Semantic segmentation based on Deep learning for the detection of Cyanobacterial Harmful Algal Blooms (CyanoHABs) using synthetic images

Cyanobacterial Harmful Algal Blooms (CyanoHABs) in lakes and reservoirs have increased substantially in recent decades due to different environmental factors. Its early detection is a crucial issue to minimize health effects, particularly in potential drinking and recreational water bodies. The use of Autonomous Surface Vehicles (ASVs) equipped with machine vision systems (cameras) onboard, represents a useful alternative at this time. In this regard, we propose an image Semantic Segmentation approach based on Deep Learning with Convolutional Neural Networks (CNNs) for the early detection of CyanoHABs considering an ASV perspective. The use of these models is justified by the fact that with their convolutional architecture, it is possible to capture both, spectral and textural information considering the context of a pixel and its neighbors. To train these models it is necessary to have data, but the acquisition of real images is a difficult task, due to the capricious appearance of the algae on water surfaces sporadically and intermittently over time and after long periods of time, requiring even years and the permanent installation of the image capture system. This justifies the generation of synthetic data so that sufficiently trained models are required to detect CyanoHABs patches when they emerge on the water surface. The data generation for training and the use of the semantic segmentation models to capture contextual information determine the need for the proposal, as well as its novelty and contribution. Three datasets of images containing CyanoHABs patches are generated: (a) the first contains real patches of CyanoHABs as foreground and images of lakes and reservoirs as background, but with a limited number of examples; (b) the second, contains synthetic patches of CyanoHABs generated with state-of-the-art Style-based Generative Adversarial Network Adaptive Discriminator Augmentation (StyleGAN2-ADA) and Neural Style Transfer as foreground and images of lakes and reservoirs as background, and (c) the third set, is the combination of the previous two. Four model architectures for semantic segmentation (UNet++, FPN, PSPNet, and DeepLabV3+), with two encoders as backbone (ResNet50 and EfficientNet-b6), are evaluated from each dataset on real test images and different distributions. The results show the feasibility of the approach and that the UNet++ model with EfficientNet-b6, trained on the third dataset, achieves good generalization and performance for the real test images.Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEComunidad Autónoma de MadridSpanish Ministry of Science, Innovation and UniversitiesMinistry of Education of PeruSpanish Ministry of Universitiespu

The Freundlich model of adsorption for calculation of specific surface areaS

The specific surface area of solids and the surface area occupied by the active phase (metal or oxide) on a support are parameters of the utmost importance in adsorption and catalysis. For the determination of the former, the BET equation is universally established. For the evaluation of the latter the works of selective chemisorption, initiated by Emmett and Brunauer (I ), for metals and by Bridges et al. (2) and Weller et al. (3), for oxides have come to represent important contributions. Some of the classical models of adsorption have also been used for evaluation of specific surfaces (Langmuir equation) (4) and the dispersion of supported metals or oxides (Freundlich equation) (5). Both of them are applicable to physisorption as well as chemisorption processes

TGFBI expression is associated with a better response to chemotherapy in NSCLC

<p>Abstract</p> <p>Background</p> <p>Lung cancer is one of the most prevalent neoplasias in developed countries. Advances in patient survival have been limited and the identification of prognostic molecules is needed. Resistance to treatment is strongly related to tumor cell adhesion to the extracellular matrix and alterations in the quantity and nature of molecules constituting the tumor cell niche. Recently, transforming growth factor beta-induced protein (TGFBI), an extracellular matrix adaptor protein, has been reported to be differentially expressed in transformed tissues. Loss of TGFBI expression has been described in several cancers including lung carcinoma, and it has been suggested to act as a tumor suppressor gene.</p> <p>Results</p> <p>To address the importance of TGFBI expression in cancer progression, we determined its expression in NSCLC clinical samples using immunohistochemistry. We identified a strong association between elevated TGFBI expression and the response to chemotherapy. Furthermore, we transiently over-expressed and silenced TGFBI in human NSCLC cell lines. Cells over-expressing TGFBI displayed increased sensitivity to etoposide, paclitaxel, cisplatin and gemcitabine. We observed that TGFBI-mediated induction of apoptosis occurred through its binding to αvβ3 integrin. We also determined that full-length TGFBI did not induce caspase 3/7 activation but its proteolytic fragments that were < 3 kDa in size, were able to activate caspase 3, 7 and 8. This pro-apoptotic effect was blocked by anti-αvβ3 integrin antibodies.</p> <p>Conclusions</p> <p>The results shown here indicate that TGFBI is a predictive factor of the response to chemotherapy, and suggest the use of TGFBI-derived peptides as possible therapeutic adjuvants for the enhancement of responses to chemotherapy.</p

Detoxifying enzymes at the cross-roads of inflammation, oxidative stress, and drug hypersensitivity: role of glutathione transferase P1-1 and aldose reductase

9 p.-2 figPhase I and II enzymes are involved in the metabolism of endogenous reactive compounds as well as xenobiotics, including toxicants and drugs. Genotyping studies have established several drug metabolizing enzymes as markers for risk of drug hypersensitivity. However, other candidates are emerging that are involved in drug metabolism but also in the generation of danger or costimulatory signals. Enzymes such as aldo-keto reductases (AKR) and glutathione transferases (GST) metabolize prostaglandins and reactive aldehydes with proinflammatory activity, as well as drugs and/or their reactive metabolites. In addition, their metabolic activity can have important consequences for the cellular redox status, and impacts the inflammatory response as well as the balance of inflammatory mediators, which can modulate epigenetic factors and cooperate or interfere with drug-adduct formation. These enzymes are, in turn, targets for covalent modification and regulation by oxidative stress, inflammatory mediators, and drugs. Therefore, they constitute a platform for a complex set of interactions involving drug metabolism, protein haptenation, modulation of the inflammatory response, and/or generation of danger signals with implications in drug hypersensitivity reactions. Moreover, increasing evidence supports their involvement in allergic processes. Here, we will focus on GSTP1-1 and aldose reductase (AKR1B1) and provide a perspective for their involvement in drug hypersensitivityThis work has been supported by grants SAF2012-36519 from MINECO and SAF-2015-68590-R from MINECO/FEDER and ISCIII RETIC RIRAAF RD12/0013/0008 to DP,and RD12/0013/0002 to J A.Peer reviewe

The oncogene PDRG1 is an interaction target of methionine adenosyltransferases

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Methionine adenosyltransferases MAT I and MAT III (encoded by Mat1a) catalyze S-adenosylmethionine synthesis in normal liver. Major hepatic diseases concur with reduced levels of this essential methyl donor, which are primarily due to an expression switch from Mat1a towards Mat2a. Additional changes in the association state and even in subcellular localization of these isoenzymes are also detected. All these alterations result in a reduced content of the moderate (MAT I) and high V max (MAT III) isoenzymes, whereas the low V max (MAT II) isoenzyme increases and nuclear accumulation of MAT I is observed. These changes derive in a reduced availability of cytoplasmic S-adenosylmethionine, together with an effort to meet its needs in the nucleus of damaged cells, rendering enhanced levels of certain epigenetic modifications. In this context, the putative role of protein-protein interactions in the control of S-adenosylmethionine synthesis has been scarcely studied. Using yeast two hybrid and a rat liver library we identified PDRG1 as an interaction target for MATα1 (catalytic subunit of MAT I and MAT III), further confirmation being obtained by immunoprecipitation and pull-down assays. Nuclear MATα interacts physically and functionally with the PDRG1 oncogene, resulting in reduced DNA methylation levels. Increased Pdrg1 expression is detected in acute liver injury and hepatoma cells, together with decreased Mat1a expression and nuclear accumulation of MATα1. Silencing of Pdrg1 expression in hepatoma cells alters their steady-state expression profile on microarrays, downregulating genes associated with tumor progression according to GO pathway analysis. Altogether, the results unveil the role of PDRG1 in the control of the nuclear methylation status through methionine adenosyltransferase binding and its putative collaboration in the progression of hepatic diseases.This work was supported by grants of the Ministerio de Economía y Competitividad (BFU2005-00050, BFU2008-00666, BFU2009-08977), and the Instituto de Salud Carlos III Carlos III (RCMN C03/08 and PI05/0563

First report of Setaria tundra in roe deer (Capreolus capreolus) from the Iberian Peninsula inferred from molecular data: epidemiological implications

Background Filarioid nematode parasites are major health hazards with important medical, veterinary and economic implications. Recently, they have been considered as indicators of climate change. Findings In this paper, we report the first record of Setaria tundra in roe deer from the Iberian Peninsula. Adult S. tundra were collected from the peritoneal cavity during the post-mortem examination of a 2 year-old male roe deer, which belonged to a private fenced estate in La Alcarria (Guadalajara, Spain). Since 2012, the area has suffered a high roe deer decline rate (75 %), for unknown reasons. Aiming to support the morphological identification and to determine the phylogenetic position of S. tundra recovered from the roe deer, a fragment of the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene from the two morphologically identified parasites was amplified, sequenced and compared with corresponding sequences of other filarioid nematode species. Phylogenetic analyses revealed that the isolate of S. tundra recovered was basal to all other formely reported Setaria tundra sequences. The presence of all other haplotypes in Northern Europe may be indicative of a South to North outbreak in Europe. Conclusions This is the first report of S. tundra in roe deer from the Iberian Peninsula, with interesting phylogenetic results, which may have further implications in the epidemiological and genetic studies of these filarioid parasites. More studies are needed to explore the reasons and dynamics behind the rapid host/geographic expansion of the filarioid parasites in EuropeThis work was supported by the Programme for Consolidating and Structuring Competitive Research Groups (GRC2015/003, Xunta de Galicia). Molecular analyses were carried out in the LEM of EBD, CSIC and funded by RNM 118; Junta AndaluciaS

Wide Area RTK: a satellite navigation system based on precise real-time ionospheric modelling

The Wide Area Real Time Kinematic (WARTK) is an augmentation system concept for multi-frequency users based on precise real-time ionospheric modeling. It is able to provide a high accuracy and integrity GNSS positioning service over continental areas using the infrastructure of a network of permanent ground monitor stations, such as the European Geostationary Navigation Overlay Service (EGNOS) network of Ranging and Integrity Monitoring Stations (RIMS) in Europe. In this way, it allows an additional benefit to be obtained from these reference stations, that is, the network has the potential to support two independent systems: a satellite-based augmentation system, such as EGNOS, and a high-precision positioning service, based on WARTK. Indeed, thanks to the accuracy of the ionospheric corrections provided, WARTK users have available in real-time an extra constraint per satellite between the carrier phase ambiguities, which helps solve them quickly. Once such ambiguities have been solved, the GNSS user obtains navigation accurate to within 20 cm at the 95th percentile (about 10 cm RMS). Moreover, this precise positioning is achieved in a few minutes (with two frequency signals) or in a single epoch, after initial convergence of the tropospheric delay (with three frequency signals), even up to hundreds of kilometers away from the nearest reference station. While previous WARTK research has been devoted to implementing the concept and assessing its feasibility, considering in particular the accuracy achievable, the work reported in this paper focused on consolidating the results by analyzing a large and representative data set, and on deeper analysis of the integrity issue. It was carried out in the context of the Multi-constellation Regional System (MRS) project, within the European Space Agency GNSS Evolution Programme, with the aim of designing a high accuracy service for GPS and/or Galileo. Three months of actual data, from more than 25 permanent GPS stations in Europe, have been processed (some of them as a roving user), for high-, mid- and low-solar cycle conditions (in 2002, 2004 and 2006 respectively). In addition, several ionospheric storms occurred during the selected periods, with Dst values reaching up to −150 nT. Results based on these data show that user domain integrity was maintained for baselines of up to 400 km. At the 95th percentile, the daily horizontal and vertical position errors were 20 and 30 cm, respectively, and the corresponding protection levels were about 1 and 2 m. The convergence time was around 5 minutes with actual GPS constellation data. The benefits of using a multi-constellation system were also studied, with simulated GPS and three-frequency Galileo data, showing that it is possible to reduce the convergence time to a few seconds.Postprint (published version

Stochastic earned value analysis using Monte Carlo simulation and statistical learning techniques

The aim of this paper is to describe a new integrated methodology for project control under uncertainty. This proposal is based on Earned Value Methodology and risk analysis and presents several refinements to previous methodologies. More specifically, the approach uses extensive Monte Carlo simulation to obtain information about the expected behavior of the project. This dataset is exploited in several ways using different statistical learning methodologies in a structured fashion. Initially, simulations are used to detect if project deviations are a consequence of the expected variability using Anomaly Detection algorithms. If the project follows this expected variability, probabilities of success in cost and time and expected cost and total duration of the project can be estimated using classification and regression approachesproject "Computational Models for Strategic Project Portfolio Management", supported by the Regional Government of Castile and Leon (Spain) with grant VA056A12-2 and by the Spanish Ministerio de Ciencia e Innovacion project CSD2010-00034 (SimulPast CONSOLIDER-INGENIO 2010)

Expression of Sirtuin 1 and 2 Is Associated with Poor Prognosis in Non-Small Cell Lung Cancer Patients

Sirtuin 1 (SIRT1) and sirtuin 2 (SIRT2) are NAD+-dependent protein deacetylases involved in the regulation of key cancer-associated genes. In this study we evaluated the relevance of these deacetylases in lung cancer biology