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Protein tyrosine phosphatase 4A3 (PTP4A3 or PRL-3) is highly expressed in a variety of cancers, where it promotes tumor cell migration and metastasis leading to poor prognosis. Despite its clinical significance, small molecule inhibitors of PRL-3 are lacking. Here, we screened 1443 FDA-approved drugs for their ability to inhibit the activity of the PRL phosphatase family. We identified five specific inhibitors for PRL-3 as well as one selective inhibitor of PRL-2. Additionally, we found nine drugs that broadly and significantly suppressed PRL activity. Two of these broad-spectrum PRL inhibitors, Salirasib and Candesartan, blocked PRL-3-induced migration in human embryonic kidney cells with no impact on cell viability. Both drugs prevented migration of human colorectal cancer cells in a PRL-3 dependent manner and were selective towards PRLs over other phosphatases. In silico modeling revealed that Salirasib binds a putative allosteric site near the WPD loop of PRL-3, while Candesartan binds a potentially novel targetable site adjacent to the CX 5 R motif. Inhibitor binding at either of these sites is predicted to trap PRL-3 in a closed conformation, preventing substrate binding and inhibiting function.

Biliverdin IXβ reductase (BLVRB) has emerged as a promising therapeutic target for thrombocytopenia due to its involvement in reactive oxygen species (ROS) mechanisms. During the pursuit of inhibitors targeting BLVRB, olsalazine (OSA) became apparent as one of the most potent candidates. However, the direct application of OSA as a BLVRB inhibitor faces challenges, as it is prone to degradation into 5-aminosalicylic acid through cleavage of the diazenyl bond by abundant azoreductase (AzoR) enzymes in gut microbiota and eukaryotic cells. To overcome this obstacle, we devised olsalkene (OSK), an inhibitor where the diazenyl bond in OSA has been substituted with an alkene bond. OSK not only matches the efficacy of OSA but also demonstrates improved stability against degradation by AzoR, presenting a promising solution to this limitation. Furthermore, we have found that both OSK and OSA inhibit BLVRB, regardless of the presence of nicotinamide adenine dinucleotide phosphate, unlike other known inhibitors. This discovery opens new avenues for investigating the roles of BLVRB in blood disorders, including thrombocytopenia.

In this work, the enzymatic cocktail produced by Pleurotus djamor fungi extracted at pH of 4.8 and 5.3 was employed for castor cake solid-state treatment. Proximal, X-ray powder diffraction and scanning electron microscopy analysis of the pristine castor cake were carried out. First, Pleurotus djamor stain was inoculated in castor cake for the enzymatic production and the enzymatic activity was determined. The maximum enzymatic activity was identified at days 14 (65.9 UI/gss) and 11 (140.3 UI/gss) for the enzymatic cocktail obtained at pH 5.3 and 4.8, respectively. Then, the enzymatic cocktail obtained at the highest enzymatic activity days was employed directly over castor cake. Lignin was degraded throughout incubation time achieving a 47 and 45% decrease for the cocktail produced at pH 4.8 and 5.3, correspondingly. These results were corroborated by the SEM and XRD analysis where a higher porosity and xylan degradation were perceived throughout the enzymatic treatment.

Tritium is released abundantly to the environment by nuclear power plants (NPP), as a product of neutron capture by hydrogen and deuterium. In normal running conditions, released cooling waters may contain levels of tritium close to or even larger than the maximum authorised limit for human consumption (drinking and irrigation). The European Council Directive 2013/51/Euratom requires a maximum level of tritium in water for human consumption lower than 100 Bq=L. Current monitoring of tritium activity in water by liquid scintillating method takes about two days and can only be carried out in a dedicated laboratory. This system is not appropriate for real time monitoring. At present, there exists no available detector device with enough sensitivity to monitor waters for human consumption with high enough sensitivity. The goal of the TRITIUM project is to build a tritium monitor capable to measure tritium activities with detection limit close to 100Bq=L, using instrumentation technique developed in recent years for Nuclear and Particle Physics, such as scintillating fibres and silicon photomultipliers (SiPM). In this paper the current status of the TRITIUM project is presented and he results of first prototypes are discussed. A detector system based on scintillating fibers read out either photomultiplier tubes (PMTs) or silicon photomultiplier (SiPM) arrays is under development and will be installed in the vicinity of Almaraz nuclear power plant (Cáceres, Spain) by the fourth term of 2019.

The Middle American rust resistance gene Ur-11 present in common bean ( Phaseolus vulgaris L.) confers resistance to all but one known race of the pathogen Uromyces appendiculatus (Pers.) Unger. Even though progress has been made in understanding the host–pathogen interactions between common bean and U. appendiculatus , the causal alleles of the majority of rust resistance loci, including Ur-11, remain unknown. A genome-wide association study (GWAS) was conducted to identify genomic regions associated with resistance to the U. appendiculatus race 31–22, which is avirulent to Ur-11 but virulent to other Middle American rust resistance genes. GWAS using genotypic data consisting of approximately 70,959 SNP markers and phenotypic data based on the median reaction type (1–9 scale) of a panel of 357 Middle American breeding lines and cultivars, plus 5 germplasm lines with the Ur-11 locus derived from PI 181996, located Ur-11 on chromosome Pv11. Twenty-seven SNP markers clustered in the 55.16–55.56 Mb region of the P. vulgaris UI111 reference. Multiple DNA sequence alignments detected a missense mutation [c.1,328A > G] in the PvUI111.11G202400 gene model that encodes a leucine-rich repeat-containing protein in response to race 31–22. A PCR allele competitive extension marker (PACE) was developed and tested across a panel of ~ 700 Middle American dry bean genotypes. No recombination event was observed for the PACE marker among the tested genotypes; suggesting that the polymorphism on which it is based is very close to or in the Ur-11 gene. This PACE marker will be a useful and reliable marker for marker-assisted selection of Ur-11 -based resistance to bean rust.

The full data set of the NEMO-3 experiment has been used to measure the half-life of the two-neutrino double beta decay of \\[^{100}\\]Mo to the ground state of \\[^{100}\\]Ru, \\[T_{1/2} = \\left[ 6.81 \\pm 0.01\\,\\left( \\text{ stat }\\right) ^{+0.38}_{-0.40}\\,\\left( \\text{ syst }\\right) \\right] \\times 10^{18}\\] year. The two-electron energy sum, single electron energy spectra and distribution of the angle between the electrons are presented with an unprecedented statistics of \\[5\\times 10^5\\] events and a signal-to-background ratio of \\[\\sim \\] 80. Clear evidence for the Single State Dominance model is found for this nuclear transition. Limits on Majoron emitting neutrinoless double beta decay modes with spectral indices of \\[\\mathrm{n}=2,3,7\\], as well as constraints on Lorentz invariance violation and on the bosonic neutrino contribution to the two-neutrino double beta decay mode are obtained.

A space-adapted visible and infrared spectrograph has been developed for the SNAP (SuperNova/Acceleration Probe) experiment proposed for JDEM. The instrument should have a high sensitivity to see faint supernovae, but also a good redshift determination better than0.003(1 + z) 0.003 ( 1 + z ) , and a precise spectrophotometry (2%). An instrument based on an integral-field method with the powerful concept of imager slicing has been designed. A large prototyping effort has been performed in France that validates the concept. In particular, a demonstrator reproducing the full optical configuration has been built and tested to prove the optical performance both in the visible and in the near-infrared range. This article, the first of two, focuses on wavelength measurement, while the second article will report on spectrophotometric performance. We address here the spectral accuracy expected both in the visible and in the near-infrared range in such a configuration, and we demonstrate, in particular, that the image slicer enhances the instrumental performances in the spectral measurement precision by removing the slit effect. This work is supported in France by CNRS/INSU/IN2P3 and by the French space agency (CNES), and in the US by the University of California.

A bstract This article presents the potential of a combined analysis of the JUNO and KM3NeT/ORCA experiments to determine the neutrino mass ordering. This combination is particularly interesting as it significantly boosts the potential of either detector, beyond simply adding their neutrino mass ordering sensitivities, by removing a degeneracy in the determination of ∆ m 31 2 between the two experiments when assuming the wrong ordering. The study is based on the latest projected performances for JUNO, and on simulation tools using a full Monte Carlo approach to the KM3NeT/ORCA response with a careful assessment of its energy systematics. From this analysis, a 5 σ determination of the neutrino mass ordering is expected after 6 years of joint data taking for any value of the oscillation parameters. This sensitivity would be achieved after only 2 years of joint data taking assuming the current global best-fit values for those parameters for normal ordering.

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.