Ultraviolet Signposts of Resonant Dynamics in the Starburst-Ringed Sab Galaxy, M94 (NGC 4736)

M94 (NGC 4736) is investigated using images from the Ultraviolet Imaging Telescope (FUV-band), Hubble Space Telescope (NUV-band), Kitt Peak 0.9-m telescope (H-alpha, R, and I bands), and Palomar 5-m telescope (B-band), along with spectra from the International Ultraviolet Explorer and Lick 1-m telescopes. The wide-field UIT image shows FUV emission from (a) an elongated nucleus, (b) a diffuse inner disk, where H-alpha is observed in absorption, (c) a bright inner ring of H II regions at the perimeter of the inner disk (R = 48 arcsec. = 1.1 kpc), and (d) two 500-pc size knots of hot stars exterior to the ring on diametrically opposite sides of the nucleus (R= 130 arcsec. = 2.9 kpc). The HST/FOC image resolves the NUV emission from the nuclear region into a bright core and a faint 20 arcsec. long ``mini-bar'' at a position angle of 30 deg. Optical and IUE spectroscopy of the nucleus and diffuse inner disk indicates an approximately 10^7 or 10^8 yr-old stellar population from low-level starbirth activity blended with some LINER activity. Analysis of the H-alpha, FUV, NUV, B, R, and I-band emission along with other observed tracers of stars and gas in M94 indicates that most of the star formation is being orchestrated via ring-bar dynamics involving the nuclear mini-bar, inner ring, oval disk, and outer ring. The inner starburst ring and bi-symmetric knots at intermediate radius, in particular, argue for bar-mediated resonances as the primary drivers of evolution in M94 at the present epoch. Similar processes may be governing the evolution of the ``core-dominated'' galaxies that have been observed at high redshift. The gravitationally-lensed ``Pretzel Galaxy'' (0024+1654) at a redshift of approximately 1.5 provides an important precedent in this regard.Comment: revised figure 1 (corrected coordinate labels on declination axis); 19 pages of text + 19 figures (jpg files); accepted for publication in A

Continuing Education Course #3: Current Practices and Future Trends in Neuropathology Assessment for Developmental Neurotoxicity Testing

The continuing education course on Developmental Neurotoxicity Testing (DNT) was designed to communicate current practices for DNT neuropathology, describe promising innovations in quantitative analysis and noninvasive imaging, and facilitate a discussion among experienced neuropathologists and regulatory scientists regarding suitable DNT practices. Conventional DNT neuropathology endpoints are qualitative histopathology and morphometric endpoints of particularly vulnerable sites (e.g., cerebral, cerebellar, or hippocampal thickness). Novel imaging and stereology measurements hold promise for automated analysis of factors that cannot be effectively examined in routinely processed specimens (e.g., cell numbers, fiber tract integrity). The panel recommended that dedicated DNT neuropathology data sets be acquired on a minimum of 8 sections (for qualitative assessment) or 3 sections (for quantitative linear and stereological analyses) using a small battery of stains to examine neurons and myelin. Where guidelines permit discretion, immersion fixation is acceptable for younger animals (postnatal day 22 or earlier), and peripheral nerves may be embedded in paraffin. Frequent concerns regarding DNT data sets include false-negative outcomes due to processing difficulties (e.g., lack of concordance among sections from different animals) and insensitive analytical endpoints (e.g., qualitative evaluation) as well as false-positive results arising from overinterpretation or misreading by inexperienced pathologists

Developmental Neurotoxicity Study of Dietary Bisphenol A in Sprague-Dawley Rats

This study was conducted to determine the potential of bisphenol A (BPA) to induce functional and/or morphological effects to the nervous system of F1 offspring from dietary exposure during gestation and lactation according to the Organization for Economic Cooperation and Development and U.S. Environmental Protection Agency guidelines for the study of developmental neurotoxicity. BPA was offered to female Sprague-Dawley Crl:CD (SD) rats (24 per dose group) and their litters at dietary concentrations of 0 (control), 0.15, 1.5, 75, 750, and 2250 ppm daily from gestation day 0 through lactation day 21. F1 offspring were evaluated using the following tests: detailed clinical observations (postnatal days [PNDs] 4, 11, 21, 35, 45, and 60), auditory startle (PNDs 20 and 60), motor activity (PNDs 13, 17, 21, and 61), learning and memory using the Biel water maze (PNDs 22 and 62), and brain and nervous system neuropathology and brain morphometry (PNDs 21 and 72). For F1 offspring, there were no treatment-related neurobehavioral effects, nor was there evidence of neuropathology or effects on brain morphometry. Based on maternal and offspring body weight reductions, the no-observed-adverse-effect level (NOAEL) for systemic toxicity was 75 ppm (5.85 and 13.1 mg/kg/day during gestation and lactation, respectively), with no treatment-related effects at lower doses or nonmonotonic dose responses observed for any parameter. There was no evidence that BPA is a developmental neurotoxicant in rats, and the NOAEL for developmental neurotoxicity was 2250 ppm, the highest dose tested (164 and 410 mg/kg/day during gestation and lactation, respectively)

The CCP4 suite: integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.Jon Agirre is a Royal Society University Research Fellow (UF160039 and URF\R\221006). Mihaela Atanasova is funded by the UK Engineering and Physical Sciences Research Council (EPSRC; EP/R513386/1). Haroldas Bagdonas is funded by The Royal Society (RGF/R1/181006). Jose´ Javier Burgos-Ma´rmol and Daniel J. Rigden are supported by the BBSRC (BB/S007105/1). Robbie P. Joosten is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 871037 (iNEXTDiscovery) and by CCP4. This work was supported by the Medical Research Council as part of United Kingdom Research and Innovation, also known as UK Research and Innovation: MRC file reference No. MC_UP_A025_1012 to Garib N. Murshudov, which also funded Keitaro Yamashita, Paul Emsley and Fei Long. Robert A. Nicholls is funded by the BBSRC (BB/S007083/1). Soon Wen Hoh is funded by the BBSRC (BB/T012935/1). Kevin D. Cowtan and Paul S. Bond are funded in part by the BBSRC (BB/S005099/1). John Berrisford and Sameer Velankar thank the European Molecular Biology Laboratory–European Bioinformatics Institute, who supported this work. Andrea Thorn was supported in the development of AUSPEX by the German Federal Ministry of Education and Research (05K19WWA and 05K22GU5) and by Deutsche Forschungsgemeinschaft (TH2135/2-1). Petr Kolenko and Martin Maly´ are funded by the MEYS CR (CZ.02.1.01/0.0/0.0/16_019/0000778). Martin Maly´ is funded by the Czech Academy of Sciences (86652036) and CCP4/STFC (521862101). Anastassis Perrakis acknowledges funding from iNEXT (grant No. 653706), iNEXT-Discovery (grant No. 871037), West-Life (grant No. 675858) and EOSC-Life (grant No. 824087) funded by the Horizon 2020 program of the European Commission. Robbie P. Joosten has been the recipient of a Veni grant (722.011.011) and a Vidi grant (723.013.003) from the Netherlands Organization for Scientific Research (NWO). Maarten L. Hekkelman, Robbie P. Joosten and Anastassis Perrakis thank the Research High Performance Computing facility of the Netherlands Cancer Institute for providing and maintaining computation resources and acknowledge the institutional grant from the Dutch Cancer Society and the Dutch Ministry of Health, Welfare and Sport. Tarik R. Drevon is funded by the BBSRC (BB/S007040/1). Randy J. Read is supported by a Principal Research Fellowship from the Wellcome Trust (grant 209407/Z/17/Z). Atlanta G. Cook is supported by a Wellcome Trust SRF (200898) and a Wellcome Centre for Cell Biology core grant (203149). Isabel Uso´n acknowledges support from STFC-UK/CCP4: ‘Agreement for the integration of methods into the CCP4 software distribution, ARCIMBOLDO_LOW’ and Spanish MICINN/AEI/FEDER/UE (PID2021-128751NB-I00). Pavol Skubak and Navraj Pannu were funded by the NWO Applied Sciences and Engineering Domain and CCP4 (grant Nos. 13337 and 16219). Bernhard Lohkamp was supported by the Ro¨ntgen A˚ ngstro¨m Cluster (grant 349-2013-597). Nicholas Pearce is currently funded by the SciLifeLab and Wallenberg Data Driven Life Science Program (grant KAW 2020.0239) and has previously been funded by a Veni Fellowship (VI.Veni.192.143) from the Dutch Research Council (NWO), a Long-term EMBO fellowship (ALTF 609-2017) and EPSRC grant EP/G037280/1. David M. Lawson received funding from BBSRC Institute Strategic Programme Grants (BB/P012523/1 and BB/P012574/1). Lucrezia Catapano is the recipient of an STFC/CCP4-funded PhD studentship (Agreement No: 7920 S2 2020 007).Peer reviewe

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

Integrated genomic characterization of oesophageal carcinoma

Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies

The CCP4 suite : integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world