Effect of hypoxia-inducible factor 1-alpha (HIF-1α) on proliferation and apoptosis of adrenocorticotropic hormone (ACTH)-secreting pituitary adenoma cells

To understand whether hypoxia-inducible factor 1-alpha (HIF-1α) could protect AtT-20 cells from hypoxia induced apoptosis, we investigated the effects of HIF-1α on proliferation and apoptosis of adrenocorticotropic hormone (ACTH)-secreting pituitary adenoma cells (AtT-20 cells). AtT-20 cells were treated with various concentrations of CoCl2 to induce hypoxia. 3-(4,5-Dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide, a yellow tetrazole (MTT) was applied to detect the proliferation of these cells. Western blot assay and real time polymerase chain reaction (PCR) were used to determine the protein and mRNA expressions of HIF-1α, respectively. In addition, AtT-20 cells were transfected with siRNA targeting HIF-1α and treated with different concentrations of CoCl2. The transfection efficacy was assessed by real-time PCR and western blot assay. Apoptosis was measured by fluorescein isothiocyanate (FITC)-annexin V/ propidium iodide (PI) staining and TUNEL staining. The effect of CoCl2 on the proliferation of AtT-20 cells was in a concentration and time dependent manner. When the concentration of CoCl2 was ≤100 μM and/or duration of CoCl2 treatment was ≤48 h, CoCl2 triggered the proliferation of AtT-20 cells. Nevertheless, the apoptosis rate of cells transfected with HIF-1α-siRNA was markedly increased after CoCl2 treatment. These findings suggest that, HIF-1α can promote the proliferation of AtT-20 cells and exert anti-apoptotic effect under hypoxic condition.Key words: Hypoxia inducible factor–1α, cobalt chloride, apoptosis, pituitary adenom

A Comparison of Centering Algorithms in the Astrometry of Cassini Imaging Science Subsystem Images and Anthe’s Astrometric Reduction

In the CAVIAR software package, a standard tool for astrometry of images from the Cassini imaging science subsystem (ISS), Gaussian fitting is used to measure the centre of point-like objects, achieving a typical precision of about 0.2 pixels. In this work, we consider how alternative methods may improve on this. We compare three traditional centroiding methods: two-dimensional Gaussian fitting, median, and modified moment. Results using 56 selected images show that the centroiding precision of the modified moment method is significantly better than the other two methods, with standard deviations for all residuals in sample and line of 0.065 and 0.063 pixels, respectively, representing a factor of over 2 improvement compared to Gaussian fitting. Secondly, a comparison of observations using Cassini ISS images of Anthe is performed. Anthe results show a similar improvement. The modified moment method is then used to reduce all ISS images of Anthe during the period 2008–2017. The observed-minus-calculated residuals relative to the JPL SAT393 ephemeris are calculated. In terms of α × cos(δ) and δ in the Cassini-centred international celestial reference frame, mean values of all residuals are close to 0 km, and their standard deviations are less than 1 km for narrow angle camera images, and about 4 km for wide angle camera images

Technology Development Through Pooling ARV Drug Patents: A Vision from China

Unaffordable prices still bar the end-users in China from accessing ARV drugs. Patent protection of ARV drugs has dramatically limited the availability of these lifesaving drugs to AIDS patients in China

Committee Machines—A Universal Method to Deal with Non-Idealities in Memristor-Based Neural Networks

Arti ficial neural networks are notoriously power- and time-consuming when implemented on conventional von Neumann computing systems. Consequently, recent years have seen an emergence of research in machine learning hardware that strives to bring memory and computing closer together. A popular approach is to realise artifi cial neural networks in hardware by implementing their synaptic weights using memristive devices. However, various device- and system-level non-idealities usually prevent these physical implementations from achieving high inference accuracy. We suggest applying a well-known concept in computer science|committee machines|in the context of memristor-based neural networks. Using simulations and experimental data from three different types of memristive devices, we show that committee machines employing ensemble averaging can successfully increase inference accuracy in physically implemented neural networks that suffer from faulty devices, device-to-device variability, random telegraph noise and line resistance. Importantly, we demonstrate that the accuracy can be improved even without increasing the total number of memristors

The universal definition of spin current

The spin current, orbit angular momentum current and total angular momentum current in a tensor form have been universally defined according to the quantum electrodynamics. Their conservation quantities and the continuity equations have been discussed in different cases. Non-relativistic approximation forms are deduced in order to explain their physical meanings, and to analyze some experimental results. The spin current of helical edge states in HgTe/CdTe quantum wells is calculated to demonstrate the properties of the spin current of the two dimensional quantum spin-Hall system. A generalized spin-orbit coupling term in the semiconducting media is deduced based on the theory of the electrodynamics in the moving media. It is recommended to use the effective total angular momentum current instead of the pure spin current to describe the distribution of polarization and the transport properties in spintronics

Understanding public speakers’ performance: first contributions to support a computational approach

Communication is part of our everyday life and our ability to communicate can have a significant role in a variety of contexts in our personal, academic, and professional lives. For long, the characterization of what is a good communicator has been subject to research and debate by several areas, particularly in Education, with a focus on improving the performance of teachers. In this context, the literature suggests that the ability to communicate is not only defined by the verbal component, but also by a plethora of non-verbal contributions providing redundant or complementary information, and, sometimes, being the message itself. However, even though we can recognize a good or bad communicator, objectively, little is known about what aspects – and to what extent—define the quality of a presentation. The goal of this work is to create the grounds to support the study of the defining characteristics of a good communicator in a more systematic and objective form. To this end, we conceptualize and provide a first prototype for a computational approach to characterize the different elements that are involved in communication, from audiovisual data, illustrating the outcomes and applicability of the proposed methods on a video database of public speakers.publishe