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The study described here examined the effects of cavitation nuclei characteristics on histotripsy. High-speed optical imaging was used to compare bubble cloud behavior and ablation capacity for histotripsy generated from intrinsic and artificial cavitation nuclei (gas-filled microbubbles, fluid-filled nanocones). Results showed a significant decrease in the cavitation threshold for microbubbles and nanocones compared with intrinsic-nuclei controls, with predictable and well-defined bubble clouds generated in all cases. Red blood cell experiments showed complete ablations for intrinsic and nanocone phantoms, but only partial ablation in microbubble phantoms. Results also revealed a lower rate of ablation in artificial-nuclei phantoms because of reduced bubble expansion (and corresponding decreases in stress and strain). Overall, this study demonstrates the potential of using artificial nuclei to reduce the histotripsy cavitation threshold while highlighting differences in the bubble cloud behavior and ablation capacity that need to be considered in the future development of these approaches. (E-mail: cwedsall@vt.edu) (C) 2020 The Author(s). Published by Elsevier Inc. on behalf of World Federation for Ultrasound in Medicine & Biology.

New therapies to treat pancreatic cancer are direly needed. However, efficacious interventions lack a strong preclinical model that can recapitulate patients’ anatomy and physiology. Likewise, the availability of human primary malignant tissue for ex vivo studies is limited. These are significant limitations in the biomedical device field. We have developed RAG2/IL2RG deficient pigs using CRISPR/Cas9 as a large animal model with the novel application of cancer xenograft studies of human pancreatic adenocarcinoma. In this proof-of-concept study, these pigs were successfully generated using on-demand genetic modifications in embryos, circumventing the need for breeding and husbandry. Human Panc01 cells injected subcutaneously into the ears of RAG2/IL2RG deficient pigs demonstrated 100% engraftment with growth rates similar to those typically observed in mouse models. Histopathology revealed no immune cell infiltration and tumor morphology was highly consistent with the mouse models. The electrical properties and response to irreversible electroporation of the tumor tissue were found to be similar to excised human pancreatic cancer tumors. The ample tumor tissue produced enabled improved accuracy and modeling of the electrical properties of tumor tissue. Together, this suggests that this model will be useful and capable of bridging the gap of translating therapies from the bench to clinical application.

The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability. Designing efficient sensors for smart tires for autonomous vehicles remains a challenge. Here, the authors present a tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis.

Coal is one of the most abundant and economic sources for global energy production. However, the burning of coal is widely recognized as a significant contributor to atmospheric particulate matter linked to deleterious respiratory impacts. Recently, we have discovered that burning coal generates large quantities of otherwise rare Magnéli phase titanium suboxides from TiO2 minerals naturally present in coal. These nanoscale Magnéli phases are biologically active without photostimulation and toxic to airway epithelial cells in vitro and to zebrafish in vivo. Here, we sought to determine the clinical and physiological impact of pulmonary exposure to Magnéli phases using mice as mammalian model organisms. Mice were exposed to the most frequently found Magnéli phases, Ti6O11, at 100 parts per million (ppm) via intratracheal administration. Local and systemic titanium concentrations, lung pathology, and changes in airway mechanics were assessed. Additional mechanistic studies were conducted with primary bone marrow derived macrophages. Our results indicate that macrophages are the cell type most impacted by exposure to these nanoscale particles. Following phagocytosis, macrophages fail to properly eliminate Magnéli phases, resulting in increased oxidative stress, mitochondrial dysfunction, and ultimately apoptosis. In the lungs, these nanoparticles become concentrated in macrophages, resulting in a feedback loop of reactive oxygen species production, cell death, and the initiation of gene expression profiles consistent with lung injury within 6 weeks of exposure. Chronic exposure and accumulation of Magnéli phases ultimately results in significantly reduced lung function impacting airway resistance, compliance, and elastance. Together, these studies demonstrate that Magnéli phases are toxic in the mammalian airway and are likely a significant nanoscale environmental pollutant, especially in geographic regions where coal combustion is a major contributor to atmospheric par

The jejunum is the segment of the small intestine responsible for several metabolism and biotransformation functions. In this report, we have cultured rat jejunum explants in vitro and integrated them with hepatocyte cultures. We have also investigated the changes in jejunum function at different locations since spatial variations in intestinal functions have been reported previously. We divided the length of the rat jejunum into three distinct regions of approximately 9 cm each. We defined the regions as proximal (adjacent to the duodenum), medial, and distal (adjacent to the ileum). Spatiotemporal variations in functions were observed between these regions within the jejunum. Alkaline phosphatase activity (a marker of enterocyte function), decreased twofold between the proximal and distal regions at 4 hr. Lysozyme activity (a marker of Paneth cell function) increased from the proximal to the distal jejunum by 40% at 24 hr. Mucin-covered areas, a marker of goblet cell function, increased by twofold between the proximal and distal segments of the jejunum at 24 hr. When hepatocytes were integrated with proximal jejunum explants, statistically higher urea (similar to 2.4-fold) and mucin (57%) production were observed in the jejunum explants. The integrated intestine-liver cultures can be used as a platform for future investigations.

Background and Objectives: Many dementia caregivers provide care for numerous years. Exhibiting grit, or commitment and persistence in the face of adversity, may bolster their ability to manage caregiving challenges. We explored grit in relationship to memory and behavior problems and response to stressors among women engaged in long-term dementia care. Research Design and Methods: Informed by a life course perspective, and guided by stress-process theory, we interviewed 10 women with a spouse or parent initially diagnosed with mild cognitive impairment 4 times over 10 years. Using Charmaz’s analysis methods and grit as a sensitizing concept, we employed an unfolding analytic strategy involving (a) thematic analysis to identify expressions of grit in response to caregiving stressors across interviews and (b) case-by-case comparisons to assess associations of grit with the use of care strategies across caregivers over time. Results: Dementia caregivers experienced unrelenting and changing psychosocial and physical challenges. Over time, most women exhibited a sustained commitment to the relationship through the ways in which they protected the identity of the person with dementia, modified their expectations for emotional intimacy, and managed their financial affairs. They persevered as their roles and relationships fluctuated, often finding purpose and relief through employment and leisure pursuits. As care intensified, women who took charge and consciously made decisions in the best interest of the care recipient and themselves minimized stress. Discussion and Implications: While some caregivers exhibited grit from the outset, all showed enhanced perseverance and commitment to the ways they managed memory-related changes over time. Developing confidence in their ability to manage and provide care helped the caregivers respond to stressors with purpose and sustain their roles and responsibilities. Enhancing grit in long-term dementia caregivers may result in better

Liver homeostasis requires the presence of both parenchymal and non-parenchymal cells (NPCs). However, systems biology studies of the liver have primarily focused on hepatocytes. Using an organotypic three-dimensional (3D) hepatic culture, we report the first transcriptomic study of liver sinusoidal endothelial cells (LSECs) and Kupffer cells (KCs) cultured with hepatocytes. Through computational pathway and interaction network analyses, we demonstrate that hepatocytes, LSECs and KCs have distinct expression profiles and functional characteristics. Our results show that LSECs in the presence of KCs exhibit decreased expression of focal adhesion kinase (FAK) signaling, a pathway linked to LSEC dedifferentiation. We report the novel result that peroxisome proliferator-activated receptor alpha (PPAR alpha) is transcribed in LSECs. The expression of downstream processes corroborates active PPAR alpha signaling in LSECs. We uncover transcriptional evidence in LSECs for a feedback mechanism between PPAR alpha and farnesoid X-activated receptor (FXR) that maintains bile acid homeostasis; previously, this feedback was known occur only in HepG2 cells. We demonstrate that KCs in 3D liver models display expression patterns consistent with an anti-inflammatory phenotype when compared to monocultures. These results highlight the distinct roles of LSECs and KCs in maintaining liver function and emphasize the need for additional mechanistic studies of NPCs in addition to hepatocytes in liver-mimetic microenvironments.

Oxygen at the surface of nanosized platinum has a direct effect on catalytic activity of oxidation−reduction chemical reactions. However, the abundance and speciation of oxygen remain uncertain for platinum with different particle size and shape characteristics, which has hindered the development of fundamental property−activity relationships. We have characterized two commercially available platinum nanocatalysts known as Pt black and Pt nanopowder to evaluate the effects of synthesis and heating conditions on the physical and surface chemical properties, as well as on catalytic activity. Characterization using complementary electron microscopy, X-ray scattering, and spectroscopic methods showed that the larger average crystallite size of Pt nanopowder (23 nm) compared to Pt black (11 nm) corresponds with a 70% greater surface oxygen concentration. Heating the samples in air resulted in an increase in surface oxygen concentration for both nanocatalysts. Surface oxygen associated with platinum is in the form of chemisorbed oxygen, and no significant amounts of chemically bonded platinum oxide were found for any of the samples. The increase in surface oxygen abundance during heating depends on the initial size and surface oxygen content. Hydrogen peroxide decomposition rate measurements showed that larger particle size and higher surface chemisorbed oxygen correlate with enhanced catalytic activity. These results are particularly important for future studies that aim to relate the properties of platinum, or other metal nanocatalysts, with surface reactivity.

Suspended aqueous aerosol droplets (< 50 mu m) are microreactors for many important atmospheric reactions. In droplets and other aquatic environments, pH is arguably the key parameter dictating chemical and biological processes. The nature of the droplet air/water interface has the potential to significantly alter droplet pH relative to bulk water. Historically, it has been challenging to measure the pH of individual droplets because of their inaccessibility to conventional pH probes. In this study, we scanned droplets containing 4-mercaptobenzoic acid-functionalized gold nanoparticle pH nanoprobes by 2D and 3D laser confocal Raman microscopy. Using surface-enhanced Raman scattering, we acquired the pH distribution inside approximately 20-mu m-diameter phosphate-buffered aerosol droplets and found that the pH in the core of a droplet is higher than that of bulk solution by up to 3.6 pH units. This finding suggests the accumulation of protons at the air/water interface and is consistent with recent thermodynamic model results. The existence of this pH shift was corroborated by the observation that a catalytic reaction that occurs only under basic conditions (i.e., dimerization of 4-aminothiophenol to produce dimercaptoazobenzene) occurs within the high pH core of a droplet, but not in bulk solution. Our nanoparticle probe enables pH quantification through the cross-section of an aerosol droplet, revealing a spatial gradient that has implications for acid-base-catalyzed atmospheric chemistry.

Thermoelectric generators (TEGs) are rapidly becoming the mainstream technology for converting thermal energy into electrical energy. The rise in the continuous deployment of TEGs is related to advancements in materials, figure of merit, and methods for module manufacturing. However, rapid optimization techniques for TEGs have not kept pace with these advancements, which presents a challenge regarding tailoring the device architecture for varying operating conditions. Here, we address this challenge by providing artificial neural network (ANN) models that can predict TEG performance on demand. Out of the several ANN models considered for TEGs, the most efficient one consists of two hidden layers with six neurons in each layer. The model predicted TEG power with an accuracy of ±0.1 W, and TEG efficiency with an accuracy of ±0.2%. The trained ANN model required only 26.4 ms per data point for predicting TEG performance against the 6.0 minutes needed for the traditional numerical simulations.

The need and desire to understand the environment, especially the quality of one’s local water and air, has continued to expand with the emergence of the digital age. The bottleneck in understanding the environment has switched from being able to store all of the data collected to collecting enough data on a broad range of contaminants of environmental concern. Nanomaterial enabled sensors represent a suite of technologies developed over the last 15 years for the highly specific and sensitive detection of environmental contaminants. With the promise of facile, low cost, field-deployable technology, the ability to quantitatively understand nature in a systematic way will soon be a reality. In this review, we first introduce nanosensor design before exploring the application of nanosensors for the detection of three classes of environmental contaminants: pesticides, heavy metals, and pathogens.

Coal, as one of the most economic and abundant energy sources, remains the leading fuel for producing electricity worldwide. Yet, burning coal produces more global warming CO2 relative to all other fossil fuels, and it is a major contributor to atmospheric particulate matter known to have a deleterious respiratory and cardiovascular impact in humans, especially in China and India. Here we have discovered that burning coal also produces large quantities of otherwise rare Magneli phases (Ti; x; O2x–1 with 4 ≤ x ≤ 9) from TiO2 minerals naturally present in coal. This provides a new tracer for tracking solid-state emissions worldwide from industrial coal-burning. In its first toxicity testing, we have also shown that nanoscale Magneli phases have potential toxicity pathways that are not photoactive like TiO2 phases, but instead seem to be biologically active without photostimulation. In the future, these phases should be thoroughly tested for their toxicity in the human lung. Solid-state emissions from coal burning remain an environmental concern. Here, the authors have found that TiO2 minerals present in coal are converted into titanium suboxides during burning, and initial biotoxicity screening suggests that further testing is needed to look into human lung consequences.

Analysis of signaling pathways and their crosstalk is a cornerstone of systems biology. Thousands of papers have been published on these topics. Surprisingly, there is no database that carefully and explicitly documents crosstalk between specific pairs of signaling pathways. We have developed XTALKDB (http://www.xtalkdb.org) to fill this very important gap. XTALKDB contains curated information for 650 pairs of pathways from over 1600 publications. In addition, the database reports the molecular components (e.g. proteins, hormones, microRNAs) that mediate crosstalk between a pair of pathways and the species and tissue in which the crosstalk was observed. The XTALKDB website provides an easy-to- use interface for scientists to browse crosstalk information by querying one or more pathways or molecules of interest.

Textured ceramic compositions having improved piezoelectric characteristics as compared with their random counterparts are provided. Methods of making the compositions and devices using them are also included. More particularly, compositions comprising textured ceramic Na0.5Bi0.5TiO3—BaTiO3(NBT-BT) materials synthesized from high aspect ratio NBT seeds exhibit improved characteristics, including an increased longitudinal piezoelectric constant (d33) and magnetoelectric coupling coefficient over randomly oriented NBT-BT. Additionally provided are compositions comprising of nanostructured Na0.5Bi0.5TiO3—BaTiO3 ferroelectric whiskers having a high aspect ratio. Nanostructured whiskers can be used to improve the piezoelectric properties of the bulk ceramics. The inventive materials are useful in microelectronic devices, with some finding particular application as multilayer actuators and transducers.

In this work, we present a modified seed-mediated synthetic strategy for the growth of silver nanoprisms with low shape polydispersity, narrow size distribution and tailored plasmonic absorbance. During the seed nucleation step, consensus sequence tetratricopeptide repeat (CTPR) proteins are utilized as potent stabilizers to facilitate the formation of planar-twinned Ag seeds. Ag nanoprisms were produced in high yield in a growth solution containing ascorbic acid and CTPR-stabilized Ag seeds. From the time-course UV-Vis and transmission electron microscopy (TEM) studies, we postulate that the growth mechanism is the combination of facet selective lateral growth and thermodynamically driven Ostwald ripening. The resultant Ag nanotriangles (NTs) exhibit excellent surface enhanced Raman spectroscopy (SERS) performance. The enhancement factor (EF) measured for the 4-mercapto benzoic acid (4-MBA) reporter is estimated to be 3.37 × 105 in solution and 2.8 × 106 for the SERS substrate.

Production of gold nanoparticle (AuNP) surface-enhanced Raman spectroscopy (SERS) nanoprobes requires replicable aggregation to produce multimers with high signal intensity. Herein, we illustrate a novel, yet simple, approach to produce SERS nanoprobes through control of co-solvent composition. AuNP multimers were produced by mixing AuNP monomers in water : ethanol co-solvent for variable periods of time. By varying the water : ethanol ratio and the amount of 4-mercaptobenzoic acid (4-MBA) present, the aggregation rate can be systematically controlled. Thiolated poly(ethylene glycol) was then added to halt the aggregation process and provide steric stability. This approach was used to produce pH nanoprobes with excellent colloidal stability in high ionic strength environments and in complex samples. The pH probe exhibits broad pH sensitivity over the range 6–11 and we calculate that a single AuNP dimer in a 35 fL volume is sufficient to generate a detectable SERS signal. As a proof-of-concept, the probes were used to detect the intracellular pH of human prostate cancer cells (PC-3). The internalized probes exhibit a strong 4-MBA signal without any interfering bands from either the cells or the culture media and produce exceptionally detailed pH maps. pH maps obtained from 19 xy surface scans and 14 yz depth scans exhibit highly consistent intracellular pH in the range of 5 to 7, thus indicating the greater reliability and reproducibility of our pH probes compared with other probes previously reported in the literature. Our water : ethanol co-solvent production process is fast, simple, and efficient. Adjustment of solvent composition may become a powerful way to produce SERS tags or nanoprobes in the future.

Magnetite nanoparticles are redox active constituents of subsurface and corrosive environments. In this study, we characterized the aggregation and sedimentation behavior of well characterized magnetite nanoparticle clusters using dynamic light scattering (DLS), UV-vis-NIR spectroscopy, and small angle X-ray scattering (SAXS). Both unfunctionalized (NaOH-magnetite) and tetramethylammonium hydroxide (TMAOH-magnetite) surface functionalized nanoparticle clusters were employed. TMAOH-magnetite has a slightly smaller primary nanoparticle radius as determined by TEM (4 ± 0.7 nm vs. 5 ± 0.8 for NaOH-magnetite) and a smaller initial DLS determined cluster radius (<30 nm vs. 100–200 nm for NaOH-magnetite). Interestingly, in spite of its smaller initial nanoparticle cluster size, TMAOH-magnetite undergoes sedimentation more rapidly than NaOH-magnetite. This behavior is consistent with the more rapid aggregation of the smaller TMAOH-magnetite clusters as well as their lower fractal dimension, as determined by SAXS. This study illustrates that both nanoparticle cluster size and fractal dimension should be carefully considered when considering the environmental transport and fate of highly aggregated nanoparticles.

Perfluorosulfonate ionomers have been shown to demonstrate a profound affinity for large cationic complexes, and the exchange of these ions may be used to provide insight regarding Nafion® morphology by contrasting molecular size with existing morphological models. The trimetallic complex, [{(bpy)2Ru(dpp)}2RhBr2]5+, is readily absorbed by ion-exchange into Na+-form Nafion® membranes under ambient conditions. The dimensions of three different isomers of the trimetallic complex were found to be: 23.6 Å × 13.3 Å × 10.8 Å, 18.9 Å × 18.0 Å × 13.7 Å, and 23.1 Å × 12.0 Å × 11.4 Å, yielding an average molecular volume of 1.2 × 103 Å3. At equilibrium, the partition coefficient for the ion-exchange of the trimetallic complex into Nafion® from a DMF solution was found to be 5.7 × 103. Furthermore, the total cationic charge of the exchanged trimetallic complexes was found to counterbalance 86 ± 2% of the anionic SO3− sites in Nafion®. The characteristic dimensions of morphological models for the ionic domains in Nafion® were found to be comparable to the molecular dimensions of the large mixed-metal complexes. Surprisingly, SAXS analysis indicated that the complexes absorbed into the ionic domains of Nafion® without significantly changing the ionomer morphology. Given the profound affinity for absorption of these large cationic molecules, a more open-channel model for the morphology of perfluorosulfonate ionomers is more reasonable, in agreement with recent experimental findings. In contrast to smaller monometallic complexes, the time dependent uptake of the large trimetallic cations was found to be biexponential. This behavior is attributed to a fast initial ion-exchange process on the surface of the membrane, accompanied by a slower transport-limited ion-exchange for exchange sites that are buried further in the ionomer matrix.

The cell cycle is composed of bistable molecular switches that govern the transitions between gap phases (G1 and G2) and the phases in which DNA is replicated (S) and partitioned between daughter cells (M). Many molecular details of the budding yeast G1–S transition (Start) have been elucidated in recent years, especially with regard to its switch-like behavior due to positive feedback mechanisms. These results led us to reevaluate and expand a previous mathematical model of the yeast cell cycle. The new model incorporates Whi3 inhibition of Cln3 activity, Whi5 inhibition of SBF and MBF transcription factors, and feedback inhibition of Whi5 by G1–S cyclins. We tested the accuracy of the model by simulating various mutants not described in the literature. We then constructed these novel mutant strains and compared their observed phenotypes to the model’s simulations. The experimental results reported here led to further changes of the model, which will be fully described in a later article. Our study demonstrates the advantages of combining model design, simulation, and testing in a coordinated effort to better understand a complex biological network.

The potential for water pollution outbreaks requires the development of rapid, yet simple detection methods for water quality monitoring. Plasmonic nanostructures such as gold (AuNPs) and silver (AgNPs) nanoparticles are compelling candidates for the development of highly sensitive biosensors due to their unique localized surface plasmon resonances (LSPRs). The LSPR of AuNPs and AgNPs lies in the visible and infrared light range and is sensitive to the composition, size, shape, surrounding medium, and aggregation state of these NPs. This plasmonic behavior provides the basis for fabrication of colorimetric sensors for environmental analyses. Furthermore, the LSPR also enhances the electromagnetic field near the NP surface, which provides the basis for surface-enhanced Raman spectroscopy (SERS) based detection. Organic or inorganic pollutants and pathogens can be detected and differentiated based upon the finger-print spectra that arise when they enter SERS-active hot spots. In this tutorial review, we summarize progress made towards environmental analysis based on LSPR-based colorimetric and SERS detection. The problems and challenges that have hindered the development of LSPR-based nanosensors for real-world environmental pollutant monitoring are extensively discussed.

Nanocellulose is of research interest due to its extraordinary optical, thermal, and mechanical properties. The incorporation of guest nanoparticles into nanocellulose substrates enables production of novel nanocomposites with a broad range of applications. In this study, gold nanoparticle/bacterial cellulose (AuNP/BC) nanocomposites were prepared and evaluated for their applicability as surface-enhanced Raman scattering (SERS) substrates. The nanocomposites were prepared by citrate mediated in situ reduction of Au3+ in the presence of a BC hydrogel at 303 K. Both the size and morphology of the AuNPs were functions of the HAuCl4 and citrate concentrations. At high HAuCl4 concentrations, Au nanoplates form within the nanocomposites and are responsible for high SERS enhancements. At lower HAuCl4 concentrations, uniform nanospheres form and the SERS enhancement is dependent on the nanosphere size. The time-resolved increase in the SERS signal was probed as a function of drying time with SERS ‘hot-spots’ primarily forming in the final minutes of nanocomposite drying. The application of the AuNP/BC nanocomposites for detection of the SERS active dyes MGITC and R6G as well as the environmental contaminant atrazine is illustrated as is its use under low and high pH conditions. The results indicate the broad applicability of this nanocomposite for analyte detection.

High-energy-density, green, safe batteries are highly desirable for meeting the rapidly growing needs of portable electronics. The incomplete oxidation of sugars mediated by one or a few enzymes in enzymatic fuel cells suffers from low energy densities and slow reaction rates. Here we show that nearly 24 electrons per glucose unit of maltodextrin can be produced through a synthetic catabolic pathway that comprises 13 enzymes in an air-breathing enzymatic fuel cell. This enzymatic fuel cell is based on non-immobilized enzymes that exhibit a maximum power output of 0.8 mW cm(-2) and a maximum current density of 6 mA cm(-2), which are far higher than the values for systems based on immobilized enzymes. Enzymatic fuel cells containing a 15% (wt/v) maltodextrin solution have an energy-storage density of 596 Ah kg(-1), which is one order of magnitude higher than that of lithium-ion batteries. Sugar-powered biobatteries could serve as next-generation green power sources, particularly for portable electronics.

This paper introduces a new synthesis procedure to form erbium-doped ceria nanoparticles (EDC NPs) that can act as an optical medium for both up-conversion and down-conversion in the same time. This synthesis process results qualitatively in a high concentration of Ce3+ ions required to obtain high fluorescence efficiency in the down-conversion process. Simultaneously, the synthesized nanoparticles contain the molecular energy levels of erbium that are required for up-conversion. Therefore, the synthesized EDC NPs can emit visible light when excited with either UV or IR photons. This opens new opportunities for applications where emission of light via both up- and down-conversions from a single nanomaterial is desired such as solar cells and bio-imaging.

Background Fungi are the second most abundant type of human pathogens. Invasive fungal pathogens are leading causes of life-threatening infections in clinical settings. Toxicity to the host and drug-resistance are two major deleterious issues associated with existing antifungal agents. Increasing a host’s tolerance and/or immunity to fungal pathogens has potential to alleviate these problems. A host’s tolerance may be improved by modulating the immune system such that it responds more rapidly and robustly in all facets, ranging from the recognition of pathogens to their clearance from the host. An understanding of biological processes and genes that are perturbed during attempted fungal exposure, colonization, and/or invasion will help guide the identification of endogenous immunomodulators and/or small molecules that activate host-immune responses such as specialized adjuvants. Results In this study, we present computational techniques and approaches using publicly available transcriptional data sets, to predict immunomodulators that may act against multiple fungal pathogens. Our study analyzed data sets derived from host cells exposed to five fungal pathogens, namely, Alternaria alternata, Aspergillus fumigatus, Candida albicans, Pneumocystis jirovecii, and Stachybotrys chartarum. We observed statistically significant associations between host responses to A. fumigatus and C. albicans. Our analysis identified biological processes that were consistently perturbed by these two pathogens. These processes contained both immune response-inducing genes such as MALT1, SERPINE1, ICAM1, and IL8, and immune response-repressing genes such as DUSP8, DUSP6, and SPRED2. We hypothesize that these genes belong to a pool of common immunomodulators that can potentially be activated or suppressed (agonized or antagonized) in order to render the host more tolerant to infections caused by A. fumigatus and C. albicans. Conclusions Our computational approaches and methodologies describe

Fifty years of genetic and molecular experiments have revealed a wealth of molecular interactions involved in the control of cell division. In light of the complexity of this control system, mathematical modeling has proved useful in analyzing biochemical hypotheses that can be tested experimentally. Stochastic modeling has been especially useful in understanding the intrinsic variability of cell cycle events, but stochastic modeling has been hampered by a lack of reliable data on the absolute numbers of mRNA molecules per cell for cell cycle control genes. To fill this void, we used fluorescence in situ hybridization (FISH) to collect single molecule mRNA data for 16 cell cycle regulators in budding yeast, Saccharomyces cerevisiae. From statistical distributions of single-cell mRNA counts, we are able to extract the periodicity, timing, and magnitude of transcript abundance during the cell cycle. We used these parameters to improve a stochastic model of the cell cycle to better reflect the variability of molecular and phenotypic data on cell cycle progression in budding yeast.

In this study, the electrical properties of four different stages of mouse ovarian surface epithelial (MOSE) cells were investigated using contactless dielectrophoresis (cDEP). This study expands the work from our previous report describing for the first time the crossover frequency and cell specific membrane capacitance of different stages of cancer cells that are derived from the same cell line. The specific membrane capacitance increased as the stage of malignancy advanced from 15.39 +/- 1.54 mF m(-2) for a non-malignant benign stage to 26.42 +/- 1.22 mF m(-2) for the most aggressive stage. These differences could be the result of morphological variations due to changes in the cytoskeleton structure, specifically the decrease of the level of actin filaments in the cytoskeleton structure of the transformed MOSE cells. Studying the electrical properties of MOSE cells provides important information as a first step to develop cancer-treatment techniques which could partially reverse the cytoskeleton disorganization of malignant cells to a morphology more similar to that of benign cells. (C) 2013 American Institute of Physics. [http://dx.doi.org/10.1063/1.4788921] Actual pdf downloaded from NCBI.

Background Microarray experiments can simultaneously identify thousands of genes that show significant perturbation in expression between two experimental conditions. Response networks, computed through the integration of gene interaction networks with expression perturbation data, may themselves contain tens of thousands of interactions. Gene set enrichment has become standard for summarizing the results of these analyses in terms functionally coherent collections of genes such as biological processes. However, even these methods can yield hundreds of enriched functions that may overlap considerably. Results We describe a new technique called Markov chain Monte Carlo Biological Process Networks (MCMC-BPN) capable of reporting a highly non-redundant set of links between processes that describe the molecular interactions that are perturbed under a specific biological context. Each link in the BPN represents the perturbed interactions that serve as the interfaces between the two processes connected by the link. We apply MCMC-BPN to publicly available liver-related datasets to demonstrate that the networks formed by the most probable inter-process links reported by MCMC-BPN show high relevance to each biological condition. We show that MCMC-BPN’s ability to discern the few key links from in a very large solution space by comparing results from two other methods for detecting inter-process links. Conclusions MCMC-BPN is successful in using few inter-process links to explain as many of the perturbed gene-gene interactions as possible. Thereby, BPNs summarize the important biological trends within a response network by reporting a digestible number of inter-process links that can be explored in greater detail.

The recent rapid progress in the field of spintronics involves extensive measurements of carrier and spin relaxation dynamics in III-V semiconductors. In addition, as the switching rates in devices are pushed to higher frequencies, it is important to understand carrier dynamic phenomena in semiconductors on femtosecond time-scales. In this work, we employed time and spin resolved differential transmission measurements; to probe carrier and spin relaxation times in several InAsP ternary alloys. Our results demonstrate the sensitivity of the spin and carrier dynamics in this material system to the excitation wavelengths, the As concentrations, and temperature. (C) 2013 AIP Publishing LLC.

Decreasing lignin content of plant biomass by genetic engineering is believed to mitigate biomass recalcitrance and improve saccharification efficiency of plant biomass. In this study, we compared two different pretreatment methods (i.e., dilute acid and cellulose solvent) on transgenic plant biomass samples having different lignin contents and investigated biomass saccharification efficiency. Without pretreatment, no correlation was observed between lignin contents of plant biomass and saccharification efficiency. After dilute acid pretreatment, a strong negative correlation between lignin content of plant samples and overall glucose release was observed, wherein the highest overall enzymatic glucan digestibility was 70% for the low-lignin sample. After cellulose solvent- and organic solvent-based lignocellulose fractionation pretreatment, there was no strong correlation between lignin contents and high saccharification efficiencies obtained (i.e., 80-90%). These results suggest that the importance of decreasing lignin content in plant biomass to saccharification was largely dependent on pretreatment choice and conditions.

Background Despite advancement of our knowledge, cholera remains a public health concern. During March-April 2010, a large cholera outbreak afflicted the eastern part of Kolkata, India. The quantification of importance of socio-environmental factors in the risk of cholera, and the calculation of the risk is fundamental for deploying vaccination strategies. Here we investigate socio-environmental characteristics between high and low risk areas as well as the potential impact of vaccination on the spatial occurrence of the disease. Methods and Findings The study area comprised three wards of Kolkata Municipal Corporation. A mass cholera vaccination campaign was conducted in mid-2006 as the part of a clinical trial. Cholera cases and data of the trial to identify high risk areas for cholera were analyzed. We used a generalized additive model (GAM) to detect risk areas, and to evaluate the importance of socio-environmental characteristics between high and low risk areas. During the one-year pre-vaccination and two-year post-vaccination periods, 95 and 183 cholera cases were detected in 111,882 and 121,827 study participants, respectively. The GAM model predicts that high risk areas in the west part of the study area where the outbreak largely occurred. High risk areas in both periods were characterized by poor people, use of unsafe water, and proximity to canals used as the main drainage for rain and waste water. Cholera vaccine uptake was significantly lower in the high risk areas compared to low risk areas. Conclusion The study shows that even a parsimonious model like GAM predicts high risk areas where cholera outbreaks largely occurred. This is useful for indicating where interventions would be effective in controlling the disease risk. Data showed that vaccination decreased the risk of infection. Overall, the GAM-based risk map is useful for policymakers, especially those from countries where cholera remains to be endemic with periodic outbreaks.

Phase change materials (PCMs) capable of storing a large amount of heat upon transitioning from the solid-to-liquid state have been widely used in the electronics and construction industries for mitigating temperature development. Here, we show that they are also beneficial for reducing the peak tissue temperature during electroporation-based therapies. A numerical model is developed of irreversible electroporation (IRE) performed with hollow needle electrodes filled with a PCM. Results indicate that this electrode design can be utilized to achieve large ablation volumes while reducing the probability for thermal damage.

Ovarian cancer is the leading cause of death from gynecological malignancies in women. The primary challenge is the detection of the cancer at an early stage, since this drastically increases the survival rate. In this study we investigated the dielectrophoretic responses of progressive stages of mouse ovarian surface epithelial (MOSE) cells, as well as mouse fibroblast and macrophage cell lines, utilizing contactless dielectrophoresis (cDEP). cDEP is a relatively new cell manipulation technique that has addressed some of the challenges of conventional dielectrophoretic methods. To evaluate our microfluidic device performance, we computationally studied the effects of altering various geometrical parameters, such as the size and arrangement of insulating structures, on dielectrophoretic and drag forces. We found that the trapping voltage of MOSE cells increases as the cells progress from a non-tumorigenic, benign cell to a tumorigenic, malignant phenotype. Additionally, all MOSE cells display unique behavior compared to fibroblasts and macrophages, representing normal and inflammatory cells found in the peritoneal fluid. Based on these findings, we predict that cDEP can be utilized for isolation of ovarian cancer cells from peritoneal fluid as an early cancer detection tool. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3699973] Actual pdf downloaded from NCBI.

The ferroelectric domain and local structures of Na0.5Bi0.5TiO3-xat.%BaTiO3 (NBT-x%BT) crystals for x = 0, 4.5, and 5.5 have been investigated by transmission electron microscopy. The results show that the size of polar nano-regions was refined with increasing xat. %BT. The tetragonal phase volume fraction, as identified by in-phase octahedral tilting, was found to be increased with BT. The findings indicate that the large electric field induced strains in morphotropic phase boundary compositions of NBT-x%BT originate not only from polarization rotation but also polarization extension. (C) 2012 American Institute of Physics. [doi: 10.1063/1.3673832]

Background The normal functioning of a living cell is characterized by complex interaction networks involving many different types of molecules. Associations detected between diseases and perturbations in well-defined pathways within such interaction networks have the potential to illuminate the molecular mechanisms underlying disease progression and response to treatment. Results In this paper, we present a computational method that compares expression profiles of genes in cancer samples to samples from normal tissues in order to detect perturbations of pre-defined pathways in the cancer. In contrast to many previous methods, our scoring function approach explicitly takes into account the interactions between the gene products in a pathway. Moreover, we compute the sub-pathway that has the highest score, as opposed to merely computing the score for the entire pathway. We use a permutation test to assess the statistical significance of the most perturbed sub-pathway. We apply our method to 20 pathways in the Netpath database and to the Global Cancer Map of gene expression in 18 cancers. We demonstrate that our method yields more sensitive results than alternatives that do not consider interactions or measure the perturbation of a pathway as a whole. We perform a sensitivity analysis to show that our approach is robust to modest changes in the input data. Our method confirms numerous well-known connections between pathways and cancers. Conclusions Our results indicate that integrating differential gene expression with the interaction structure in a pathway is a powerful approach for detecting links between a cancer and the pathways perturbed in it. Our results also suggest that even well-studied pathways may be perturbed only partially in any given cancer. Further analysis of cancer-specific sub-pathways may shed new light on the similarities and differences between cancers.

Background Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account. Results Our approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i) determine which functions are enriched in a given network, ii) given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii) given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms. Conclusions We presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are implemented in C++ and are f

The hydrogen economy presents an appealing energy future but its implementation must solve numerous problems ranging from low-cost sustainable production, high-density storage, costly infrastructure, to eliminating safety concern. The use of renewable carbohydrate as a high-density hydrogen carrier and energy source for hydrogen production is possible due to emerging cell-free synthetic biology technology—cell-free synthetic pathway biotransformation (SyPaB). Assembly of numerous enzymes and co-enzymes in vitro can create complicated set of biological reactions or pathways that microorganisms or catalysts cannot complete, for example, C6H10O5 (aq) + 7 H2O (l) à 12 H2 (g) + 6 CO2 (g) (PLoS One 2007, 2:e456). Thanks to 100% selectivity of enzymes, modest reaction conditions, and high-purity of generated hydrogen, carbohydrate is a promising hydrogen carrier for end users. Gravimetric density of carbohydrate is 14.8 H2 mass% if water can be recycled from proton exchange membrane fuel cells or 8.33% H2 mass% without water recycling. Renewable carbohydrate can be isolated from plant biomass or would be produced from a combination of solar electricity/hydrogen and carbon dioxide fixation mediated by high-efficiency artificial photosynthesis mediated by SyPaB. The construction of this carbon-neutral carbohydrate economy would address numerous sustainability challenges, such as electricity and hydrogen storage, CO2 fixation and long-term storage, water conservation, transportation fuel production, plus feed and food production.

Background Energy efficiency analysis for different biomass-utilization scenarios would help make more informed decisions for developing future biomass-based transportation systems. Diverse biofuels produced from biomass include cellulosic ethanol, butanol, fatty acid ethyl esters, methane, hydrogen, methanol, dimethyether, Fischer-Tropsch diesel, and bioelectricity; the respective powertrain systems include internal combustion engine (ICE) vehicles, hybrid electric vehicles based on gasoline or diesel ICEs, hydrogen fuel cell vehicles, sugar fuel cell vehicles (SFCV), and battery electric vehicles (BEV). Methodology/Principal Findings We conducted a simple, straightforward, and transparent biomass-to-wheel (BTW) analysis including three separate conversion elements -- biomass-to-fuel conversion, fuel transport and distribution, and respective powertrain systems. BTW efficiency is a ratio of the kinetic energy of an automobile's wheels to the chemical energy of delivered biomass just before entering biorefineries. Up to 13 scenarios were analyzed and compared to a base line case – corn ethanol/ICE. This analysis suggests that BEV, whose electricity is generated from stationary fuel cells, and SFCV, based on a hydrogen fuel cell vehicle with an on-board sugar-to-hydrogen bioreformer, would have the highest BTW efficiencies, nearly four times that of ethanol-ICE. Significance In the long term, a small fraction of the annual US biomass (e.g., 7.1%, or 700 million tons of biomass) would be sufficient to meet 100% of light-duty passenger vehicle fuel needs (i.e., 150 billion gallons of gasoline/ethanol per year), through up to four-fold enhanced BTW efficiencies by using SFCV or BEV. SFCV would have several advantages over BEV: much higher energy storage densities, faster refilling rates, better safety, and less environmental burdens.

The liver plays a vital role in glucose homeostasis, the synthesis of bile acids and the detoxification of foreign substances. Liver culture systems are widely used to test adverse effects of drugs and environmental toxicants. The two most prevalent liver culture systems are hepatocyte monolayers (HMs) and collagen sandwiches (CS). Despite their wide use, comprehensive transcriptional programs and interaction networks in these culture systems have not been systematically investigated. We integrated an existing temporal transcriptional dataset for HM and CS cultures of rat hepatocytes with a functional interaction network of rat genes. We aimed to exploit the functional interactions to identify statistically significant linkages between perturbed biological processes. To this end, we developed a novel approach to compute Contextual Biological Process Linkage Networks (CBPLNs). CBPLNs revealed numerous meaningful connections between different biological processes and gene sets, which we were successful in interpreting within the context of liver metabolism. Multiple phenomena captured by CBPLNs at the process level such as regulation, downstream effects, and feedback loops have well described counterparts at the gene and protein level. CBPLNs reveal high-level linkages between pathways and processes, making the identification of important biological trends more tractable than through interactions between individual genes and molecules alone. Our approach may provide a new route to explore, analyze, and understand cellular responses to internal and external cues within the context of the intricate networks of molecular interactions that control cellular behavior.

Developing in vitro engineered hepatic tissues that exhibit stable phenotype is a major challenge in the field of hepatic tissue engineering. However, the rapid dedifferentiation of hepatic parenchymal (hepatocytes) and non-parenchymal (liver sinusoidal endothelial, LSEC) cell types when removed from their natural environment in vivo remains a major obstacle. The primary goal of this study was to demonstrate that hepatic cells cultured in layered architectures could preserve or potentially enhance liver-specific behavior of both cell types. Primary rat hepatocytes and rat LSECs (rLSECs) were cultured in a layered three-dimensional (3D) configuration. The cell layers were separated by a chitosan-hyaluronic acid polyelectrolyte multilayer (PEM), which served to mimic the Space of Disse. Hepatocytes and rLSECs exhibited several key phenotypic characteristics over a twelve day culture period. Immunostaining for the sinusoidal endothelial 1 antibody (SE-1) demonstrated that rLSECs cultured in the 3D hepatic model maintained this unique feature over twelve days. In contrast, rLSECs cultured in monolayers lost their phenotype within three days. The unique stratified structure of the 3D culture resulted in enhanced heterotypic cell-cell interactions, which led to improvements in hepatocyte functions. Albumin production increased three to six fold in the rLSEC-PEM-Hepatocyte cultures. Only rLSEC-PEM-Hepatocyte cultures exhibited increasing CYP1A1/2 and CYP3A activity. Well-defined bile canaliculi were observed only in the rLSEC-PEM-Hepatocyte cultures. Together, these data suggest that rLSEC-PEM-Hepatocyte cultures are highly suitable models to monitor the transformation of toxins in the liver and their transport out of this organ. In summary, these results indicate that the layered rLSEC-PEM-hepatocyte model, which recapitulates key features of hepatic sinusoids, is a potentially powerful medium for obtaining comprehensive knowledge on liver metabolism, detoxification and s

We investigate the effect of nickel nanoparticle size on thermal transport in multilayer nanocomposites consisting of alternating layers of nickel nanoparticles and yttria stabilized zirconia (YSZ) spacer layers that are grown with pulsed laser deposition. Using time-domain thermoreflectance, we measure thermal conductivities of k=1.8, 2.4, 2.3, and 3.0 W m(-1) K(-1) for nanocomposites with nickel nanoparticle diameters of 7, 21, 24, and 38 nm, respectively, and k=2.5 W m(-1) K(-1) for a single 80 nm thick layer of YSZ. We use an effective medium theory to estimate the lower limits for interface thermal conductance G between the nickel nanoparticles and the YSZ matrix (G>170 MW m(-2) K(-1)), and nickel nanoparticle thermal conductivity.

Background Cell-free protein synthesis (CFPS) is a rapid and high throughput technology for obtaining proteins from their genes. The primary energy source ATP is regenerated from the secondary energy source through substrate phosphorylation in CFPS. Results Distinct from common secondary energy sources (e.g., phosphoenolpyruvate - PEP, glucose-6-phosphate), maltodextrin was used for energizing CFPS through substrate phosphorylation and the glycolytic pathway because (i) maltodextrin can be slowly catabolized by maltodextrin phosphorylase for continuous ATP regeneration, (ii) maltodextrin phosphorylation can recycle one phosphate per reaction for glucose-1-phosphate generation, and (iii) the maltodextrin chain-shortening reaction can produce one ATP per glucose equivalent more than glucose can. Three model proteins, esterase 2 from Alicyclobacillus acidocaldarius, green fluorescent protein, and xylose reductase from Neurospora crassa were synthesized for demonstration. Conclusion Slowly-metabolized maltodextrin as a low-cost secondary energy compound for CFPS produced higher levels of proteins than PEP, glucose, and glucose-6-phospahte. The enhancement of protein synthesis was largely attributed to better-controlled phosphate levels (recycling of inorganic phosphate) and a more homeostatic reaction environment.

We present the results on SiCN-(La,Sr)MnO3 (LSMO) composites correlating the observed large piezoresistance behavior with the microstructural features and defect chemistry. Scanning electron microscopy characterization revealed the presence of self-assembled periodic microvalleys in the microstructure with width of 1-5 mu m and depth of 600-1000 nm. The microvalleys act as stress concentration points providing change in volume with applied stress. High resolution transmission electron microscopy measurements conducted on composites showed that LSMO grains consist of SiCN phase but no inclusions were observed.

Few nanometer large (<2 nm) inclusions of DO(3)-phase structure have been identified in the A2 matrix of highly magnetostrictive Fe-19% Ga alloys by high-resolution transmission electron microscopy (HRTEM). In addition, we have found that these nanostructures include a high density of {100} line defects with a Burgers vector of a(bcc)/2 < 100 >. This dispersion of DO(3)-phase nanostructures formed within the main A2 matrix and the lifting of their coherency by defects are consistent with a recent theory for the structure and properties of magnetostrictive Fe-Ga and Fe-Al alloys.

We report damage threshold measurements of novel absorbers comprised of either liquid-cooled silicon carbide or vitreous carbon foams. The measurements demonstrate damage thresholds up to 1.6 x 104 W/cm(2) at an incident circular spot size of 2 mm with an absorbance of 96% at 1.064 mu m. We present a summary of the damage threshold as a function of the water flow velocity and the absorbance measurements. We also present a qualitative description of a damage mechanism based on a two-phase heat transfer between the foam and the flowing water. (c) 2007 Optical Society of America.