pinecone/core-2020-05-10-deduplication huggingface dataset:
Selective Knockdowns in Maize by Sequence-Specific Protein Aggregation

Protein aggregation is determined by 5-15 amino acids peptides of the target protein sequence, so-called aggregation-prone regions (APRs) that specifically self-associate to form β-structured inclusions. The presence of APRs in a target protein can be predicted by a dedicated algorithm, such as TANGO. Synthetic aggregation-prone proteins are designed by expressing specific APRs fused to a fluorescent carrier for stability and visualization. Previously, the stable expression of these proteins in Zea mays (maize) has been demonstrated to induce aggregation of target proteins with specific localization, such as the starch-degrading enzyme α-glucan water dikinase, giving rise to plants displaying knockdown phenotypes. Here, we describe how to design synthetic aggregation-prone proteins to harness the sequence specificity of APRs to generate aggregation-associated phenotypes in a targeted manner and in different subcellular compartments. This method points toward the application of induced targeted aggregation as a useful tool to knock down protein functions in maize and to generate crops with improved traits.status: publishe
Towards a tropical Hodge bundle

The moduli space $M_g^{trop}$ of tropical curves of genus $g$ is a
generalized cone complex that parametrizes metric vertex-weighted graphs of
genus $g$. For each such graph $\Gamma$, the associated canonical linear system
$\vert K_\Gamma\vert$ has the structure of a polyhedral complex. In this
article we propose a tropical analogue of the Hodge bundle on $M_g^{trop}$ and
study its basic combinatorial properties. Our construction is illustrated with
explicit computations and examples.Comment: 19 pages, 10 figure
Using RT qPCR for quantifying Mycobacteria marinum from in vitro and in vivo samples

Mycobacterium marinum, the causative agent of fish tuberculosis, is rarely a human pathogen causing a chronic skin infection. It is now wildely used as a model system in animal models, especially in zebra fish model, to study the pathology of tuberculosis and as a means of screening new anti-tuberculosis agent. To facilitate such research, quantifying the viable count of M. marinum bacteria is a crucial step. The main approach used currently is still by counting the number of colony forming units (cfu), a method that has been in place for almost 100 years. Though this method well established, understood and relatively easy to perform, it is time-consuming and labor-intensive. The result can be compromised by failure to grow effectively and the relationship between count and actual numbers is confused by clumping of the bacteria where a single colony is made from multiple organisms. More importantly, this method is not able to detect live but not cultivable bacteria, and there is increasing evidence that mycobacteria readily enter a "dormant" state which confounds the relationship between bacterial number in the host and the number detected in a cfu assay. DNA based PCR methods detect both living and dead organisms but here we describe a method, which utilizes species specific Taq-Man assay and RT-qPCR technology for quantifying the viable M. marinum bacterial load by detecting 16S ribosomal RNA (16S rRNA).Postprin
Detecting phenotypically resistant Mycobacterium tuberculosis using wavelength modulated Raman spectroscopy

Raman spectroscopy is a non-destructive and label-free technique. Wavelength modulated Raman (WMR) spectroscopy was applied to investigate Mycobacterium tuberculosis cell state, lipid rich (LR) and lipid poor (LP). Compared to LP cells, LR cells can be up to 40 times more resistant to key antibiotic regimens. Using this methodology single lipid rich (LR) from lipid poor (LP) bacteria can be differentiated with both high sensitivity and specificity. It can also be used to investigate experimentally infected frozen tissue sections where both cell types can be differentiated. This methodology could be utilized to study the phenotype of mycobacterial cells in other tissues.Postprin
Enhanced methodologies for detecting phenotypic resistance in mycobacteria

Lipid droplets found in algae and other microscopic organisms have become of interest to many researchers partially because they carry the capacity to produce bio-oil for the mass market. They are of importance in biology and clinical practice because their presence can be a phenotypic marker of an altered metabolism, including reversible resistance to antibiotics, prompting intense research.A useful stain for detecting lipid bodies in the lab is Nile red. It is a dye that exhibits solvatochromism; its absorption band varies in spectral position, shape and intensity with the nature of its solvent environment, it will fluoresce intensely red in polar environment and blue shift with the changing polarity of its solvent. This makes it ideal for the detection of lipid bodies within Mycobacterium spp. This is because mycobacterial lipid bodies' primary constituents are nonpolar lipids such as triacylglycerols but bacterial cell membranes are primarily polar lipid species. In this chapter we describe an optimal method for using Nile red to distinguish lipid containing (Lipid rich or LR cells) from those without lipid bodies (Lipid Poor or LP). As part of the process we have optimized a method for separating LP and LR cells that does not require the use of an ultracentrifuge or complex separation media. We believe that these methods will facilitate further research in these enigmatic, transient and important cell states.Postprin
Figures of light in the early history of relativity (1905-1914)

Albert Einstein's bold assertion of the form-invariance of the equation of a spherical light wave with respect to inertial frames of reference (Einstein 1905) became, in the space of six years, the preferred foundation of his theory of relativity. Early on, however, Einstein's universal light-sphere invariance was challenged on epistemological grounds by Henri Poincaré, who promoted an alternative demonstration of the foundations of relativity theory based on the notion of a light ellipsoid. A third figure of light, Hermann Minkowski's lightcone also provided a new means of envisioning the foundations of relativity. Drawing in part on archival sources, this paper shows how an informal, international group of physicists, mathematicians, and engineers, including Einstein, Paul Langevin, Poincaré, Hermann Minkowski, Ebenezer Cunningham, Harry Bateman, Otto Berg, Max Planck, Max Laue, A. A. Robb, and Ludwig Silberstein, employed figures of light during the formative years of relativity theory in their discovery of the salient features of the relativistic worldview
Implementing a transcription factor interaction prediction system using the genometric query language

Novel technologies and growing interest have resulted in a large increase in the amount of data available for genomics and transcriptomics studies, both in terms of volume and contents. Biology is relying more and more on computational methods to process, investigate, and extract knowledge from this huge amount of data. In this work, we present the TICA web server (available at http://www.gmql.eu/tica/), a fast and compact tool developed to support data-driven knowledge discovery in the realm of transcription factor interaction prediction. TICA leverages both the GenoMetric Query Language, a novel query tool (based on the Apache Hadoop and Spark technologies) specialized in the integration and management of heterogeneous, large genomic datasets, and a statistical method for robust detection of co-locations across interval-based data, in order to infer physically interacting transcription factors. Notably, TICA allows investigators to upload and analyze their own ChIP-seq experiments datasets, comparing them both against ENCODE data or between themselves, achieving computation time which increases linearly with respect to dataset size and density. Using ENCODE data from three well-studied cell lines as reference, we show that TICA predictions are supported by existing biological knowledge, making the web server a reliable and efficient tool for interaction screening and data-driven hypothesis generation
Gene regulatory network inference: An Introductory Survey

Gene regulatory networks are powerful abstractions of biological systems. Since the advent of high-throughput measurement technologies in biology in the late 90s, reconstructing the structure of such networks has been a central computational problem in systems biology. While the problem is certainly not solved in its entirety, considerable progress has been made in the last two decades, with mature tools now available. This chapter aims to provide an introduction to the basic concepts underpinning network inference tools, attempting a categorisation which highlights commonalities and relative strengths. While the chapter is meant to be self-contained, the material presented should provide a useful background to the later, more specialised chapters of this book
Unsupervised gene network inference with decision trees and Random forests

In this chapter, we introduce the reader to a popular family of machine learning algorithms, called decision trees. We then review several approaches based on decision trees that have been developed for the inference of gene regulatory networks (GRNs). Decision trees have indeed several nice properties that make them well-suited for tackling this problem: they are able to detect multivariate interacting effects between variables, are non-parametric, have good scalability, and have very few parameters. In particular, we describe in detail the GENIE3 algorithm, a state-of-the-art method for GRN inference
Tree-based learning of regulatory network topologies and dynamics with Jump3

Inference of gene regulatory networks (GRNs) from time series data is a well established field in computational systems biology. Most approaches can be broadly divided in two families: model-based and model-free methods. These two families are highly complementary: model-based methods seek to identify a formal mathematical model of the system. They thus have transparent and interpretable semantics, but rely on strong assumptions and are rather computationally intensive. On the other hand, model-free methods have typically good scalability. Since they are not based on any parametric model, they are more flexible that model-based methods, but also less interpretable.
In this chapter, we describe Jump3, a hybrid approach that bridges the gap between model-free and model-based methods. Jump3 uses a formal stochastic differential equation to model each gene expression, but reconstructs the GRN topology with a non-parametric method based on decision trees. We briefly review the theoretical and algorithmic foundations of Jump3, and then proceed to provide a step by step tutorial of the associated software usage
Mitochondrial proteomics : analysis of a whole mitochondrial extract with two-dimensional electrophoresis.

Mitochondria are complex organelles, and their proteomics analysis requires a combination of techniques. The emphasis in this chapter is made first on mitochondria preparation from cultured mammalian cells, then on the separation of the mitochondrial proteins with two-dimensional electrophoresis (2DE), showing some adjustment over the classical techniques to improve resolution of the mitochondrial proteins. This covers both the protein solubilization, the electrophoretic part per se, and the protein detection on the gels, which makes the interface with the protein identification part relying on mass spectrometry
Experimental Control and Characterization of Autophagy in Drosophila

Insects such as the fruit fly Drosophila melanogaster, which fundamentally reorganize their body plan during metamorphosis, make extensive use of autophagy for their normal development and physiology. In the fruit fly, the hepatic/adipose organ known as the fat body accumulates nutrient stores during the larval feeding stage. Upon entering metamorphosis, as well as in response to starvation, these nutrients are mobilized through a massive induction of autophagy, providing support to other tissues and organs during periods of nutrient deprivation. High levels of autophagy are also observed in larval tissues destined for elimination, such as the salivary glands and larval gut. Drosophila is emerging as an important system for studying the functions and regulation of autophagy in an in vivo setting. In this chapter we describe reagents and methods for monitoring autophagy in Drosophila, focusing on the larval fat body. We also describe methods for experimentally activating and inhibiting autophagy in this system and discuss the potential for genetic analysis in Drosophila to identify novel genes involved in autophagy
Transdermal drug delivery devices: Skin perturbation systems

???The original publication is available at www.springerlink.com???. Copyright Springer.  DOI: 10.1007/978-1-59745-210-6_5Human skin serves a protective function by imposing physicochemical limitations to the type of permeant that can traverse the barrier. For a drug to be delivered passively via the skin it needs to have a suitable lipophilicity and a molecular weight <500 Da. The number of commercially available products based on transdermal or dermal delivery has been limited by these requirements. In recent years various passive and active strategies have emerged to optimize delivery. The passive approach entails the optimization of formulation or drug carrying vehicle to increase skin permeability. However passive methods do not greatly improve the permeation of drugs with molecular weights >500 Da. In contrast active methods, normally involving physical or mechanical methods of enhancing delivery have been shown to be generally superior. The delivery of drugs of differing lipophilicity and molecular weight including proteins, peptides, and oligonucletides has been shown to be improved by active methods such as iontophoresis, electroporation, mechanical perturbation, and other energy-related techniques such as ultrasound and needless injection. This chapter details one practical example of an active skin abrasion device to demonstrate the success of such active methods. The enhanced in vitro permeation of acyclovir through human epidermal membrane using a rotating brush abrasion device was compared to acyclovir delivery using iontophoresis. It was found that application of brush treatment for 10 seconds at a pressure of 300Nm-2 was comparable to 10 minutes of iontophoresis. The observed enhancement of permeability observed using the rotating brush was as a result of disruption of the cells of the stratum corneum causing a reduction of the barrier function of the skin.  However, for these novel delivery methods to succeed and compete with those already on the market, the prime issues that require consideration include device design and safety, efficacy, ease of handling, and cost-effectiveness. This chapter provides a detailed review of the next generation of active delivery technologies
Trees from Trees : Construction of Phylogenetic Supertrees Using Clann

Supertree methods combine multiple phylogenetic trees to produce the overall best "supertree." They can be used to combine phylogenetic information from datasets only partially overlapping and from disparate sources (like molecular and morphological data), or to break down problems thought to be computationally intractable. Some of the longest standing phylogenetic conundrums are now being brought to light using supertree approaches. We describe the most widely used supertree methods implemented in the software program "clann" and provide a step by step tutorial for investigating phylogenetic information and reconstructing the best supertree. Clann is freely available for Windows, Mac and Unix/Linux operating systems under the GNU public licence at (http://bioinf.nuim.ie/software/clann).publishersversio
Solubilization of Proteins in 2DE: An Outline.

International audienceProtein solubilization for two-dimensional electrophoresis (2DE) has to break molecular interactions to separate the biological contents of the material of interest into isolated and intact polypeptides. This must be carried out in conditions compatible with the first dimension of 2DE, namely isoelectric focusing. In addition, the extraction process must enable easy removal of any nonprotein component interfering with the isoelectric focusing. The constraints brought in this process by the peculiar features of isoelectric focusing are discussed, as well as their consequences in terms of possible solutions and limits for the solubilization process
Silver Staining of Proteins in 2DE Gels.

International audienceSilver staining detects proteins after electrophoretic separation on polyacrylamide gels. Its main positive features are its excellent sensitivity (in the low nanogram range) and the use of very simple and cheap equipment and chemicals. The sequential phases of silver staining are protein fixation, then sensitization, then silver impregnation, and finally image development. Several variants of silver staining are described here, which can be completed in a time range from 2 h to 1 day after the end of the electrophoretic separation. Once completed, the stain is stable for several weeks
Defining the role of salt bridges in protein stability

Although the energetic balance of forces stabilizing proteins has been established qualitatively over the last decades, quantification of the energetic contribution of particular interactions still poses serious problems. The reasons are the strong cooperativity and the interdependence of noncovalent interactions. Salt bridges are a typical example. One expects that ionizable side chains frequently form ion pairs in innumerable crystal structures. Since electrostatic attraction between opposite charges is strong per se, salt bridges can intuitively be regarded as an important factor stabilizing the native structure. Is that really so? In this chapter we critically reassess the available methods to delineate the role of electrostatic interactions and salt bridges to protein stability, and discuss the progress and the obstacles in this endeavor. The basic problem is that formation of salt bridges depends on the ionization properties of the participating groups, which is significantly influenced by the protein environment. Furthermore, salt bridges experience thermal fluctuations, continuously break and re-form, and their lifespan in solution is governed by the flexibility of the protein. Finally, electrostatic interactions are long-range and might be significant in the unfolded state, thus seriously influencing the energetic profile. Elimination of salt bridges by protonation/deprotonation at extreme pH or by mutation provides only rough energetic estimates, since there is no way to account for the nonadditive response of the protein moiety. From what we know so far, the strength of electrostatic interactions is strongly context-dependent, yet it is unlikely that salt bridges are dominant factors governing protein stability. Nevertheless, proteins from thermophiles and hyperthermophiles exhibit more, and frequently networked, salt bridges than proteins from the mesophilic counterparts. Increasing the thermal (not the thermodynamic) stability of proteins by optimization of charge–charge interactions is a good example for an evolutionary solution utilizing physical factors
Protein processing characterized by a gel-free proteomics approach

We describe a method for the specific isolation of representative N-terminal peptides of proteins and their proteolytic fragments. Their isolation is based on a gel-free, peptidecentric proteomics approach using the principle of diagonal chromatography. We will indicate that the introduction of an altered chemical property to internal peptides holding a free α-N-terminus results in altered column retention of these peptides, thereby enabling the isolation and further characterization by mass spectrometry of N-terminal peptides. Besides pointing to changes in protein expression levels when performing such proteome surveys in a differential modus, protease specificity and substrate repertoires can be allocated since both are specified by neo-N-termini generated after a protease cleavage event. As such, our gel-free proteomics technology is widely applicable and amenable for a variety of proteome-driven protease degradomics research
Exercise in the Prevention of Osteoporosis-Related Fractures

The prevention of osteoporotic fracture by exercise intervention requires a two-pronged  approach, that is, the maximization of bone strength and the minimization of falls. The  former is most effectively addressed before peak bone mass has been attained, so that the latter is the primary option for the older, osteoporotic individual. Intense animal and human research activity over the last 20 years has generated a wealth of data that has led to recommendations for exercise prescriptions to both enhance bone strength and minimize risk of falling. Whether those exercise protocols will be shown to effectively reduce actual fracture incidence requires the analysis of longer term data than is currently available.Full Tex
Analysis of Meiotic Recombination Products from Human Sperm

This is the author's final draft of the paper published as Methods in Molecular Biology, 2009, 557, pp. 323-355.   The original publication is available at www.springerlink.com.  Doi: 10.1007/978-1-59745-527-5_20Traditional methods for surveying meiotic recombination in humans are limited to pedigree and linkage disequilibrium analyses. We have developed assays that allow the direct detection of crossover and gene conversion molecules in batches of sperm DNA. To date, we have characterized 26 recombination hotspots by allele-specific PCR and selectively amplified recombinant DNA molecules from these regions. These analyses have revealed that meiotic crossover hotspots in humans are highly localized and flanked by DNA segments where recombination is suppressed. The centers of crossover hotspots are also active in noncrossover recombination, displaying short conversion tracts
Toll-like receptors and rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory disease that ultimately leads to the progressive destruction of cartilage and bone in numerous joints. There is mounting evidence for an important function of innate immunity in the pathogenesis of RA. Activation of cells by microbial components and also by endogenous molecules via Toll-like receptor (TLR) results in the production of a variety of proinflammatory cytokines, chemokines, and destructive enzymes, some of which can characteristically be found in RA.By immunohistochemistry we found elevated TLR2, 3, and 4 expressions in the rheumatoid synovium. In the synovial lining layer and at sites of invasion into cartilage, RA synovial fibroblasts (RASF) are the major cells expressing TLR2, 3, and 4. Stimulation of cultured RASF in vitro with the TLR2 ligand bacterial lipoprotein (bLP), the TLR3 ligand poly(I-C), and the TLR4 ligand LPS was shown to upregulate IL-6 as well as matrix metalloproteinases (MMPs) 1 and 3. These results suggest an important role for TLR2, 3, and 4 in the activation of synovial fibroblasts in RA leading to chronic inflammation and joint destruction