Erratum: COMPARE CPM-RMI trial: Intramyocardial transplantation of autologous bone marrow-derived CD133+ cells and MNCs during CABG in patients with recent MI: A phase II/III, multicenter, placebo-controlled, randomized, double-blind clinical trial. (Cell Journal (2018) 20:3 (449) DOI: 10.22074/cellj.2018.5197)

This article published in Cell J (Yakhteh), Vol 20, No 2, Jul-Sep 2018, on pages 267-277, four affiliations (1, 4, 5, and 10) were changed based on authors request. © 2018 Royan Institute (ACECR). All rights reserved

COMPARE CPM-RMI Trial: Intramyocardial transplantation of autologous bone marrow-derived CD133+ Cells and MNCs during CABG in patients with recent MI: A Phase II/III, multicenter, placebo-controlled, randomized, double-blind clinical trial

Objective: The regenerative potential of bone marrow-derived mononuclear cells (MNCs) and CD133+ stem cells in the heart varies in terms of their pro-angiogenic effects. This phase II/III, multicenter and double-blind trial is designed to compare the functional effects of intramyocardial autologous transplantation of both cell types and placebo in patients with recent myocardial infarction (RMI) post-coronary artery bypass graft. Materials and Methods: This was a phase II/III, randomized, double-blind, placebo-controlled trial COMPARE CPM-RMI (CD133, Placebo, MNCs - recent myocardial infarction) conducted in accordance with the Declaration of Helsinki that assessed the safety and efficacy of CD133 and MNCs compared to placebo in patients with RMI. We randomly assigned 77 eligible RMI patients selected from 5 hospitals to receive CD133+ cells, MNC, or a placebo. Patients underwent gated single photon emission computed tomography assessments at 6 and 18 months post-intramyocardial transplantation. We tested the normally distributed efficacy outcomes with a mixed analysis of variance model that used the entire data set of baseline and between-group comparisons as well as within subject (time) and group�time interaction terms. Results: There were no related serious adverse events reported. The intramyocardial transplantation of both cell types increased left ventricular ejection fraction by 9 95% confidence intervals (CI): 2.14% to 15.78%, P=0.01 and improved decreased systolic wall thickening by -3.7 (95% CI: -7.07 to -0.42, P=0.03). The CD133 group showed significantly decreased non-viable segments by 75% (P=0.001) compared to the placebo and 60% (P=0.01) compared to the MNC group. We observed this improvement at both the 6- and 18-month time points. Conclusion: Intramyocardial injections of CD133+ cells or MNCs appeared to be safe and efficient with superiority of CD133+ cells for patients with RMI. Although the sample size precluded a definitive statement about clinical outcomes, these results have provided the basis for larger studies to confirm definitive evidence about the efficacy of these cell types (Registration Number: NCT01167751). © 2018 Royan Institute (ACECR). All Rights Reserved

Toward superlensing with metal-dielectric composites and multilayers

We report on the fabrication of two types of adjustable, near-field superlens designs: metal-dielectric composites and metal-dielectric multilayer films. We fabricated a variety of films with different materials, thicknesses and compositions. These samples were characterized physically and optically to determine their film composition, quality, and optical responses. Our results on metal-dielectric composites indicate that although the real part of the effective permittivity generally follows effective medium theory predictions, the imaginary part does not and substantially higher losses are observed. Going forward, it appears that multilayer metal-dielectric designs are more suitable for sub-diffraction imaging applications because they could provide both tunability and low loss

WHO Expert Committee on Biological Standardization Sixty-seventh report

Afdeling Klinische Chemie en Laboratoriumgeneeskunde (AKCL

Disruption prediction with artificial intelligence techniques in tokamak plasmas

In nuclear fusion reactors, plasmas are heated to very high temperatures of more than 100 million kelvin and, in so-called tokamaks, they are confined by magnetic fields in the shape of a torus. Light nuclei, such as deuterium and tritium, undergo a fusion reaction that releases energy, making fusion a promising option for a sustainable and clean energy source. Tokamak plasmas, however, are prone to disruptions as a result of a sudden collapse of the system terminating the fusion reactions. As disruptions lead to an abrupt loss of confinement, they can cause irreversible damage to present-day fusion devices and are expected to have a more devastating effect in future devices. Disruptions expected in the next-generation tokamak, ITER, for example, could cause electromagnetic forces larger than the weight of an Airbus A380. Furthermore, the thermal loads in such an event could exceed the melting threshold of the most resistant state-of-the-art materials by more than an order of magnitude. To prevent disruptions or at least mitigate their detrimental effects, empirical models obtained with artificial intelligence methods, of which an overview is given here, are commonly employed to predict their occurrence—and ideally give enough time to introduce counteracting measures