecycline treatment. Then, CCNE2 was overexpressed to rescue tigecycline‐induced effect. The results showed that CCNE2 overexpression significantly rescued tigecycline‐inhibited cell proliferation and migration/invasion. Collectively, we showed that tigecycline inhibits cell proliferation, migration and invasion via down‐regulating CCNE2, and tigecycline might be used as a potential drug for PDAC treatment alone or combined with gemcitabine.

Yang, Jie↗

A Field-Deployable Magnetic Resonance Imaging Rhizotron for Modeling and Enhancing Root Growth and Biogeochemical Function

A collaborative team from Texas A&M AgriLife Research, ABQMR Inc., the Soil Health Institute, the Athinoula A. Martinos Center for Biomedical Imaging, and NIST developed low-field magnetic resonance imaging (LF-MRI) instrumentation capable of imaging intact soil-root systems. The system measured root biomass, architecture, 3D mass distribution, and growth rates, providing a non-destructive means to evaluate ideal plant characteristics based on root metrics. It also successfully generated three-dimensional images of soil water content, a key property influencing root growth and exploration. Operating much like an MRI used in a medical setting, the system functioned in field conditions without damaging plants, overcoming the limitations of traditional methods such as trenching, soil coring, and root excavation. Over the course of the project, the team designed and built three functional prototype systems. These prototypes provided new insights into root–water–soil interactions that drive processes such as nutrient uptake, water use, and carbon management. This information contributed to efforts to optimize plants for carbon sequestration without sacrificing economic yield. The project also supported the identification of desirable traits for energy sorghum, including high root growth rates, more vertical root angles, and enhanced drought resilience under water-limiting conditions.

09 BIOMASS FUELS↗

Acoustics at the nanoscale (nanoacoustics): A comprehensive literature review. Part II: Nanoacoustics for biomedical imaging and therapy

We report in the past decade, acoustics at the nanoscale (i.e., nanoacoustics) has evolved rapidly with continuous and substantial expansion of capabilities and refinement of techniques. Motivated by research innovations in the last decade, for the first time, recent advancements of acoustics-associated nanomaterials/nanostructures and nanodevices for different applications are outlined in this comprehensive review, which is written in two parts. As part II of this two-part review, this paper concentrates on nanoacoustics in biomedical imaging and therapy applications, including molecular ultrasound imaging, photoacoustic imaging, ultrasound-mediated drug delivery and therapy, and photoacoustic drug delivery and therapy. Firstly, the recent developments of nanosized ultrasound and photoacoustic contrast agents as well as their various imaging applications are examined. Secondly, different types of nanomaterials/nanostructures as nanocarriers for ultrasound and photoacoustic therapies are discussed. Finally, a discussion of challenges and future research directions are provided for nanoacoustics in medical imaging and therapy.

47 OTHER INSTRUMENTATION↗

Drug discovery efforts at George Mason University

With over 39,000 students, and research expenditures in excess of $200 million, George Mason University (GMU) is the largest R1 (Carnegie Classification of very high research activity) university in Virginia. Mason scientists have been involved in the discovery and development of novel diagnostics and therapeutics in areas as diverse as infectious diseases and cancer. Below are highlights of the efforts being led by Mason researchers in the drug discovery arena. To enable targeted cellular delivery, and non-biomedical applications, Veneziano and colleagues have developed a synthesis strategy that enables the design of self-assembling DNA nanoparticles (DNA origami) with prescribed shape and size in the 10 to 100 nm range. The nanoparticles can be loaded with molecules of interest such as drugs, proteins and peptides, and are a promising new addition to the drug delivery platforms currently in use. The investigators also recently used the DNA origami nanoparticles to fine tune the spatial presentation of immunogens to study the impact on B cell activation. These studies are an important step towards the rational design of vaccines for a variety of infectious agents. To elucidate the parameters for optimizing the delivery efficiency of lipid nanoparticles (LNPs), Buschmann, Paige and colleagues have devised methods for predicting and experimentally validating the pKa of LNPs based on the structure of the ionizable lipids used to formulate the LNPs. These studies may pave the way for the development of new LNP delivery vehicles that have reduced systemic distribution and improved endosomal release of their cargo post administration. To better understand protein-protein interactions and identify potential drug targets that disrupt such interactions, Luchini and colleagues have developed a methodology that identifies contact points between proteins using small molecule dyes. The dye molecules noncovalently bind to the accessible surfaces of a protein complex with very high affinity, but are excluded from contact regions. When the complex is denatured and digested with trypsin, the exposed regions covered by the dye do not get cleaved by the enzyme, whereas the contact points are digested. The resulting fragments can then be identified using mass spectrometry. The data generated can serve as the basis for designing small molecules and peptides that can disrupt the formation of protein complexes involved in disease processes. For example, using peptides based on the interleukin 1 receptor accessory protein (IL-1RAcP), Luchini, Liotta, Paige and colleagues disrupted the formation of IL-1/IL-R/IL-1RAcP complex and demonstrated that the inhibition of complex formation reduced the inflammatory response to IL-1B. Working on the discovery of novel antimicrobial agents, Bishop, van Hoek and colleagues have discovered a number of antimicrobial peptides from reptiles and other species. DRGN-1, is a synthetic peptide based on a histone H1-derived peptide that they had identified from Komodo Dragon plasma. DRGN-1 was shown to disrupt bacterial biofilms and promote wound healing in an animal model. The peptide, along with others, is being developed and tested in preclinical studies. Other research by van Hoek and colleagues focuses on in silico antimicrobial peptide discovery, screening of small molecules for antibacterial properties, as well as assessment of diffusible signal factors (DFS) as future therapeutics. The above examples provide insight into the cutting-edge studies undertaken by GMU scientists to develop novel methodologies and platform technologies important to drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Scalable Knowledge Graph Analytics at 136 Petaflop/s

We are motivated by newly proposed methods for data mining large-scale corpora of scholarly publications, such as the full biomedical literature, which may consist of tens of millions of papers spanning decades of research. In this setting, analysts seek to discover how concepts relate to one another. They construct graph representations from annotated text databases and then formulate the relationship-mining problem as one of computing all-pairs shortest paths (APSP), which becomes a significant bottleneck. In this context, we present a new high-performance algorithm and implementation of the Floyd-Warshall algorithm for distributed-memory parallel computers accelerated by GPUs, which we call DSNAPSHOT (Distributed Accelerated Semiring All-Pairs Shortest Path). For our largest experiments, we ran DSNAPSHOT on a connected input graph with millions of vertices using 4, 096nodes (24,576GPUs) of the Oak Ridge National Laboratory's Summit supercomputer system. We find DSNAPSHOT achieves a sustained performance of 136×1015 floating-point operations per second (136petaflop/s) at a parallel efficiency of 90% under weak scaling and, in absolute speed, 70% of the best possible performance given our computation (in the single-precision tropical semiring or “min-plus” algebra). Looking forward, we believe this novel capability will enable the mining of scholarly knowledge corpora when embedded and integrated into artificial intelligence-driven natural language processing workflows at scale.

Kannan, Ramakrishnan {ramki}↗

Multidimensional perspectives of geo-epidemiology: from interdisciplinary learning and research to cost–benefit oriented decision-making

Research typically promotes two types of outcomes (inventions and discoveries), which induce a virtuous cycle: something suspected or desired (not previously demonstrated) may become known or feasible once a new tool or procedure is invented and, later, the use of this invention may discover new knowledge. Research also promotes the opposite sequence—from new knowledge to new inventions. This bidirectional process is observed in geo-referenced epidemiology—a field that relates to but may also differ from spatial epidemiology. Geo-epidemiology encompasses several theories and technologies that promote inter/transdisciplinary knowledge integration, education, and research in population health. Based on visual examples derived from geo-referenced studies on epidemics and epizootics, this report demonstrates that this field may extract more (geographically related) information than simple spatial analyses, which then supports more effective and/or less costly interventions. Actual (not simulated) bio-geo-temporal interactions (never captured before the emergence of technologies that analyze geo-referenced data, such as geographical information systems) can now address research questions that relate to several fields, such as Network Theory. Thus, a new opportunity arises before us, which exceeds research: it also demands knowledge integration across disciplines as well as novel educational programs which, to be biomedically and socially justified, should demonstrate cost-effectiveness. Grounded on many bio-temporal-georeferenced examples, this report reviews the literature that supports this hypothesis: novel educational programs that focus on geo-referenced epidemic data may help generate cost-effective policies that prevent or control disease dissemination.

59 BASIC BIOLOGICAL SCIENCES↗

HOSS: an implementation of the combined finite-discrete element method

Nearly thirty years since its inception, the combined finite-discrete element method (FDEM) has made remarkable strides in becoming a mainstream analysis tool within the field of Computational Mechanics. FDEM was developed to effectively “bridge the gap” between two disparate Computational Mechanics approaches known as the finite and discrete element meth-ods. At Los Alamos National Laboratory (LANL) researchers developed the Hybrid Optimization Software Suite (HOSS) as a hybrid multi-physics platform, based on FDEM, for the simulation of solid material behavior complemented with the latest technological enhancements for full fluid–solid interaction. Furthermore, in HOSS, several newly developed FDEM algorithms have been implemented that yield more accurate material deformation formulations, inter-particle interaction solvers, and fracture and fragmentation solutions. Additionally, an explicit computational fluid dynamics solver and a novel fluid–solid interaction algorithms have been fully integrated (as opposed to coupled) into the HOSS’ solid mechanical solver, allowing for the study of an even wider range of problems. Advancements such as this are leading HOSS to become a tool of choice for multi-physics problems. Finally, HOSS has been successfully applied by a myriad of researchers for analysis in rock mechanics, oil and gas industries, engineering application (structural, mechanical and biomedical engineering), mining, blast loading, high velocity impact, as well as seismic and acoustic analysis. This paper intends to summarize the latest development and application efforts for HOSS.

58 GEOSCIENCES↗

Fabrication and testing of high-performance all-metal neutron guides and axisymmetric mirrors by electrochemical replication

Neutron scattering is one of the most useful methods of studying the structure of matter, with applications to biomedical, structural, magnetic and energy-related materials. Neutron-scattering instruments are installed around research reactors or accelerator-based neutron sources, and neutron guides are critical components of these facilities. They are neutron-transport optical devices consisting of state-of-the-art mirrors often tens of meters long. Here we demonstrate a novel fabrication method of all-metallic neutron guides and axisymmetric mirrors by electroplating from precision mandrels. The process allows for the fabrication of single-piece all-metal guides of prismatic and axisymmetric shapes. We also demonstrate supermirror guides and axisymmetric focusing supermirrors produced with the same technology. We present the fabrication and tests of the multilayer-coated replicated guides and optic and show that the mandrel is reproduced with high fidelity and reliability. Furthermore, such supermirror optics will provide game-changing improvements in neutron techniques.

36 MATERIALS SCIENCE↗

Flexible organic integrated electronics for self-powered multiplexed ocular monitoring

Smart contact lens has drawn extensive research interests due to the noninvasive real-time detection of the human body to provide biomedical information for health management. However, it has been difficult to accurately measure the physiological signals in tears, and the use of external power source has also hindered the future applications. Here, we demonstrated an organic electrochemical transistor based multiplexed sensors self-powered by the organic solar cells (OSCs). The integrated device was fabricated via simple process including solution blade-coating and thermal evaporation. OSCs were optimized to provide optimal operation voltage for the sensors that exhibit semilog-linear response to the glucose and calcium ions in tear fluids without any peripheral circuits. The sensing signals can be transmitted to the laptop wirelessly through a near filed communication unit. This integrated self-powered multiplexed sensing device will provide real-time monitoring of the biomarkers in tears, prospected to be installed on the smart contact lens for the early detection and diagnosis of diabetes.

36 MATERIALS SCIENCE↗

Preparation of Highly Crystalline Silk Nanofibrils and Their Use in the Improvement of the Mechanical Properties of Silk Films

Due to their commendable biocompatibility, regenerated silk fibroin (RSF) films have attracted considerable research interest. However, the poor mechanical properties of RSF films have limited their use in various biomedical applications. In this study, a novel, highly crystalline silk fibril was successfully extracted from silk by combining degumming with ultrasonication. Ultrasonication accelerated the development of silk nanofibrils measuring 130–200 nm on the surface of the over-degummed silk fibers, which was confirmed via scanning electron microscopy. Additionally, the crystallinity index of silk fibril was found to be significantly higher (~68%) than that of conventionally degummed silk (~54%), as confirmed by the Fourier-transform infrared (FTIR) spectroscopy results. Furthermore, the breaking strength and elongation of the RSF film were increased 1.6 fold and 3.4 fold, respectively, following the addition of 15% silk nanofibrils. Thus, the mechanical properties of the RSF film were remarkably improved by the addition of the silk nanofibrils, implying that it can be used as an excellent reinforcing material for RSF films.

36 MATERIALS SCIENCE↗

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Abstract Machine‐learning (ML) parameterizations of subgrid processes (here of turbulence, convection, and radiation) may one day replace conventional parameterizations by emulating high‐resolution physics without the cost of explicit simulation. However, uncertainty about the relationship between offline and online performance (i.e., when integrated with a large‐scale general circulation model) hinders their development. Much of this uncertainty stems from limited sampling of the noisy, emergent effects of upstream ML design decisions on downstream online hybrid simulation. Our work rectifies the sampling issue via the construction of a semi‐automated, end‐to‐end pipeline for size ensembles of hybrid simulations, revealing important nuances in how systematic reductions in offline error manifest in changes to online error and online stability. For example, removing dropout and switching from a Mean Squared Error to a Mean Absolute Error loss both reduce offline error, but they have opposite effects on online error and online stability. Other design decisions, like incorporating memory, converting moisture input from specific humidity to relative humidity, using batch normalization, and training on multiple climates do not come with any such compromises. Finally, we show that ensemble sizes of may be necessary to reliably detect causally relevant differences online. By enabling rapid online experimentation at scale, we can empirically settle debates regarding subgrid ML parameterization design that would have otherwise remained unresolved in the noise.

Lin, Jerry [Department of Earth System Sciences Un↗

Collaborative Research Proposal: Time Resolved Optical Emissions Spectroscopy and Laser Induced Fluorescence Spectroscopy of Nanosecond Pulsed Discharges in a Gas-Liquid Water Film Reactor

Electrical discharge plasma formed in contact with liquid water is of interest for a wide range of applications in chemical, biomedical, agricultural, electrical, and materials science and engineering. Such plasma reactors are of very timely importance since they also have significant disinfection capability by inactivating bacteria, viruses and other pathogens. Many types of plasma sources including those driven by AC, DC, RF, microwave, and pulsed electrical power supplies coupled to a wide range of different electrode configurations and reactor designs have been developed and explored which contact the plasma with liquid water. Recent roadmaps have recommended that further work is needed to develop our understanding of the fundamental chemical and physical process which occur at the interface of non-thermal plasma with liquid water solutions in order to advance this large diversity of applications which ultimately depend upon efficient production of key reactive chemical species. There is a wide range of interacting factors that affect the chemical reactions that occur in the plasma, in the liquid phase, and at the interface. These factors ultimately govern the key reactive chemical species formed and used in the various applications and they include a) the reactor design and input parameters, b) the discharge and transport processes, c) the plasma properties, and d) the resulting chemical reactions. For pulsed discharges, the power supply design and output parameters control the applied voltage, frequency, rise time, and width (duration) of the applied pulses. The reactor design involves specification of the gas-liquid contacting methods, electrode gap distance, reactor volume and shape, and gas and liquid flow rates achievable. The gas and liquid compositions as well as the liquid properties such as pH and conductivity are also of key importance in determination of the resulting chemical reactions. In addition, the important plasma properties include plasma gas temperature, electron density, electron energy (distribution), and size of the plasma channels which are all affected by the discharge and transport properties. Many studies have focused on specific aspects of these various processes. Of particular important and relevance to the proposed work is the utilization of nanosecond pulses to generate plasma in gas-liquid systems, liquid bubbles, underwater, and in gases. Recent advances in nanosecond pulses provide significant advantages in utilization with liquid water. For example, fast rise time and short pulses are less sensitive to water conductivity, such short pulses may provide advantages in fast temporal quenching of the plasma, and fundamental analysis of pulse properties, including pulse shape and width, may be facilitated by investigation of single filamentary fast pulses. Many studies have also dealt with the role of the gas composition on formation of reactive oxygen species (ROS) (i.e., hydroxyl radicals – ·OH, hydrogen peroxide – H 2 O 2 , various atomic oxygen species, ozone-O 3 , hydroperoxyl radicals HO 2 ·) and reactive nitrogen species (RNS) (i.e., nitrogen oxides – NO, NO 2 , N 2 O - collectively termed NO X , nitrite-NO 2 - , nitrate-NO 3 - , peroxynitrite-ONOO - ). The hydroxyl radical is the critical species in many chemical oxidation reactions for chemical degradation of toxic compounds in water and gases and for synthesis of some compounds. The mixture of various nitrogen oxide species is important for many biochemical and biological processes involved in biomedical and agricultural applications including disinfection and fertilizer production. The present proposal focuses on determination of the effects of time resolved electron density and hydroxyl radicals on plasma chemical reactions through collaboration with the Princeton Collaborative Low Temperature Plasma Research Facility (PCRF) at the Princeton Plasma Physics Laboratory (PPPL). In order to further investigate the role of the plasma generated electrons and hydroxyl radicals on the overall formation of the key species including hydrogen peroxide, hydroxyl radicals, and nitrogen oxides, the proposed work, thus seeks to determine high resolution time resolved electron density by optical emissions spectroscopy and time resolved hydroxyl radicals using laser induced fluorescence in the nanosecond discharge reactor. The combination of data on electron density and hydroxyl radical concentration will be utilized in the present work to more fully characterize the chemical reaction processes in this system and to advance the design, development, and operation of such chemical reactors for a wide range of applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Sol–Gel‐Based Advanced Porous Silica Materials for Biomedical Applications

Abstract Porous silica‐based materials have burgeoning applications ranging from fillers and additives, to adsorbents, catalysts, and recently therapeutic agents and vaccines in nanomedicine. The preponderance of these materials is made by sol–gel processing wherein soluble silica precursors are reacted to form amorphous networks composed of siloxane bonds. The facile sol–gel approach allows for an unlimited variety of binary tertiary and more complex chemical compositions including organic ligands and networks resulting in so‐called organic–inorganic hybrid materials. Here, a brief review of the recent progress in sol–gel‐derived silica materials prepared as particles, thin films, biosilica/silica bioreplicas (of molecules, cells and organisms), and their related preparation, properties, and bioapplications is provided. First, it highlights the recent achievements of mesoporous silica nanoparticles in biomedical applications, including therapeutic agent delivery, multimodal imaging and theranostics, and bone tissue engineering and repair. Second, the research in evaporation‐induced self‐assembly (EISA)‐based mesostructured silica thin films and cell‐directed EISA in bio/nano interfaces for various bioapplications, such as bioactive coatings, biosensing, and living cell immobilization, has been reviewed. Third, the pioneering work in biomimetic silicification/immobilization of biomolecules and bio‐organisms and silica bioreplication of complex bio‐organisms is summarized. Finally, it is concluded with personal perspectives on the directions of future work on this field.

Lei, Qi↗

Foundational insights into the mechanical and molecular evolution of porcine skin gelatin during gelation

Gelatin is a widely used material in biomedical fields, particularly in regenerative medicine and tissue engineering, due to its biocompatibility and versatile properties. While prior research has explored methods to enhance gelatin's mechanical strength and stability, fundamental studies on gelatin, specifically its curing process, mechanical stiffness, and chemical evolution during gelation, remain limited. This study uses ultrasonic testing and Fourier Transform Infrared Spectroscopy (FTIR) to examine gelatin's stiffness and molecular changes during gelation. Samples of 175 and 300 Porcine Skin Bloom Strength Gelatin at concentrations of 2% and 6% (w/v) were analyzed. Through transmission ultrasonic testing helped identify key transition points in gelation, with higher concentrations exhibiting delayed transitions. FTIR revealed that C-N bond formation peaks early while N-H bond deformation persists. A correlation emerged between sound speed and peak absorbance, suggesting that changes in molecular mobility may contribute to the observed sound speed behavior during periods of active bond formation. However, as gelation continues, fewer bonding components may be available, potentially decreasing molecular movement and contributing to the observed increase in sound speed. These findings provide insights into gelatin's mechanical and chemical evolution, offering a framework for improved control over its gelation kinetics. Swept-Frequency Acoustic Interferometry (SFAI) was performed at the end of the curing process to measure the sound speed, enabling the calculation of the bulk moduli of the gelatin samples. The combined use of ultrasonic and FTIR testing provides a non-destructive method for characterizing gelatin and other biomaterials. This approach advances understanding of gelatin curing behavior and supports the development of safer biomaterials with tailored mechanical properties for various applications such as tissue engineering and regenerative medicine.

Biomaterials↗

Current and future directions in network biology

Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseases across biological systems and scales. Although the field has been around for two decades, it remains nascent. It has witnessed rapid evolution, accompanied by emerging challenges. These stem from various factors, notably the growing complexity and volume of data together with the increased diversity of data types describing different tiers of biological organization. We discuss prevailing research directions in network biology, focusing on molecular/cellular networks but also on other biological network types such as biomedical knowledge graphs, patient similarity networks, brain networks, and social/contact networks relevant to disease spread. In more detail, we highlight areas of inference and comparison of biological networks, multimodal data integration and heterogeneous networks, higher-order network analysis, machine learning on networks, and network-based personalized medicine. Following the overview of recent breakthroughs across these five areas, we offer a perspective on future directions of network biology. Additionally, we discuss scientific communities, educational initiatives, and the importance of fostering diversity within the field. This article establishes a roadmap for an immediate and long-term vision for network biology.

59 BASIC BIOLOGICAL SCIENCES↗

Overview and Current Status of Neutron Imaging at Oak Ridge National Laboratory

Neutron imaging is a non-destructive technique used to study the internal structure and composition of a wide range of materials. At Oak Ridge National Laboratory (ORNL), there are two neutron imaging beamlines that provide complementary capabilities that serve a diverse community, from materials science and engineering to biomedical and plant sciences. This report provides an overview of the current ORNL imaging capabilities that support materials research for a broad user community.

Torres, James [ORNL] (ORCID:0000000289407610)↗

BioHackathon 2015: Semantics of data for life sciences and reproducible research

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.

97 MATHEMATICS AND COMPUTING↗