Diabetes and Critical Limb Ischemia. Evaluation of Serological Vascular damage markers: quantitative determination of circulating mature endothelial cells

OBIETTIVO : Quantificare le CECs/ml nei pazienti affetti da ischemia critica (IC) degli arti inferiori, eventuali correlazioni tra i fattori di rischio, lo stadio clinico con l’ aumento delle CECs. Valutare i cambiamenti strutturali (calcificazione ed infiltratto infiammatorio) e l’ angiogenesi (numero di capillari /sezione) della parete arteriosa. MATERIALI E METODI: Da Maggio 2006 ad Aprile 2008 in modo prospettico abbiamo arruolato paziente affetti da IC da sottoporre ad intervento chirurgico. In un data base abbiamo raccolto : caratteristiche demografiche, fattori di rischio, stadiazione dell'IC secondo Leriche-Fontaine (L-F), il tipo di intervento chirurgico. Per ogni paziente abbiamo effettuato un prelievo ematico di 2 ml per la quantificazione immunomagnetica delle CECs e prelievo di parete arteriosa. RISULTATI: In modo consecutivo abbiamo arruolato 33 pazienti (75.8% maschi) con età media di 71 aa (range 34-91aa), affetti da arteriopatia ostruttiva cronica periferica al IV stadio di L-F nel 84.8%, da cardiopatia ischemica cronica nel 60.6%, da ipertensione arteriosa nel 72.7% e da diabete mellito di II tipo nel 66.6%. Il valore medio di CECs/ml è risultato significativamente più elevato (p= 0.001) nei soggetti affetti da IC (CECs/ml =531.24 range 107- 3330) rispetto ai casi controllo (CECs/ml = 125.8 range 19-346 ). Le CECs/ml nei pazienti diabetici sono maggiori rispetto alle CECs/ml nei pazienti non diabetici ( 726.7 /ml vs 325.5/ml ), p< 0.05 I pazienti diabetici hanno presentato maggior incidenza di lesioni arteriose complesse rispetto ai non diabetici (66% vs 47%) e minor densità capillare (65% vs 87%). Conclusioni : Le CECs sono un marker sierologico attendibile di danno vascolare parietale, la loro quantità è maggiore nei pazienti diabetici e ipertesi. La minor capacità angiogenetica della parete arteriosa in presenza di maggior calcificazioni ed infiltrato infiammatorio nei diabetici, dimostra un danno istopatologico di parete maggiore .OBJECTIVE: To quantify the number of circulating endothelial mature cells (EMC) in patients with critical limb ischemia (CI), and if correlations exit with risk factors, clinical stage and the number of cEMC. Evaluate the vascular structure changes (calcification and inflammatory infiltrate) and angiogenesis (number of capillary/arterial slice) of arterial wall. METHODS: Between 2006, may, and 2008, april, we’ve enrolled in a prospective study patients with CI scheduled for surgery. Demographic data, risk factors, clinical stage according to Leriche-Fontaine, type of surgery have been collected and stored in a database. For every patient 2 ml of blood have been sampled for immunomagnetic quantification of cEMC, so as a sample of the arterial wall. RESULTS: Thirtythree patients (25 males, 75,8%), aged 34-91, average 71years old, with CI underwent surgical revascularization have been enrolled. Twentyeight patients (84.8%) had a IV stage PAOD, chronic heart ischemia (60.6%), hypertension (72.7%) and diabetes mellitus type II (66.6%). The average concentration of cEMC/ml is significant higher (p=0.001) in patients with CI (cEMC=531.24, range 107-3330) than in control cases (cEMC =125.8, range 19-346). Also patients with diabetes type II have a higher concentration of cEMC than the non-diabetic patients (726.7/mm vs 325.5/ml vs.), with a p<0.05. Arterial wall of pts. with diabetes , compared with control group, revealed a higher incidence of complex arterial lesions (66% vs. 47%) and a lower capillary density (65% vs. 87%). CONCLUSION: cEMC are a reliable marker of vascular wall damage. Their concentration is higher in patients with diabetes, hypertensive disease. In patients with diabetes type 2 we’ve found a minor angiogenic capability with more calcifications and inflammatory infiltrate, showing a more serious damag

Modeling Data Analytics Architecture for Smart Cities Data-Driven Applications using DAT

Extracting valuable insights from vast amounts of information is a critical process that involves acquiring, storing, managing, analyzing, and visualizing data. Providing an abstract overview of data analytics applications is crucial to ensure that collected data is transformed into meaningful information. One effective way of achieving this objective is through Data Architecture. This article shares our experiences in developing a Data Analytics Architecture (DAA) using model-driven engineering for Data-Driven Smart Cities applications utilizing DAT

Progetto e sviluppo di un'architettura Wireless Mesh Network basata su standard IEEE 802.11s

In questa tesi è stata sviluppata un'architettura software per l'implementazione di una Wireless Mesh Network basata sul più recente draft a disposizione dello standard IEEE 802.11s. Il sistema si presenta come una interfaccia logica del livello MAC IEEE 802.11 implementata in un software user space. In particolare è stato realizzato un framework di base per il supporto di più moduli funzioanli ed alcune funzionalità sono state sviluppate nel dettaglio. I moduli principali del programma si occupano della creazione e gestione automatica della topologia di rete e dell'implementazione del protocollo di routing HWMP completamente a livello 2. In particolare è stato sviluppata la parte dei routing preventiva per la formazione di un albero di inoltro verso il Portal della rete; sono state aggiunte delle procedure di ottimizzazione e mantenimento dell'albero e alcuni meccanismi ulteriori per permettere il recupero della connettività nel caso di caduta di un nodo. Inoltre è stato realizzato un testbed per verificare le funzionalità del framework

Data Architecture for Digital Object Space Management Service (DOSM) using DAT

The Internet of Things (IoT) data and social media data are two of the fastest-growing data segments. Having high-quality data is crucial for making informed business decisions. The strategic process of leveraging insights from data is known as data-driven decision-making. To achieve this, it is necessary to collect, store, analyze, and protect data in the best ways possible. Data architecture is a complex task that involves describing the flow of data from its source to its destination and creating a blueprint for managing the data to meet business needs for information. In this paper, we utilize the Data Architecture Tool (DAT) to model data for Digital Space Management Service, which was developed as part of the VASARI project. This work focuses on describing the movement of data, data formats, data location, data processing (batch or real-time), data storage technologies, and main operations on the data

The first ultra-high resolution Digital Terrain Model of the shallow-water sector around Lipari Island (Aeolian Islands, Italy)

Very high resolution bathymetric map obtained through multibeam echosounders data are crucial to generate accurate Digital Terrain Models from which the morphological setting of active volcanic areas can be analyzed in detail. Here we show and discuss the main results from the first multibeam bathymetric survey performed in shallow-waters around the island of Lipari, the largest and the most densely populated of the Aeolian Islands (southern Italy). Data have been collected in the depth range of 0.1-150 m and complete the already existent high-resolution multibeam bathymetry realized between 100 and 1300 m water depth. The new ultrahigh resolution bathymetric maps at 0.1-0.5 m provide new insights on the shallow seafloor of Lipari, allowing to detail a large spectrum of volcanic, erosive-depositional and anthropic features. Moreover, the presented data allow outlining the recent morphological evolution of the shallow coastal sector of this active volcanic island, indicating the presence of potential geo-hazard factors in shallow waters

DAT: Data Architecture Modeling Tool for Data-Driven Applications

Data is the key to success for any Data-Driven Organization, and managing it is considered the most challenging task. Data Architecture (DA) focuses on describing, collecting, storing, processing, and analyzing the data to meet business needs. In this tool demo paper, we present the DAT, a model-driven engineering tool enabling data architects, data engineers, and other stakeholders to describe how data flows through the system and provides a blueprint for managing data that saves time and effort dedicated to Data Architectures for IoT applications. We evaluated this work by modeling five case studies, receiving expressiveness and ease of use feedback from two companies, more than six researchers, and eighteen undergraduate students from the software architecture cours