Proinflammatory Interleukin-33 Induces Dichotomic Effects on Cell Proliferation in Normal Gastric Epithelium and Gastric Cancer

Interleukin (IL)-33 is a member of the interleukin (IL)-1 family of cytokines linked to the development of inflammatory conditions and cancer in the gastrointestinal tract. This study is designed to investigate whether IL-33 has a direct effect on human gastric epithelial cells (GES-1), the human gastric adenocarcinoma cell line (AGS), and the gastric carcinoma cell line (NCI-N87) by assessing its role in the regulation of cell proliferation, migration, cell cycle, and apoptosis. Cell cycle regulation was also determined in ex vivo gastric cancer samples obtained during endoscopy and surgical procedures. Cell lines and tissue samples underwent stimulation with rhIL-33. Proliferation was assessed by XTT and CFSE assays, migration by wound healing assay, and apoptosis by caspase 3/7 activity assay and annexin V assay. Cell cycle was analyzed by means of propidium iodine assay, and gene expression regulation was assessed by RT-PCR profiling. We found that IL-33 has an antiproliferative and proapoptotic effect on cancer cell lines, and it can stimulate proliferation and reduce apoptosis in normal epithelial cell lines. These effects were also confirmed by the analysis of cell cycle gene expression, which showed a reduced expression of pro-proliferative genes in cancer cells, particularly in genes involved in G0/G1 and G2/M checkpoints. These results were confirmed by gene expression analysis on bioptic and surgical specimens. The aforementioned results indicate that IL-33 may be involved in cell proliferation in an environment- and cell-type-dependent manner.     

On Approximate Majority and Probabilistic Time

We prove new results on the circuit complexity of approximate majority, which is the problem of computing the majority of a given bit string whose fraction of 1’s is bounded away from 1/2 (by a constant). We then apply these results to obtain new relationships between probabilistic time, BPTime (t), and alternating time, ∑_O(1)Time (t). Our main results are the following:

Markerless human articulated tracking using hierarchical particle swarm optimisation

In this paper, we address markerless full-body articulated human motion tracking from multi-view video sequences acquired in a studio environment. The tracking is formulated as a multi-dimensional non-linear optimisation and solved using particle swarm optimisation (PSO), a swarm-intelligence algorithm which has gained popularity in recent years due to its ability to solve difficult non-linear optimisation problems. We show that a small number of particles achieves accuracy levels comparable with several recent algorithms. PSO initialises automatically, does not need a sequence-specific motion model and recovers from temporary tracking divergence through the use of a powerful hierarchical search algorithm (HPSO). We compare experimentally HPSO with particle filter (PF), annealed particle filter (APF) and partitioned sampling annealed particle filter (PSAPF) using the computational framework provided by Balan et al. HPSO accuracy and consistency are better than PF and compare favourably with those of APF and PSAPF, outperforming it in sequences with sudden and fast motion. We also report an extensive experimental study of HPSO over ranges of values of its parameters.     

Synchronizing automata with finitely many minimal synchronizing words

A synchronizing word for a given synchronizing DFA is called minimal if none of its proper factors is synchronizing. We characterize the class of synchronizing automata having only finitely many minimal synchronizing words (the class of such automata is denoted by FG). Using this characterization we prove that any such automaton possesses a synchronizing word of length at most 3n-5. We also prove that checking whether a given DFA A is in FG is co-NP-hard and provide an algorithm for this problem which is exponential in the number of states A.     

Design of high stroke electrostatic micropumps: a charge control approach with ring electrodes

A novel design strategy to avoid pull-in occurrence in electrostatic micro electro mechanical systems is proposed. It combines charge control with ring electrodes, on a circular geometry. This idea is introduced here for the design of efficient and reliable high stroke electrostatic diaphragm micropumps, while it has a broad potential applicability. A minimal lumped one degree-of-freedom model is derived and used to introduce and demonstrate the proposed approach for a circular plate geometry. Finite element models are subsequently adopted for a more detailed device modelling. As expected, charge control exhibits a stabilizing effect with respect to voltage drive, but not sufficient to achieve a full-range stability for the considered geometry. When the electrode area is properly defined, stability range can be extended up to gap closure in the central part of the membrane. In this configuration, the increase in voltage required for full-range device drive would be relevant, while in charge control the penalty is considerably lower. Finally, loading conditions and geometrical parameters for an optimized actuation are suggested.     

EEG signal preprocessing for biometric recognition

Electroencephalography (EEG) has been recently investigated as a biometric modality for automatic people recognition purposes. Several studies have shown that brain signals possess subject-specific traits that allow distinguishing people. Nonetheless, extracting discriminative characteristics from EEG recordings may be a challenging task, due to the significant presence of artifacts in the acquired data. In order to cope with such issue, in this paper we evaluate the effectiveness of some preprocessing techniques in automatically removing undesired EEG contributions, with the aim of improving the achievable recognition rates. Specifically, methods based on blind source separation and sample entropy estimation are here investigated. An extensive set of experimental tests, performed over a large database comprising recordings taken from 50 healthy subjects during three distinct sessions spanning a period of about one month, in both eyes-closed and eyes-open conditions, is carried out to analyze the performance of the proposed approaches.     

Sensorless supervision of linear dynamical systems: The Feed-Forward Command Governor approach

This paper proposes a novel class of Command Governor (CG) strategies for input and state-related constrained discrete-time LTI systems subject to bounded disturbances in the absence of explicit state or output measurements. While in traditional CG schemes the set-point manipulation is undertaken on the basis of either the actual measure of the state or its suitable estimation, it is shown here that the CG design problem can be solved, with limited performance degradation and with similar properties, also in the case that such an explicit measure is not available. This approach, which will be referred to as the Feed-Forward CG (FF-CG) approach, may be a convenient alternative CG solution in all situations whereby the cost of measuring the state may be a severe limitation, e.g. in distributed or decentralized applications. In order to evaluate the method proposed here, numerical simulations on a physical example have been undertaken and comparisons with the standard state-based CG solution reported.     

Trade-offs Between the Size of Advice and Broadcasting Time in Trees

We study the problem of the amount of information required to perform fast broadcasting in tree networks. The source located at the root of a tree has to disseminate a message to all nodes. In each round each informed node can transmit to one child. Nodes do not know the topology of the tree but an oracle knowing it can give a string of bits of advice to the source which can then pass it down the tree with the source message. The quality of a broadcasting algorithm with advice is measured by its competitive ratio: the worst case ratio, taken over n-node trees, between the time of this algorithm and the optimal broadcasting time in the given tree. Our goal is to find a trade-off between the size of advice and the best competitive ratio of a broadcasting algorithm for n-node trees. We establish such a trade-off with an approximation factor of O(n ^ε ), for an arbitrarily small positive constant ε. This is the first communication problem for which a trade-off between the size of advice and the efficiency of the solution is shown for arbitrary size of advice.     

Self-Organising Maps: A new way to screen the level of satisfaction of dialysis patients

Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a residual area of low satisfaction in dialysis patients.The FME Patient Satisfaction Programme questionnaire was distributed to haemodialysis (HD) patients treated in 335 centers of its network. It contained 79 questions covering various satisfaction aspects regarding Dialysis Unit, Dialysis Arrangement, Nurses, Doctors, etc.To analyse the data provided by the questionnaire, the Self-Organising Map (SOM) method was used. SOM is a neural network model for clustering and projecting high-dimensional data into a low-dimensional space, preserving topological relationships of original high-dimensional data spaces.10,632 HD patients completed the questionnaire. Mean age was 63.05 ± 14.93 years with 56.69% males. Response rate was 66%. Overall level of satisfaction was 1.99 (range from ?3 to +3). On average patients were very satisfied with all issues. Nevertheless, a group of patients, around 60 years old, balanced gender ratio, whose level of satisfaction was lower than 1, were highlighted.In the NephroCare clinics patient satisfaction with service is rather high. While traditional analysis usually stops here, the SOM method allows identification of areas of potential improvement for specific patient groups.