The effect of cis-5,8,11,14,17-eicosapentaenoic acid upon the contractile mechanisms linked to calcium influx and the mobilisation of intracellular calcium in aortic smooth muscle

Epidemiological studies previously identified cis-5,8,11,14,17-eicosapentaenoic acid (EPA) as the biologically active component of fish oil of benefit to the cardiovascular system. Although clinical investigations demonstrated its usefulness in surgical procedures, its mechanism of action still remained unclear. It was shown in this thesis, that EPA partially blocked the contraction of aortic smooth muscle cells to the vasoactive agents KCl and noradrenaline. The latter effect was likely caused by reducing calcium influx through receptor-operated channels, supporting a recent suggestion by Asano et al (1997). Consistently, EPA decreased noradrenaline-induced contractures in aortic tissue, in support of previous reports (Engler, 1992b). The observed effect of EPA on cell contractions to KCl was not simple due to blocking calcium influx through L-type channels, consistent with a previous suggestion by Hallaq et al (1992). Moreover, EPA caused a transient increase in [Ca2+]i in the absence of extracellular calcium. To resolve this it was shown that EPA increased inositol phosphate formation which, it is suggested, caused the release of calcium from an inositol phosphate-dependent internal binding site, possibly that of an intracellular membrane or superficial sarcoplasmic reticulum, producing the transient increase in [Ca2+]i. As it was shown that the cellular contractile filaments were not desensitised to calcium by EPA, it is suggested that the transient increase in [Ca2+]i subsequently blocks further cell contraction to KCl by activating membrane-associated potassium channels. Activation of potassium channels induces the cellular efflux of potassium ions, thereby hyperpolarising the plasma membrane and moving the membrane potential farther from the activation range for calcium channels. This would prevent calcium influx in the longer term and could explain the initial observed effect of EPA to block cell contraction to KCl.

Handling high level of censoring for endovascular aortic repair risk prediction

Feature selection is important in medical field for many reasons. However, selecting important variables is a difficult task with the presence of censoring that is a unique feature in survival data analysis. This paper proposed an approach to deal with the censoring problem in endovascular aortic repair survival data through Bayesian networks. It was merged and embedded with a hybrid feature selection process that combines cox's univariate analysis with machine learning approaches such as ensemble artificial neural networks to select the most relevant predictive variables. The proposed algorithm was compared with common survival variable selection approaches such as; least absolute shrinkage and selection operator LASSO, and Akaike information criterion AIC methods. The results showed that it was capable of dealing with high censoring in the datasets. Moreover, ensemble classifiers increased the area under the roc curves of the two datasets collected from two centers located in United Kingdom separately. Furthermore, ensembles constructed with center 1 enhanced the concordance index of center 2 prediction compared to the model built with a single network. Although the size of the final reduced model using the neural networks and its ensembles is greater than other methods, the model outperformed the others in both concordance index and sensitivity for center 2 prediction. This indicates the reduced model is more powerful for cross center prediction.

The risk of re-intervention after endovascular aortic aneurysm repair

This thesis studies survival analysis techniques dealing with censoring to produce predictive tools that predict the risk of endovascular aortic aneurysm repair (EVAR) re-intervention. Censoring indicates that some patients do not continue follow up, so their outcome class is unknown. Methods dealing with censoring have drawbacks and cannot handle the high censoring of the two EVAR datasets collected. Therefore, this thesis presents a new solution to high censoring by modifying an approach that was incapable of differentiating between risks groups of aortic complications. Feature selection (FS) becomes complicated with censoring. Most survival FS methods depends on Cox's model, however machine learning classifiers (MLC) are preferred. Few methods adopted MLC to perform survival FS, but they cannot be used with high censoring. This thesis proposes two FS methods which use MLC to evaluate features. The two FS methods use the new solution to deal with censoring. They combine factor analysis with greedy stepwise FS search which allows eliminated features to enter the FS process. The first FS method searches for the best neural networks' configuration and subset of features. The second approach combines support vector machines, neural networks, and K nearest neighbor classifiers using simple and weighted majority voting to construct a multiple classifier system (MCS) for improving the performance of individual classifiers. It presents a new hybrid FS process by using MCS as a wrapper method and merging it with the iterated feature ranking filter method to further reduce the features. The proposed techniques outperformed FS methods based on Cox's model such as; Akaike and Bayesian information criteria, and least absolute shrinkage and selector operator in the log-rank test's p-values, sensitivity, and concordance. This proves that the proposed techniques are more powerful in correctly predicting the risk of re-intervention. Consequently, they enable doctors to set patients’ appropriate future observation plan.

Design and performance assessment of aortic heart valve for tissue engineering

Current artificial heart valves are classified as mechanical and bioprosthetic. An appealing pathway that promises to overcome the shortcomings of commercially available heart valves is offered by the interdisciplinary approach of cardiovascular tissue engineering. However, the mechanical properties of the Tissue Engineering Heart Valves (TEHV) are limited and generally fail in the long-term use. To meet this performance challenge novel biodegradable triblock copolymer poly(ethylene oxide)-polypropylene oxide)-poly(ethylene oxide) (PEO-PPO-PEO or F108) crosslinked to Silk Fibroin (F108-SilkC) to be used as tri-leaflet heart valve material was investigated. ^ Synthesis of ten polymers with varying concentration and thickness (55 µm, 75 µm and 100 µm) was achieved via a covalent crosslinking scheme using bifunctional polyethylene glycol diglycidyl ether (PEGDE). Static and fatigue testing were used to assess mechanical properties of films, and hydrodynamic testing was performed to determine performance under a simulated left ventricular flow regime. The crosslinked copolymer (F108-Silk C) showed greater flexibility and resilience, but inferior ultimate tensile strength, by increasing concentration of PEGDE. Concentration molar ratio of 80:1 (F108: Silk) and thickness of 75 µm showed longer fatigue life for both tension-tension and bending fatigue tests. Four valves out of twelve designed satisfactorily complied with minimum performance requirement ISO 5840, 2005. ^ In conclusion, it was demonstrated that the applicability of a degradable polymer in conjugation with silk fibroin for tissue engineering cardiovascular use, specifically for aortic valve leaflet design, met the performance demands. Thinner thicknesses (t<75 µm) in conjunction with stiffness lower than 320 MPa (80:1, F108: Silk) are essential for the correct functionality of proposed heart valve biomaterial F108-SilkC. Fatigue tests were demonstrated to be a useful tool to characterize biomaterials that undergo cyclic loading. ^

Safety and Use of Anticoagulation After Aortic Valve Replacement With Bioprostheses: A Meta-Analysis.

BACKGROUND: The American College of Cardiology guidelines recommend 3 months of anticoagulation after replacement of the aortic valve with a bioprosthesis. However, there remains great variability in the current clinical practice and conflicting results from clinical studies. To assist clinical decision making, we pooled the existing evidence to assess whether anticoagulation in the setting of a new bioprosthesis was associated with improved outcomes or greater risk of bleeding. METHODS AND RESULTS: We searched the PubMed database from the inception of these databases until April 2015 to identify original studies (observational studies or clinical trials) that assessed anticoagulation with warfarin in comparison with either aspirin or no antiplatelet or anticoagulant therapy. We included the studies if their outcomes included thromboembolism or stroke/transient ischemic attacks and bleeding events. Quality assessment was performed in accordance with the Newland Ottawa Scale, and random effects analysis was used to pool the data from the available studies. I(2) testing was done to assess the heterogeneity of the included studies. After screening through 170 articles, a total of 13 studies (cases=6431; controls=18210) were included in the final analyses. The use of warfarin was associated with a significantly increased risk of overall bleeding (odds ratio, 1.96; 95% confidence interval, 1.25-3.08; P<0.0001) or bleeding risk at 3 months (odds ratio, 1.92; 95% confidence interval, 1.10-3.34; P<0.0001) compared with aspirin or placebo. With regard to composite primary outcome variables (risk of venous thromboembolism, stroke, or transient ischemic attack) at 3 months, no significant difference was seen with warfarin (odds ratio, 1.13; 95% confidence interval, 0.82-1.56; P=0.67). Moreover, anticoagulation was also not shown to improve outcomes at time interval >3 months (odds ratio, 1.12; 95% confidence interval, 0.80-1.58; P=0.79). CONCLUSIONS: Contrary to the current guidelines, a meta-analysis of previous studies suggests that anticoagulation in the setting of an aortic bioprosthesis significantly increases bleeding risk without a favorable effect on thromboembolic events. Larger, randomized controlled studies should be performed to further guide this clinical practice.

A time bomb in the thorax: the giant ascending aortic aneurysm. Case report

We report the case of a 82-year-old woman, asymptomatic, subject to chest computed tomography for trauma. Then the patient underwent surgery. Before sternotomy, femoro-femoral bypass was starter in order to decompress the aneurysm; using deep hypothermia and circulatory arrest, ascending aorta and hemiarch replacement were performed with a Dacron graft. Post-operative course was uneventful.

Aortic valve replacement through the upper ministernotomy. Preliminary experience with modified technique

Minimally invasive approach for aortic valve surgery has been developed since 1995, reducing the complications related to the full sternotomy. We have introduced a new method for central cannulation that reduces the length of surgical incision for the aortic valve replacement through upper mini-sternotomy. To improve the surgical view without enlargement of the incision, two small additional incisions are performed for both arterial and atrial cannulation. We have used the modified technique in 60 patients without sternal infection or other surgical complications and with good cosmetic results. Cardiac surgery - Aortic valve replacement - Minimally invasive approach.