Combined differentiating therapy for myelodysplastic syndromes: a phase II study

An in vitro synergism between different inducers of AML cell differentiation has been previously observed. Therefore, we treated 53 myelodysplastic (MDS) patients with a low dose combination of cis-retinoic acid (cRA, 20-40 mg/day) and 1,25 alpha (OH)2 cholecalciferol [(OH)2D3, 1-1.5 micrograms/day] +/- intermittent 6-thioguanine (30 mg/m2/day). The latter was reserved for patients with bone marrow (BM) blast excess (> or = 5%). The treatment was well tolerated, without major toxicity. Among 25 patients with BM blasts less than 5%, we observed one complete, eight partial and four minor responses (response rate 52%) with a median response duration of 8 months (2 +/- 24). Median survival, which did not correlate with response, is projected at 76 months. Thirty-one patients with BM blast excess (> or = 5%), including three of the previous group who progressed to refractory anemia with excess of blasts (RAEB), were treated with the three-drug protocol. One complete, 12 partial and six minor responses were obtained (response rate 61%) with a median response duration of 6 months (2-29+). A significant difference in survival (P < 0.005) was observed between the 19 responders (median 25 months) and the 12 non-responders (median 9 months). A reduction in the transfusion need was observed in 41% of the transfusion-dependent patients with blast excess and in 53% of those without blast excess. Therefore, combined differentiating therapy seems more effective than previously reported single agent treatments and should be considered for a larger randomized study to assess its actual impact on survival of MDS patients.     

Microalbuminuria in IDDM is associated with increased expression of monocyte procoagulant activity

Insulin-like growth factor II (IGF-II) plays a key role in mammalian growth, influencing foetal cell division and differentiation and possibly metabolic regulation. The mature 67 amino acid peptide shares sequence homology with both insulin and IGF-I. The liver is the main endocrine source of IGFs, but autocrine/paracrine activity is found in most tissues. The type 1 receptor mediates most of the biological effects of IGF-I and IGF-II; the type 2 receptor is involved with IGF-II degradation. Binding proteins may both localise IGFs to the receptors and regulate their activities. The IGF2 gene is maternally imprinted in mouse and human. Relaxation of IGF2 imprinting occurs in the Beckwith-Wiedemann syndrome of somatic overgrowth, sporadic Wilms' tumour and a number of other cancers. In the general adult population, the IGF2-INS gene cluster may also influence body weight, in which case IGF-II function could become a target for therapeutic intervention in obesity.     

Experience classification for transfer learning in traffic signal control

In recent years, due to the drastic rise in the number of vehicles and the lack of sufficient infrastructure, traffic jams, air pollution, and fuel consumption have increased in cities. The optimization of timing for traffic lights is one of the solutions for the mentioned problems. Many methods have been introduced to deal with these problems, including reinforcement learning. Although a great number of learning-based methods have been used in traffic signal control, they suffer from poor performance and slow learning convergence. In this paper, a transfer learning-based method for traffic signal control has been proposed. Multi-agent system has also been used for modelling the traffic network and transfer learning has been used to make reinforcement learning agents transfer their experience to each other. Furthermore, a classifier has been utilized to classify the transferred experiences. The results show that using the proposed method leads to a significant improvement on average delay time and convergence time of the learning process.

     

Liar liar,pants on fire; or how to use subjective logic and argumentation to evaluate information from untrustworthy sources

This paper presents a non-prioritized belief change operator, designed specifically for incorporating new information from many heterogeneous sources in an uncertain environment. We take into account that sources may be untrustworthy and provide a principled method for dealing with the reception of contradictory information. We specify a novel Data-Oriented Belief Revision Operator, that uses a trust model, subjective logic, and a preference-based argumentation framework to evaluate novel information and change the agent’s belief set accordingly. We apply this belief change operator in a collaborative traffic scenario, where we show that (1) some form of trust-based non-prioritized belief change operator is necessary, and (2) in a direct comparison between our operator and a previous proposition, our operator performs at least as well in all scenarios, and significantly better in some.     

Critical Review of the Evolution of Extracellular Vesicles’ Knowledge: From 1946 to Today

Extracellular vesicles (EVs) are a family of particles/vesicles present in blood and body fluids, composed of phospholipid bilayers that carry a variety of molecules that can mediate cell communication, modulating crucial cell processes such as homeostasis, induction/dampening of inflammation, and promotion of repair. Their existence, initially suspected in 1946 and confirmed in 1967, spurred a sharp increase in the number of scientific publications. Paradoxically, the increasing interest for EV content and function progressively reduced the relevance for a precise nomenclature in classifying EVs, therefore leading to a confusing scientific production. The aim of this review was to analyze the evolution of the progress in the knowledge and definition of EVs over the years, with an overview of the methodologies used for the identification of the vesicles, their cell of origin, and the detection of their cargo. The MISEV 2018 guidelines for the proper recognition nomenclature and ways to study EVs are summarized. The review finishes with a “more questions than answers” chapter, in which some of the problems we still face to fully understand the EV function and potential as a diagnostic and therapeutic tool are analyzed.     

A Distributed Approach for Coordination of Traffic Signal Agents

Innovative control strategies are needed to cope with the increasing urban traffic chaos. In most cases, the currently used strategies are based on a central traffic-responsive control system which can be demanding to implement and maintain. Therefore, a functional and spatial decentralization is desired. For this purpose, distributed artificial intelligence and multi-agent systems have come out with a series of techniques which allow coordination and cooperation. However, in many cases these are reached by means of communication and centrally controlled coordination processes, giving little room for decentralized management. Consequently, there is a lack of decision-support tools at managerial level (traffic control centers) capable of dealing with decentralized policies of control and actually profiting from them. In the present work a coordination concept is used, which overcomes some disadvantages of the existing methods. This concept makes use of techniques of evolutionary game theory: intersections in an arterial are modeled as individually-motivated agents or players taking part in a dynamic process in which not only their own local goals but also a global one has to be taken into account. The role of the traffic manager is facilitated since s/he has to deal only with tactical ones, leaving the operational issues to the agents. Thus the system ultimately provides support for the traffic manager to decide on traffic control policies. Some application in traffic scenarios are discussed in order to evaluate the feasibility of transferring the responsibility of traffic signal coordination to agents. The results show different performances of the decentralized coordination process in different scenarios (e.g. the flow of vehicles is nearly equal in both opposing directions, one direction has a clearly higher flow, etc.). Therefore, the task of the manager is facilitate once s/he recognizes the scenario and acts accordingly.     

Liquid Chromatography–Tandem Mass Spectrometry Multiclass Method for 46 Antibiotics Residues in Milk and Meat: Development and Validation

A screening method for analysis of 46 antibiotics residues, belonging to different classes, such as tetracyclines, sulfonamides, fluoroquinolones, β-lactams, cephalosporins, macrolides and other minority groups was developed and validated for application in bovine milk and bovine, swine, poultry, equine, fish and shrimp meat samples. Sample preparation consists in solvent extraction followed by clean up with C18 bulk and low temperature purification. Instrumental analysis was performed using liquid chromatography coupled to tandem mass spectrometry system. Chromatographic separation was achieved using a C18 column. Mobile phase was composed by methanol and water. The method was validated according to Commission Decision 2002/657/EC criteria. Validation parameters such as specificity and detection capability (CCβ) were determined and considered suitable to the established criteria. Values of CCβ ranged from 1.0 to 50.0 μg L^?1 or μg Kg^?1, depending on the compound and the matrix. The proposed method has been applied into Brazilian National Residue Control Plan since 2013 for the determination of antibiotic residues. A total of 3833 samples were analyzed until the current date and 13 samples showed positive results with concentrations above the permitted. The method is fast, easy and adequate for high throughput analysis in routine laboratories.     

Distributed clustering for group formation and task allocation in multiagent systems: A swarm intelligence approach

Most clustering methods rely on central data structures and/or cannot cope with dynamically changing settings. Besides, these methods need some hints about the target clustering. However, issues related to the current use of Internet resources (distribution of data, privacy, etc.) require new ways of dealing with data clustering. In multiagent systems this is also becoming an issue as one wishes to group agents according to some features of the environment in order to have agents accomplishing the available tasks in an efficient way. In this paper we discuss the application of a clustering algorithm that is inspired by swarm intelligence techniques such as organization of bee colonies and task allocation among social insects. This application involves a complex task allocation scenario, the RoboCup Rescue, where tasks with different characteristics must be allocated to agents with different capabilities. Our results have shown that clustering agents is effective in this scenario as agents act in a more coordinated way.     

Modification of the structure of diamond with MeV ion implantation

We present experimental results and numerical simulations to investigate the modification of structural–mechanical properties of ion-implanted single-crystal diamond. A phenomenological model is used to derive an analytical expression for the variation of mass density and elastic properties as a function of damage density in the crystal. These relations are applied together with SRIM Monte Carlo simulations to set up finite element simulations for the determination of internal strains and surface deformation of MeV-ion-implanted diamond samples. The results are validated through comparison with high resolution X-ray diffraction and white-light interferometric profilometry experiments. The former are carried out on 180 keV B implanted diamond samples, to determine the induced structural variation, in terms of lattice spacing and disorder, whilst the latter are performed on 1.8 MeV He implanted diamond samples to measure surface swelling. The effect of thermal processing on the evolution of the structural–mechanical properties of damaged diamond is also evaluated by performing the same profilometric measurements after annealing at 1000 °C, and modeling the obtained trends with a suitably modified analytical model. The results allow the development of a coherent model describing the effects of MeV-ion-induced damage on the structural–mechanical properties of single-crystal diamond. In particular, we suggest a more reliable method to determine the so-called diamond “graphitization threshold” for the considered implantation type.     

Holonic multi-agent system for traffic signals control

Agent-based technologies are rapidly growing as a powerful tool for modelling and developing large-scale distributed systems. Recently, multi-agent systems are largely used for intelligent transportation systems modelling. Traffic signals control is a challenging issue in this area, especially in a large-scale urban network. In a large traffic network, where each agent represents a traffic signals controller, there are many entities interacting with each other and hence it is a complex system. An approach to reduce the complexity of such systems is using organisation-based multi-agent system. In this paper, we use an organisation called holonic multi-agent system (HMAS) to model a large traffic network. A traffic network containing fifty intersections is partitioned into a number of regions and holons are assigned to control each region. The holons are hierarchically arranged in two levels, intersection controller holons in the first level and region controller holons in the second level. We introduce holonic Q-learning to control the signals in both levels. The inter-level interactions between the holons in the two levels contribute to the learning process. Experimental results show that the holonic Q-learning prevents the network to be over-saturated while it causes less average delay time and higher flow rate.