Miracle-dz/UniFAR-FTUs huggingface dataset:
Palytoxin Found in Palythoa sp. Zoanthids (Anthozoa, Hexacorallia) Sold in the Home Aquarium Trade

Zoanthids (Anthozoa, Hexacorallia) are colonial anemones that contain one of the deadliest toxins ever discovered, palytoxin (LD50 in mice 300 ng/kg), but it is generally believed that highly toxic species are not sold in the home aquarium trade. We previously showed that an unintentionally introduced zoanthid in a home aquarium contained high concentrations of palytoxin and was likely responsible for a severe respiratory reaction when an individual attempted to eliminate the contaminant colonies using boiling water. To assess the availability and potential exposure of palytoxin to marine aquarium hobbyists, we analyzed zoanthid samples collected from local aquarium stores for palytoxin using liquid chromatography and high resolution mass spectrometry and attempted to identify the specimens through genetic analysis of 16S and cytochrome c oxidase 1 (COI) markers. We found four specimens of the same apparent species of zoanthid, that we described previously to be responsible for a severe respiratory reaction in a home aquarium, to be available in three aquarium stores in the Washington D.C. area. We found all of these specimens (n = 4) to be highly toxic with palytoxin or palytoxin-like compounds (range 0.5–3.5 mg crude toxin/g zoanthid). One of the most potent non-protein compounds ever discovered is present in dangerous quantities in a select species of zoanthid commonly sold in the home aquarium trade.
A genetic toolkit for tagging intronic MiMIC containing genes

Previously, we described a large collection of Minos-Mediated Integration Cassettes (MiMICs) that contain two phiC31 recombinase target sites and allow the generation of a new exon that encodes a protein tag when the MiMIC is inserted in a codon intron (Nagarkar-Jaiswal et al., 2015). These modified genes permit numerous applications including assessment of protein expression pattern, identification of protein interaction partners by immunoprecipitation followed by mass spec, and reversible removal of the tagged protein in any tissue. At present, these conversions remain time and labor-intensive as they require embryos to be injected with plasmid DNA containing the exon tag. In this study, we describe a simple and reliable genetic strategy to tag genes/proteins that contain MiMIC insertions using an integrated exon encoding GFP flanked by FRT sequences. We document the efficiency and tag 60 mostly uncharacterized genes. DOI: http://dx.doi. org/10.7554/eLife.08469. 001
Control System for an All-Terrain Mobile Robot

An idea of a control system architecture for a new wheeled mobile robot is proposed. The robot construction is characterized by an original drive mechanism and constitutes an extension of the previous research performed in Hochschule Ravensburg-Weingarten. In the new construction, the robot is given the ability to rise or lower its chassis. No complicated additional hardware is required as the level of the chassis can be changed by means of torque differences on the wheels. A modular approach is adopted to develop a hierarchical two-level and layered control system. Low and high levels correspond to local and global vehicle control. The low level is described in more detail, defining the layers and providing appropriate justification.
Slicing and dicing the information space using local contexts

In recent years there has been growing interest in faceted grouping of documents for Interactive Information Retrieval (IIR). It is suggested that faceted grouping can offer a flexible way of browsing a collection compared to clustering. However, the success of faceted grouping seems to rely on sufficient knowledge of collection structure. In this paper we propose an approach based on the local contexts of query terms, which is inspired by the interaction of faceted search and browsing. The use of local contexts is appealing since it requires less knowledge of the collection than existing approaches. A task-based user study was carried out to investigate the effectiveness of our interface in varied complexity. The results suggest that the local contexts can be exploited as the source of search result browsing in IIR, and that our interface appears to facilitate different aspects of search process over the task complexity. The implication of the evaluation methodology using high complexity tasks is also discussed.
Fungal volatiles as indicators of food and feeds spoilage.

Fungal growth leads to spoilage of food and animal feeds and to formation of mycotoxins and potentially allergenic spores. Fungi produce volatile compounds, during both primary and secondary metabolism, which can be used for detection and identification. Fungal volatiles from mainly Aspergillus, Fusarium, and Penicillium have been characterized with gas chromatography, mass spectrometry, and sensory analysis. Common volatiles are 2-methyl-1-propanol, 3-methyl-1-butanol, 1-octen-3-ol, 3-octanone, 3-methylfuran, ethyl acetate, and the malodorous 2-methyl-isoborneol and geosmin. Volatile sesquiterpenes can be used for taxonomic classification and species identification in Penicillium, as well as to indicate mycotoxin formation in Fusarium and Aspergillus. Developments in sensor technology have led to the construction of "electronic noses" (volatile compound mappers). Exposure of different nonspecific sensors to volatile compounds produces characteristic electrical signals. These are collected by a computer and processed by multivariate statistical methods or in an artificial neural network (ANN). Such systems can grade cereal grain with regard to presence of molds as efficiently as sensory panels evaluating grain odor. Volatile compound mapping can also be used to predict levels of ergosterol and fungal colony-forming units in grain. Further developments should make it possible to detect individual fungal species as well as the degree of mycotoxin contamination of food and animal feeds.
Recombineering strategies for developing next generation BAC transgenic tools for optogenetics and beyond

The development and application of diverse BAC transgenic rodent lines has enabled rapid progress for precise molecular targeting of genetically-defined cell types in the mammalian central nervous system. These transgenic tools have played a central role in the optogenetic revolution in neuroscience. Indeed, an overwhelming proportion of studies in this field have made use of BAC transgenic Cre driver lines to achieve targeted expression of optogenetic probes in the brain. In addition, several BAC transgenic mouse lines have been established for direct cell-type specific expression of Channelrhodopsin-2 (ChR2). While the benefits of these new tools largely outweigh any accompanying challenges, many available BAC transgenic lines may suffer from confounds due in part to increased gene dosage of one or more “extra” genes contained within the large BAC DNA sequences. Here we discuss this under-appreciated issue and propose strategies for developing the next generation of BAC transgenic lines that are devoid of extra genes. Furthermore, we provide evidence that these strategies are simple, reproducible, and do not disrupt the intended cell-type specific transgene expression patterns for several distinct BAC clones. These strategies may be widely implemented for improved BAC transgenesis across diverse disciplines.
CoDNaS: a database of conformational diversity in the native state of proteins

MOTIVATION Conformational diversity is a key concept in the understanding of different issues related with protein function such as the study of catalytic processes in enzymes, protein-protein recognition, protein evolution and the origins of new biological functions. Here, we present a database of proteins with different degrees of conformational diversity. Conformational Diversity of Native State (CoDNaS) is a redundant collection of three-dimensional structures for the same protein derived from protein data bank. Structures for the same protein obtained under different crystallographic conditions have been associated with snapshots of protein dynamism and consequently could characterize protein conformers. CoDNaS allows the user to explore global and local structural differences among conformers as a function of different parameters such as presence of ligand, post-translational modifications, changes in oligomeric states and differences in pH and temperature. Additionally, CoDNaS contains information about protein taxonomy and function, disorder level and structural classification offering useful information to explore the underlying mechanism of conformational diversity and its close relationship with protein function. Currently, CoDNaS has 122 122 structures integrating 12 684 entries, with an average of 9.63 conformers per protein. AVAILABILITY The database is freely available at http://www.codnas. com.ar/.
Consequence-based reasoning for ontology classification

Description logics (DLs) are knowledge representation languages that provide the theoretical underpinning for modern ontology languages such as OWL and serve as the basis for the development of ontology reasoners and tools. Most modern ontology reasoners are based on optimized tableau algorithms, which perform reasoning by trying to build counter-models. More recently, another kind of reasoning algorithms has been introduced that, instead of building counter-models, directly derive logical consequences of axioms in the ontology using inference rules. Such consequence-based algorithms were first introduced for the EL family of DLs, and later extended to more expressive Horn DLs. However, up until now, consequence-based algorithms could not handle non-Horn features such as disjunctions. We consider several complementary aspects of consequence-based reasoning in this thesis. Firstly, we describe the parallelized consequence-based reasoner ELK, which is currently the fastest reasoner for EL ontologies. Secondly, we demonstrate how consequence-based algorithms can be extended to handle disjunctions using inference rules reminiscent of ordered resolution. Finally, we combine our consequence-based framework with methods based on tree decompositions, and thus obtain what we believe are the first fixed-parameter tractability results for subsumption reasoning in DLs.
Phase Transitions in Classical Planning: An Experimental Study

Phase transitions in the solubility of problem instances are known in many types of computational problems relevant for artificial intelligence, most notably for the satisfiability problem of the classical propositional logic. However, phase transitions in classical planning have received far less attention. Bylander has investigated phase transitions theoretically as well as experimentally by using simplified planning algorithms, and shown that most of the soluble problems can be solved by a naive hill-climbing algorithm. Because of the simplicity of his algorithms he did not investigate hard problems on the phase transition region. In this paper, we address exactly this problem. We introduce two new models of problem instances, one eliminating the most trivially insoluble instances from Bylander's model, and the other restricting the class of problem instances further. Then we perform experiments on the behavior of different types of planning algorithms on hard problems from the phase transition region, showing that a planner based on general-purpose satisfiability algorithms outperforms two planners based on heuristic local search.
Defining Words with Words: Beyond the Distributional Hypothesis

The way humans define words is a powerful way of representing them. In this work, we propose to measure word similarity by comparing the overlap in their definition. This highlights linguistic phenomena that are complementary to the information extracted from standard context-based representation learning techniques. To acquire a large amount of word definitions in a cost-efficient manner, we designed a simple interactive word game, Word Sheriff. As a byproduct of game play, it generates short word sequences that can be used to uniquely identify words. These sequences can not only be used to evaluate the quality of word representations, but it could ultimately give an alternative way of learning them, as it overcomes some of the limitations of the distributional hypothesis. Moreover, inspecting player behaviour reveals interesting aspects about human strategies and knowledge acquisition beyond those of simple word association games, due to the conversational nature of the game. Lastly, we outline a vision of a communicative evaluation setting, where systems are evaluated based on how well a given representation allows a system to communicate with human and computer players.
Automatic Re-Organization of Group-Wised Web Courseware

With the increasing popularity of the Internet, there is a growing demand for web-based education, which allows students to study and learn at their own pace over the Internet. However in order to improve the teaching quality, such systems should be able to adapt the teaching in accordance with individual students’ ability and progress. Focusing on this objective, this paper proposes a new method to construct group-wised courseware by mining both context and structure of the courseware to build personalized Web tutor trees. To this end, the concept of Web tutor units and the notion of similarity are presented. Five algoriths, including the Naive Algorithm for tutor concept tree and the Level-generate Algorithm to generate Web tutor units of K+1 levels, are proposed. Experimental results are presented to demonstrate the effectiveness of the new method.
Multiscale analysis of abrasion damage on stainless steel

Abstract Topography is a surface characteristic which is as important as the chemical composition with regard to its functional properties. Topography can be mainly described by three kinds of roughness parameters: amplitude, frequency and hybrid parameters. The present study aims to perform a multiscale morphological analysis of 316L austenitic stainless steel ground surfaces with 11 different paper grades. It is shown that the values of the most commonly used roughness parameters Ra (average arithmetic roughness) and Rt (peak to valley) depend on the observation scale with values distributed into three characteristic stages. At small observation scales, less than ∼5 μm, the abraded surfaces are not characterised by any particular scaling law. At large observation scales, more than ∼60 μm, the evolution of the roughness parameters indicates that the abrasion mechanism follows an homothetic scaling law for the different paper grades. These two extreme stages are separated by a transition stage that can be characterised by an index, which exhibits an increasing linear evolution with the size of the abrasive grains.
CLA-1/SR-BI is expressed in atherosclerotic lesion macrophages and regulated by activators of peroxisome proliferator-activated receptors.

BACKGROUND The scavenger receptors are cell-surface receptors for native and modified lipoproteins that play a critical role in the accumulation of lipids by macrophages. CLA-1/SR-BI binds HDL with high affinity and is involved in the cholesterol reverse-transport pathway. Peroxisome proliferator-activated receptors (PPARs) are transcription factors regulating the expression of genes implicated in lipid metabolism, cellular differentiation, and inflammation. Here, we investigated the expression of CLA-1/SR-BI in macrophages and its regulation by PPARs. METHODS AND RESULTS CLA-1 is undetectable in human monocytes and is induced upon differentiation into macrophages. Immunohistological analysis on human atherosclerotic lesions showed high expression of CLA-1 in macrophages of the lipid core colocalizing with PPARalpha and PPARgamma staining. Activation of PPARalpha and PPARgamma resulted in the induction of CLA-1 protein expression in monocytes and in differentiated macrophages. Finally, SR-BI expression is increased in atherosclerotic lesions of apoE-null mice treated with either PPARgamma or PPARalpha ligands. CONCLUSIONS Our data demonstrate that CLA-1/SR-BI is expressed in atherosclerotic lesion macrophages and induced by PPAR activation, identifying a potential role for PPARs in cholesterol homeostasis in atherosclerotic lesion macrophages.
Interactive rendering of large unstructured grids using dynamic level-of-detail

We describe a new dynamic level-of-detail (LOD) technique that allows real-time rendering of large tetrahedral meshes. Unlike approaches that require hierarchies of tetrahedra, our approach uses a subset of the faces that compose the mesh. No connectivity is used for these faces so our technique eliminates the need for topological information and hierarchical data structures. By operating on a simple set of triangular faces, our algorithm allows a robust and straightforward graphics hardware (GPU) implementation. Because the subset of faces processed can be constrained to arbitrary size, interactive rendering is possible for a wide range of data sets and hardware configurations.
Comparative Proteomics Profiling of a Phospholamban Mutant Mouse Model of Dilated Cardiomyopathy Reveals Progressive Intracellular Stress Responses*S

Defective mobilization of Ca2+ by cardiomyocytes can lead to cardiac insufficiency, but the causative mechanisms leading to congestive heart failure (HF) remain unclear. In the present study we performed exhaustive global proteomics surveys of cardiac ventricle isolated from a mouse model of cardiomyopathy overexpressing a phospholamban mutant, R9C (PLN-R9C), and exhibiting impaired Ca2+ handling and death at 24 weeks and compared them with normal control littermates. The relative expression patterns of 6190 high confidence proteins were monitored by shotgun tandem mass spectrometry at 8, 16, and 24 weeks of disease progression. Significant differential abundance of 593 proteins was detected. These proteins mapped to select biological pathways such as endoplasmic reticulum stress response, cytoskeletal remodeling, and apoptosis and included known biomarkers of HF (e.g. brain natriuretic peptide/atrial natriuretic factor and angiotensin-converting enzyme) and other indicators of presymptomatic functional impairment. These altered proteomic profiles were concordant with cognate mRNA patterns recorded in parallel using high density mRNA microarrays, and top candidates were validated by RT-PCR and Western blotting. Mapping of our highest ranked proteins against a human diseased explant and to available data sets indicated that many of these proteins could serve as markers of disease. Indeed we showed that several of these proteins are detectable in mouse and human plasma and display differential abundance in the plasma of diseased mice and affected patients. These results offer a systems-wide perspective of the dynamic maladaptions associated with impaired Ca2+ homeostasis that perturb myocyte function and ultimately converge to cause HF.
A Framework for the Next Generation Screen Readers for Visually Impaired

Despite shortcomings, Screen Readers have been the primary tool for using internet by visually impaired. In this paper, we present a framework for an advanced Screen Reader that aims at eliminating the drawbacks that are associated with the existing systems. The proposed framework makes the use of informed search technique to enhance the usability and navigability. Some of its features like background music to appraise the layout structure of web page, mouse hovering to speak out glimpses of the underlying text make the use of image processing techniques. These features are implemented independent of the rest development therefore they can also be used to enhance any existing Screen Reader.
Coordinated Multi-Point Transmission Strategies for TDD Systems with Non-Ideal Channel Reciprocity

This paper studies transmission strategies for downlink time division duplex coordinated multi-point (CoMP) systems with non-ideal uplink-downlink channel reciprocity, where several multi-antenna base stations (BSs) jointly serve multiple single-antenna users. Due to the inherent antenna calibration errors among different BSs, the uplink-downlink channels are no longer reciprocal such that the channel information at the BSs is with multiplicative noises. To mitigate the performance degradation caused by the imperfect channels, we employ a weighted sum rate estimate as the objective function for robust precoder design. To show the impact of data sharing on the performance of CoMP under the non-ideal channel reciprocity, we provide a unified framework for designing precoder for CoMP systems with different amount of data sharing. The optimal parametric linear precoder structure that maximizes the weighted sum rate estimate under per-BS power constraints is characterized, based on which a closed-form robust signal-to-leakage-plus-noise ratio (SLNR) precoder is proposed to exploit the statistics of the calibration errors. Simulation results show that the proposed precoder in conjunction with user scheduling provides substantial performance gain over Non-CoMP transmission and the CoMP transmission with non-robust precoders.
Letter regarding ‘Comparison between low-cost marker-less and high-end marker-based motion capture systems for the computer-aided assessment of working ergonomics’ by Patrizi et al. and research reproducibility

Abstract The reporting of research in a manner that allows reproduction in subsequent investigations is important for scientific progress. Several details of the recent study by Patrizi et al., ‘Comparison between low-cost marker-less and high-end marker-based motion capture systems for the computer-aided assessment of working ergonomics’, are absent from the published manuscript and make reproduction of findings impossible. As new and complex technologies with great promise for ergonomics develop, new but surmountable challenges for reporting investigations using these technologies in a reproducible manner arise. Practitioner Summary: As with traditional methods, scientific reporting of new and complex ergonomics technologies should be performed in a manner that allows reproduction in subsequent investigations and supports scientific advancement.
Selective Lentiviral Gene Delivery to CD133-Expressing Human Glioblastoma Stem Cells

Glioblastoma multiforme (GBM) is a deadly primary brain malignancy. Glioblastoma stem cells (GSC), which have the ability to self-renew and differentiate into tumor lineages, are believed to cause tumor recurrence due to their resistance to current therapies. A subset of GSCs is marked by cell surface expression of CD133, a glycosylated pentaspan transmembrane protein. The study of CD133-expressing GSCs has been limited by the relative paucity of genetic tools that specifically target them. Here, we present CD133-LV, a lentiviral vector presenting a single chain antibody against CD133 on its envelope, as a vehicle for the selective transduction of CD133-expressing GSCs. We show that CD133-LV selectively transduces CD133+ human GSCs in dose-dependent manner and that transduced cells maintain their stem-like properties. The transduction efficiency of CD133-LV is reduced by an antibody that recognizes the same epitope on CD133 as the viral envelope and by shRNA-mediated knockdown of CD133. Conversely, the rate of transduction by CD133-LV is augmented by overexpression of CD133 in primary human GBM cultures. CD133-LV selectively transduces CD133-expressing cells in intracranial human GBM xenografts in NOD.SCID mice, but spares normal mouse brain tissue, neurons derived from human embryonic stem cells and primary human astrocytes. Our findings indicate that CD133-LV represents a novel tool for the selective genetic manipulation of CD133-expressing GSCs, and can be used to answer important questions about how these cells contribute to tumor biology and therapy resistance.