Integratable non-clogging microconcentrator based on counter-flow principle for continuous enrichment of CaSki cells sample

This study addresses the need to reduce the risk of clogging when preparing samples for cell concentration, i.e., the CaSki Cell-lines (epidermoid cervical carcinoma cells). Aiming to develop a non-clogging microconcentrator, we proposed a new counter-flow concentration unit characterized by the directions of penetrating flows being at an obtuse angle to the main flow, due to employment of streamlined turbine blade-like micropillars. Based on the optimization results of the counter-flow unit profile, a fractal arrangement for the counter-flow concentration unit was developed. A counter-flow microconcentrator chip was then designed and fabricated, with both the processing layer and collecting layer arranged in terms of the honeycomb structure. Visualized experiments using CaSki cell samples on the microconcentrator chip demonstrated that no cell-clogging phenomena occurred during the test and that no cells were found in the final filtrate. The test results show an excellent concentration performance for the microconcentrator chip, while a concentrating ratio of >4 with the flow rate being below 1.0 ml/min. As only geometrical structure is employed in the passive device, the counter-flow microconcentrator can be easily integrated into advanced microfluidic systems. Owing to the merit of non-clogging and continuous processing ability, the counter-flow microconcentrator is not only suitable for the sample preparation within biomedical field, but also applicable in water-particle separation.     

Computational study on the interaction of a ring-hydroxylating dioxygenase from Sphingomonas CHY-1 with PAHs

The massive computational resources available in the framework of a grid paradigm approach represent an emerging tool in the bioinformatics field. In this paper, we used the above approach in the rapid determination of the interactions between the ring-hydroxylating dioxygenase, comprised six enzymatic subunits, and polycyclic aromatic hydrocarbons (PAHs) in their optimal positions. The results were obtained by simulating enzyme dynamics at 300 K through molecular dynamics calculations. For the first time, the equilibrated structure of the dioxygenase revealed a network of channels throughout the enzyme that were sufficiently large to allow a flow of small ions or molecules from the inner core of the complex to its exterior surface. The ring-hydroxylating dioxygenase was able to interact with some of the studied PAHs. Additionally, not only the number of aromatic rings but also the PAH shape were critical in predicting the ability of the dioxygenase to interact with these types of molecules. Docking calculations shed light on a new possible binding site that is far from the enzymatic one, which is potentially interesting in considering the stability of the enzyme itself.     

Active fault tolerant control of discrete event systems using online diagnostics

The aim of this paper is to deal with the problem of fault tolerant control in the framework of discrete event systems modeled as automata. A fault tolerant controller is a controller able to satisfy control specifications both in nominal operation and after the occurrence of a fault. This task is solved by means of a parameterized controller that is suitably updated on the basis of the information provided by online diagnostics: the supervisor actively reacts to the detection of a malfunctioning component in order to eventually meet degraded control specifications. Starting from an appropriate model of the system, we recall the notion of safe diagnosability as a necessary step in order to achieve fault tolerant control. We then introduce two new notions: (i) “safe controllability”, which represents the capability, after the occurrence of a fault, of steering the system away from forbidden zones and (ii) “active fault tolerant system”, which is the property of safely continuing operation after faults. Finally, we show how the problem can be solved using a general control architecture based on the use of special kind of diagnoser, called “diagnosing controller”, which is used to safely detect faults and to switch between the nominal control policy and a bank of reconfigured control policies. A simple example is used to illustrate the new notions and the control architecture introduced in the paper.     

Experiments on the reliability of stochastic spiking neural P systems

In the area of membrane computing, time-freeness has been defined as the ability for a timed membrane system to produce always the same result, independently of the execution times associated to the rules. In this paper, we use a similar idea in the framework of spiking neural P systems, a model inspired by the structure and the functioning of neural cells. In particular, we introduce stochastic spiking neural P systems where the time of firing for an enabled spiking rule is probabilistically chosen and we investigate when, and how, these probabilities can influence the ability of the systems to simulate, in a reliable way, universal machines, such as register machines.     

Adaptive course generation through learning styles representation

This paper presents an approach to automatic course generation and student modeling. The method has been developed during the European funded projects Diogene and Intraserv, focused on the construction of an adaptive e-learning platform. The aim of the platform is the automatic generation and personalization of courses, taking into account pedagogical knowledge on the didactic domain as well as statistic information on both the student’s knowledge degree and learning preferences. Pedagogical information is described by means of an innovative methodology suitable for effective and efficient course generation and personalization. Moreover, statistic information can be collected and exploited by the system in order to better describe the student’s preferences and learning performances. Learning material is chosen by the system matching the student’s learning preferences with the learning material type, following a pedagogical approach suggested by Felder and Silverman. The paper discusses how automatic learning material personalization makes it possible to facilitate distance learning access to both able-bodied and disabled people. Results from the Diogene and Intraserv evaluation are reported and discussed.     

Simulating Emergent Properties of Coordination in Maude: the Collective Sort Case

Recent coordination languages and models are moving towards the application of techniques coming from the research context of complex systems: adaptivity and self-organization are exploited in order to tackle the openness, dynamism and unpredictability of today's distributed systems. In this area, systems are to be described using stochastic models, and simulation is a valuable tool both for analysis and design. Accordingly, in this work we focused on modelling and simulating emergent properties of coordination techniques.We first develop a framework acting as a general-purpose engine for simulating stochastic transition systems, built as a library for the Maude term rewriting system. We then evaluate this tool to a coordination problem called collective sort, where autonomous agents move tuples across different tuple spaces according to local criteria, and resulting in the emergence of the complete clustering property.     

On‐Chip Magnetic Platform for Single‐Particle Manipulation with Integrated Electrical Feedback

Methods for the manipulation of single magnetic particles have become very interesting, in particular for in vitro biological studies. Most of these studies require an external microscope to provide the operator with feedback for controlling the particle motion, thus preventing the use of magnetic particles in high‐throughput experiments. In this paper, a simple and compact system with integrated electrical feedback is presented, implementing in the very same device both the manipulation and detection of the transit of single particles. The proposed platform is based on zig‐zag shaped magnetic nanostructures, where transverse magnetic domain walls are pinned at the corners and attract magnetic particles in suspension. By applying suitable external magnetic fields, the domain walls move to the nearest corner, thus causing the step by step displacement of the particles along the nanostructure. The very same structure is also employed for detecting the bead transit. Indeed, the presence of the magnetic particle in suspension over the domain wall affects the depinning field required for its displacement. This characteristic field can be monitored through anisotropic magnetoresistance measurements, thus implementing an integrated electrical feedback of the bead transit. In particular, the individual manipulation and detection of single 1‐μm sized beads is demonstrated.     

High-performance flat-panel solar thermoelectric generators with high thermal concentration

The conversion of sunlight into electricity has been dominated by photovoltaic and solar thermal power generation. Photovoltaic cells are deployed widely, mostly as flat panels, whereas solar thermal electricity generation relying on optical concentrators and mechanical heat engines is only seen in large-scale power plants. Here we demonstrate a promising flat-panel solar thermal to electric power conversion technology based on the Seebeck effect and high thermal concentration, thus enabling wider applications. The developed solar thermoelectric generators (STEGs) achieved a peak efficiency of 4.6% under AM1.5G (1 kW m(-2)) conditions. The efficiency is 7-8 times higher than the previously reported best value for a flat-panel STEG, and is enabled by the use of high-performance nanostructured thermoelectric materials and spectrally-selective solar absorbers in an innovative design that exploits high thermal concentration in an evacuated environment. Our work opens up a promising new approach which has the potential to achieve cost-effective conversion of solar energy into electricity.     

Platelet-Derived miR-126-3p Directly Targets AKT2 and Exerts Anti-Tumor Effects in Breast Cancer Cells: Further Insights in Platelet-Cancer Interplay

Among the surrounding cells influencing tumor biology, platelets are recognized as novel players as they release microvesicles (MVs) that, once delivered to cancer cells, modulate signaling pathways related to cell growth and dissemination. We have previously shown that physiological delivery of platelet MVs enriched in miR-126 exerted anti-tumor effects in different breast cancer (BC) cell lines. Here, we seek further insight by identifying AKT2 kinase as a novel miR-126-3p direct target, as assessed by bioinformatic analysis and validated by luciferase assay. Both ectopic expression and platelet MV-mediated delivery of miR-126-3p downregulated AKT2 expression, thus suppressing proliferating and invading properties, in either triple negative (BT549 cells) or less aggressive Luminal A (MCF-7 cells) BC subtypes. Accordingly, as shown by bioinformatic analysis, both high miR-126 and low AKT2 levels were associated with favorable long-term prognosis in BC patients. Our results, together with the literature data, indicate that miR-126-3p exerts suppressor activity by specifically targeting components of the PIK3/AKT signaling cascade. Therefore, management of platelet-derived MV production and selective delivery of miR-126-3p to tumor cells may represent a useful tool in multimodal therapeutic approaches in BC patients.