Magnetic track array for efficient bead capture in microchannels

Magnetism-based microsystems, as those dedicated to immunoaffinity separations or (bio)chemical reactions, take benefit of the large surface area-to-volume ratio provided by the immobilized magnetic beads, thus increasing the sensitivity of the analysis. As the sensitivity is directly linked to the efficiency of the magnetic bead capture, this paper presents a simple method to enhance the capture in a microchannel. Considering a microchannel surrounded by two rectangular permanent magnets of different length (Lm=2, 5, 10 mm) placed in attraction, it is shown that the amount of trapped beads is limited by the magnetic forces mainly located at the magnet edges. To overcome this limitation, a polyethylene terephthalate (PET) microchip with an integrated magnetic track array has been prototyped by laser photo-ablation. The magnetic force is therefore distributed all along the magnet length. It results in a multi-plug bead capture, observed by microscope imaging, with a magnetic force value locally enhanced. The relative amount of beads, and so the specific binding surface for further immunoassays, presents a significant increase of 300% for the largest magnets. The influence of the track geometry and relative permeability on the magnetic force was studied by numerical simulations, for the microchip operating with 2-mm-long magnets

Genomic organization and evolutionary conservation of plant D-type cyclins

Plants contain more genes encoding core cell cycle regulators than other organisms but it is unclear whether these represent distinct functions. D-type cyclins (CYCD) play key roles in the G1-to-S-phase transition, and Arabidopsis (Arabidopsis thaliana) contains 10 CYCD genes in seven defined subgroups, six of which are conserved in rice (Oryza sativa). Here, we identify 22 CYCD genes in the poplar (Populus trichocarpa) genome and confirm that these six CYCD subgroups are conserved across higher plants, suggesting subgroup-specific functions. Different subgroups show gene number increases, with CYCD3 having three members in Arabidopsis, six in poplar, and a single representative in rice. All three species contain a single CYCD7 gene. Despite low overall sequence homology, we find remarkable conservation of intron/exon boundaries, because in most CYCD genes of plants and mammals, the first exon ends in the conserved cyclin signature. Only CYCD3 genes contain the complete cyclin box in a single exon, and this structure is conserved across angiosperms, again suggesting an early origin for the subgroup. The single CYCD gene of moss has a gene structure closely related to those of higher plants, sharing an identical exon/intron structure with several higher plant subgroups. However, green algae have CYCD genes structurally unrelated to higher plants. Conservation is also observed in the location of potential cyclin-dependent kinase phosphorylation sites within CYCD proteins. Subgroup structure is supported by conserved regulatory elements, particularly in the eudicot species, including conserved E2F regulatory sites within CYCD3 promoters. Global expression correlation analysis further supports distinct expression patterns for CYCD subgroups

Magnetic forces produced by rectangular permanent magnets in static microsystems

Finite element numerical simulations were carried out in 2D geometries to map the magnetic field and force distribution produced by rectangular permanent magnets as a function of their size and position with respect to a microchannel. A single magnet, two magnets placed in attraction and in repulsion have been considered. The goal of this work is to show where magnetic beads are preferentially captured in a microchannel. These simulations were qualitatively corroborated, in one geometrical case, by microscopic visualizations of magnetic bead plug formation in a capillary. The results show that the number of plugs is configuration dependent with: in attraction, one plug in the middle of the magnets; in repulsion, two plugs near the edges of the magnets; and with a single magnet, a plug close to the center of the magnet. The geometry of the magnets (h and l are the height and length of the magnets respectively) and their relative spacing s has a significant impact on the magnetic flux density. Its value inside a magnet increases with the h/l ratio. Consequently, bar magnets produce larger and more uniform values than flat magnets. The l/s ratio also influences the magnetic force value in the microchannel, both increasing concomitantly for all the configurations. In addition, a zero force zone in the middle appears in the attraction configuration as the l/s ratio increases, while with a single magnet, the number of maxima and minima goes from one to two, producing two focusing zones instead of only one

Benchmark data and model independent event classification for the large hadron collider

We describe the outcome of a data challenge conducted as part of the Dark Machines (https://www.darkmachines.org) initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims to detect signals of new physics at the Large Hadron Collider (LHC) using unsupervised machine learning algorithms. First, we propose how an anomaly score could be implemented to define model-independent signal regions in LHC searches. We define and describe a large benchmark dataset, consisting of > 1 billion simulated LHC events corresponding to 10 fb−1 of proton-proton collisions at a center-of-mass energy of 13 TeV. We then review a wide range of anomaly detection and density estimation algorithms, developed in the context of the data challenge, and we measure their performance in a set of realistic analysis environments. We draw a number of useful conclusions that will aid the development of unsupervised new physics searches during the third run of the LHC, and provide our benchmark dataset for future studies at https://www.phenoMLdata.org. Code to reproduce the analysis is provided at https://github.com/bostdiek/DarkMachines-UnsupervisedChallenge

Clarifying the meaning of mantras in wildland fire behaviour modelling: reply to Cruz <i>et al.</i> (2017)

International audienceIn a recent communication, Cruz et al. (2017) called attention to several recurring statements (mantras) in the wildland fire literature regarding empirical and physical fire behaviour models. Motivated by concern that these mantras have not been fully vetted and are repeated blindly, Cruz et al. (2017) sought to verify five mantras they identify. This is a worthy goal and here we seek to extend the discussion and provide clarification to several confusing aspects of the Cruz et al. (2017) communication. In particular, their treatment of what they call physical models is inconsistent, neglects to reference current research activity focussed on combined experimentation and model development, and misses an opportunity to discuss the potential use of physical models to fire behaviour outside the scope of empirical approaches

Gene duplications are extensive and contribute significantly to the toxic proteome of nematocysts isolated from Acropora digitifera (Cnidaria: Anthozoa: Scleractinia)

Background: Gene duplication followed by adaptive selection is a well-accepted process leading to toxin diversification in venoms. However, emergent genomic, transcriptomic and proteomic evidence now challenges this role to be at best equivocal to other processess . Cnidaria are arguably the most ancient phylum of the extant metazoa that are venomous and such provide a definitive ancestral anchor to examine the evolution of this trait.\ud Methods: Here we compare predicted toxins from the translated genome of the coral Acropora digitifera to putative toxins revealed by proteomic analysis of soluble proteins discharged from nematocysts, to determine the extent to which gene duplications contribute to venom innovation in this reef-building coral species. A new bioinformatics tool called HHCompare was developed to detect potential gene duplications in the genomic data, which is made freely available (https://github.com/rgacesa/HHCompare).\ud Results: A total of 55 potential toxin encoding genes could be predicted from the A. digitifera genome, of which 36 (65 %) had likely arisen by gene duplication as evinced using the HHCompare tool and verified using two standard phylogeny methods. Surprisingly, only 22 % (12/55) of the potential toxin repertoire could be detected\ud following rigorous proteomic analysis, for which only half (6/12) of the toxin proteome could be accounted for as peptides encoded by the gene duplicates. Biological activities of these toxins are dominatedby putative phospholipases and toxic peptidases.\ud Conclusions: Gene expansions in A. digitifera venom are the most extensive yet described in any venomous animal, and gene duplication plays a significant role leading to toxin diversification in this coral species. Since such low numbers of toxins were detected in the proteome, it is unlikely that the venom is evolving rapidly by preydriven positive natural selection. Rather we contend that the venom has a defensive role deterring predation or\ud harm from interspecific competition and overgrowth by fouling organisms. Factors influencing translation of toxin encoding genes perhaps warrants more profound experimental consideration.United Kingdom Medical Research Council (MRC grant G82144A to R. Gacesa, D. Hranueli and P. F. Long)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP grants 2010/50174-7 to A. C. Morandini and 2011/50242-5 to A. C. Marques)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq grant 301039/2013-5 to A. C. Morandini)Universidade de São Paulo (USP grant 13.1.1502.9.8)NP-BioMar program at the Universidade de São Paul

LHC phenomenology of dark matter with a color-octet partner

Colored dark sectors where the dark matter particle is accompanied by colored partners have recently attracted theoretical and phenomenological interest. We explore the possibility that the dark sector consists of the dark matter particle and a color-octet partner, where the interaction with the Standard Model is governed by an effective operator involving gluons. The resulting interactions resemble the color analogues of electric and magnetic dipole moments. Although many phenomenological features of this kind of model only depend on the group representation of the partner under SU(3)c, we point out that interesting collider signatures such as R-hadrons are indeed controlled by the interaction operator between the dark and visible sector. We perform a study of the current constraints and future reach of LHC searches, where the complementarity between different possible signals is highlighted and exploited

Systematic Analysis of Stability Patterns in Plant Primary Metabolism

Metabolic networks are characterized by complex interactions and regulatory mechanisms between many individual components. These interactions determine whether a steady state is stable to perturbations. Structural kinetic modeling (SKM) is a framework to analyze the stability of metabolic steady states that allows the study of the system Jacobian without requiring detailed knowledge about individual rate equations. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. Until now, SKM experiments applied univariate tests to detect the network components with the largest influence on stability. In this work, we present an extended SKM approach relying on supervised machine learning to detect patterns of enzyme-metabolite interactions that act together in an orchestrated manner to ensure stability. We demonstrate its application on a detailed SK-model of the Calvin-Benson cycle and connected pathways. The identified stability patterns are highly complex reflecting that changes in dynamic properties depend on concerted interactions between several network components. In total, we find more patterns that reliably ensure stability than patterns ensuring instability. This shows that the design of this system is strongly targeted towards maintaining stability. We also investigate the effect of allosteric regulators revealing that the tendency to stability is significantly increased by including experimentally determined regulatory mechanisms that have not yet been integrated into existing kinetic models