Multi-level analysis of on-chip optical wireless links

Networks-on-chip are being regarded as a promising solution to meet the on-going requirement for higher and higher computation capacity. In view of future kilo-cores architectures, electrical wired connections are likely to become inefficient and alternative technologies are being widely investigated. Wireless communications on chip may be therefore leveraged to overcome the bottleneck of physical interconnections. This work deals with wireless networks-on-chip at optical frequencies, which can simplify the network layout and reduce the communication latency, easing the antenna on-chip integration process at the same time. On the other end, optical wireless communication on-chip can be limited by the heavy propagation losses and the possible cross-link interference. Assessment of the optical wireless network in terms of bit error probability and maximum communication range is here investigated through a multi-level approach. Manifold aspects, concurring to the final system performance, are simultaneously taken into account, like the antenna radiation properties, the data-rate of the core-to core communication, the geometrical and electromagnetic layout of the chip and the noise and interference level. Simulations results suggest that communication up to some hundreds of \u3bcm can be pursued provided that the antenna design and/or the target data-rate are carefully tailored to the actual layout of the chip

Dielectric and plasmonic vivaldi antennas for on-chip wireless communication

In this paper, different technologies enabling wireless on-chip communication are investigated. In particular, plasmonic Vivaldi antennas coupled to silicon waveguides and all-dielectric Vivaldi antennas are proposed. The design criteria and the performances of the two antenna configurations are also discussed

Stabilizing versus destabilizing the microtubules: A double-edge sword for an effective cancer treatment option?

Microtubules are dynamic and structural cellular components involved in several cell functions, including cell shape, motility, and intracellular trafficking. In proliferating cells, they are essential components in the division process through the formation of the mitotic spindle. As a result of these functions, tubulin and microtubules are targets for anticancer agents. Microtubule-targeting agents can be divided into two groups: microtubule-stabilizing, and microtubule-destabilizing agents. The former bind to the tubulin polymer and stabilize microtubules, while the latter bind to the tubulin dimers and destabilize microtubules. Alteration of tubulin-microtubule equilibrium determines the disruption of the mitotic spindle, halting the cell cycle at the metaphase-anaphase transition and, eventually, resulting in cell death. Clinical application of earlier microtubule inhibitors, however, unfortunately showed several limits, such as neurological and bone marrow toxicity and the emergence of drug-resistant tumor cells. Here we review several natural and synthetic microtubule-targeting agents, which showed antitumor activity and increased efficacy in comparison to traditional drugs in various preclinical and clinical studies. Cryptophycins, combretastatins, ombrabulin, soblidotin, D-24851, epothilones and discodermolide were used in clinical trials. Some of them showed antiangiogenic and antivascular activity and others showed the ability to overcome multidrug resistance, supporting their possible use in chemotherapy

CALR MUTATIONS IN SICILIAN ESSENTIAL THROMBOCYTHEMIA AND MYELOFIBROSIS PATIENTS.

Background. Essential thrombocythemia (ET) and primary myelofibrosis (MF) are myeloproliferative neoplasms characterized by the overproduction of mature cells such as platelets (ET) or early bone marrow fibrosis due to scarring induced by highly proliferating myeloid progenitors and pathological stimulation of local fibroblasts (MF). Somatic mutations in CALR gene have recently identified in the majority of JAK2-V617F and MPL negative ET and MF patients. In this study we evaluated the frequency and type of CALR mutations and their clinical and hematological features. Methods. A total of 54 patients, 29 ET and 25 MF patient, was included in this study. All patients were JAK2 V617F and MPL negative. We registered clinical and hematological characteristics of patients i.e. age, hemoglobin level, white blood cell count, platelet count, International Prognostic Scoring System (IPSS), risk of thrombosis. Samples were collected from peripheral blood and DNA was extracted by using the QIAamp DNA mini kit (QIAGEN); CALR mutations were analyzed by direct sequencing method. Results. CALR mutations were present in 20.4 % of patients (4 ET; 7 MF). Four types of CALR mutations were detected; type 1 (p.L367fs*46) was isolated in 6 MF patient, type 2 (p.K385fs*47) was isolated in 3 ET patient; we also found 2 deletion mutations (p.E371fs*49 and D373fs*47), which are less common deletions, in the remaining patients. Patients carrying CALR mutations were younger (mediane age: 50 vs 65; p=0.2) than CALR negative patients. Furthermore, they did not show thrombosis and IPSS high risk. Conclusions. Our observations are in agreement with the findings of literature. We can assert an improved outcome of CALR mutated patients and we can also speculate a possible protective role of CARL mutations given the absence of thrombosis events and of IPSS high risk. However, the cohort of patients with myeloproliferative disease need to be implemented to draw final conclusion

Investigation of N/OFQ effects in peripheral fibers

This project of the duration of 1 year is focussed at the study in vitro and in vivo of N/OFQ effects in different kind of peripheral neuronal fibers. Cal\uf2 G. principal investigator Project sponsored by Allergan pharm

PRIN 2006 - Il sistema neuropeptide S - recettore NPSR: identificazione di nuovi ligandi e studio delle attivita' biologiche in vitro ed in vivo

Il neuropeptide S (NPS) \ue8 stato recentemente identificato come ligando endogeno del recettore GPCR precedentemente orfano, ora denominato NPSR. Questo progetto, della durata di due anni (2007-2008), ha lo scopo di identificare e caratterizzare in vitro e in vivo nuovi ligandi del recettore NPSR. G. Cal\uf2 responsabile nazionale e responsabile di R

In vitro characterization of novel NOP ligands

This project of the duration of 1 year is focussed at the in vitro characterization of novel NOP ligands, at the recombinant and native receptor. Cal\uf2 G. principal investigator Project sponsored by Allergan pharm

Outlier detection via Forward Serach: a proposal based on mixture models

The Forward Search (FS) consists in ordering the observations by closeness to the multivariate normal model and progressively including them into the subset that is used for parameter estimation and that, at the beginning, is outlier free. In this paper we propose to enlarge the applicability of FS-oultier detection methods by assuming a mixture of K>1 normal components as a null model. Both the identification of the starting subset and the criterion for progressing in the search are based on the estimated values of the mixture density; outlying observations are detected by monitoring the values of a proper statistic during the search, as suggested by Atkinson et al. (2004

Gaussian mixture model classification: A projection pursuit approach

Gaussian mixture models (GMM) are commonly employed in nonparametric supervised classification. In high-dimensional problems it is often the case that information relevant to the separation of the classes is contained in a few directions. A GMM fitting procedure oriented to supervised classification is proposed, with the aim of reducing the number of free parameters. It resorts to projection pursuit as a dimension reduction method and combines it with GM modelling of class-conditional densities. In its derivation, issues regarding the forward and backward projection pursuit algorithms are discussed. The proposed procedure avoids the \u201ccurse of dimensionality\u201d, is able to model structure in subspaces and regularizes the classification model. Its performance is illustrated on a simulation experiment and on a real data set, in comparison with other GMM-based classification methods