A prediction of bone remodeling thanks to a mechanical signal on cells - Predizione del rimodellamento osseo a partire da un segnale meccanico sulle cellule

This text wants to explore the process of bone remodeling. The idea supported is that the signal, the cells acquire and which suggest them to change in their architectural conformation, is the potential difference on the free boundaries surfaces of collagen fibers. These ones represent the bone in the nanoscale. This work has as subject a multiscale model. Lots of studies have been made to try to discover the relationship between a macroscopic external bone load and the cellular scale. The tree first simulations have been a longitudinal, a flexion and a transversal compression force on a full longitudinal fiber 0-0 sample. The results showed first the great difference between a fully longitudinal stress and a flexion stress. Secondly a decrease in the potential difference has been observed in the transversal force configuration, suggesting that such a signal could be taken as the one, who leads the bone remodeling. To also exclude that the obtained results was not to attribute to a piezoelectric collagen effect and not to a mechanical load, different coupling analyses have been developed. Such analyses show this effect is really less important than the one the mechanical load is responsible of. At this point the work had to explore how bone remodeling could develop. The analyses involved different geometry and fibers percentage. Moreover at the beginning the model was to manually implement. The author, after an initial improvement of it, provided to implement a standalone version thanks to integration between Comsol Multiphysic, Matlab and Excel.

A Phase Space Box-counting based Method for Arrhythmia Prediction from Electrocardiogram Time Series

Arrhythmia is one kind of cardiovascular diseases that give rise to the number of deaths and potentially yields immedicable danger. Arrhythmia is a life threatening condition originating from disorganized propagation of electrical signals in heart resulting in desynchronization among different chambers of the heart. Fundamentally, the synchronization process means that the phase relationship of electrical activities between the chambers remains coherent, maintaining a constant phase difference over time. If desynchronization occurs due to arrhythmia, the coherent phase relationship breaks down resulting in chaotic rhythm affecting the regular pumping mechanism of heart. This phenomenon was explored by using the phase space reconstruction technique which is a standard analysis technique of time series data generated from nonlinear dynamical system. In this project a novel index is presented for predicting the onset of ventricular arrhythmias. Analysis of continuously captured long-term ECG data recordings was conducted up to the onset of arrhythmia by the phase space reconstruction method, obtaining 2-dimensional images, analysed by the box counting method. The method was tested using the ECG data set of three different kinds including normal (NR), Ventricular Tachycardia (VT), Ventricular Fibrillation (VF), extracted from the Physionet ECG database. Statistical measures like mean (μ), standard deviation (σ) and coefficient of variation (σ/μ) for the box-counting in phase space diagrams are derived for a sliding window of 10 beats of ECG signal. From the results of these statistical analyses, a threshold was derived as an upper bound of Coefficient of Variation (CV) for box-counting of ECG phase portraits which is capable of reliably predicting the impeding arrhythmia long before its actual occurrence. As future work of research, it was planned to validate this prediction tool over a wider population of patients affected by different kind of arrhythmia, like atrial fibrillation, bundle and brunch block, and set different thresholds for them, in order to confirm its clinical applicability.

Distribuzione, prevalenza e host range della Skeleton Eroding Band nell'atollo di Faafu, Repubblica delle Maldive

Lo studio delle malattie che colpiscono i coralli rappresenta un campo di ricerca nuovo e poche sono le ricerche concentrate nell’Oceano Indo-Pacifico, in particolare nella Repubblica delle Maldive. Lo scopo di questa ricerca è stato approfondire le conoscenze riguardo distribuzione, prevalenza e host range della Skeleton Eroding Band (SEB) nell’atollo di Faafu. Durante il lavoro, svolto in campo tra il novembre e il dicembre 2013, sono state indagate le isole di: Magoodhoo, Filitheyo e Adangau al fine di rilevare differenze nei livelli di prevalenza della SEB in relazione ai diversi gradi di utilizzo da parte dell’uomo delle 3 isole. Il piano di campionamento ha previsto la scelta casuale, in ciascuna delle isole, di 4 siti in cui sono stati realizzati 3 belt transect e 3 point intercept transect a 2 profondità predefinite. La SEB è stata ritrovata con una prevalenza media totale di 0,27%. Dai risultati dell’analisi statistica le differenze fra le isole non sono apparse significative, facendo ipotizzare che i livelli di prevalenza differiscano a causa di oscillazioni casuali di carattere naturale e che quindi non siano dovute a dinamiche legate al diverso sfruttamento da parte dell’uomo. I generi Acropora e Pocillopora sono risultati quelli maggiormente colpiti con valori di prevalenza totale di 0,46% e 1,33%. Infine è stata rilevata una correlazione positiva tra il numero di colonie di madrepore affette dalla SEB e il numero di colonie in cui la malattia è associata alla presenza di lesioni provocate da danni meccanici. I dati di prevalenza ottenuti e le previsioni di cambiamenti climatici in grado di aumentare distribuzione, host range, abbondanza della patologia, pongono l’accento sulla necessità di chiarire il ruolo delle malattie dei coralli nel deterioramento, resilienza e recupero dei coral reefs, al fine di attuare politiche di gestione adatte alla protezione di questi fragili ecosistemi.