Target Score—A Proteomics Data Selection Tool Applied to Esophageal Cancer Identifies GLUT1-Sialyl Tn Glycoforms as Biomarkers of Cancer Aggressiveness

Esophageal cancer (EC) is a life-threatening disease, demanding the discovery of new biomarkers and molecular targets for precision oncology. Aberrantly glycosylated proteins hold tremendous potential towards this objective. In the current study, a series of esophageal squamous cell carcinomas (ESCC) and EC-derived circulating tumor cells (CTCs) were screened by immunoassays for the sialyl-Tn (STn) antigen, a glycan rarely expressed in healthy tissues and widely observed in aggressive gastrointestinal cancers. An ESCC cell model was glycoengineered to express STn and characterized in relation to cell proliferation and invasion in vitro. STn was found to be widely present in ESCC (70% of tumors) and in CTCs in 20% of patients, being associated with general recurrence and reduced survival. Furthermore, STn expression in ESCC cells increased invasion in vitro, while reducing cancer cells proliferation. In parallel, an ESCC mass spectrometry-based proteomics dataset, obtained from the PRIDE database, was comprehensively interrogated for abnormally glycosylated proteins. Data integration with the Target Score, an algorithm developed in-house, pinpointed the glucose transporter type 1 (GLUT1) as a biomarker of poor prognosis. GLUT1-STn glycoproteoforms were latter identified in tumor tissues in patients facing worst prognosis. Furthermore, healthy human tissues analysis suggested that STn glycosylation provided cancer specificity to GLUT1. In conclusion, STn is a biomarker of worst prognosis in EC and GLUT1-STn glycoforms may be used to increase its specificity on the stratification and targeting of aggressive ESCC forms.     

Immune Checkpoint Inhibitors: A Promising Treatment Option for Metastatic Castration-Resistant Prostate Cancer?

Since 2010, several treatment options have been available for men with metastatic castration-resistant prostate cancer (mCRPC), including immunotherapeutic agents, although the clinical benefit of these agents remains inconclusive in unselected mCRPC patients. In recent years, however, immunotherapy has re-emerged as a promising therapeutic option to stimulate antitumor immunity, particularly with the use of immune checkpoint inhibitors (ICIs), such as PD-1/PD-L1 and CTLA-4 inhibitors. There is increasing evidence that ICIs may be especially beneficial in specific subgroups of patients with high PD-L1 tumor expression, high tumor mutational burden, or tumors with high microsatellite instability/mismatch repair deficiency. If we are to improve the efficacy of ICIs, it is crucial to have a better understanding of the mechanisms of resistance to ICIs and to identify predictive biomarkers to determine which patients are most likely to benefit. This review focuses on the current status of ICIs for the treatment of mCRPC (either as monotherapy or in combination with other drugs), mechanisms of resistance, potential predictive biomarkers, and future challenges in the management of mCRPC.     

Carbohydrate type and amount alter intravascular processing and catabolism of plasma lipoproteins in guinea pigs

To test the effects of exchanging dietary complex and simple carbohydrate for fat calories on lipoprotein metabolism, guinea pigs were fed two different fat/carbohydrate ratios: 2.5∶58% (w/w) or 25∶29% (w/w) with either sucrose or starch as the carbohydrate source. Animals fed high-fat had higher plasma low-density lipoprotein (LDL) and hepatic cholesterol concentrations than animals fed low-fat diets (P<0.01). The cholesteryl ester content per particle was higher, and the number of triacylglycerol (TAG) molecules was lower in very low density lipoprotein (VLDL) and LDL from animals fed high-fat diets. Intake of high-fat/sucrose resulted in higher plasma LDL concentrations than intake of high-fat/starch, and animals fed low-fat/starch had the highest plasma TAG concentrations associated with VLDL particles containing more TAG molecules, as well as a TAG-enriched LDL. The activity of plasma lecithin cholesteryl:acyl transferase (LCAT) was highest in animals fed high-fat/sucrose, and heart lipoprotein lipase (LPL) activity was higher in animals fed high-fat diets. Hepatic apoprotein B/E (apo B/E) receptor number (B_max) was increased 21% with low-fat diets (P<0.01). These results suggest that the hypercholesterolemia induced by high-fat and by sucrose intake are associated with a higher plasma LCAT activity which results in a cholesteryl ester-enriched VLDL which, by the action of LPL, might be more readily converted to LDL through the delipidation cascade leading to downregulation of hepatic apo B/E receptors. The hypertriglyceridemia associated with low-fat intake may result from increased production of VLDL TAG, which would explain the increased TAG content and the higher TAG/CE ratio of VLDL from animals fed the low-fat/starch diet.     

Photoluminiscent Manganese Nanoparticles from Solid State Polyphosphazenes Organometallic Derivatives

Pyrolysis in air at 800°C of [{NP(OC₁₂H₁₀)}_0.6{NP(OC₆H₄PPh₂·(π-CH₃C₅H₄)−Mn(CO)₂)₂}_0.4] _n (1) in the solid state affords product 2 containing nanoclusters of Mn₂P₂O₇ with sizes ranging from 50 to 90 nm and averaging about 74 nm. The egg-shape of the unpyrolyzed organometallic polymer is retained but with increased particle size after pyrolysis. The pyrolytic material shows near-infrared photoluminescence attributed to the emission of tetrahedral Mn²⁺ embedded in a matrix of Mn₂P₂O₇. The solid-state pyrolysis of organometallic derivatives of polyphosphazenes may be a useful and general route to nano-structured Mn₂P₂O₇. An erratum to this article can be found at     

I3WSN: Industrial Intelligent Wireless Sensor Networks for indoor environments

Sensor Web Enablement (SWE) technologies have been successfully applied to a great variety of outdoor scenarios but, in practical terms, little effort has been applied for indoor environments, and even less in the field of industrial applications. This article presents an intelligent SWE application for an indoor and industrial scenario, with the aim of improving and increasing the levels of human safety. The base low-level architecture is built on top of wireless sensor networks (WSN) connected to a Sensor Observation Service (SOS). Higher layers in the architecture include services that make real time decisions based on the collected data. Both simulation and experimental results are presented. The paper shows the viability of our approach in terms of performance, scalability, modularity and safety.     

Sustainability in Web server systems

The exponential growth of Internet during the last decade leads us to make more efforts in the researching and developing of sustainable Web servers in order to decrease the global energy demand. In this paper, we cover, as a first step, a proper review of the literature related to the energy efficiency research in Web server systems to depict the state of the art to plan further contributions as more research in sustainable Web systems. We also propose and implement an energy metric that permits to establish a relation between the Quality of Service (QoS) obtained by the system and the power it consumes.     

A web-based platform for biosignal visualization and annotation

With the advent of wearable sensing and mobile technologies, biosignals have seen an increasingly growing number of application areas, leading to the collection of large volumes of data. One of the difficulties in dealing with these data sets, and in the development of automated machine learning systems which use them as input, is the lack of reliable ground truth information. In this paper we present a new web-based platform for visualization, retrieval and annotation of biosignals by non-technical users, aimed at improving the process of ground truth collection for biomedical applications. Moreover, a novel extendable and scalable data representation model and persistency framework is presented. The results of the experimental evaluation with possible users has further confirmed the potential of the presented framework.     

Beast methodology: An agile testing methodology for multi-agent systems based on behaviour driven development

This paper presents a testing methodology to apply Behaviour Driven Development (BDD) techniques while developing Multi-Agent Systems (MASs), termed BEhavioural Agent Simple Testing (BEAST) Methodology. This methodology is supported by the open source framework (BEAST Tool) which automatically generates test cases skeletons from BDD scenarios specifications. The developed framework allows the testing of MASs based on JADE or JADEX platforms. In addition, this framework offers a set of configurable Mock Agents with the aim of being able to execute tests while the MAS is under development. The BEAST Methodology presents transparent traceability from user requirements to test cases. Thus, the stakeholders can be aware of the project status. The methodology and the associated tool have been validated in the development of a MAS for fault diagnosis in FTTH (Fiber To The Home) networks. The results have been measured in quantifiable way obtaining a reduction of the tests implementation time.     

A genetic algorithm for job-shop scheduling with operators enhanced by weak Lamarckian evolution and search space narrowing

The job-shop scheduling problem with operators is a very interesting problem that generalizes the classic job-shop problem in such a way that an operation must be algorithm to solve this problem considering makespan minimization. The genetic algorithm uses permutations with repetition to encode chromosomes and a schedule generation scheme, termed OG&T, as decoding algorithm. This combination guaranties that at least one of the chromosomes represents and optimal schedule and, at the samhat machines and operators are idle while an operation is available to be processed. To improve the quality of the schedules for large instances, we use Lamarckian evolution and modify the OG&T algorithm to further reduce the idle time of the machines and operators, in this case at the risk of leaving all optimal schedules out of the search space. We conducted a large experimental study showing that these improvements allow the genetic algorithm to reach high quality solutions in very short time, and so it is quite competitive with the current state-of-the-art methods.     

Laser-induced fluorescence visualization of ion transport in a pseudo-porous capacitive deionization microstructure

In this paper, a microfluidic experimental set-up is introduced to study the ionic transport in an artificial capacitive deionization (CDI) cell. CDI is a promising desalination technique, which relies on the application of an external electric field and high surface area porous electrodes for ion separation and storage. Photolithography and deep reactive ion etching were used to fabricate a micro-CDI channel with pseudo-porous electrodes on a silicon-on-insulator substrate. Laser-induced fluorescence was performed using cationic Sulforhodamine B (SRB) fluorescent dye to measure ion concentration within the bulk solution and more importantly, within the porous electrodes during the desalination process, with an average normalized root mean square deviation of 8.2 %. Using this set-up, electromigration of ions within the electrode was visualized and the effect of applied electric potential on bulk solution concentration distribution is quantified. In addition, SRB and Fluorescein were used together to visualize anion and cation concentrations simultaneously. The method presented in this study can be used for solution concentrations up to approximately 0.7 mM. The ionic concentration profiles obtained by this approach can be used to test and validate the existing electrosorption models, and pseudo-porous electrodes can be modified to observe the effects of pore size, shape and distribution on electrosorption performance. Furthermore, with proper modifications, the microfabricated structure and experimental set-up can be used for CDI-on-a-chip applications and bio-separation devices.