Digital Technologies in Providing Development of Algorithms Surgical Treatment of Supraventricular Arrhythmias

The aim of the study was the development and clinical application of patient selection algorithm for surgical treatment of longlasting persistent atrial fibrillation. The study included 235 patients with acquired heart disease and coronary artery disease, which in the period from 1999 to 2015 performed surgical treatment of long-term persistent atrial fibrillation (RF “MAZE III” procedure) in conjunction with the correction of the underlying heart disease. The patients were divided into 2 groups according to the method of operation: the group 1 – 135 patients (76 women and 59 men) who have applied an integrated approach to surgery for atrial fibrillation, including penetrating method of RF effects on atrial myocardium and the study of the function of the sinus node before and after the operation (these patients were operated on from 2008 to 2015). The group 2 – 100 patients (62 women and 38 men) with a “classical” method of monopolar RF “MAZE III”, which the sinus node function was not studied. We used the combined (epi- and endocardial) method of RF "MAZE". This algorithm is decreasing of possible permanent pacemaker postoperatively. The initial sinus node function in these patients, measured using the original method, the basic line of this algorithm was taken. The results showed that use this algorithm for selection of patients allows significantly reduce the possibility of pacemaker implantation in the postoperative perio

Distinguishing Parkinson's disease from atypical parkinsonian syndromes using PET data and a computer system based on support vector machines and Bayesian networks

Differentiating between Parkinson's disease (PD) and atypical parkinsonian syndromes (APS) is still a challenge, specially at early stages when the patients show similar symptoms. During last years, several computer systems have been proposed in order to improve the diagnosis of PD, but their accuracy is still limited. In this work we demonstrate a full automatic computer system to assist the diagnosis of PD using 18F-DMFP PET data. First, a few regions of interest are selected by means of a two-sample t-test. The accuracy of the selected regions to separate PD from APS patients is then computed using a support vector machine classifier. The accuracy values are finally used to train a Bayesian network that can be used to predict the class of new unseen data. This methodology was evaluated using a database with 87 neuroimages, achieving accuracy rates over 78%. A fair comparison with other similar approaches is also provided.This work is part of a project approved by the Andalucía Talent Hub Program launched by the Andalusian Knowledge Agency, co-funded by the European Union's Seventh Framework Program, Marie Sklodowska-Curie actions (COFUND Grant Agreement no 291780) and the Ministry of Economy, Innovation, Science and Employment of the Junta de Andalucía. The work was also supported by the University of Granada (Spain), the University for Munich (Germany), the MICINN (Spain) under the TEC2012–34306 project and the Consejera de Innovacin, Ciencia y Empresa (Junta de Andaluca, Spain) under the P11–TIC–7103 excellence project

Treatment of refractory epilepsy with natalizumab in a patient with multiple sclerosis. Case report

Background. Multiple sclerosis (MS) is considered an autoimmune disease of the central nervous system and therapeutic inhibition of leukocyte migration with natalizumab, an anti-alpha4 integrin antibody, is highly effective in patients with MS. Recent studies performed in experimental animal models with relevance to human disease suggested a key role for blood-brain barrier damage and leukocyte trafficking mechanisms also in the pathogenesis of epilepsy. In addition, vascular alterations and increased leukocyte accumulation into the brain were recently documented in patients with refractory epilepsy independently on the disease etiology. Case report. Here we describe the clinical course of a 24-year-old patient with MS in whom abrupt tonic-clonic generalized seizures manifested at disease onset. Although MS had a more favorable course, treatment with glatiramer acetate and antiepileptic drugs for 7 years had no control on seizure generation and the patient developed severe refractory epilepsy. Interestingly, generalized seizures preceded new MS relapses suggesting that seizure activity may contribute to MS worsening creating a positive feedback loop between the two disease conditions. Notably, treatment with natalizumab for 12 months improved MS condition and led to a dramatic reduction of seizures. Conclusion. Our case report suggests that inhibition of leukocyte adhesion may represent a new potential therapeutic approach in epilepsy and complement the traditional therapy with anti-epileptic drugs

An Experimental and Computational Study of the Effect of ActA Polarity on the Speed of Listeria monocytogenes Actin-based Motility

Listeria monocytogenes is a pathogenic bacterium that moves within infected cells and spreads directly between cells by harnessing the cell's dendritic actin machinery. This motility is dependent on expression of a single bacterial surface protein, ActA, a constitutively active Arp2,3 activator, and has been widely studied as a biochemical and biophysical model system for actin-based motility. Dendritic actin network dynamics are important for cell processes including eukaryotic cell motility, cytokinesis, and endocytosis. Here we experimentally altered the degree of ActA polarity on a population of bacteria and made use of an ActA-RFP fusion to determine the relationship between ActA distribution and speed of bacterial motion. We found a positive linear relationship for both ActA intensity and polarity with speed. We explored the underlying mechanisms of this dependence with two distinctly different quantitative models: a detailed agent-based model in which each actin filament and branched network is explicitly simulated, and a three-state continuum model that describes a simplified relationship between bacterial speed and barbed-end actin populations. In silico bacterial motility required a cooperative restraining mechanism to reconstitute our observed speed-polarity relationship, suggesting that kinetic friction between actin filaments and the bacterial surface, a restraining force previously neglected in motility models, is important in determining the effect of ActA polarity on bacterial motility. The continuum model was less restrictive, requiring only a filament number-dependent restraining mechanism to reproduce our experimental observations. However, seemingly rational assumptions in the continuum model, e.g. an average propulsive force per filament, were invalidated by further analysis with the agent-based model. We found that the average contribution to motility from side-interacting filaments was actually a function of the ActA distribution. This ActA-dependence would be difficult to intuit but emerges naturally from the nanoscale interactions in the agent-based representation

An evaluation of the PM2.5 trace elemental composition in the VeniceLagoon area and an analysis of the possible sources

Global emissions reported by many authors have shown as natural and anthropic sources can contribute to the principal aerosol classes, but values change according the local scenario. The Venice Lagoon is exposed to different anthropic source emissions like vehicular traffic, industrial thermoelectric power plant, petrochemical plant, incinerator plant, domestic heating, ship traffic, glass factories and airport. Samplings of PM2.5 were daily performed between March and November 2007 in Sacca San Biagio island (Venice), and values of PM2.5 concentration and element concentration were obtained. Monthly average concentrations (mgm3) during this period show higher values during the spring and the autumn. A good relationship between data obtained and concentration values from environmental local agencies is evidenced, both for PM2.5 from urban area (Venezia Mestre), and for PM10 sampled in the same area, as well as the influence of some meteorological parameters on PM2.5 concentration sampled. Trace elements samples were measured by an Inductively Coupled Plasma-Quadrupole Mass Spectrometry (ICP-QMS), and values (ng m3 and mg g1) for elements regulated by European directives (As, Cd, Ni, Pb), as well as, other elements (Na, Al, K, Ti, V, Mn, Fe, Co, Zn, Se, Ag) are also reported. Data analysis by mean of Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) pointed out four principal groups of elements like Mn–Fe–K, As–Se–Cd, V–Co, and Pb that could be assigned to specific sources of the Venetian wetland basin

Identification of Key Processes that Control Tumor Necrosis Factor Availability in a Tuberculosis Granuloma

Tuberculosis (TB) granulomas are organized collections of immune cells comprised of macrophages, lymphocytes and other cells that form in the lung as a result of immune response to Mycobacterium tuberculosis (Mtb) infection. Formation and maintenance of granulomas are essential for control of Mtb infection and are regulated in part by a pro-inflammatory cytokine, tumor necrosis factor-α (TNF). To characterize mechanisms that control TNF availability within a TB granuloma, we developed a multi-scale two compartment partial differential equation model that describes a granuloma as a collection of immune cells forming concentric layers and includes TNF/TNF receptor binding and trafficking processes. We used the results of sensitivity analysis as a tool to identify experiments to measure critical model parameters in an artificial experimental model of a TB granuloma induced in the lungs of mice following injection of mycobacterial antigen-coated beads. Using our model, we then demonstrated that the organization of immune cells within a TB granuloma as well as TNF/TNF receptor binding and intracellular trafficking are two important factors that control TNF availability and may spatially coordinate TNF-induced immunological functions within a granuloma. Further, we showed that the neutralization power of TNF-neutralizing drugs depends on their TNF binding characteristics, including TNF binding kinetics, ability to bind to membrane-bound TNF and TNF binding stoichiometry. To further elucidate the role of TNF in the process of granuloma development, our modeling and experimental findings on TNF-associated molecular scale aspects of the granuloma can be incorporated into larger scale models describing the immune response to TB infection. Ultimately, these modeling and experimental results can help identify new strategies for TB disease control/therapy

Intracellular Trafficking Considerations in the Development of Natural Ligand-Drug Molecular Conjugates for Cancer

Overexpressed receptors, characteristic of many cancers, have been targeted by various researchers to achieve a more specific treatment for cancer. A common approach is to use the natural ligand for the overexpressed receptor as a cancer-targeting agent which can deliver a chemically or genetically conjugated toxic molecule. However, it has been found that the therapeutic efficacy of such ligand-drug molecular conjugates can be limited, since they naturally follow the intracellular trafficking pathways of the endogenous ligands. Therefore, a thorough understanding of the intracellular trafficking properties of these ligands can lead to novel design criteria for engineering ligands to be more effective drug carriers. This review presents a few commonly used ligand/receptor systems where intracellular trafficking considerations can potentially improve the therapeutic efficacy of the ligand-drug molecular conjugates