Comparison between transcatheter and surgical prosthetic valve implantation in patients with severe aortic stenosis and reduced left ventricular ejection fraction.

BACKGROUND: Patients with severe aortic stenosis and reduced left ventricular ejection fraction (LVEF) have a poor prognosis with conservative therapy but a high operative mortality when treated surgically. Recently, transcatheter aortic valve implantation (TAVI) has emerged as an alternative to surgical aortic valve replacement (SAVR) for patients considered at high or prohibitive operative risk. The objective of this study was to compare TAVI and SAVR with respect to postoperative recovery of LVEF in patients with severe aortic stenosis and reduced LV systolic function. METHODS AND RESULTS: Echocardiographic data were prospectively collected before and after the procedure in 200 patients undergoing SAVR and 83 patients undergoing TAVI for severe aortic stenosis (aortic valve area ≤1 cm(2)) with reduced LV systolic function (LVEF ≤50%). TAVI patients were significantly older (81±8 versus 70±10 years; P<0.0001) and had more comorbidities compared with SAVR patients. Despite similar baseline LVEF (34±11% versus 34±10%), TAVI patients had better recovery of LVEF compared with SAVR patients (ΔLVEF, 14±15% versus 7±11%; P=0.005). At the 1-year follow-up, 58% of TAVI patients had a normalization of LVEF (>50%) as opposed to 20% in the SAVR group. On multivariable analysis, female gender (P=0.004), lower LVEF at baseline (P=0.005), absence of atrial fibrillation (P=0.01), TAVI (P=0.007), and larger increase in aortic valve area after the procedure (P=0.01) were independently associated with better recovery of LVEF. CONCLUSION: In patients with severe aortic stenosis and depressed LV systolic function, TAVI is associated with better LVEF recovery compared with SAVR. TAVI may provide an interesting alternative to SAVR in patients with depressed LV systolic function considered at high surgical risk.

Repulsion and metabolic switches in the collective behavior of bacterial colonies.

Bacteria inoculated on surfaces create colonies that spread out, forming patterns shaped by their mutual interactions. Here, by a combination of experiments and modeling, we address two striking phenomena observed when colonies spread out circularly, without dendritic instabilities. First, the velocity of spreading is generically found to decrease as levels of nutrients initially deposited on the surface increase. We demonstrate that the slowdown is due to phenomena of differentiation, leading to the coexistence of bacteria in different states of motility and we model their dynamics. Second, colonies spreading out from different inocula on the same surface are observed to merge or repel (halting at a finite distance), depending on experimental conditions. We identify the parameters that determine the fate of merging versus repulsion, and predict the profile of arrest in the cases of repulsion.

Inferring maps of forces inside cell membrane microdomains.

Mapping of the forces on biomolecules in cell membranes has spurred the development of effective labels, e.g., organic fluorophores and nanoparticles, to track trajectories of single biomolecules. Standard methods use particular statistics, namely the mean square displacement, to analyze the underlying dynamics. Here, we introduce general inference methods to fully exploit information in the experimental trajectories, providing sharp estimates of the forces and the diffusion coefficients in membrane microdomains. Rapid and reliable convergence of the inference scheme is demonstrated on trajectories generated numerically. The method is then applied to infer forces and potentials acting on the receptor of the toxin labeled by lanthanide-ion nanoparticles. Our scheme is applicable to any labeled biomolecule and results show its general relevance for membrane compartmentation.

A model for thermal exchange in axons during action potential propagation.

Several experiments have shown that during propagation of the action potential in axons, thermal energy is locally exchanged. In this paper, we use a simple model based on statistical physics to show that an important part of this exchange comes from the physics of the effusion. We evaluate, during the action potential propagation, the variation of internal energy and of the energy associated with the chemical potential of the effusion of water and ions to extract the thermal energy exchanged. The temperature exchanged is then evaluated on the area where the action potential is active. Results give a good correspondence between experimental work and this model, showing that an important part of the thermal energy exchange comes from the statistical cooling power of the effusion.