pinecone/core-2020-05-10-deduplication huggingface dataset:
Sample Preparation for N-Glycosylation Analysis of Therapeutic Monoclonal Antibodies by Electrophoresis

There are a considerable number of biopharmaceuticals that have been approved for clinical use in the past \ud
decade. Over half of these new generation drugs are glycoproteins, such as monoclonal antibodies or other \ud
recombinant glycoproteins, which are mostly produced in mammalian cell lines. The linked carbohydrate \ud
moieties affect not only their physicochemical properties and thermal stability but also crucial features like \ud
receptor-binding activity, circulating half-life, as well as immunogenicity. The structural diversity of these \ud
attached glycans can be manifested in altered monosaccharide composition and linkages/positions among \ud
the monosaccharide building blocks. In addition, as more and more biosimilar products hit the market, \ud
understanding the effects of their glycosylation modifi\ud
 cation has become a recent target in effi\ud
 cacy  and \ud
safety issues. To ensure consistent quality of these products, glycosylation profi\ud
 les have to be monitored \ud
and controlled in all steps of the manufacturing process, i.e., from clone selection to lot release. In this \ud
paper, we describe some of the recently introduced and commonly used sample preparation techniques for \ud
capillary electrophoresis (CE)-based profi\ud
 ling and structural elucidation of N-glycans. The presented pro-\ud
tocols include protein A affi\ud
 nity partitioning of monoclonal antibodies (mAbs), enzymatic release of the \ud
N-linked glycans, labeling of the liberated carbohydrates, reaction mixture purifi\ud
 cation techniques to \ud
remove the excess labeling reagent, and high-resolution and rapid capillary electrophoresis-laser-induced \ud
fl\ud
 uorescence (CE-LIF)-based profi\ud
 ling of the labeled and purifi\ud
 ed N-glycans
Identification of protein-protein interactions by standard gal4p-based yeast two-hybrid screening

Yeast two-hybrid (Y2H) screening permits identification of completely new protein interaction partners for a protein of interest, in addition to confirming binary protein-protein interactions. After discussing the general advantages and drawbacks of Y2H and existing alternatives, this chapter provides a detailed protocol for traditional Gal4p-based Y2H library screens in Saccharomyces cerevisiae AH109. This includes bait transformation, bait auto-activation testing, prey library transformation, Y2H evaluation, and subsequent identification of the prey plasmids. Moreover, a one-on-one mating protocol to confirm interactions between suspected partners is given. Finally, a quantitative α-galactosidase assay protocol to compare interaction strengths is provided.status: publishe
Geometric Computational Electrodynamics with Variational Integrators and
  Discrete Differential Forms

In this paper, we develop a structure-preserving discretization of the
Lagrangian framework for electromagnetism, combining techniques from
variational integrators and discrete differential forms. This leads to a
general family of variational, multisymplectic numerical methods for solving
Maxwell's equations that automatically preserve key symmetries and invariants.
  In doing so, we demonstrate several new results, which apply both to some
well-established numerical methods and to new methods introduced here. First,
we show that Yee's finite-difference time-domain (FDTD) scheme, along with a
number of related methods, are multisymplectic and derive from a discrete
Lagrangian variational principle. Second, we generalize the Yee scheme to
unstructured meshes, not just in space but in 4-dimensional spacetime. This
relaxes the need to take uniform time steps, or even to have a preferred time
coordinate at all. Finally, as an example of the type of methods that can be
developed within this general framework, we introduce a new asynchronous
variational integrator (AVI) for solving Maxwell's equations. These results are
illustrated with some prototype simulations that show excellent energy and
conservation behavior and lack of spurious modes, even for an irregular mesh
with asynchronous time stepping.Comment: 37 pages, 12 figures. v3: broadly revised, including incorporation of
  free source terms, new numerical experiments and figure
Chaos in the Kepler problem with quadrupole perturbations

We use the Melnikov integral method to prove that the Hamiltonian flow on the
zero-energy manifold for the Kepler problem perturbed by a quadrupole moment is
chaotic, irrespective of the perturbation being of prolate or oblate type. This
result helps to elucidate some recent conflicting works in the physical
literature based on numerical simulations.Comment: 6 pages, 1 figure. Contribution submitted to the volume "Geometry,
  Mechanics and Dynamics: the Legacy of Jerrold E. Marsden", Springer (2013
The role of SE(d)-reduction for swimming in Stokes and Navier-Stokes
  fluids

Steady swimming appears both periodic and stable. These characteristics are
the very definition of limit cycles, and so we ask "Can we view swimming as a
limit cycle?" In this paper we will not be able to answer this question in
full. However, we shall find that reduction by SE(d)-symmetry brings us closer.
Upon performing reduction by symmetry, we will find a stable fixed point which
corresponds to a motionless body in stagnant water. We will then speculate on
the existence of periodic orbits which are "approximately" limit cycles in the
reduced system. When we lift these periodic orbits from the reduced phase
space, we obtain dynamically robust relatively periodic orbits wherein each
period is related to the previous by an SE(d)-phase. Clearly, an SE(d) phase
consisting of nonzero translation and identity rotation means directional
swimming, while non-trivial rotations correspond to turning with a constant
turning radius.Comment: 29 pages, accepted to the Fields institute communications series. An
  alternative description of the content here can be found in H.O.J, "Swimming
  as a limit cycle", arXiv:1211.268
cDNA Library Generation for the Analysis of Small RNAs by High-Throughput Sequencing

The RNome of a cell is highly diverse and consists besides messenger RNAs (mRNAs), transfer RNAs (tRNAs), and ribosomal RNAs (rRNAs) also of other small and long transcript entities without apparent coding potential. This class of molecules, commonly referred to as non-protein-coding RNAs (ncRNAs), is involved in regulating numerous biological processes and thought to contribute to cellular complexity. Therefore, much effort is put into their identification and further functional characterization. Here we provide a cost-effective and reliable method for cDNA library construction of small RNAs in the size range of 20-500 residues. The effectiveness of the described method is demonstrated by the analysis of ribosome-associated small RNAs in the eukaryotic model organism Trypanosoma brucei
Two-Dimensional Gel-Based Protein Standardization Verified by Western Blot Analysis

In data presentation of biochemical investigation the amount of a target protein is shown in the y-axis against the x-axis representing time, concentrations of various agents, or other parameters. Western blot is a versatile and convenient tool in such an analysis to quantify and display the amount of proteins. In western blot, so-called housekeeping gene product(s), or "housekeeping proteins," are widely used as internal standards. The rationale of using housekeeping proteins for standardization of western blot is based on the assumption that the expression of chosen housekeeping gene is always constant, which could be false under certain physiological or pathological conditions. We have devised a two-dimensional gel-based standardization method in which the protein content of each sample is determined by scanning the total protein density of two-dimensional gels and the expression of each protein is quantified as the density ratio of each protein divided by the density of the total proteins on the two-dimensional gel. The advantage of this standardization method is that it is not based on any presumed "housekeeping proteins" that are supposed to be being expressed constantly under all physiological conditions. We will show that the total density of a two-dimensional gel can render a reliable protein standardization parameter by running western blot analysis on one of the proteins analyzed by two-dimensional gels
A Hedged Monte Carlo Approach to Real Option Pricing

In this work we are concerned with valuing optionalities associated to invest
or to delay investment in a project when the available information provided to
the manager comes from simulated data of cash flows under historical (or
subjective) measure in a possibly incomplete market. Our approach is suitable
also to incorporating subjective views from management or market experts and to
stochastic investment costs. It is based on the Hedged Monte Carlo strategy
proposed by Potters et al (2001) where options are priced simultaneously with
the determination of the corresponding hedging. The approach is particularly
well-suited to the evaluation of commodity related projects whereby the
availability of pricing formulae is very rare, the scenario simulations are
usually available only in the historical measure, and the cash flows can be
highly nonlinear functions of the prices.Comment: 25 pages, 14 figure
The Geometry and Moduli of K3 Surfaces

These notes will give an introduction to the theory of K3 surfaces. We begin
with some general results on K3 surfaces, including the construction of their
moduli space and some of its properties. We then move on to focus on the theory
of polarized K3 surfaces, studying their moduli, degenerations and the
compactification problem. This theory is then further enhanced to a discussion
of lattice polarized K3 surfaces, which provide a rich source of explicit
examples, including a large class of lattice polarizations coming from elliptic
fibrations. Finally, we conclude by discussing the ample and Kahler cones of K3
surfaces, and give some of their applications.Comment: 34 pages, 2 figures. (R. Laza, M. Schutt and N. Yui, eds.
Functional Analysis of the Role of Toxin-Antitoxin (TA) Loci in Bacterial Persistence.

Bacterial Persistence: Methods and ProtocolsThe final publication is available at Springer via http://dx.doi.org/10.1007/978-1-4939-2854-5_11We have developed a method to analyze the functionality of putative TA loci by expressing them in Escherichia coli. Here, we describe the procedure for cloning recombinant TA genes into inducible plasmids and expressing these in E. coli. Following expression, toxicity, resuscitation of growth, and changes in persister cell formation are assayed. This can confirm whether predicted TA loci are active in E. coli and whether expression can affect persister cell formation
Distance-Based Phylogeny Reconstruction: Safety and Edge Radius

International audienceA phylogeny is an evolutionary tree tracing the shared history, including common ancestors, of a set of extant species or “taxa”. Phylogenies are increasingly reconstructed on the basis of molecular data (DNA and protein sequences) using statistical techniques such as likelihood and Bayesian methods. Algorithmically, these techniques suffer from the discrete nature of tree topology space. Since the number of tree topologies increases exponentially as a function of the number of taxa, and each topology requires a separate likelihood calculation, it is important to restrict the search space and to design efficient heuristics. Distance methods for phylogeny reconstruction serve this purpose by inferring trees in a fraction of the time required for the more statistically rigorous methods. Distance methods also provide fairly accurate starting trees to be further refined by more sophisticated methods. Moreover, the input to a distance method is the matrix of pairwise evolutionary distances among taxa, which are estimated by maximum likelihood, so that distance methods also have sound statistical justifications
Some analytic results on the FPU paradox

We present some analytic results aiming at explaining the lack of
thermalization observed by Fermi Pasta and Ulam in their celebrated numerical
experiment. In particular we focus on results which persist as the number $N$
of particles tends to infinity. After recalling the FPU experiment and some
classical heuristic ideas that have been used for its explanation, we
concentrate on more recent rigorous results which are based on the use of (i)
canonical perturbation theory and KdV equation, (ii) Toda lattice, (iii) a new
approach based on the construction of functions which are adiabatic invariants
with large probability in the Gibbs measure
Assessment of B cell repertoire in humans

The B cell receptor (BCR) repertoire is highly diverse. Repertoire diversity is achieved centrally by somatic recombination of immunoglobulin (Ig) genes and peripherally by somatic hypermutation and Ig heavy chain class-switching. Throughout these processes, there is selection for functional gene rearrangements, selection against gene combinations resulting in self-reactive BCRs, and selection for BCRs with high affinity for exogenous antigens after challenge. Hence, investigation of BCR repertoires from different groups of B cells can provide information on stages of B cell development and shed light on the etiology of B cell pathologies. In most instances, the third complementarity determining region of the Ig heavy chain (CDR-H3) contributes the majority of amino acids to the antibody/antigen binding interface. Although CDR-H3 spectratype analysis provides information on the overall diversity of BCR repertoires, this fairly simple technique analyzes the relative quantities of CDR-H3 regions of each size, within a range of approximately 10–80 bp, without sequence detail and thus is limited in scope. High-throughput sequencing (HTS) techniques on the Roche 454 GS FLX Titanium system, however, can generate a wide coverage of Ig sequences to provide more qualitative data such as V, D, and J usage as well as detailed CDR3 sequence information. Here we present protocols in detail for CDR-H3 spectratype analysis and HTS of human BCR repertoires
Effects of offshore wind farms on the early life stages of Dicentrarchus labrax

Anthropogenically generated underwater noise in the marine environment is ubiquitous, comprising both intense impulse and continuous noise. The installation of offshore wind farms across the North Sea has triggered a range of ecological questions regarding the impact of anthropogenically produced underwater noise on marine wildlife. Our interest is on the impact on the "passive drifters," i.e., the early life stages of fish that form the basis of fish populations and are an important prey for pelagic predators. This study deals with the impact of pile driving and operational noise generated at offshore wind farms on Dicentrarchus labrax (sea bass) larvae
The challenges of analyzing behavioral response study data : an overview of the MOCHA (Multi-study OCean acoustics Human effects Analysis) project

Date of Acceptance:This paper describes the MOCHA project which aims to develop novel approaches for the analysis of data collected during Behavioral Response Studies (BRSs). BRSs are experiments aimed at directly quantifying the effects of controlled dosages of natural or anthropogenic stimuli (typically sound) on marine mammal behavior. These experiments typically result in low sample size, relative to variability, and so we are looking at a number of studies in combination to maximize the gain from each one. We describe a suite of analytical tools applied to BRS data on beaked whales, including a simulation study aimed at informing future experimental design.Postprin
Assessment of impulsive and continuous low- frequency noise in Irish waters

As part of the European Union Marine Strategy Framework Directive (MSFD), member states are required to address noise pollution in the marine environment under Descriptor 11. This study aimed to provide a practical desk-based application of Descriptor 11 assessment, focusing on the main contributors of ocean noise pollution in Irish waters, seismic surveying and shipping. To highlight specifi c geographical areas subject to elevated levels of noise pollution, the proportion of days over a calendar year that seismic air guns were operational was calculated and the vessel density per 50-km 2 grids was determined across Ireland’s exclusive economic zone (EEZ). Additionally, cetacean sighting data were used to determine the degree of spatial overlap between areas of elevated noise pollution and areas of cetacean abundance
The use of deep water berths and the effect of noise on bottlenose dolphins in the Shannon Estuary cSAC

The Shannon Estuary on the west coast of Ireland is one of Europe’s premier deepwater berths catering for ships up to 200,000 deadweight tonnage. It is also Ireland’s only designated candidate special area of conservation for bottlenose dolphins under the EU Habitats Directive. Long-term static acoustic monitoring was carried out at a number of intensive shipping sites. In 2012, noise monitoring took place over a 6-month period (at 1 site) as part of Ireland’s requirements under the Marine Strategy Framework Directive (MSFD). This is the first assessment of the potential effect of vessel traffic on the behavior of this discrete dolphin population
Characterizing fluctuations of arterial and cerebral tissue oxygenation in preterm neonates by means of data analysis techniques for nonlinear dynamical systems

The cerebral autoregulatory state as well as fluctuations in arterial (SpO2) and cerebral tissue oxygen saturation (StO2) are potentially new relevant clinical parameters in preterm neonates. The aim of the present study was to test the investigative capabilities of data analysis techniques for nonlinear dynamical systems, looking at fluctuations and their interdependence. StO2, SpO2 and the heart rate (HR) were measured on four preterm neonates for several hours. The fractional tissue oxygenation extraction (FTOE) was calculated. To characterize the fluctuations in StO2, SpO2, FTOE and HR, two methods were employed: (1) phase-space modeling and application of the recurrence quantification analysis (RQA), and (2) maximum entropy spectral analysis (MESA). The correlation between StO2 and SpO2 as well as FTOE and HR was quantified by (1) nonparametric nonlinear regression based on the alternating conditional expectation (ACE) algorithm, and (2) the maximal information-based nonparametric exploration (MINE) technique. We found that (1) each neonate showed individual characteristics, (2) a ~60 min oscillation was observed in all of the signals, (3) the nonlinear correlation strength between StO2 and SpO2 as well as FTOE and HR was specific for each neonate and showed a high value for a neonate with a reduced health status, possibly indicating an impaired cerebral autoregulation. In conclusion, our data analysis framework enabled novel insights into the characteristics of hemodynamic and oxygenation changes in preterm infants. To the best of our knowledge, this is the first application of RQA, MESA, ACE and MINE to human StO2 data measured with near-infrared spectroscopy (NIRS)
Raiders of the lost spacetime

Spacetime as we know and love it is lost in most approaches to quantum
gravity. For many of these approaches, as inchoate and incomplete as they may
be, one of the main challenges is to relate what they take to be the
fundamental non-spatiotemporal structure of the world back to the classical
spacetime of GR. The present essay investigates how spacetime is lost and how
it may be regained in one major approach to quantum gravity, loop quantum
gravity.Comment: 33 pages, 3 figures. Forthcoming in Dennis Lehmkuhl (ed.), Towards a
  Theory of Spacetime Theories, Birkh\"ause
Next-generation pathology

The field of pathology is rapidly transforming from a semiquantitative and empirical science toward a big data discipline. Large data sets from across multiple omics fields may now be extracted from a patient's tissue sample. Tissue is, however, complex, heterogeneous, and prone to artifact. A reductionist view of tissue and disease progression, which does not take this complexity into account, may lead to single biomarkers failing in clinical trials. The integration of standardized multi-omics big data and the retention of valuable information on spatial heterogeneity are imperative to model complex disease mechanisms. Mathematical modeling through systems pathology approaches is the ideal medium to distill the significant information from these large, multi-parametric, and hierarchical data sets. Systems pathology may also predict the dynamical response of disease progression or response to therapy regimens from a static tissue sample. Next-generation pathology will incorporate big data with systems medicine in order to personalize clinical practice for both prognostic and predictive patient care.Postprin
Systems medicine and infection

By using a systems based approach, mathematical and computational techniques can be used to develop models that describe the important mechanisms involved in infectious diseases. An iterative approach to model development allows new discoveries to continually improve the model, and ultimately increase the accuracy of predictions. SIR models are used to describe epi demics, predicting the extent and spread of disease. Genome-wide genotyping and sequencing technologies can be used to identify the biological mechanisms behind diseases. These tools help to build strategies for disease prevention and treatment, an example being the recent outbreak of Ebola in West Africa where these techniques were deployed. HIV is a complex disease where much is still to be learnt about the virus and the best effective treatment. With basic mathematical modelling techniques, significant discoveries have been made over the last 20 years. With recent technological advances, the computation al resources now available and interdisciplinary cooperation, further breakthroughs are inevitable. In TB, modelling has traditionally been empirical in nature, with clinical data providing the fuel for this top-down approach. Recently, projects have begun to use data derived from laboratory experiments and clinical trials to create mathematical models that describe the mechanisms responsible for the disease. A systems medicine approach to infection modelling helps identify important biological questions that then direct future experiments , the results of which improve the model in an iterative cycle . This means that data from several model systems can be integrated and synthesised to explore complex biological systems .Postprin