Janus kinase inhibitors: a new tool for the treatment of axial spondyloarthritis

Axial spondyloarthritis (axSpA) is a chronic inflammatory disease involving the spine, peripheral joints, and entheses. This condition causes stiffness, pain, and significant limitation of movement. In recent years, several effective therapies have become available based on the use of biologics that selectively block cytokines involved in the pathogenesis of the disease, such as tumor necrosis factor-α (TNFα), interleukin (IL)-17, and IL-23. However, a significant number of patients show an inadequate response to treatment. Over 10 years ago, small synthetic molecules capable of blocking the activity of Janus kinases (JAK) were introduced in the therapy of rheumatoid arthritis. Subsequently, their indication extended to the treatment of other inflammatory rheumatic diseases. The purpose of this review is to discuss the efficacy and safety of these molecules in axSpA therapy

Advances in the pathogenesis and treatment of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a genetically predisposed, female-predominant disease, characterized by multiple organ damage, that in its most severe forms can be life-threatening. The pathogenesis of SLE is complex and involves cells of both innate and adaptive immunity. The distinguishing feature of SLE is the production of autoantibodies, with the formation of immune complexes that precipitate at the vascular level, causing organ damage. Although progress in understanding the pathogenesis of SLE has been slower than in other rheumatic diseases, new knowledge has recently led to the development of effective targeted therapies, that hold out hope for personalized therapy. However, the new drugs available to date are still an adjunct to conventional therapy, which is known to be toxic in the short and long term. The purpose of this review is to summarize recent advances in understanding the pathogenesis of the disease and discuss the results obtained from the use of new targeted drugs, with a look at future therapies that may be used in the absence of the current standard of care or may even cure this serious systemic autoimmune disease

Flux creep in Bi2Sr2CaCu2O8(sub +x) single crystals

The results of a magnetic study on a Bi2Sr2CaCu2O(8+x) single crystal are reported. Low field susceptibility (dc and ac), magnetization cycles and time dependent measurements were performed. With increasing the temperature the irreversible regime of the magnetization cycles is rapidly restricted to low fields, showing that the critical current J(sub c) becomes strongly field dependent well below T(sub c). At 2.4 K the critical current in zero field, determined from the remanent magnetization by using the Bean formula for the critical state, is J(sub c) = 2 10(exp 5) A/sq cm. The temperature dependence of J(sub c) is satisfactorily described by the phenomenological law J(sub c) = J(sub c) (0) (1 - T/T(sub c) (sup n), with n = 8. The time decay of the zero field cooled magnetization and of the remanent magnetization was studied at different temperatures for different magnetic fields. The time decay was found to be logarithmic in both cases, at least at low temperatures. At T = 4.2 K for a field of 10 kOe applied parallel to the c axis, the average pinning energy, determined by using the flux creep model, is U(sub o) = 0.010 eV

Solving classification tasks by a receptron based on nonlinear optical speckle fields

Among several approaches to tackle the problem of energy consumption in modern computing systems, two solutions are currently investigated: one consists of artificial neural networks (ANNs) based on photonic technologies, the other is a different paradigm compared to ANNs and it is based on random networks of nonlinear nanoscale junctions resulting from the assembling of nanoparticles or nanowires as substrates for neuromorphic computing. These networks show the presence of emergent complexity and collective phenomena in analogy with biological neural networks characterized by self-organization, redundancy, non-linearity. Starting from this background, we propose and formalize a generalization of the perceptron model to describe a classification device based on a network of interacting units where the input weights are nonlinearly dependent. We show that this model, called "receptron", provides substantial advantages compared to the perceptron as, for example, the solution of non-linearly separable Boolean functions with a single device. The receptron model is used as a starting point for the implementation of an all-optical device that exploits the non-linearity of optical speckle fields produced by a solid scatterer. By encoding these speckle fields we generated a large variety of target Boolean functions without the need for time-consuming machine learning algorithms. We demonstrate that by properly setting the model parameters, different classes of functions with different multiplicity can be solved efficiently. The optical implementation of the receptron scheme opens the way for the fabrication of a completely new class of optical devices for neuromorphic data processing based on a very simple hardware

Discovery of chemotherapy-associated ovarian cancer antigens by interrogating memory T cells

According to the immunogenic cell death hypothesis, clinical chemotherapy treatments may result in CD8(+) and CD4(+) T-cell responses against tumor cells. To discover chemotherapy-associated antigens (CAAs), T cells derived from ovarian cancer (OC) patients (who had been treated with appropriate chemotherapy protocols) were interrogated with proteins isolated from primary OC cells. We screened for immunogenicity using two-dimensional electrophoresis gel-eluted OC proteins. Only the selected immunogenic antigens were molecularly characterized by mass-spectrometry-based analysis. Memory T cells that recognized antigens associated with apoptotic (but not live) OC cells were correlated with prolonged survival in response to chemotherapy, supporting the model of chemotherapy-induced apoptosis as an adjuvant of anti-tumor immunity. The strength of both memory CD4(+) and CD8(+) T cells producing either IFN- or IL-17 in response to apoptotic OC antigens was also significantly greater in Responders to chemotherapy than in nonresponders. Immunogenicity of some of these antigens was confirmed using recombinant proteins in an independent set of patients. The T-cell interrogation system represents a strategy of reverse tumor immunology that proposes to identify CAAs, which may then be validated as possible prognostic tumor biomarkers or cancer vaccines

Combination of chemotherapy and PD-1 blockade induces T cell responses to tumor non-mutated neoantigens

Grimaldi and Cammarata et al. develop a proteomics-based, target discovery platform to identify immunogenic proteins specific to apoptotic tumor cells. This study highlights the importance of protein modifications in apoptotic tumor cells as a mechanism of generating immunogenic neoantigens that can be targeted for T cell-based immunotherapy.Here, we developed an unbiased, functional target-discovery platform to identify immunogenic proteins from primary non-small cell lung cancer (NSCLC) cells that had been induced to apoptosis by cisplatin (CDDP) treatment in vitro, as compared with their live counterparts. Among the multitude of proteins identified, some of them were represented as fragmented proteins in apoptotic tumor cells, and acted as non-mutated neoantigens (NM-neoAgs). Indeed, only the fragmented proteins elicited effective multi-specific CD4(+) and CD8(+) T cell responses, upon a chemotherapy protocol including CDDP. Importantly, these responses further increased upon anti-PD-1 therapy, and correlated with patients' survival and decreased PD-1 expression. Cross-presentation assays showed that NM-neoAgs were unveiled in apoptotic tumor cells as the result of caspase-dependent proteolytic activity of cellular proteins. Our study demonstrates that apoptotic tumor cells generate a repertoire of immunogenic NM-neoAgs that could be potentially used for developing effective T cell-based immunotherapy across multiple cancer patients

Brixsino High-Flux Dual X-Ray and THz Radiation Source Based on Energy Recovery Linacs

We present the conceptual design of a compact light source named BriXSinO. BriXSinO was born as demonstrator of the Marix project, but it is also a dual high flux radiation source Inverse Compton Source (ICS) of X-ray and Free-Electron Laser of THz spectral range radiation conceived for medical applications and general applied research. The accelerator is a push-pull CW-SC Energy Recovery Linac (ERL) based on superconducting cavities technology and allows to sustain MW-class beam power with almost just one hundred kW active power dissipation/consumption. ICS line produces 33 keV monochromatic X-Rays via Compton scattering of the electron beam with a laser system in Fabry-Pérot cavity at a repetition rate of 100 MHz. The THz FEL oscillator is based on an undulator imbedded in optical cavity and generates THz wavelengths from 15 to 50 micron

A coherent polarimeter array for the Large Scale Polarization Explorer balloon experiment

We discuss the design and expected performance of STRIP (STRatospheric Italian Polarimeter), an array of coherent receivers designed to fly on board the LSPE (Large Scale Polarization Explorer) balloon experiment. The STRIP focal plane array comprises 49 elements in Q band and 7 elements in W-band using cryogenic HEMT low noise amplifiers and high performance waveguide components. In operation, the array will be cooled to 20 K and placed in the focal plane of a $\sim 0.6$ meter telescope providing an angular resolution of $\sim1.5$ degrees. The LSPE experiment aims at large scale, high sensitivity measurements of CMB polarization, with multi-frequency deep measurements to optimize component separation. The STRIP Q-band channel is crucial to accurately measure and remove the synchrotron polarized component, while the W-band channel, together with a bolometric channel at the same frequency, provides a crucial cross-check for systematic effects.Comment: In press on the Proceedings of the SPIE Conference Astronomical Telescopes + instrumentation 2012, Amsterdam, paper 8446-27

Odontostomatologic management of patients receiving oral anticoagulant therapy: a retrospective multicentric study

Introduction: Today, we frequently find patients taking oral anticoagulant therapy (OAT), a prophylaxis against the occurrence of thromboembolic events. An oral surgeon needs to know how to better manage such patients, in order to avoid hemorrhagic and thromboembolic complications. Materials and methods: A group of 193 patients (119 men aged between 46 and 82 and 74 women aged between 54 and 76) undergoing OAT for more than 5 years were managed with a standardized management protocol and a 2-months follow-up. The aim of the present study was to apply a protocol, which could provide a safe intra- and postoperative management of patients on OAT. Results: Among the 193 patients, only 2 had postoperative complications. Conclusions: We think that the protocol used in the present study can be used for complete safety in the treatment of this type of patients. Keywords: Oral Anticoagulant Therapy (OAT), Tranexamic Acid, Oral Surger

The Utilization of Data Analysis Techniques in Predicting Student Performance in Massive Open Online Courses (MOOCs)

The growth of the Internet has enabled the popularity of open online learning platforms to increase over the years. This has led to the inception of Massive Open Online Courses (MOOCs) that enrol, millions of people, from all over the world. Such courses operate under the concept of open learning, where content does not have to be delivered via standard mechanisms that institutions employ, such as physically attending lectures. Instead learning occurs online via recorded lecture material and online tasks. This shift has allowed more people to gain access to education, regardless of their learning background. However, despite these advancements in delivering education, completion rates for MOOCs are low. In order to investigate this issue, the paper explores the impact that technology has on open learning and identifies how data about student performance can be captured to predict trend so that at risk students can be identified before they drop-out. In achieving this, subjects surrounding student engagement and performance in MOOCs and data analysis techniques are explored to investigate how technology can be used to address this issue. The paper is then concluded with our approach of predicting behaviour and a case study of the eRegister system, which has been developed to capture and analyse data. Keywords: Open Learning; Prediction; Data Mining; Educational Systems; Massive Open Online Course; Data Analysi