Marco Righi

Sorafenib Inhibits Lymphoma Xenografts by Targeting MAPK/ERK and AKT Pathways in Tumor and Vascular Cells

The anti-lymphoma activity and mechanism(s) of action of the multikinase inhibitor sorafenib were investigated using a panel of lymphoma cell lines, including SU-DHL-4V, Granta-519, HD-MyZ, and KMS-11 cell lines. In vitro, sorafenib significantly decreased cell proliferation and phosphorylation levels of MAPK and PI3K/Akt pathways while increased apoptotic cell death. In vivo, sorafenib treatment resulted in a cytostatic rather than cytotoxic effect on tumor cell growth associated with a limited inhibition of tumor volumes. However, sorafenib induced an average 50% reduction of tumor vessel density and a 2-fold increase of necrotic areas. Upon sorafenib treatment, endothelial and tumor cells from SU-DHL-4V, Granta-519, and KMS-11 nodules showed a potent inhibition of either phospho-ERK or phospho-AKT, whereas a concomitant inhibition of phospho-ERK and phospho-AKT was only observed in HD-MyZ nodules. In conclusion, sorafenib affects the growth of lymphoid cell lines by triggering antiangiogenic mechanism(s) and directly targeting tumor cells.

Thesaurus project: design of new autonomous underwater vehicles for documentation and protection of underwater archaeological sites

The Thesaurus Project, funded by the Regione Toscana, combines humanistic and technological research aiming at developing a new generation of cooperating Autonomous Underwater Vehicles and at documenting ancient and modern Tuscany shipwrecks. Technological research will allow performing an archaeological exploration mission through the use of a swarm of autonomous, smart and self-organizing underwater vehicles. Using acoustic communications, these vehicles will be able to exchange each other data related to the state of the exploration and then to adapt their behavior to improve the survey. The archival research and archaeological survey aim at collecting all reports related to the underwater evidences and the events of sinking occurred in the sea of Tuscany. The collected data will be organized in a specific database suitably modeled.

Detection of signs of brain dysfunction in epileptic children by recognition of transient changes in the correlation of seizure-free EEG.

Seizure-free EEG signals recorded from epileptic children were compared with EEG signals recorded from normal children. The comparison was based on the detection of transient events characterized by decrease in the correlation between different traces. For this purpose, a conceptually and mathematically simple method was applied. Two clear and remarkable phenomena, able to quantitatively discriminate between the two groups of subjects, were evidenced, with high statistical significance. In fact, it was observed that: (a) The number of events for the epileptic group was larger; (b) Applying restrictive criteria for event definition, the number of subjects in the epileptic group presenting events was larger. The results support the hypothesis of a decrease in brain correlation in children with epilepsy under treatment. This confirms the efficacy of the EEG signal in evaluating cortical functional differences not visible by visual inspection, independently of the cause (epilepsy or drugs), and demonstrate the specific effectiveness of the analysis method applied.

Mirror Mirror on the Wall... An Unobtrusive Intelligent Multisensory Mirror for Well-Being Status Self-Assessment and Visualization

A persons well-being status is reflected by their face through a combination of facial expressions and physical signs. The SEMEOTICONS project translates the semeiotic code of the human face into measurements and computational descriptors that are automatically extracted from images, videos, and three-dimensional scans of the face. SEMEOTICONS developed a multisensory platform in the form of a smart mirror to identify signs related to cardio-metabolic risk. The aim was to enable users to self-monitor their well-being status over time and guide them to improve their lifestyle. Significant scientific and technological challenges have been addressed to build the multisensory mirror, from touchless data acquisition, to real-time processing and integration of multimodal data.

A methodological approach for combining super-resolution and pattern-recognition to image identification

Image acquisition systems integrated with laboratory automation produce multi-dimensional datasets. An effective computational approach for automatic analysis of image datasets is given by pattern recognition methods; in some cases, it can be advantageous to accomplish pattern recognition with image super-resolution procedures. In this paper, we define a method derived from pattern recognition techniques for the recognition of artefacts and noise on set of images combined with super resolution algorithms. The advantage of our approach is automatic artefacts recognition, opening the possibility to build a general framework for artefact recognition independently by the specific application where it is used.

A new method combining enhanced resolution and pattern identification

We present a simple and general-purpose method able to combine high-resolution procedure with the classification and identification of objects of interest from microscopy imaging. The method is composed of two stages. First (pattern recognition), promising components (possible objects of interest) in the image are detected and small regions containing the objects of interest are extracted using a feature finder. Second, high-resolution algorithms are applied to such identified components in order to approach a multiple scales of resolution. Although the method is indeed to be applied to any microscopy technique, in this paper, we have focused the attention on biological systems, like animal cells, recorded with an atomic force microscopy.

Remote Sensing for Maritime Monitoring and Vessel Prompt Identification

The main purpose of the work described in this paper concerns the development of a platform dedicated to sea surveillance, capable of detecting and identifying illegal maritime traffic. This platform results from the cascade implementation of several image processing algorithms that take as input Radar or Optical maps captured by satellite-borne sensors. More in detail, the processing chain is dedicated to (i) the detection of vessel targets in the input map, (ii) the refined estimation of the vessel most descriptive geometrical features and, finally, (iii) the estimation of the kinematic status of the vessel. This platform will represent a new tool for combating unauthorized fishing, irregular migration and related smuggling activities.

Phantom based point by point photon counting and imaging of human skin tissue

Time-correlated single photon counting (TCSPC) is popular in the resolved techniques due to its prominent performance such as ultra-high time resolution and ultra-high sensitivity. This paper presents advance signal processing techniques on the optical TCSPC signals obtained from the series of experiments on fabricated tissue like phantom. A pulsed laser sources at a wavelength of 830 rim transmits the light through the surface of phantom and finally at receiver side, photon counting device generates the histogram of the receiving signal. The noisy data obtained from the photon counter is processed with the splitting based denoising method. The method divide the signal into different subsets based on the transitions. Each subset is then processed individually and final merging of all subsets gives noise free signal. The main objective of this work is to analyze the signal obtained from photon counter in context of skin blood absorption. We had examined the signal obtained by varying the distance between transmitter and receiver to extract the features. Experimental results with our prototype shows more scattering with the increase in the distance at 3dB level and hence less absorption with increase in the distance.

An image enhancement tool: Pattern Recognition Image Augmented Resolution

PRIAR (Pattern Recognition Image Augmented Resolution) is an innovative approach to singleframe super-resolution that combines common single-frame super-resolution with pattern-recognition algorithms. PRIAR uses the information gained through pattern-recognition to enhance resolution for low quality images, and to allow the end user to explore, recognize and super-resolve low-resolution images. In this paper, we present the basic functionality of the PRIAR algorithm that we have implemented. The program is modular and each module is easily combined. In addition, such modularity permits us to work on images where single modules can be changed in order to resolve different classes of problems. In this paper, we firstly present the features of the PRIAR program processing images reproducing animal cells recorded with a scanning probe microscope.

A Low Cost, Portable Device for Breath Analysis and Self-monitoring, the Wize Sniffer

Here we describe the implementation of the first prototype of the Wize Sniffer 1.x (WS 1.x), a low cost, portable electronic device for breath analysis. The device is being developed in the framework of the Collaborative European Project SEMEOTICONS (SEMEiotic Oriented Technology for Individuals CardiOmetabolic risk self-assessmeNt and Self-monitoring). In the frame of SEMEOTICONS project, the Wize Sniffer will help the user monitor his/her state of health, in particular giving feedbacks about those noxious habits for cardio-metabolic risk, such as alcohol intake and smoking. The low cost and compactness of the device allows for a daily screening that, even if without a real diagnostic meaning, could represent a pre-monitoring, useful for an optimal selection of more sophisticated and standard medical analysis.