Differences in the signaling pathways of α1A- and α1B-adrenoceptors are related to different endosomal targeting

Aims: To compare the constitutive and agonist-dependent endosomal trafficking of α1A- and α1B-adrenoceptors (ARs) and to establish if the internalization pattern determines the signaling pathways of each subtype. Methods: Using CypHer5 technology and VSV-G epitope tagged α1A- and α1B-ARs stably and transiently expressed in HEK 293 cells, we analyzed by confocal microscopy the constitutive and agonist-induced internalization of each subtype, and the temporal relationship between agonist induced internalization and the increase in intracellular calcium (determined by FLUO-3 flouorescence), or the phosphorylation of ERK1/2 and p38 MAP kinases (determined by Western blot). Results and Conclusions: Constitutive as well as agonist-induced trafficking of α1A and α1B ARs maintain two different endosomal pools of receptors: one located close to the plasma membrane and the other deeper into the cytosol. Each subtype exhibited specific characteristics of internalization and distribution between these pools that determines their signaling pathways: α1A-ARs, when located in the plasma membrane, signal through calcium and ERK1/2 pathways but, when translocated to deeper endosomes, through a mechanism sensitive to β-arrestin and concanavalin A, continue signaling through ERK1/2 and also activate the p38 pathway. α1B-ARs signal through calcium and ERK1/2 only when located in the membrane and the signals disappear after endocytosis and by disruption of the membrane lipid rafts by methyl-β-cyclodextrin

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Early phase clinical trials of anticancer agents in children and adolescents — an ITCC perspective

In the past decade, the landscape of drug development in oncology has evolved dramatically; however, this paradigm shift remains to be adopted in early phase clinical trial designs for studies of molecularly targeted agents and immunotherapeutic agents in paediatric malignancies. In drug development, prioritization of drugs on the basis of knowledge of tumour biology, molecular 'drivers' of disease and a drug's mechanism of action, and therapeutic unmet needs are key elements; these aspects are relevant to early phase paediatric trials, in which molecular profiling is strongly encouraged. Herein, we describe the strategy of the Innovative Therapies for Children with Cancer (ITCC) Consortium, which advocates for the adoption of trial designs that enable uninterrupted patient recruitment, the extrapolation from studies in adults when possible, and the inclusion of expansion cohorts. If a drug has neither serious dose-related toxicities nor a narrow therapeutic index, then studies should generally be started at the adult recommended phase II dose corrected for body surface area, and act as dose-confirmation studies. The use of adaptive trial designs will enable drugs with promising activity to progress rapidly to randomized studies and, therefore, will substantially accelerate drug development for children and adolescents with cancer

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Modelling the size and composition of fruit, grain and seed by process-based simulation models

International audienceUnderstanding what determines the size and composition of fruit, grain and seed in response to the environment and genotype is challenging, as these traits result from several linked processes controlled at different levels of organization, from the subcellular to the crop level, with subtle interactions occurring at or between the levels of organization. Process-based simulation models (PBSMs) implement algorithms to simulate metabolic and biophysical aspects of cell, tissue and organ behaviour. In this review, fruit, grain and seed PBSMs describing the main phases of growth, development and storage metabolism are discussed. From this concurrent work, it is possible to identify generic storage organ processes which can be modelled similarly for fruit, grain and seed. Spatial heterogeneity at the tissue and whole-plant level is found to be a key consideration in modelling the effects of the environment and genotype on fruit, grain and seed end-use value. In the future, PBSMs may well become the main link between studies at the molecular and whole-plant levels. To bridge this phenotype-to-genotype gap, future models need to remain plastic without becoming overparameterized