707 research outputs found
Symmetric and Asymmetric Coalescence of Drops on a Substrate
The coalescence of viscous drops on a substrate is studied experimentally and
theoretically. We consider cases where the drops can have different contact
angles, leading to a very asymmetric coalescence process. Side view experiments
reveal that the "bridge" connecting the drops evolves with self-similar
dynamics, providing a new perspective on the coalescence of sessile drops. We
show that the universal shape of the bridge is accurately described by
similarity solutions of the one-dimensional lubrication equation. Our theory
predicts a bridge that grows linearly in time and stresses the strong
dependence on the contact angles. Without any adjustable parameters, we find
quantitative agreement with all experimental observations.Comment: 5 pages, 4 figure
Large genomic differences between Moraxella bovoculi isolates acquired from the eyes of cattle with infectious bovine keratoconjunctivitis versus the deep nasopharynx of asymptomatic cattle
Citation: Dickey, A. M., Loy, J. D., Bono, J. L., Smith, T. P. L., Apley, M. D., Lubbers, B. V., . . . Clawson, M. L. (2016). Large genomic differences between Moraxella bovoculi isolates acquired from the eyes of cattle with infectious bovine keratoconjunctivitis versus the deep nasopharynx of asymptomatic cattle. Veterinary Research, 47, 11. doi:10.1186/s13567-016-0316-2Moraxella bovoculi is a recently described bacterium that is associated with infectious bovine keratoconjunctivitis (IBK) or "pinkeye" in cattle. In this study, closed circularized genomes were generated for seven M. bovoculi isolates: three that originated from the eyes of clinical IBK bovine cases and four from the deep nasopharynx of asymptomatic cattle. Isolates that originated from the eyes of IBK cases profoundly differed from those that originated from the nasopharynx of asymptomatic cattle in genome structure, gene content and polymorphism diversity and consequently placed into two distinct phylogenetic groups. These results suggest that there are genetically distinct strains of M. bovoculi that may not associate with IBK
Modeling BCR-ABL and MLL-AF9 leukemia in a human bone marrow-like scaffold based xenograft model
While NOD-SCID IL2Rγ(-/-) (NSG) xenograft mice are currently the most frequently used model to study human leukemia in vivo, the absence of a human niche severely hampers faithful recapitulation of the disease. We used NSG mice in which ceramic scaffolds seeded with human mesenchymal stromal cells were implanted to generate a human bone marrow (huBM-sc)-like niche. We observed that, in contrast to the murine bone marrow (mBM) niche, expression of BCR-ABL or MLL-AF9 was sufficient to induce both primary AML and ALL. Stemness was preserved within the human niches as demonstrated by serial transplantation assays. Efficient engraftment of AML MLL-AF9 and blast-crisis CML patient cells was also observed, whereby the immature blast-like phenotype was maintained in the huBM-sc niche, but to a much lesser extent in mBM niches. We compared transcriptomes of leukemias derived from mBM niches versus leukemias from huBM-like scaffold-based niches, which revealed striking differences in expression of genes associated with hypoxia, mitochondria and metabolism. Finally, we utilized the huBM-sc MLL-AF9 B-ALL model to evaluate the efficacy of the I-BET151 inhibitor in vivo. In conclusion, we have established human niche models in which the myeloid and lymphoid features of BCR-ABL(+) and MLL-AF9(+) leukemias can be studied in detail.
Accepted article preview online 29 April 2016; Advance online publication 17 May 2016This work was supported by grants from the Dutch Cancer Society (2009-4411; VU2011-5127) and by the EU (ITN EuroCSC). I-BET151 was kindly provided by Nicholas Smithers (GSK R&D, UK)
Temporal networks of face-to-face human interactions
The ever increasing adoption of mobile technologies and ubiquitous services
allows to sense human behavior at unprecedented levels of details and scale.
Wearable sensors are opening up a new window on human mobility and proximity at
the finest resolution of face-to-face proximity. As a consequence, empirical
data describing social and behavioral networks are acquiring a longitudinal
dimension that brings forth new challenges for analysis and modeling. Here we
review recent work on the representation and analysis of temporal networks of
face-to-face human proximity, based on large-scale datasets collected in the
context of the SocioPatterns collaboration. We show that the raw behavioral
data can be studied at various levels of coarse-graining, which turn out to be
complementary to one another, with each level exposing different features of
the underlying system. We briefly review a generative model of temporal contact
networks that reproduces some statistical observables. Then, we shift our focus
from surface statistical features to dynamical processes on empirical temporal
networks. We discuss how simple dynamical processes can be used as probes to
expose important features of the interaction patterns, such as burstiness and
causal constraints. We show that simulating dynamical processes on empirical
temporal networks can unveil differences between datasets that would otherwise
look statistically similar. Moreover, we argue that, due to the temporal
heterogeneity of human dynamics, in order to investigate the temporal
properties of spreading processes it may be necessary to abandon the notion of
wall-clock time in favour of an intrinsic notion of time for each individual
node, defined in terms of its activity level. We conclude highlighting several
open research questions raised by the nature of the data at hand.Comment: Chapter of the book "Temporal Networks", Springer, 2013. Series:
Understanding Complex Systems. Holme, Petter; Saram\"aki, Jari (Eds.
Detection of bovine inflammatory cytokines IL-1β, IL-6, and TNF-α with a multiplex electrochemiluminescent assay platform
Commercially available bovine-specific assays are limited in number, and multiplex assays for this species are rare. Our objective was to develop a multiplex assay for the bovine inflammatory cytokines IL-1β, IL-6, and TNFα using the Meso Scale Discovery U-PLEX platform. Do-It-Yourself ELISA kits that contained polyclonal antibodies, both unlabeled and biotinylated, and the specific recombinant bovine cytokine standard, were purchased for each of these three cytokines. The biotinylated antibodies were coupled to linkers that bind to specific locations within each well of the U-PLEX plate. Unique linkers were used for each of the cytokines. The unlabeled antibodies were conjugated with electrochemiluminescent labels to serve as detection antibodies. Each cytokine assay was optimized individually prior to performing an optimization on the multiplex assay containing reagents for all three cytokines. To calculate cytokine concentrations, standard curves were developed using the recombinant cytokines and were run concurrently on each plate. Standard curves for IL-1β and TNF-α were run at concentrations ranging from 0 to 50,000 pg/mL, and for IL-6 from 0 to 10,000 pg/mL. The average lowest level of detection concentration measured by the standard curves were 5.3 pg/mL, 0.92 pg/mL, and 22.34 pg/mL for IL-1β, IL-6, and TNF-α respectively, as determined by data from seven plates containing bovine plasma samples from a combination of healthy and diseased cattle. The U-PLEX platform was a viable means to develop custom analyte- and species-specific multiplex assays using privately developed or purchased sets of commercially available reagents
Building nonparametric -body force fields using Gaussian process regression
Constructing a classical potential suited to simulate a given atomic system
is a remarkably difficult task. This chapter presents a framework under which
this problem can be tackled, based on the Bayesian construction of
nonparametric force fields of a given order using Gaussian process (GP) priors.
The formalism of GP regression is first reviewed, particularly in relation to
its application in learning local atomic energies and forces. For accurate
regression it is fundamental to incorporate prior knowledge into the GP kernel
function. To this end, this chapter details how properties of smoothness,
invariance and interaction order of a force field can be encoded into
corresponding kernel properties. A range of kernels is then proposed,
possessing all the required properties and an adjustable parameter
governing the interaction order modelled. The order best suited to describe
a given system can be found automatically within the Bayesian framework by
maximisation of the marginal likelihood. The procedure is first tested on a toy
model of known interaction and later applied to two real materials described at
the DFT level of accuracy. The models automatically selected for the two
materials were found to be in agreement with physical intuition. More in
general, it was found that lower order (simpler) models should be chosen when
the data are not sufficient to resolve more complex interactions. Low GPs
can be further sped up by orders of magnitude by constructing the corresponding
tabulated force field, here named "MFF".Comment: 31 pages, 11 figures, book chapte
Identification of Digital Health Priorities for Palliative Care Research: Modified Delphi Study.
Background: Developments in digital health have the potential to transform the delivery of health and social care to help citizens manage their health. Currently, there is a lack of consensus about digital health research priorities in palliative care and a lack of theories about how these technologies might improve care outcomes. Therefore, it is important for health care leaders to identify innovations to ensure that an increasingly frail population has appropriate access to palliative care services. Consequently, it is important to articulate research priorities as the first step in determining how finite resources should be allocated to a field saturated with rapidly developing innovation. Objective: The aim of this study is to identify research priority areas for digital health in palliative care. Methods: We selected digital health trends, most relevant to palliative care, from a list of emerging trends reported by a leading institute of quantitative futurists. We conducted 2 rounds of the Delphi questionnaire, followed by a consensus meeting and public engagement workshop to establish a final consensus on research priorities for digital technology in palliative care. We used the views of public representatives to gain their perspectives on the agreed priorities. Results: A total of 103 experts (representing 11 countries) participated in the first Delphi round. Of the 103 experts, 55 (53.3%) participated in the second round. The final consensus meetings were attended by 10.7% (11/103) of the experts. We identified 16 priority areas, which involved many applications of technologies, including care for patients and caregivers, self-management and reporting of diseases, education and training, communication, care coordination, and research methodology. We summarized the priority areas into eight topics: big data, mobile devices, telehealth and telemedicine, virtual reality, artificial intelligence, smart home, biotechnology, and digital legacy. Conclusions:The priorities identified in this study represent a wide range of important emerging areas in the fields of digital health, personalized medicine, and data science. Human-centered design and robust governance systems should be considered in future research. It is important that the risks of using these technologies in palliative care are properly addressed to ensure that these tools are used meaningfully, wisely, and safely and do not cause unintentional harm
From DNA sequence to application: possibilities and complications
The development of sophisticated genetic tools during the past 15 years have facilitated a tremendous increase of fundamental and application-oriented knowledge of lactic acid bacteria (LAB) and their bacteriophages. This knowledge relates both to the assignments of open reading frames (ORF’s) and the function of non-coding DNA sequences. Comparison of the complete nucleotide sequences of several LAB bacteriophages has revealed that their chromosomes have a fixed, modular structure, each module having a set of genes involved in a specific phase of the bacteriophage life cycle. LAB bacteriophage genes and DNA sequences have been used for the construction of temperature-inducible gene expression systems, gene-integration systems, and bacteriophage defence systems.
The function of several LAB open reading frames and transcriptional units have been identified and characterized in detail. Many of these could find practical applications, such as induced lysis of LAB to enhance cheese ripening and re-routing of carbon fluxes for the production of a specific amino acid enantiomer. More knowledge has also become available concerning the function and structure of non-coding DNA positioned at or in the vicinity of promoters. In several cases the mRNA produced from this DNA contains a transcriptional terminator-antiterminator pair, in which the antiterminator can be stabilized either by uncharged tRNA or by interaction with a regulatory protein, thus preventing formation of the terminator so that mRNA elongation can proceed. Evidence has accumulated showing that also in LAB carbon catabolite repression in LAB is mediated by specific DNA elements in the vicinity of promoters governing the transcription of catabolic operons.
Although some biological barriers have yet to be solved, the vast body of scientific information presently available allows the construction of tailor-made genetically modified LAB. Today, it appears that societal constraints rather than biological hurdles impede the use of genetically modified LAB.
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