(C) 2011 American Institute of Physics. [doi:10.1063/1.3554623]“
“Background:

Pulmonary vein cryoablation (PVC) is a new approach in the treatment of recurrent atrial fibrillation (AF). Computed tomography (CT) can be used to evaluate the left atrium anatomy and PVs dimensions to facilitate the procedure. In radiofrequency procedures, some anatomic variants such as common left (CLPV) or right selleck chemicals llc (CRPV) PV were reported as factors associated with technical procedure difficulties and potential long-term complications. We hypothesized that the absence of CLPV as determined by CT would predict better AF-free survival after PVC.

Methods and results: We included 118 consecutive patients (mean age 56 +/- 10 years; 77% males) with drug refractory paroxysmal (72%)/persistent (28%) AF, with more than 6 months follow-up, who underwent PVC. On CT scanning images performed within 1 month prior to ablation, we evaluated PV anatomic patterns: presence of CLPV or CRPV. Each patient was evaluated

by 24-hour Holter monitoring within 1 and 3 months and all patients were periodically evaluated at 1, 3, and 6 months, and every 6 months thereafter. Patients see more were asked to record their 12-lead electrocardiogram whenever they experienced symptoms suggestive of AF. Recurrence was defined as AF that lasted at least 30 seconds. CLPV was present in 30 (25%) patients and no patients with CRPV were identified. At the end of the 13 months follow-up, patients with normal PVs had significantly better AF-free survival compared to patients with CLPV (67% vs 50%, P = 0.02). The difference was present in patients with paroxysmal AF (P = 0.008) but not in patients with persistent AF (P = 0.92).

Conclusion: In patients undergoing cryoballoon PV isolation for AF, the presence of normal PVs pattern is associated with better AF-free survival as compared to atypical PV anatomy with CLPV, particularly in patients with paroxysmal AF. (PACE 2011; 34: 837-843)”
“The mycobacterial cell envelope has been implicated in the pathogenicity of tuberculosis and therefore has been a prime target for the identification and characterization

of surface proteins with potential application in drug and vaccine development. In this study, the genome of Mycobacterium tuberculosis H37Rv was screened using Machine Pfizer Licensed Compound Library Learning tools that included feature-based predictors, general localizers and transmembrane topology predictors to identify proteins that are potentially secreted to the surface of M. tuberculosis, or to the extracellular milieu through different secretory pathways. The subcellular localization of a set of 8 hypothetically secreted/surface candidate proteins was experimentally assessed by cellular fractionation and immunoelectron microscopy (IEM) to determine the reliability of the computational methodology proposed here, using 4 secreted/surface proteins with experimental confirmation as positive controls and 2 cytoplasmic proteins as negative controls.