4,220 research outputs found
The Cauchy Operator for Basic Hypergeometric Series
We introduce the Cauchy augmentation operator for basic hypergeometric
series. Heine's transformation formula and Sears'
transformation formula can be easily obtained by the symmetric property of some
parameters in operator identities. The Cauchy operator involves two parameters,
and it can be considered as a generalization of the operator . Using
this operator, we obtain extensions of the Askey-Wilson integral, the Askey-Roy
integral, Sears' two-term summation formula, as well as the -analogues of
Barnes' lemmas. Finally, we find that the Cauchy operator is also suitable for
the study of the bivariate Rogers-Szeg\"o polynomials, or the continuous big
-Hermite polynomials.Comment: 21 pages, to appear in Advances in Applied Mathematic
Computational modelling of optical tweezers with many degrees of freedom using dynamic simulation: cylinders, nanowires, and multiple particles
Computational tasks such as the calculation and characterization of the optical force acting on a sphere are relatively straightforward in a Gaussian beam trap. Resulting properties of the trap such as the trap strength, spring constants, and equilibrium position can be easily determined. More complex systems with non-spherical particles or multiple particles add many more degrees of freedom to the problem. Extension of the simple methods used for single spherical particles could result in required computational time of months or years. Thus, alternative methods must be used. One powerful tool is to use dynamic simulation: model the dynamics and motion of a particle or particles within the trap. We demonstrate the use of dynamic simulation for non-spherical particles and multi-particle systems. Using a hybrid discrete dipole approximation (DDA) and T-matrix method, we find plausible equilibrium positions and orientations of cylinders of varying size and aspect ratio. Orientation landscapes revealing different regimes of behaviour for micro-cylinders and nanowires with different refractive indices trapped with beams of differing polarization are also presented. This investigation provides a solid background in both the function and properties of micro-cylinders and nanowires trapped in optical tweezers. This method can also be applied to particles with other shapes. We also investigate multiple-particle trapping, which is quite different from single particle systems, as they can include effects such as optical binding. We show that equilibrium positions, and the strength of interactions between particles can be found in systems of two and more particles
Interleukin-23 engineering improves CAR T cell function in solid tumors
Cytokines that stimulate T cell proliferation, such as interleukin (IL)-15, have been explored as a means of boosting the antitumor activity of chimeric antigen receptor (CAR) T cells. However, constitutive cytokine signaling in T cells and activation of bystander cells may cause toxicity. IL-23 is a two-subunit cytokine known to promote proliferation of memory T cells and T helper type 17 cells. We found that, upon T cell antigen receptor (TCR) stimulation, T cells upregulated the IL-23 receptor and the IL-23α p19 subunit, but not the p40 subunit. We engineered expression of the p40 subunit in T cells (p40-Td cells) and obtained selective proliferative activity in activated T cells via autocrine IL-23 signaling. In comparison to CAR T cells, p40-Td CAR T cells showed improved antitumor capacity in vitro, with increased granzyme B and decreased PD-1 expression. In two xenograft and two syngeneic solid tumor mouse models, p40-Td CAR T cells showed superior efficacy in comparison to CAR T cells and attenuated side effects in comparison to CAR T cells expressing IL-18 or IL-15
Probability Density Function of Longitudinal Velocity Increment in Homogeneous Turbulence
Two conditional averages for the longitudinal velocity increment u_r of the
simulated turbulence are calculated: h(u_r) is the average of the increment of
the longitudinal Laplacian velocity field with u_r fixed, while g(u_r) is the
corresponding one of the square of the difference of the gradient of the
velocity field. Based on the physical argument, we suggest the formulae for h
and g, which are quite satisfactorily fitted to the 512^3 DNS data. The
predicted PDF is characterized as
(1) the Gaussian distribution for the small amplitudes,
(2) the exponential distribution for the large ones, and (3) a prefactor
before the exponential function for the intermediate ones.Comment: 4 pages, 4 figures, using RevTeX3.
Gene expression time delays & Turing pattern formation systems
The incorporation of time delays can greatly affect the behaviour of partial differential equations and dynamical systems. In addition, there is evidence that time delays in gene expression due to transcription and translation play an important role in the dynamics of cellular systems. In this paper, we investigate the effects of incorporating gene expression time delays into a one-dimensional putative reaction diffusion pattern formation mechanism on both stationary domains and domains with spatially uniform exponential growth. While oscillatory behaviour is rare, we find that the time taken to initiate and stabilise patterns increases dramatically as the time delay is increased. In addition, we observe that on rapidly growing domains the time delay can induce a failure of the Turing instability which cannot be predicted by a naive linear analysis of the underlying equations about the homogeneous steady state. The dramatic lag in the induction of patterning, or even its complete absence on occasions, highlights the importance of considering explicit gene expression time delays in models for cellular reaction diffusion patterning
CD30-redirected chimeric antigen receptor T cells target CD30+ and CD30- embryonal carcinoma via antigen-dependent and fas/fasl interactions
Tumor antigen heterogeneity limits success of chimeric antigen receptor (CAR) T-cell therapies. Embryonal carcinomas (EC) and mixed testicular germ cell tumors (TGCT) containing EC, which are the most aggressive TGCT subtypes, are useful for dissecting this issue as ECs express the CD30 antigen but also containCD30-/dim cells.Wefound that CD30- redirected CAR T cells (CD30.CAR T cells) exhibit antitumor activity in vitro against the human EC cell lines Tera-1, Tera-2, and NCCIT and putative EC stem cells identified by Hoechst dye staining. Cytolytic activity of CD30.CAR T cells was complemented by their sustained proliferation and proinflammatory cytokine production. CD30.CAR T cells also demonstrated antitumor activity in an in vivo xenograft NOD/SCID/gcnull (NSG)mousemodel of metastatic EC.Weobserved that CD30. CAR T cells, while targeting CD30+ EC tumor cells through the CAR (i.e., antigen-dependent targeting), also eliminated surrounding CD30- EC cells in an antigen-independent manner, via a cell-cell contact-dependent Fas/FasL interaction. In addition, ectopic Fas (CD95)expression inCD30+ Fas-ECwas sufficient to improve CD30.CAR T-cell antitumor activity. Overall, these data suggest that CD30.CAR T cells might be useful as an immunotherapy for ECs. Additionally, Fas/FasL interaction between tumor cells and CAR T cells can be exploited to reduce tumor escapedue to heterogeneous antigen expression or to improve CAR T-cell antitumor activity
A novel long non-coding natural antisense RNA is a negative regulator of Nos1 gene expression
Long non-coding natural antisense transcripts (NATs) are widespread in eukaryotic species. Although recent studies indicate that long NATs are engaged in the regulation of gene expression, the precise functional roles of the vast majority of them are unknown. Here we report that a long NAT (Mm-antiNos1 RNA) complementary to mRNA encoding the neuronal isoform of nitric oxide synthase (Nos1) is expressed in the mouse brain and is transcribed from the non-template strand of the Nos1 locus. Nos1 produces nitric oxide (NO), a major signaling molecule in the CNS implicated in many important functions including neuronal differentiation and memory formation. We show that the newly discovered NAT negatively regulates Nos1 gene expression. Moreover, our quantitative studies of the temporal expression profiles of Mm-antiNos1 RNA in the mouse brain during embryonic development and postnatal life indicate that it may be involved in the regulation of NO-dependent neurogenesis
Structured Sparsity: Discrete and Convex approaches
Compressive sensing (CS) exploits sparsity to recover sparse or compressible
signals from dimensionality reducing, non-adaptive sensing mechanisms. Sparsity
is also used to enhance interpretability in machine learning and statistics
applications: While the ambient dimension is vast in modern data analysis
problems, the relevant information therein typically resides in a much lower
dimensional space. However, many solutions proposed nowadays do not leverage
the true underlying structure. Recent results in CS extend the simple sparsity
idea to more sophisticated {\em structured} sparsity models, which describe the
interdependency between the nonzero components of a signal, allowing to
increase the interpretability of the results and lead to better recovery
performance. In order to better understand the impact of structured sparsity,
in this chapter we analyze the connections between the discrete models and
their convex relaxations, highlighting their relative advantages. We start with
the general group sparse model and then elaborate on two important special
cases: the dispersive and the hierarchical models. For each, we present the
models in their discrete nature, discuss how to solve the ensuing discrete
problems and then describe convex relaxations. We also consider more general
structures as defined by set functions and present their convex proxies.
Further, we discuss efficient optimization solutions for structured sparsity
problems and illustrate structured sparsity in action via three applications.Comment: 30 pages, 18 figure
In silico assessment of potential druggable pockets on the surface of α1-Antitrypsin conformers
The search for druggable pockets on the surface of a protein is often performed on a single conformer, treated as a rigid body. Transient druggable pockets may be missed in this approach. Here, we describe a methodology for systematic in silico analysis of surface clefts across multiple conformers of the metastable protein α1-antitrypsin (A1AT). Pathological mutations disturb the conformational landscape of A1AT, triggering polymerisation that leads to emphysema and hepatic cirrhosis. Computational screens for small molecule inhibitors of polymerisation have generally focused on one major druggable site visible in all crystal structures of native A1AT. In an alternative approach, we scan all surface clefts observed in crystal structures of A1AT and in 100 computationally produced conformers, mimicking the native solution ensemble. We assess the persistence, variability and druggability of these pockets. Finally, we employ molecular docking using publicly available libraries of small molecules to explore scaffold preferences for each site. Our approach identifies a number of novel target sites for drug design. In particular one transient site shows favourable characteristics for druggability due to high enclosure and hydrophobicity. Hits against this and other druggable sites achieve docking scores corresponding to a Kd in the µM–nM range, comparing favourably with a recently identified promising lead. Preliminary ThermoFluor studies support the docking predictions. In conclusion, our strategy shows considerable promise compared with the conventional single pocket/single conformer approach to in silico screening. Our best-scoring ligands warrant further experimental investigation
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