Effects of acute exercise on expressions of functional receptors on CD56dim and CD56bright natural killer cells

PURPOSE: Mobilization and cytotoxicity of natural killer (NK) cells are regulated by cell surface receptors such as adhesion molecules and activating/inhibitory receptors. In this study, we examined the effects of acute exercise on the expression of these cell surface molecules and receptors. METHODS: Six healthy male college students (22.8 ± 0.8 years olds) exercised on the cycle ergometer for 30 min at intensities corresponding to the individual onset of blood lactate accumulation level (70-85%VO2max). Venous blood samples were collected at rest (PRE); just before the end of exercise (END) and 30 (POST 30), 60 (POST 60), 120 (POST 120) and 180 (POST 180) min post exercise. The densities of cell surface molecules and receptors on CD56dim and CD56bright NK cells were determined by flow cytometry. One-way ANOVA and MANOVA were used for statistical analyses. RESULTS: At PRE, expressions of CD16, CD56, CD44, CD62L, CD314, CD335, CD159a and CX3CR1 differed between CD56dim and CD56bright NK cells. Expressions of adhesion molecules CD62L and CX3CR1 changed significantly in both subsets during and after exercise. The expressions of CD62L tended to decrease at END, and then they increased significantly at POST 30. These changes were mainly due to the proportional changes in CD62Lnegative cells. The opposite patterns of changes were seen in the expressions of CX3CR1. Additionally, the expressions of CX3CR1 decreased at POST 120 and 180 only in CD56dim NK cells. The changes in the expressions of CD44 were similar to those seen in the expressions of CD62L. Although changes in the expression of adhesion molecules were statistically significant, they were relatively unclear in histogram analyses. With regard to the expressions of NK cell activating/inhibitory receptors, most changes were observed in CD56dim NK cells. The expressions of CD16 decreased at END and returned at POST 30. The expressions of CD212 dropped from END to POST 30. In contrast, the expressions of CD335 increased from END to POST 30. Exceptionally, changes in the expressions of CD226 were found in both subsets. The expressions decreased at POST180. CONCLUSION: These results suggest that acute exercise influences the expressions of cell surface molecules and receptors. Changes were mainly observed at END and POST 30 in CD56dim NK cell. However, the delayed changes were also seen in some receptors. The changes in several receptors were related to cell mobilization. In contrast, the changes in other receptors were not directly related to mobilization and cytotoxicity

Precision scans of the pixel cell response of double sided 3D pixel detectors to pion and x-ray beams

hree-dimensional (3D) silicon sensors offer potential advantages over standard planar sensors for radiation hardness in future high energy physics experiments and reduced charge-sharing for X-ray applications, but may introduce inefficiencies due to the columnar electrodes. These inefficiencies are probed by studying variations in response across a unit pixel cell in a 55μm pitch double-sided 3D pixel sensor bump bonded to TimePix and Medipix2 readout ASICs. Two complementary characterisation techniques are discussed: the first uses a custom built telescope and a 120GeV pion beam from the Super Proton Synchrotron (SPS) at CERN; the second employs a novel technique to illuminate the sensor with a micro-focused synchrotron X-ray beam at the Diamond Light Source, UK. For a pion beam incident perpendicular to the sensor plane an overall pixel efficiency of 93.0±0.5% is measured. After a 10o rotation of the device the effect of the columnar region becomes negligible and the overall efficiency rises to 99.8±0.5%. The double-sided 3D sensor shows significantly reduced charge sharing to neighbouring pixels compared to the planar device. The charge sharing results obtained from the X-ray beam study of the 3D sensor are shown to agree with a simple simulation in which charge diffusion is neglected. The devices tested are found to be compatible with having a region in which no charge is collected centred on the electrode columns and of radius 7.6±0.6μm. Charge collection above and below the columnar electrodes in the double-sided 3D sensor is observed

QED and String Theory

We analyze the D9-D9bar system in type IIB string theory using Dp-brane probes. It is shown that the world-volume theory of the probe Dp-brane contains two-dimensional and four-dimensional QED in the cases with p=1 and p=3, respectively, and some applications of the realization of these well-studied quantum field theories are discussed. In particular, the two-dimensional QED (the Schwinger model) is known to be a solvable theory and we can apply the powerful field theoretical techniques, such as bosonization, to study the D-brane dynamics. The tachyon field created by the D9-D9bar strings appears as the fermion mass term in the Schwinger model and the tachyon condensation is analyzed by using the bosonized description. In the T-dualized picture, we obtain the potential between a D0-brane and a D8-D8bar pair using the Schwinger model and we observe that it consists of the energy carried by fundamental strings created by the Hanany-Witten effect and the vacuum energy due to a cylinder diagram. The D0-brane is treated quantum mechanically as a particle trapped in the potential, which turns out to be a system of a harmonic oscillator. As another application, we obtain a matrix theory description of QED using Taylor's T-duality prescription, which is actually applicable to a wide variety of field theories including the realistic QCD. We show that the lattice gauge theory is naturally obtained by regularizing the matrix size to be finite.Comment: 33 pages, Latex, 4 figures, a reference adde

The Intricacies of Identifying Equatorial Waves

Equatorial waves (EWs) are synoptic- to planetary-scale propagating disturbances at low latitudes with periods from a few days to several weeks. Here, this term includes Kelvin waves, equatorial Rossby waves, mixed Rossby–gravity waves, and inertio-gravity waves, which are well described by linear wave theory, but it also other tropical disturbances such as easterly waves and the intraseasonal Madden–Julian Oscillation with more complex dynamics. EWs can couple with deep convection, leading to a substantial modulation of clouds and rainfall. EWs are amongst the dynamic features of the troposphere with the longest intrinsic predictability, and models are beginning to forecast them with an exploitable level of skill. Most of the methods developed to identify and objectively isolate EWs in observations and model fields rely on (or at least refer to) the adiabatic, frictionless linearized primitive equations on the sphere or the shallow-water system on the equatorial -plane. Common ingredients to these methods are zonal wave-number–frequency filtering (Fourier or wavelet) and/or projections onto predefined empirical or theoretical dynamical patterns. This paper gives an overview of six different methods to isolate EWs and their structures, discusses the underlying assumptions, evaluates the applicability to different problems, and provides a systematic comparison based on a case study (February 20–May 20, 2009) and a climatological analysis (2001–2018). In addition, the influence of different input fields (e.g., winds, geopotential, outgoing long-wave radiation, rainfall) is investigated. Based on the results, we generally recommend employing a combination of wave-number–frequency filtering and spatial-projection methods (and of different input fields) to check for robustness of the identified signal. In cases of disagreement, one needs to carefully investigate which assumptions made for the individual methods are most probably not fulfilled. This will help in choosing an approach optimally suited to a given problem at hand and avoid misinterpretation of the results

A Subaru Search for Lymanα\alpha Emitters at Redshift 5.7

We present the results of a survey for Ly$\alpha$ emitters at $z\approx 5.7$ based on optical narrow-band ($\lambda_{\rm c} = 8150$ \AA ~ and $\Delta\lambda = 120$ \AA), and broad-band ($B$, $R_{\rm C}$, $I_{\rm C}$, and $z^\prime$) observations of the field surrounding the high redshift quasar, SDSSp J104433.04$-$012522.2, on the 8.2 m Subaru Telescope with the Subaru Prime Focus Camera, Suprime-Cam. This survey covers a sky area of $\approx 720$ arcmin$^2$ and a co-moving volume of $\simeq 2 \times 10^5 ~ h_{0.7}^{-3}$ Mpc$^3$. We have found 20 candidates of Ly$\alpha$ emitters at $z \approx$ 5.7 with $\Delta z \approx 0.1$. Two of them have been confirmed star-forming galaxies at $z=5.655$ and $z=5.687$ from our follow-up optical spectroscopy. We discuss star-formation properties of the 20 objects from a statistical point of view. Our survey leads to a new estimate of the star formation rate density at $z \approx 5.7$, $\sim 1.2 \times 10^{-3} h_{0.7} M_\odot$ yr$^{-1}$ Mpc$^{-3}$.Comment: 18 pages, 19 figures, accepted for A

Assessing the druggability of protein-protein interactions by a supervised machine-learning method

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions (PPIs) are challenging but attractive targets of small molecule drugs for therapeutic interventions of human diseases. In this era of rapid accumulation of PPI data, there is great need for a methodology that can efficiently select drug target PPIs by holistically assessing the druggability of PPIs. To address this need, we propose here a novel approach based on a supervised machine-learning method, support vector machine (SVM).</p> <p>Results</p> <p>To assess the druggability of the PPIs, 69 attributes were selected to cover a wide range of structural, drug and chemical, and functional information on the PPIs. These attributes were used as feature vectors in the SVM-based method. Thirty PPIs known to be druggable were carefully selected from previous studies; these were used as positive instances. Our approach was applied to 1,295 human PPIs with tertiary structures of their protein complexes already solved. The best SVM model constructed discriminated the already-known target PPIs from others at an accuracy of 81% (sensitivity, 82%; specificity, 79%) in cross-validation. Among the attributes, the two with the greatest discriminative power in the best SVM model were the number of interacting proteins and the number of pathways.</p> <p>Conclusion</p> <p>Using the model, we predicted several promising candidates for druggable PPIs, such as SMAD4/SKI. As more PPI data are accumulated in the near future, our method will have increased ability to accelerate the discovery of druggable PPIs.</p