633 research outputs found
Qualitative and quantitative characterization of exosomes secreted by rat hepatocytes
Comunicaciones a congreso
ISG15 and ISGylation is required for pancreatic cancer stem cell mitophagy and metabolic plasticity
Pancreatic cancer stem cells (PaCSCs) drive pancreatic cancer tumorigenesis, chemoresistance and metastasis. While eliminating this subpopulation of cells would theoretically result in tumor eradication, PaCSCs are extremely plastic and can successfully adapt to targeted therapies. In this study, we demonstrate that PaCSCs increase expression of interferon-stimulated gene 15 (ISG15) and protein ISGylation, which are essential for maintaining their metabolic plasticity. CRISPR-mediated ISG15 genomic editing reduces overall ISGylation, impairing PaCSCs self-renewal and their in vivo tumorigenic capacity. At the molecular level, ISG15 loss results in decreased mitochondrial ISGylation concomitant with increased accumulation of dysfunctional mitochondria, reduced oxidative phosphorylation (OXPHOS) and impaired mitophagy. Importantly, disruption in mitochondrial metabolism affects PaCSC metabolic plasticity, making them susceptible to prolonged inhibition with metformin in vivo. Thus, ISGylation is critical for optimal and efficient OXPHOS by ensuring the recycling of dysfunctional mitochondria, and when absent, a dysregulation in mitophagy occurs that negatively impacts PaCSC stemness
Improving trading saystems using the RSI financial indicator and neural networks.
Proceedings of: 11th International Workshop on Knowledge Management and Acquisition for
Smart Systems and Services (PKAW 2010), 20 August-3 September 2010, Daegu (Korea)Trading and Stock Behavioral Analysis Systems require efficient Artificial Intelligence techniques for analyzing Large Financial Datasets (LFD) and have become in the current economic landscape a significant challenge for multi-disciplinary research. Particularly, Trading-oriented Decision Support Systems based on the Chartist or Technical Analysis Relative Strength Indicator (RSI) have been published and used worldwide. However, its combination with Neural Networks as a branch of computational intelligence which can outperform previous results remain a relevant approach which has not deserved enough attention. In this paper, we present the Chartist Analysis Platform for Trading (CAST, in short) platform, a proof-of-concept architecture and implementation of a Trading Decision Support System based on the RSI and Feed-Forward Neural Networks (FFNN). CAST provides a set of relatively more accurate financial decisions yielded by the combination of Artificial Intelligence techniques to the RSI calculation and a more precise and improved upshot obtained from feed-forward algorithms application to stock value datasets.This work is supported by the Spanish Ministry of Industry,
Tourism, and Commerce under the EUREKA project SITIO (TSI-020400-2009-148),
SONAR2 (TSI-020100-2008-665 and GO2 (TSI-020400-2009-127). Furthermore,
this work is supported by the General Council of Superior Technological Education of
Mexico (DGEST). Additionally, this work is sponsored by the National Council of
Science and Technology (CONACYT) and the Public Education Secretary (SEP)
through PROMEP.Publicad
S isotopes in space : Shell-model interpretation
The structure of S isotopes is described by performing
comprehensive shell model calculations with SDPF-U and SDPFMW interactions.
Protons and neutrons are restricted to the -shell for , neutrons
start to fill the -shell for . Natural parity states are described
by only in-shell mixing, unnatural parity states with 1p-1h inter-shell neutron
excitations. With SDPF-U interaction, reported are the results for natural
parity states only because this interaction is not suitable for cross shell
excitations. Calculated energy levels, electromagnetic properties and
spectroscopic factors are in good agreement with the recently available
experimental data.Comment: 13 pages, 5 figures, 3 tables; Accepted for publication in Nuclear
Physics
Performance and operational effectiveness of evacuated flat plate solar collectors compared with conventional thermal, PVT and PV panels
The concept of an evacuated flat plate (EFP) collector was proposed over 40 years ago but, despite its professed advantages, very few manufacturers have developed commercial versions. This situation suggests both technical difficulties in manufacturing a competitively-priced sealed for life panel and a lack of awareness of the bene fits of such panels. This paper demonstrates an evacuated flat plate simulation that closely models experimental efficiency measurements. Having established the validity of the model, it compares published data for a commercial EFP collector with predictions for an optimal design to investigate whether any further efficiency improvement might be possible. The optimised design is then evaluated against alternative solar energy devices by modelling a number of possible applications. These comparisons should inform choices about solar options for delivering heat: EFP collectors are well-suited to some of these applications. Evacuated flat plate collectors are a possible alternative to concentrating collectors for Organic Rankine Cycle power generation. The annual output for all the modelled collectors was found to be a quadratic function of delivery temperature: this enabled a novel optimisation of ORC source temperature. Predictions for concentrating and non-concentrating ORC plant are compared with a PV/thermal alternative. The ORC output is significantly less than a PV panel would achieve; applications needing both heat and power are better served by PVT panels. This is an original and novel result
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