Phylogeography and non-invasive landscape genetics of the European pine marten ("martes martes" L. 1758) : insights into ancient and contemporary processes shaping genetic variation

283 p. : graf., map.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Novel equation to determine the hepatic triglyceride concentration in humans by MRI: diagnosis and monitoring of NAFLD in obese patients before and after bariatric surgery

Background: Non-alcoholic fatty liver disease (NAFLD) is caused by abnormal accumulation of lipids within liver cells. Its prevalence is increasing in developed countries in association with obesity, and it represents a risk factor for non-alcoholic steatohepatitis (NASH), cirrhosis and hepatocellular carcinoma. Since NAFLD is usually asymptomatic at diagnosis, new non-invasive approaches are needed to determine the hepatic lipid content in terms of diagnosis, treatment and control of disease progression. Here, we investigated the potential of magnetic resonance imaging (MRI) to quantitate and monitor the hepatic triglyceride concentration in humans. Methods: A prospective study of diagnostic accuracy was conducted among 129 consecutive adult patients (97 obesity and 32 non-obese) to compare multi-echo MRI fat fraction, grade of steatosis estimated by histopathology, and biochemical measurement of hepatic triglyceride concentration (that is, Folch value). Results: MRI fat fraction positively correlates with the grade of steatosis estimated on a 0 to 3 scale by histopathology. However, this correlation value was stronger when MRI fat fraction was linked to the Folch value, resulting in a novel equation to predict the hepatic triglyceride concentration (mg of triglycerides/g of liver tissue = 5.082 + (432.104 * multi-echo MRI fat fraction)). Validation of this formula in 31 additional patients (24 obese and 7 controls) resulted in robust correlation between the measured and estimated Folch values. Multivariate analysis showed that none of the variables investigated improves the Folch prediction capacity of the equation. Obese patients show increased steatosis compared to controls using MRI fat fraction and Folch value. Bariatric surgery improved MRI fat fraction values and the Folch value estimated in obese patients one year after surgery. Conclusions: Multi-echo MRI is an accurate approach to determine the hepatic lipid concentration by using our novel equation, representing an economic non-invasive method to diagnose and monitor steatosis in humans.

Application of Entropy and Fractal Dimension Analyses to the Pattern Recognition of Contaminated Fish Responses in Aquaculture

The objective of the work was to develop a non-invasive methodology for image acquisition, processing and nonlinear trajectory analysis of the collective fish response to a stochastic event. Object detection and motion estimation were performed by an optical flow algorithm in order to detect moving fish and simultaneously eliminate background, noise and artifacts. The Entropy and the Fractal Dimension (FD) of the trajectory followed by the centroids of the groups of fish were calculated using Shannon and permutation Entropy and the Katz, Higuchi and Katz-Castiglioni's FD algorithms respectively. The methodology was tested on three case groups of European sea bass (Dicentrarchus labrax), two of which were similar (C1 control and C2 tagged fish) and very different from the third (C3, tagged fish submerged in methylmercury contaminated water). The results indicate that Shannon entropy and Katz-Castiglioni were the most sensitive algorithms and proved to be promising tools for the non-invasive identification and quantification of differences in fish responses. In conclusion, we believe that this methodology has the potential to be embedded in online/real time architecture for contaminant monitoring programs in the aquaculture industry.

Pazienteen bihotz eta arnasketa maiztasunen monitorizazioa burmuineko infragorri hurbileko espektroskopia seinaleak erabiliz

Lan honen helburua, burmuineko oxigeno maila neurtzeko NIRS (Near Infrarred Spectroscopy) teknika ez-inbaditzaileaz baliatzen den sistema baten eraginkortasuna neurtzea da, pazientearen parametro fisiologikoak diren bihotz eta arnasketa maiztasunak neurtzerako orduan. Orain arte, pazientearen oxigenazioaren monitorizazioa gauzatzea beharrezkoa den egoeratan, atzamarreko oxigenazio maila neurtzea ahalbidetzen duen PPG (Photoplethysmogram) teknika erabili da. Emergentzia egoeratan, ordea, sistema kardiobaskularrak bizi irauteko nahitaezkoak diren organoei ematen die lehentasuna, garuna eta bihotzari, alegia. Bi organo hauek oxigeno jario jarraituaz hornituak direla egiaztatzeko, ezinbestekoa izango da burmuineko oxigenazio maila neurtzea eta berriki frogatu da NIRS teknikak esparru honetan etorkizun handiko emaitzak eskaini ditzakeela. Hau dela eta, azken urteotan, NIRS teknikak lekua hartu dio orain arte agertoki mediku gehienetan erabilitako PPG teknikari, gaur egun teknika hau aplikazio ugaritan erabiltzen hasia delarik, adibidez kirurgia kardiobaskularraren monitorizazioa edo anestesia orokorraren bitarteko monitorizazioa. NIRS teknikak, garuneko oxigenazio mailaz aparte, pazientearen beste hainbat parametro fisiologikoren neurketa ahalbidetuko balu (arnasketa eta bihotz maiztasuna), agertoki mediku asko erraztuko lituzke, gailu bakar batekin pazientearen bizi-konstante anitzen monitorizazio eramango baitzen aurrera. Tresna hau egingarria dela egiaztatzeko, lehenik eta behin, NIRS seinalea bizi-konstante hauen berri emateko gai dela balioetsi behar da eta hauxe da, hain zuzen, proiektu honen xede nagusia. Azken helburu hau lortzeko, hainbat azpi-helburu proposatzen dira hemen aurkeztuko den proiektuan: lehenik eta behin, NIRS seinaleak eta bizi konstante hauek era fidagarrian lortzea ahalbidetzen duten seinaleak biltegiratzen dituen datu base bat sortuko da. Datu base hau osatzeko, aurreko seinale guztiak aldi berean eskuratuko dituen neurketa sistema sinkrono bat sortzea ezinbestekoa izango da eta azkenik, NIRS seinaleen eraginkortasuna ebaluatzeko, seinaleen prozesaketan oinarritutako hainbat algoritmo garatuko dira.

Molecular ecology of european mustelids: Unraveling evolutionary and ecological patterns in Martes and Lutra genera

208 p.

New neuroimaging methods for clinical neuroscience and neurological disorders

236 p.

Predictive score for mortality in patients with COPD exacerbations attending hospital emergency departments

Background: Limited information is available about predictors of short-term outcomes in patients with exacerbation of chronic obstructive pulmonary disease (eCOPD) attending an emergency department (ED). Such information could help stratify these patients and guide medical decision-making. The aim of this study was to develop a clinical prediction rule for short-term mortality during hospital admission or within a week after the index ED visit. Methods: This was a prospective cohort study of patients with eCOPD attending the EDs of 16 participating hospitals. Recruitment started in June 2008 and ended in September 2010. Information on possible predictor variables was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up. Main short-term outcomes were death during hospital admission or within 1 week of discharge to home from the ED, as well as at death within 1 month of the index ED visit. Multivariate logistic regression models were developed in a derivation sample and validated in a validation sample. The score was compared with other published prediction rules for patients with stable COPD. Results: In total, 2,487 patients were included in the study. Predictors of death during hospital admission, or within 1 week of discharge to home from the ED were patient age, baseline dyspnea, previous need for long-term home oxygen therapy or non-invasive mechanical ventilation, altered mental status, and use of inspiratory accessory muscles or paradoxical breathing upon ED arrival (area under the curve (AUC) = 0.85). Addition of arterial blood gas parameters (oxygen and carbon dioxide partial pressures (PO2 and PCO2)) and pH) did not improve the model. The same variables were predictors of death at 1 month (AUC = 0.85). Compared with other commonly used tools for predicting the severity of COPD in stable patients, our rule was significantly better. Conclusions: Five clinical predictors easily available in the ED, and also in the primary care setting, can be used to create a simple and easily obtained score that allows clinicians to stratify patients with eCOPD upon ED arrival and guide the medical decision-making process.

Fluorescence cross-correlation spectroscopy to study hemodynamics

[EN] In the recent years a series of optical correlation techniques have been developed in order to be able to measure flow velocity with high spatial resolution while being non-invasive in order to be employed in-vivo on biological organisms. The technique employed in my thesis work, scanning laser image correlation (SLIC), is a powerful approach for the detection of flow motions because it overcomes some limitations of the classical spectroscopy techniques. SLIC method consists in repeated laser scans over a linear pattern and on the cross correlation of the signal emitted by the excited fluorophores in different positions along the scan line. Therefore, the resulting measurements for flow velocity are really accurate.

Long-Term Epidemiology of Streptococcus pneumoniae Serogroup 6 in a Region of Southern Europe with Special Reference to Serotype 6E

Streptococcus pneumoniae serotype 6E has recently been described, but its long-term epidemiology is not well known. From 1981-2013, 704 serogroup 6 clinical isolates were obtained in Gipuzkoa, Basque Country, Spain. All invasive and one in four non-invasive isolates were included. Overall, 75, 97, 51 and 45 serotypes 6A, 6B, 6C and 6E isolates, respectively, were detected. No serotype 6D isolates were identified. The prevalence of serotypes 6E and 6B, but not that of serotypes 6A and 6C, declined after the introduction of pneumococcal conjugate vaccines. Serotype 6E isolates showed the highest resistance rate. Most serotype 6E isolates were ST90.