On the graphical extraction of multipole mixing ratios of nuclear transitions

We propose a novel graphical method for determining the mixing ratios {\delta} and their associated uncertainties for mixed nuclear transitions. It incorporates the uncertainties both on both the measured and the theoretical conversion coefficients. The accuracy of the method has been studied by deriving the corresponding probability density function. The domains of applicability of the method are carefully defined

Impact of depth of response on survival in patients treated with cobimetinib ± vemurafenib: pooled analysis of BRIM-2, BRIM-3, BRIM-7 and coBRIM.

BackgroundThis pooled analysis investigated the prognostic value of depth of response in two cohorts of patients with BRAFV600-mutated metastatic melanoma treated with vemurafenib or cobimetinib plus vemurafenib.MethodsThe data were pooled from BRIM-2, BRIM-3, BRIM-7 and coBRIM. Association of depth of response with survival was estimated by Cox proportional hazards regression, adjusted for clinically relevant covariates. Depth of response was analysed in previously identified prognostic subgroups based on disease characteristics and gene signatures.ResultsGreater tumour reduction and longer time to maximal response were significantly associated with longer progression-free survival (PFS) and overall survival (OS) when evaluated as continuous variables. Patients with the deepest responses had long-lasting survival outcomes (median PFS: 14 months; OS: 32 months with vemurafenib; not estimable with cobimetinib plus vemurafenib). Cobimetinib plus vemurafenib improved depth of response versus vemurafenib monotherapy regardless of other prognostic factors, including gene signatures.ConclusionsGreater depth of response was associated with improved survival, supporting its utility as a measure of treatment efficacy in melanoma and further evaluation of its incorporation into existing prognostic models. Cobimetinib plus vemurafenib improved outcomes across quartiles of response regardless of prognostic factors or gene signatures and provided durable survival benefits in patients with deep responses

Readout of GEM Detectors Using the Medipix2 CMOS Pixel Chip

We have operated a Medipix2 CMOS readout chip, with amplifying, shaping and charge discriminating front-end electronics integrated on the pixel-level, as a highly segmented direct charge collecting anode in a three-stage gas electron multiplier (Triple-GEM) to detect the ionization from $^{55}$Fe X-rays and electrons from $^{106}$Ru. The device allows to perform moderate energy spectroscopy measurements (20 % FWHM at 5.9 keV $X$-rays) using only digital readout and two discriminator thresholds. Being a truly 2D-detector, it allows to observe individual clusters of minimum ionizing charged particles in $Ar/CO_2$ (70:30) and $He/CO_2$ (70:30) mixtures and to achieve excellent spatial resolution for position reconstruction of primary clusters down to $\sim 50 \mu m$, based on the binary centroid determination method.Comment: 18 pages, 14 pictures. submitted to Nuclear Instruments and Methods in Physics Research

Local electronic structure of the peptide bond probed by resonant inelastic soft X-ray scattering.

The local valence orbital structure of solid glycine, diglycine, and triglycine is studied using soft X-ray emission spectroscopy (XES), resonant inelastic soft X-ray scattering (RIXS) maps, and spectra calculations based on density-functional theory. Using a building block approach, the contributions of the different functional groups of the peptides are separated. Cuts through the RIXS maps furthermore allow monitoring selective excitations of the amino and peptide functional units, leading to a modification of the currently established assignment of spectral contributions. The results thus paint a new-and-improved picture of the peptide bond, enhance the understanding of larger molecules with peptide bonds, and simplify the investigation of such molecules in aqueous environment

A hysteresis model with dipole interaction: one more devil-staircase

Magnetic properties of 2D systems of magnetic nanoobjects (2D regular lattices of the magnetic nanoparticles or magnetic nanostripes) are considered. The analytical calculation of the hysteresis curve of the system with interaction between nanoobjects is provided. It is shown that during the magnetization reversal system passes through a number of metastable states. The kinetic problem of the magnetization reversal was solved for three models. The following results have been obtained. 1) For 1D system (T=0) with the long-range interaction with the energy proportional to $r^{-p}$, the staircase-like shape of the magnetization curve has self-similar character. The nature of the steps is determined by interplay of the interparticle interaction and coercivity of the single nanoparticle. 2) The influence of the thermal fluctuations on the kinetic process was examined in the framework of the nearest-neighbor interaction model. The thermal fluctuations lead to the additional splitting of the steps on the magnetization curve. 3) The magnetization curve for system with interaction and coercivity dispersion was calculated in mean field approximation. The simple method to experimentally distinguish the influence of interaction and coercivity dispersion on the magnetization curve is suggested.Comment: 22 pages, 8 figure

Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data

Summary Selecting the most promising treatment strategy for breast cancer crucially depends on determining the correct subtype. In recent years, gene expression profiling has been investigated as an alternative to histochemical methods. Since databases like TCGA provide easy and unrestricted access to gene expression data for hundreds of patients, the challenge is to extract a minimal optimal set of genes with good prognostic properties from a large bulk of genes making a moderate contribution to classification. Several studies have successfully applied machine learning algorithms to solve this so-called gene selection problem. However, more diverse data from other OMICS technologies are available, including methylation. We hypothesize that combining methylation and gene expression data could already lead to a largely improved classification model, since the resulting model will reflect differences not only on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10-20% and classification error of 1-50%, depending on breast cancer subtype and model. The gene expression model was clearly superior to the methylation model, which was also reflected in the combined model, which mainly selected features from gene expression data. However, the methylation model was able to identify unique features not considered as relevant by the gene expression model, which might provide deeper insights into breast cancer subtype differentiation on an epigenetic level.</jats:p

The helicase HAGE prevents interferon-a-induced PML expression in ABCB5+ malignant melanoma-initiating cells by promoting the expression of SOCS1

The tumour suppressor PML (promyelocytic leukaemia protein) regulates several cellular pathways involving cell growth, apoptosis, differentiation and senescence. PML also has an important role in the regulation of stem cell proliferation and differentiation. Here, we show the involvement of the helicase HAGE in the transcriptional repression of PML expression in ABCB5 + malignant melanoma-initiating cells (ABCB5 + MMICs), a population of cancer stem cells which are responsible for melanoma growth, progression and resistance to drug-based therapy. HAGE prevents PML gene expression by inhibiting the activation of the JAK-STAT (janus kinase-signal transducers and activators of transcription) pathway in a mechanism which implicates the suppressor of cytokine signalling 1 (SOCS1). Knockdown of HAGE led to a significant decrease in SOCS1 protein expression, activation of the JAK-STAT signalling cascade and a consequent increase of PML expression. To confirm that the reduction in SOCS1 expression was dependent on the HAGE helicase activity, we showed that SOCS1, effectively silenced by small interfering RNA, could be rescued by re-introduction of HAGE into cells lacking HAGE. Furthermore, we provide a mechanism by which HAGE promotes SOCS1 mRNA unwinding and protein expression in vitro