The discovery, monitoring and environment of SGR J1935+2154

We report on the discovery of a new member of the magnetar class, SGR J1935+2154, and on its timing and spectral properties measured by an extensive observational campaign carried out between 2014 July and 2015 March with Chandra and XMM–Newton (11 pointings). We discovered the spin period of SGR J1935+2154 through the detection of coherent pulsations at a period of about 3.24 s. The magnetar is slowing down at a rate of P˙=1.43(1)×10−11 s s−1 and with a decreasing trend due to a negative P¨ of −3.5(7) × 10−19 s s−2. This implies a surface dipolar magnetic field strength of ∼2.2 × 1014 G, a characteristic age of about 3.6 kyr and a spin-down luminosity Lsd ∼1.7 × 1034 erg s−1. The source spectrum is well modelled by a blackbody with temperature of about 500 eV plus a power-law component with photon index of about 2. The source showed a moderate long-term variability, with a flux decay of about 25 per cent during the first four months since its discovery, and a re-brightening of the same amount during the second four months. The X-ray data were also used to study the source environment. In particular, we discovered a diffuse emission extending on spatial scales from about 1 arcsec up to at least 1 arcmin around SGR J1935+2154 both in Chandra and XMM–Newton data. This component is constant in flux (at least within uncertainties) and its spectrum is well modelled by a power-law spectrum steeper than that of the pulsar. Though a scattering halo origin seems to be more probable we cannot exclude that part, or all, of the diffuse emission is due to a pulsar wind nebula.NR is supported by an NWO Vidi Grant, and by grants AYA2012-39303 and SGR2014-1073. This work is partially supported by the European COST ActionMP1304 (NewCOMPSTAR)

A strongly magnetized pulsar within the grasp of the milky way’s supermassive black hole

The center of our Galaxy hosts a supermassive black hole, Sagittarius (Sgr) A∗. Young, massive stars within 0.5 pc of Sgr A∗ are evidence of an episode of intense star formation near the black hole a few million years ago, which might have left behind a young neutron star traveling deep into Sgr A∗’s gravitational potential. On 2013 April 25, a short X-ray burst was observed from the direction of the Galactic center. With a series of observations with the Chandra and the Swift satellites, we pinpoint the associated magnetar at an angular distance of 2.4±0.3 arcsec from Sgr A∗, and refine the source spin period and its derivative (P = 3.7635537(2) s and ˙ P = 6.61(4) × 10−12 s s−1), confirmed by quasi simultaneous radio observations performed with the Green Bank Telescope and Parkes Radio Telescope, which also constrain a dispersion measure of DM = 1750 ± 50 pc cm−3, the highest ever observed for a radio pulsar. We have found that this X-ray source is a young magnetar at ≈0.07–2 pc from Sgr A∗. Simulations of its possible motion around Sgr A∗ show that it is likely (∼90% probability) in a bound orbit around the black hole. The radiation front produced by the past activity from the magnetar passing through the molecular clouds surrounding the Galactic center region might be responsible for a large fraction of the light echoes observed in the Fe fluorescence features.We acknowledge support by grants AYA 2012-39303, SGR2009-811, iLINK 2011-0303, AYA 2010-21097-C03-02, Prometeo 2009/103, AYA2010-17631, P08-TIC-4075, INAF 2010 PRIN grant, Chandra Awards GO2-13076X, G03-14060X, GO3-14099X and G03-14121X, and an EU Marie Curie IEF (FP7-PEOPLE-2012-IEF-331095)

Simple model systems: a challenge for Alzheimer's disease

The success of biomedical researches has led to improvement in human health and increased life expectancy. An unexpected consequence has been an increase of age-related diseases and, in particular, neurodegenerative diseases. These disorders are generally late onset and exhibit complex pathologies including memory loss, cognitive defects, movement disorders and death. Here, it is described as the use of simple animal models such as worms, fishes, flies, Ascidians and sea urchins, have facilitated the understanding of several biochemical mechanisms underlying Alzheimer's disease (AD), one of the most diffuse neurodegenerative pathologies. The discovery of specific genes and proteins associated with AD, and the development of new technologies for the production of transgenic animals, has helped researchers to overcome the lack of natural models. Moreover, simple model systems of AD have been utilized to obtain key information for evaluating potential therapeutic interventions and for testing efficacy of putative neuroprotective compounds

External relations of an Industry 4.0 cluster: the case study of the Hamburg aviation cluster

Based on the case study of the Hamburg aviation cluster (HAv), this paper touches upon the nature of cluster processes in digital transformation (Industry 4.0). The discussion is carried out with reference to the concept of hubbing, while highlighting the difference between classic internationalization. The aim of the paper is to unearth the nature of the cluster’s external expansion in the digitally reshaped era by investigating the case of an advanced aviation cluster officially branded as an Industry 4.0 cluster.</p

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174 radiomic features. Materials and Methods Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kuhl and Truhn in this issue

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

International audienceBackground Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174 radiomic features. Materials and Methods Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kuhl and Truhn in this issue

Genome and transcriptome analysis of the Mesoamerican common bean and the role of gene duplications in establishing tissue and temporal specialization of genes

Background: Legumes are the third largest family of angiosperms and the second most important crop class. Legume genomes have been shaped by extensive large-scale gene duplications, including an approximately 58 million year old whole genome duplication shared by most crop legumes. Results: We report the genome and the transcription atlas of coding and non-coding genes of a Mesoamerican genotype of common bean (Phaseolus vulgaris L., BAT93). Using a comprehensive phylogenomics analysis, we assessed the past and recent evolution of common bean, and traced the diversification of patterns of gene expression following duplication. We find that successive rounds of gene duplications in legumes have shaped tissue and developmental expression, leading to increased levels of specialization in larger gene families. We also find that many long non-coding RNAs are preferentially expressed in germ-line-related tissues (pods and seeds), suggesting that they play a significant role in fruit development. Our results also suggest that most bean-specific gene family expansions, including resistance gene clusters, predate the split of the Mesoamerican and Andean gene pools. Conclusions: The genome and transcriptome data herein generated for a Mesoamerican genotype represent a counterpart to the genomic resources already available for the Andean gene pool. Altogether, this information will allow the genetic dissection of the characters involved in the domestication and adaptation of the crop, and their further implementation in breeding strategies for this important crop.This work was supported by Ibero-American Programme for Science, Technology and Development - CYTED (PhasIbeAm project); Spanish Government - Ministry of Economy and Competitiveness (EUI2009-04052, BIO2011-26205); Brazilian Government — National Council for Scientific and Technological Development - CNPq/Prosul (490725/2010-4) and Brazilian Agricultural Research Corporation - Embrapa (MP2-0212000050000); Ministerio de Ciencia, Tecnología e Innovación Productiva de la República Argentina; the European Molecular Biology Laboratory; Consejo Nacional de Ciencia y Tecnología - Conacyt, Mexico (J010-214-2009) for financial support to undertake parts of research presented in this study. We acknowledge support of the Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia Severo Ochoa 2013-2017’, SEV-2012-0208 and Instituto Nacional de Bioinformatica (INB, Project PT13/0001/0021, ISCIII — Subdirección General de Evaluación y Fomento de la Investigación/FEDER “Una Manera de hacer Europa”)