Open source vacuum oven design for low-temperature drying: Performance evaluation for recycled pet and biomass

Vacuum drying can dehydrate materials further than dry heat methods, while protecting sensitive materials from thermal degradation. Many industries have shifted to vacuum drying as cost-or time-saving measures. Small-scale vacuum drying, however, has been limited by the high costs of specialty scientific tools. To make vacuum drying more accessible, this study provides design and performance information for a small-scale open source vacuum oven, which can be fabricated from off-the-shelf and 3-D printed components. The oven is tested for drying speed and effectiveness on both waste plastic polyethylene terephthalate (PET) and a consortium of bacteria developed for bioprocessing of terephthalate wastes to assist in distributed recycling of PET for both additive manufacturing as well as potential food. Both materials can be damaged when exposed to high temperatures, making vacuum drying a desirable solution. The results showed that the open source vacuum oven was effective at drying both plastic and biomaterials, drying at a higher rate than a hot-air dryer for small samples or for low volumes of water. The system can be constructed for less than 20% of commercial vacuum dryer costs for several laboratory-scale applications, including dehydration of bio-organisms, drying plastic for distributed recycling and additive manufacturing, and chemical processing

Investigation of the Thomson scattering-ECE discrepancy in ICRF heated plasmas at Alcator C-Mod

This paper reports on new experiments at Alcator C-Mod that were performed in order to investigate the long-standing, unresolved discrepancy between Thomson scattering (TS) and electron cyclotron emission (ECE) measurements of electron temperature in high temperature tokamak plasmas. Ion cyclotron range of frequency (ICRF) heating is used to produce high temperature conditions where the type of TS-ECE discrepancy observed in the past at JET and TFTR should become observable. At Alcator C-Mod, plasmas with Te(0) up to 8 keV are obtained using ion cyclotron resonance heating (ICRH), ICRF mode conversion heating and a combination of the two heating methods in order to explore the hypothesis that the presence of ICRH-generated fast ions may be related to the discrepancy. In all high temperature cases, the TS and ECE measurements of electron temperature agree to within experimental uncertainties. We find no evidence for the type of discrepancy reported at JET and TFTR. These results show that the TS-ECE discrepancy does not depend on high temperatures alone and also that the presence of ICRH-generated fast ions is insufficient to cause the TS-ECE discrepancy.United States. Dept. of Energy (DE-FC02-99ER54512

Metal-Insulator Transitions in Degenerate Hubbard Models and Ax_xC60_{60}

Mott-Hubbard metal-insulator transitions in $N$-fold degenerate Hubbard models are studied within the Gutzwiller approximation. For any rational filling with $x$ (integer) electrons per site it is found that metal-insulator transition occurs at a critical correlation energy $U_c(N,x)=U_c(N,2N-x)=\gamma(N,x)|\bar{\epsilon}(N,x)|$, where $\bar{\epsilon}$ is the band energy per particle for the uncorrelated Fermi-liquid state and $\gamma(N,x)$ is a geometric factor which increases linearly with $x$. We propose that the alkali metal doped fullerides $A_xC_{60}$ can be described by a 3-fold degenerate Hubbard model. Using the current estimate of band width and correlation energy this implies that most of ${\rm A_xC_{60}}$, at integer $x$, are Mott-Hubbard insulators and ${\rm A_3C_{60}}$ is a strongly correlated metal.Comment: 10 pages, Revte

Fragment merging using a graph database samples different catalogue space than similarity search

Fragment merging is a promising approach to progressing fragments directly to on-scale potency: each designed compound incorporates the structural motifs of overlapping fragments in a way that ensures compounds recapitulate multiple high-quality interactions. Searching commercial catalogues provides one useful way to quickly and cheaply identify such merges and circumvents the challenge of synthetic accessibility, provided they can be readily identified. Here, we demonstrate that the Fragment Network, a graph database that provides a novel way to explore the chemical space surrounding fragment hits, is well-suited to this challenge. We use an iteration of the database containing >120 million catalogue compounds to find fragment merges for four crystallographic screening campaigns and contrast the results with a traditional fingerprint-based similarity search. The two approaches identify complementary sets of merges that recapitulate the observed fragment–protein interactions but lie in different regions of chemical space. We further show our methodology is an effective route to achieving on-scale potency by retrospective analyses for two different targets; in analyses of public COVID Moonshot and Mycobacterium tuberculosis EthR inhibitors, potential inhibitors with micromolar IC50 values were identified. This work demonstrates the use of the Fragment Network to increase the yield of fragment merges beyond that of a classical catalogue search

Derivation of High Spatial Resolution Albedo from UAV Digital Imagery:Application over the Greenland Ice Sheet

Measurements of albedo are a prerequisite for modeling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimeter resolution albedo products with accuracies of ?5% using consumer-grade digital camera and unmanned aerial vehicle (UAV) technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique could become increasingly common in field studies and used for a wide range of applications. These include the mapping of debris, dust, cryoconite and bioalbedo, and directly constraining surface energy balance models.publishersversionPeer reviewe

Rapid optimisation of fragments and hits to lead compounds from screening of crude reaction mixtures

Fragment based methods are now widely used to identify starting points in drug discovery and generation of tools for chemical biology. A significant challenge is optimization of these weak binding fragments to hit and lead compounds. We have developed an approach where individual reaction mixtures of analogues of hits can be evaluated without purification of the product. Here, we describe experiments to optimise the processes and then assess such mixtures in the high throughput crystal structure determination facility, XChem. Diffraction data for crystals of the proteins Hsp90 and PDHK2 soaked individually with 83 crude reaction mixtures are analysed manually or with the automated XChem procedures. The results of structural analysis are compared with binding measurements from other biophysical techniques. This approach can transform early hit to lead optimisation and the lessons learnt from this study provide a protocol that can be used by the community

e-Fungi: a data resource for comparative analysis of fungal genomes.

BACKGROUND: The number of sequenced fungal genomes is ever increasing, with about 200 genomes already fully sequenced or in progress. Only a small percentage of those genomes have been comprehensively studied, for example using techniques from functional genomics. Comparative analysis has proven to be a useful strategy for enhancing our understanding of evolutionary biology and of the less well understood genomes. However, the data required for these analyses tends to be distributed in various heterogeneous data sources, making systematic comparative studies a cumbersome task. Furthermore, comparative analyses benefit from close integration of derived data sets that cluster genes or organisms in a way that eases the expression of requests that clarify points of similarity or difference between species. DESCRIPTION: To support systematic comparative analyses of fungal genomes we have developed the e-Fungi database, which integrates a variety of data for more than 30 fungal genomes. Publicly available genome data, functional annotations, and pathway information has been integrated into a single data repository and complemented with results of comparative analyses, such as MCL and OrthoMCL cluster analysis, and predictions of signaling proteins and the sub-cellular localisation of proteins. To access the data, a library of analysis tasks is available through a web interface. The analysis tasks are motivated by recent comparative genomics studies, and aim to support the study of evolutionary biology as well as community efforts for improving the annotation of genomes. Web services for each query are also available, enabling the tasks to be incorporated into workflows. CONCLUSION: The e-Fungi database provides fungal biologists with a resource for comparative studies of a large range of fungal genomes. Its analysis library supports the comparative study of genome data, functional annotation, and results of large scale analyses over all the genomes stored in the database. The database is accessible at http://www.e-fungi.org.uk, as is the WSDL for the web services.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies. Reliable and accurate quantification of the proteins present in a cell or tissue remains a major challenge for post-genome scientists. Proteins are the primary functional molecules in biological systems and knowledge of their abundance and dynamics is an important prerequisite to a complete understanding of natural physiological processes, or dysfunction in disease. Accordingly, much effort has been spent in the development of reliable, accurate and sensitive techniques to quantify the cellular proteome, the complement of proteins expressed at a given time under defined conditions (1). Moreover, the ability to model a biological system and thus characterize it in kinetic terms, requires that protein concentrations be defined in absolute numbers (2, 3). Given the high demand for accurate quantitative proteome data sets, there has been a continual drive to develop methodology to accomplish this, typically using mass spectrometry (MS) as the analytical platform. Many recent studies have highlighted the capabilities of MS to provide good coverage of the proteome at high sensitivity often using yeast as a demonstrator system (4⇓⇓⇓⇓⇓–10), suggesting that quantitative proteomics has now “come of age” (1). However, given that MS is not inherently quantitative, most of the approaches produce relative quantitation and do not typically measure the absolute concentrations of individual molecular species by direct means. For the yeast proteome, epitope tagging studies using green fluorescent protein or tandem affinity purification tags provides an alternative to MS. Here, collections of modified strains are generated that incorporate a detectable, and therefore quantifiable, tag that supports immunoblotting or fluorescence techniques (11, 12). However, such strategies for copies per cell (cpc) quantification rely on genetic manipulation of the host organism and hence do not quantify endogenous, unmodified protein. Similarly, the tagging can alter protein levels - in some instances hindering protein expression completely (11). Even so, epitope tagging methods have been of value to the community, yielding high coverage quantitative data sets for the majority of the yeast proteome (11, 12). MS-based methods do not rely on such nonendogenous labels, and can reach genome-wide levels of coverage. Accurate estimation of absolute concentrations i.e. protein copy number per cell, also usually necessitates the use of (one or more) external or internal standards from which to derive absolute abundance (4). Examples include a comprehensive quantification of the Leptospira interrogans proteome that used a 19 protein subset quantified using selected reaction monitoring (SRM)1 to calibrate their label-free data (8, 13). It is worth noting that epitope tagging methods, although also absolute, rely on a very limited set of standards for the quantitative western blots and necessitate incorporation of a suitable immunogenic tag (11). Other recent, innovative approaches exploiting total ion signal and internal scaling to estimate protein cellular abundance (10, 14), avoid the use of internal standards, though they do rely on targeted proteomic data to validate their approach. The use of targeted SRM strategies to derive proteomic calibration standards highlights its advantages in comparison to label-free in terms of accuracy, precision, dynamic range and limit of detection and has gained currency for its reliability and sensitivity (3, 15⇓–17). Indeed, SRM is often referred to as the “gold standard proteomic quantification method,” being particularly well-suited when the proteins to be quantified are known, when appropriate surrogate peptides for protein quantification can be selected a priori, and matched with stable isotope-labeled (SIL) standards (18⇓–20). In combination with SIL peptide standards that can be generated through a variety of means (3, 15), SRM can be used to quantify low copy number proteins, reaching down to ∼50 cpc in yeast (5). However, although SRM methodology has been used extensively for S. cerevisiae protein quantification by us and others (19, 21, 22), it has not been used for large protein cohorts because of the requirement to generate the large numbers of attendant SIL peptide standards; the largest published data set is only for a few tens of proteins. It remains a challenge therefore to robustly quantify an entire eukaryotic proteome in absolute terms by direct means using targeted MS and this is the focus of our present study, the Census Of the Proteome of Yeast (CoPY). We present here direct and absolute quantification of nearly 2000 endogenous proteins from S. cerevisiae grown in steady state in a chemostat culture, using the SRM-based QconCAT approach. Although arguably not quantification of the entire proteome, this represents an accurate and rigorous collection of direct yeast protein quantifications, providing a gold-standard data set of endogenous protein levels for future reference and comparative studies. The highly reproducible SIL-SRM MS data, with robust CVs typically less than 20%, is compared with other extant data sets that were obtained via alternative analytical strategies. We also report a matched high quality transcriptome from the same cells using RNA-seq, which supports additional calculations including a refined estimate of the total protein content in yeast cells, and a simple linear model of translation explaining 70% of the variance between RNA and protein levels in yeast chemostat cultures. These analyses confirm the validity of our data and approach, which we believe represents a state-of-the-art absolute quantification compendium of a significant proportion of a model eukaryotic proteome

Possible climate-related signals in high-resolution topography of lobate debris aprons in Tempe Terra, Mars

Lobate debris aprons are common features in the midlatitudes of Mars that are assumed to be the result of the flow of ice-rich material. We produce high-resolution digital elevation models of two of these features in the Tempe Terra region of Mars using HiRISE stereo images. We identify two main topographic features of different wavelength using a power spectrum analysis approach. Short wavelength features, between approximately 10 and 20 m in length, correspond to a polygonal surface texture present throughout our study area. Long wavelength features, between approximately 700 and 1800 m in length, correspond to broad ridges that are up to 20 m in amplitude. We interpret both topographic signals to be the likely result of climate change affecting the debris contribution and/or the flow regime of the lobate debris aprons. The apparent surface age of about 300 Ma could be evidence of an astronomical forcing mechanism recorded in these lobate debris aprons at this time in Mars' history. Citation: Grindrod, P. M., and S. A. Fawcett (2011), Possible climate-related signals in high-resolution topography of lobate debris aprons in Tempe Terra, Mars, Geophys. Res. Lett., 38, L19201, doi: 10.1029/2011GL049295