The n-acetyl phenylalanine glucosamine derivative attenuates the inflammatory/catabolic environment in a chondrocyte-synoviocyte co-culture system

Osteoarthritis (OA), the most prevalent degenerative joint disease, still lacks a true disease-modifying therapy. The involvement of the NF-κB pathway and its upstream activating kinases in OA pathogenesis has been recognized for many years. The ability of the N-acetyl phenylalanine glucosamine derivative (NAPA) to increase anabolism and reduce catabolism via inhibition of IKKα kinase has been previously observed in vitro and in vivo. The present study aims to confirm the chondroprotective effects of NAPA in an in vitro model of joint OA established with primary cells, respecting both the crosstalk between chondrocytes and synoviocytes and their phenotypes. This model satisfactorily reproduces some features of the previously investigated DMM model, such as the prominent induction of ADAMTS-5 upon inflammatory stimulation. Both gene and protein expression analysis indicated the ability of NAPA to counteract key cartilage catabolic enzymes (ADAMTS-5) and effectors (MCP-1). Molecular analysis showed the ability of NAPA to reduce IKKα nuclear translocation and H3Ser10 phosphorylation, thus inhibiting IKKα transactivation of NF-κB signalling, a pivotal step in the NF-κB-dependent gene expression of some of its targets. In conclusion, our data confirm that NAPA could truly act as a disease-modifying drug in OA

The ``Out-Longitudinal'' Cross Term and Other Model Independent Features of the Two-Particle HBT Correlation Function

Using two specific models and a model independent formalism, we show that an ``out-longitudinal'' cross term should be included in any gaussian fits to correlation data. In addition, we show that correlation radii (including the cross term) measure lengths of homogeneity within the source, not necessarily geometric sizes.Comment: 4 pages, uuencoded compressed postscrip

Full counting statistics and phase diagram of a dissipative Rydberg gas

Ultra-cold gases excited to strongly interacting Rydberg states are a promising system for quantum simulations of many-body systems. For off-resonant excitation of such systems in the dissipative regime, highly correlated many-body states exhibiting, among other characteristics, intermittency and multi-modal counting distributions are expected to be created. So far, experiments with Rydberg atoms have been carried out in the resonant, non-dissipative regime. Here we realize a dissipative gas of rubidium Rydberg atoms and measure its full counting statistics for both resonant and off-resonant excitation. We find strongly bimodal counting distributions in the off-resonant regime that are compatible with intermittency due to the coexistence of dynamical phases. Moreover, we measure the phase diagram of the system and find good agreement with recent theoretical predictions. Our results pave the way towards detailed studies of many-body effects in Rydberg gases.Comment: 12 pages, 5 figure

Urticaria associated with hyper-IgE in a patient with psoriasis undergoing treatment with efalizumab.

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Feature Selection Based on a Genetic Algorithm for Optimizing Weaning Success

Finding the right time for weaning from ventilator is a difficult clinical decision. Several systems based on machine or deep learning are reported in literature. However, the results of these applications are not completely satisfactory and may be improved. An important aspect is represented by the features used as input of these systems. In this paper we present the results of the application of genetic algorithms to perform feature selection on a dataset containing 13688 patients under mechanical ventilation characterizing by 58 variables, extracted from the MIMIC III database. The results show that all features are important, but four of them are essential: 'Sedation_days', 'Mean_Airway_Pressure', 'PaO2', and 'Chloride'. This is only the initial step to obtain a tool to be added to the other clinical indices for minimize the risk of extubation failure

Immuno-Metabolism and Microenvironment in Cancer: Key Players for Immunotherapy

Immune checkpoint inhibitors (ICIs) have changed therapeutic algorithms in several malignancies, although intrinsic and secondary resistance is still an issue. In this context, the dysregulation of immuno-metabolism plays a leading role both in the tumor microenvironment (TME) and at the host level. In this review, we summarize the most important immune-metabolic factors and how they could be exploited therapeutically. At the cellular level, an increased concentration of extracellular adenosine as well as the depletion of tryptophan and uncontrolled activation of the PI3K/AKT pathway induces an immune-tolerant TME, reducing the response to ICIs. Moreover, aberrant angiogenesis induces a hypoxic environment by recruiting VEGF, Treg cells and immune-suppressive tumor associated macrophages (TAMs). On the other hand, factors such as gender and body mass index seem to affect the response to ICIs, while the microbiome composition (and its alterations) modulates both the response and the development of immune-related adverse events. Exploiting these complex mechanisms is the next goal in immunotherapy. The most successful strategy to date has been the combination of antiangiogenic drugs and ICIs, which prolonged the survival of patients with non-small-cell lung cancer (NSCLC) and hepatocellular carcinoma (HCC), while results from tryptophan pathway inhibition studies are inconclusive. New exciting strategies include targeting the adenosine pathway, TAMs and the microbiota with fecal microbiome transplantation

Comparison between manual scaling and Autoscala automatic scaling applied to Sodankylä Geophysical Observatory ionograms

This paper presents a comparison between standard ionospheric parameters manually and automatically scaled from ionograms recorded at the high-latitude Sodankylä Geophysical Observatory (SGO, ionosonde SO166, 64.1° geomagnetic latitude), located in the vicinity of the auroral oval. The study is based on 2610 ionograms recorded during the period June–December 2013. The automatic scaling was made by means of the Autoscala software. A few typical examples are shown to outline the method, and statistics are presented regarding the differences between manually and automatically scaled values of F2, F1, E and sporadic E (Es) layer parameters. We draw the conclusions that: 1. The F2 parameters scaled by Autoscala, foF2 and M(3000)F2, are reliable. 2. F1 is identified by Autoscala in significantly fewer cases (about 50 %) than in the manual routine, but if identified the values of foF1 are reliable. 3. Autoscala frequently (30% of the cases) detects an E layer when the manual scaling process does not. When identified by both methods, the Autoscala E-layer parameters are close to those manually scaled, foE agreeing to within 0.4 MHz. 4. Es and parameters of Es identified by Autoscala are in many cases different from those of the manual scaling. Scaling of Es at auroral latitudes is often a difficult task

NATO and CSDP: party and public positioning in Germany and France

This is the final version. Available on open access from the NATO Defense College via the link in this recordVolkswagen Foundatio