Photoemission core level binding energies from multiple sized nanoparticles on the same support: TiO₂(110)/Au

A novel method of measuring the core level binding energies of multiple sized nanoparticles on the same substrate is demonstrated using the early stage of Au nanoparticle growth on reduced r-TiO2(110). This method employed in situ scanning tunneling microscopy (STM) and microfocused X-ray photoemission spectroscopy. An STM tip-shadowing method was used to synthesize patterned areas of Au nanoparticles on the substrate with different coverages and sizes. Patterns were identified and imaged using a UV photoelectron emission microscope. The Au 4f core level binding energies of the nanoparticles were investigated as a function of Au nanoparticle coverage and size. A combination of initial and final state effects modifies the binding energies of the Au 4f core levels as the nanoparticle size changes. When single Au atoms and Au3 clusters are present, the Au 4f7/2 binding energy, 84.42 eV, is similar to that observed at a high coverage (1.8 monolayer equivalent), resulting from a cancellation of initial and final state effects. As the coverage is increased, there is a decrease in binding energy, which then increases at a higher coverage to 84.39 eV. These results are consistent with a Volmer-Weber nucleation-growth model of Au nanoparticles at oxygen vacancies, resulting in electron transfer to the nanoparticles

Serial interferon-gamma release assays during treatment of active tuberculosis in young adults

<p>Abstract</p> <p>Background</p> <p>The role of interferon-γ release assay (IGRA) in monitoring responses to anti-tuberculosis (TB) treatment is not clear. We evaluated the results of the QuantiFERON-TB Gold In-tube (QFT-GIT) assay over time during the anti-TB treatment of adults with no underlying disease.</p> <p>Methods</p> <p>We enrolled soldiers who were newly diagnosed with active TB and admitted to the central referral military hospital in South Korea between May 1, 2008 and September 30, 2009. For each participant, we preformed QFT-GIT assay before treatment (baseline) and at 1, 3, and 6 months after initiating anti-TB medication.</p> <p>Results</p> <p>Of 67 eligible patients, 59 (88.1%) completed the study protocol. All participants were males who were human immunodeficiency virus (HIV)-negative and had no chronic diseases. Their median age was 21 years (range, 20-48). Initially, 57 (96.6%) patients had positive QFT-GIT results, and 53 (89.8%), 42 (71.2%), and 39 (66.1%) had positive QFT-GIT results at 1, 3, and 6 months, respectively. The IFN-γ level at baseline was 5.31 ± 5.34 IU/ml, and the levels at 1, 3, and 6 months were 3.95 ± 4.30, 1.82 ± 2.14, and 1.50 ± 2.12 IU/ml, respectively. All patients had clinical and radiologic improvements after treatment and were cured. A lower IFN-γ level, C-reactive protein ≥ 3 mg/dl, and the presence of fever (≥ 38.3°C) at diagnosis were associated with negative reversion of the QFT-GIT assay.</p> <p>Conclusion</p> <p>Although the IFN-γ level measured by QFT-GIT assay decreased after successful anti-TB treatment in most participants, less than half of them exhibited QFT-GIT reversion. Thus, the reversion to negativity of the QFT-GIT assay may not be a good surrogate for treatment response in otherwise healthy young patients with TB.</p

Investigation of Polyurea-Crosslinked Silica Aerogels as a Neuronal Scaffold: A Pilot Study

BACKGROUND: Polymer crosslinked aerogels are an attractive class of materials for future implant applications particularly as a biomaterial for the support of nerve growth. The low density and nano-porous structure of this material combined with large surface area, high mechanical strength, and tunable surface properties, make aerogels materials with a high potential in aiding repair of injuries of the peripheral nervous system. however, the interaction of neurons with aerogels remains to be investigated. METHODOLOGY: In this work the attachment and growth of neurons on clear polyurea crosslinked silica aerogels (PCSA) coated with: poly-L-lysine, basement membrane extract (BME), and laminin1 was investigated by means of optical and scanning electron microscopy. After comparing the attachment and growth capability of neurons on these different coatings, laminin1 and BME were chosen for nerve cell attachment and growth on PCSA surfaces. The behavior of neurons on treated petri dish surfaces was used as the control and behavior of neurons on treated PCSA discs was compared against it. CONCLUSIONS/SIGNIFICANCE: This study demonstrates that: 1) untreated PCSA surfaces do not support attachment and growth of nerve cells, 2) a thin application of laminin1 layer onto the PCSA discs adhered well to the PCSA surface while also supporting growth and differentiation of neurons as evidenced by the number of processes extended and b3-tubulin expression, 3) three dimensional porous structure of PCSA remains intact after fixing protocols necessary for preservation of biological samples and 4) laminin1 coating proved to be the most effective method for attaching neurons to the desired regions on PCSA discs. This work provides the basis for potential use of PCSA as a biomaterial scaffold for neural regeneration

A Man-Made ATP-Binding Protein Evolved Independent of Nature Causes Abnormal Growth in Bacterial Cells

Recent advances in de novo protein evolution have made it possible to create synthetic proteins from unbiased libraries that fold into stable tertiary structures with predefined functions. However, it is not known whether such proteins will be functional when expressed inside living cells or how a host organism would respond to an encounter with a non-biological protein. Here, we examine the physiology and morphology of Escherichia coli cells engineered to express a synthetic ATP-binding protein evolved entirely from non-biological origins. We show that this man-made protein disrupts the normal energetic balance of the cell by altering the levels of intracellular ATP. This disruption cascades into a series of events that ultimately limit reproductive competency by inhibiting cell division. We now describe a detailed investigation into the synthetic biology of this man-made protein in a living bacterial organism, and the effect that this protein has on normal cell physiology

The inference of gray whale (Eschrichtius robustus) historical population attributes from whole-genome sequences

Commercial whaling caused extensive demographic declines in many great whale species, including gray whales that were extirpated from the Atlantic Ocean and dramatically reduced in the Pacific Ocean. The Eastern Pacific gray whale has recovered since the 1982 ban on commercial whaling, but the Western Pacific gray whale-once considered possibly extinct-consists of only about 200 individuals and is considered critically endangered by some international authorities. Herein, we use whole-genome sequencing to investigate the demographic history of gray whales from the Pacific and use environmental niche modelling to make predictions about future gene flow.Our sequencing efforts and habitat niche modelling indicate that: i) western gray whale effective population sizes have declined since the last glacial maximum; ii) contemporary gray whale genomes, both eastern and western, harbor less autosomal nucleotide diversity than most other marine mammals and megafauna; iii) the extent of inbreeding, as measured by autozygosity, is greater in the Western Pacific than in the Eastern Pacific populations; and iv) future climate change is expected to open new migratory routes for gray whales.Our results indicate that gray whale genomes contain low nucleotide diversity and have been subject to both historical and recent inbreeding. Population sizes over the last million years likely peaked about 25,000 years before present and have declined since then. Our niche modelling suggests that novel migratory routes may develop within the next century and if so this could help retain overall genetic diversity, which is essential for adaption and successful recovery in light of global environmental change and past exploitation

Large-Scale Bi-Level Strain Design Approaches and Mixed-Integer Programming Solution Techniques

The use of computational models in metabolic engineering has been increasing as more genome-scale metabolic models and computational approaches become available. Various computational approaches have been developed to predict how genetic perturbations affect metabolic behavior at a systems level, and have been successfully used to engineer microbial strains with improved primary or secondary metabolite production. However, identification of metabolic engineering strategies involving a large number of perturbations is currently limited by computational resources due to the size of genome-scale models and the combinatorial nature of the problem. In this study, we present (i) two new bi-level strain design approaches using mixed-integer programming (MIP), and (ii) general solution techniques that improve the performance of MIP-based bi-level approaches. The first approach (SimOptStrain) simultaneously considers gene deletion and non-native reaction addition, while the second approach (BiMOMA) uses minimization of metabolic adjustment to predict knockout behavior in a MIP-based bi-level problem for the first time. Our general MIP solution techniques significantly reduced the CPU times needed to find optimal strategies when applied to an existing strain design approach (OptORF) (e.g., from ∼10 days to ∼5 minutes for metabolic engineering strategies with 4 gene deletions), and identified strategies for producing compounds where previous studies could not (e.g., malate and serine). Additionally, we found novel strategies using SimOptStrain with higher predicted production levels (for succinate and glycerol) than could have been found using an existing approach that considers network additions and deletions in sequential steps rather than simultaneously. Finally, using BiMOMA we found novel strategies involving large numbers of modifications (for pyruvate and glutamate), which sequential search and genetic algorithms were unable to find. The approaches and solution techniques developed here will facilitate the strain design process and extend the scope of its application to metabolic engineering