High-dose therapy and autologous stem cell transplantation in first relapse for diffuse large B cell lymphoma in the rituximab era:an analysis based on data from the European Blood and Marrow Transplantation Registry

Autologous stem cell transplantation (ASCT) consolidation remains the treatment of choice for patients with relapsed diffuse large B cell lymphoma. The impact of rituximab combined with chemotherapy in either first- or second-line therapy on the ultimate results of ASCT remains to be determined, however. This study was designed to evaluate the benefit of ASCT in patients achieving a second complete remission after salvage chemotherapy by retrospectively comparing the disease-free survival (DFS) after ASCT for each patient with the duration of the first complete remission (CR1). Between 1990 and 2005, a total of 470 patients who had undergone ASCT and reported to the European Blood and Bone Transplantation Registry with Medical Essential Data Form B information were evaluated. Of these 470 patients, 351 (74%) had not received rituximab before ASCT, and 119 (25%) had received rituximab before ASCT. The median duration of CR1 was 11 months. The median time from diagnosis to ASCT was 24 months. The BEAM protocol was the most frequently used conditioning regimen (67%). After ASCT, the 5-year overall survival was 63% (95% confidence interval, 58%-67%) and 5-year DFS was 48% (95% confidence interval, 43%-53%) for the entire patient population. Statistical analysis showed a significant increase in DFS after ASCT compared with duration of CR1 (median, 51 months versus 11 months; P < .001). This difference was also highly significant for patients with previous exposure to rituximab (median, 10 months versus not reached; P < .001) and for patients who had experienced relapse before 1 year (median, 6 months versus 47 months; P < .001). Our data indicate that ASCT can significantly increase DFS compared with the duration of CR1 in relapsed diffuse large B cell lymphoma and can alter the disease course even in patients with high-risk disease previously treated with rituximab.

Mathematics Learning Support in Ireland in 2015

The provision of mathematics learning support in higher-level institutions on the island of Ireland has developed rapidly in recent times with the number of institutions providing some form of support doubling in the past seven years. The Irish Mathematics Learning Support Network aims to inform all mathematics support practitioners in Ireland on relevant issues. Consequently it was decided that a detailed picture of current provision was necessary. A comprehensive online survey was conducted to amass the necessary data. The ultimate aim of the survey is to benefit all mathematics support practitioners in Ireland, in particular those in third-level institutions who require further support to enhance the mathematical learning experience of their students. The survey reveals that the majority of Irish higher-level institutions provide mathematics learning support to some extent, with 65% doing so through a support centre. Learners of service mathematics are the primary users: first-year science, engineering and business undergraduates, with non-traditional students being a sizeable element. Despite the growing recognition for the need to offer mathematics learning support almost half of the centres are subject to annual review. Further, less than half the support offerings have a dedicated full-time manager, while 60% operate with a staff of five or fewer. The elevation of mathematics support as a viable and worthwhile career in order to attract and retain high quality staff is seen by many respondents as the crucial next phase of development.

Extraordinary mechanical properties of monatomic C3N2 chain

One-dimensional monatomic chains are promising candidates for technical applications in the field of nanoelectronics due to their unique mechanical, electrical and optical properties. In particular, we investigate the mechanical properties including Young's modulus, ultimate strength and ultimate strain, which are necessities for the stability of the materials by the Car-Parrinello molecular dynamics in this work. The comparative studies for the alternating carbon-nitrogen (C₃N₂) chain and carbon chains (carbyne) of different lengths show that the carbon-nitrogen (C-N) chain is obviously stronger and stiffer than carbynes. Thus the C-N chain, which has been found in decomposition products of the nitromethane explosive simulations, could be a superior nano-mechanical material than the carbyne chain. Furthermore, it is found that the bond order of weakest bond in monatomic chains is positively correlated with Young's modulus and ultimate strength of materials.

Label-free based quantitative proteomics analysis of primary neonatal porcine Leydig cells exposed to the persistent contaminant 3-methylsulfonyl-DDE

Evidence that persistent environmental pollutants may target the male reproductive system is increasing. The male reproductive system is regulated by secretion of testosterone by testicular Leydig cells, and perturbation of Leydig cell function may have ultimate consequences. 3-Methylsulfonyl-DDE (3-MeSO₂-DDE) is a potent adrenal toxicants formed from the persistent insecticide DDT. Although studies have revealed the endocrine disruptive effect of 3-MeSO₂-DDE, the underlying mechanisms at cellular level in steroidogenic Leydig cells remains to be established. The current study addresses the effect of 3-MeSO₂-DDE on viability, hormone production and proteome response of primary neonatal porcine Leydig cells. The AlamarBlue™ assay was used to evaluate cell viability. Solid phase radioimmunoassay was used to measure concentration of hormones produced by both unstimulated and Luteinizing hormone (LH)-stimulated Leydig cells following 48h exposure. Protein samples from Leydig cells exposed to a non-cytotoxic concentration of 3-MeSO₂-DDE (10μM) were subjected to nano-LC-MS/MS and analyzed on a Q Exactive mass spectrometer and quantified using label-free quantitative algorithm. Gene Ontology (GO) and Ingenuity Pathway Analysis (IPA) were carried out for functional annotation and identification of protein interaction networks. 3-MeSO₂-DDE regulated Leydig cell steroidogenesis differentially depending on cell culture condition. Whereas its effect on testosterone secretion at basal condition was stimulatory, the effect on LH-stimulated cells was inhibitory. From triplicate experiments, a total of 6804 proteins were identified in which the abundance of 86 proteins in unstimulated Leydig cells and 145 proteins in LH-stimulated Leydig cells was found to be significantly regulated in response to 3-MeSO₂-DDE exposure. These proteins not only are the first reported in relation to 3-MeSO₂-DDE exposure, but also display small number of proteins shared between culture conditions, suggesting the action of 3-MeSO₂-DDE on several targeted pathways, including mitochondrial dysfunction, oxidative phosphorylation, EIF2-signaling, and glutathione-mediated detoxification. Further identification and characterization of these proteins and pathways may build our understanding to the molecular basis of 3-MeSO₂-DDE induced endocrine disruption in Leydig cells.

Influence of service loading and the resulting micro-cracks on chloride resistance of concrete

Chloride-induced corrosion of steel in reinforced concrete structures is one of the main problems affecting their durability, but most previous research projects and case studies have focused on concretes without cracks or not subjected to any structural load. Although it has been recognised that structural cracks do influence the chloride transport and chloride induced corrosion in reinforced concrete structures, there is little published work on the influence of micro-cracks due to service loads on these properties. Therefore the effect of micro-cracks caused by loading on chloride transport into concrete was studied. Four different stress levels (0%, 25%, 50% and 75% of the stress at ultimate load – fu) were applied to 100 mm diameter concrete discs and chloride migration was measured using a bespoke test setup based on the NT BUILD 492 test. The effects of replacing Portland cement CEMI by ground granulated blast-furnace slag (GGBS), pulverised fuel ash (PFA) and silica fume (SF) on chloride transport in concrete under sustained loading were studied. The results have indicated that chloride migration coefficients changed little when the stress level was below 50% of the fu; however, it is desirable to keep concrete stress less than 25% fu if this is practical. The effect of removing the load on the change of chloride migration coefficient was also studied. A recovery of around 50% of the increased chloride migration coefficient was found in the case of concretes subjected to 75% of the fu when the load was removed.

Learning from Outdoor Webcams: Surveillance of Physical Activity Across Environments

Abstract
Publicly available, outdoor webcams continuously view the world and share images. These cameras include traffic cams, campus cams, ski-resort cams, etc. The Archive of Many Outdoor Scenes (AMOS) is a project aiming to geolocate, annotate, archive, and visualize these cameras and images to serve as a resource for a wide variety of scientific applications. The AMOS dataset has archived over 750 million images of outdoor environments from 27,000 webcams since 2006. Our goal is to utilize the AMOS image dataset and crowdsourcing to develop reliable and valid tools to improve physical activity assessment via online, outdoor webcam capture of global physical activity patterns and urban built environment characteristics.
This project’s grand scale-up of capturing physical activity patterns and built environments is a methodological step forward in advancing a real-time, non-labor intensive assessment using webcams, crowdsourcing, and eventually machine learning. The combined use of webcams capturing outdoor scenes every 30 min and crowdsources providing the labor of annotating the scenes allows for accelerated public health surveillance related to physical activity across numerous built environments. The ultimate goal of this public health and computer vision collaboration is to develop machine learning algorithms that will automatically identify and calculate physical activity patterns.