Bar Evolution Over the Last Eight Billion Years: A Constant Fraction of Strong Bars in GEMS

One third of present-day spirals host optically visible strong bars that drive their dynamical evolution. However, the fundamental question of how bars evolve over cosmological times has yet to be addressed, and even the frequency of bars at intermediate redshifts remains controversial. We investigate the frequency of bars out to z~1.0 drawing on a sample of 1590 galaxies from the GEMS survey, which provides morphologies from HST ACS two-color images, and highly accurate redshifts from the COMBO-17 survey. We identify spiral galaxies using the Sersic index, concentration parameter, and rest-frame color. We characterize bars and disks by fitting ellipses to F606W and F850LP images, taking advantage of the two bands to minimize bandpass shifting. We exclude highly inclined (i>60 deg) galaxies to ensure reliable morphological classifications, and apply completeness cuts of M_v <= -19.3 and -20.6. More than 40% of the bars that we detect have semi major axes a<0.5" and would be easily missed in earlier surveys without the small PSF of ACS. The bars that we can reliably detect are fairly strong (with ellipticities e>=0.4) and have a in the range ~1.2-13 kpc. We find that the optical fraction of such strong bars remains at ~(30% +- 6%) from the present-day out to look-back times of 2-6 Gyr (z~0.2-0.7) and 6-8 Gyr (z~0.7-1.0); it certainly shows no sign of a drastic decline at z>0.7. Our findings of a large and similar bar fraction at these three epochs favor scenarios in which cold gravitationally unstable disks are already in place by z~1, and where on average bars have a long lifetime (well above 2 Gyr). The distributions of structural bar properties in the two slices are, however, not statistically identical and therefore allow for the possibility that the bar strengths and sizes may evolve over time.Comment: Accepted by ApJ Letters, to appear in Nov 2004 issue. Minor revisions,updated reference

An Indication of Anisotropy in Arrival Directions of Ultra-high-energy Cosmic Rays through Comparison to the Flux Pattern of Extragalactic Gamma-Ray Sources

A new analysis of the data set from the Pierre Auger Observatory provides evidence for anisotropy in the arrivaldirections of ultra-high-energy cosmic rays on an intermediate angular scale, which is indicative of excess arrivalsfrom strong, nearby sources. The data consist of 5514 events above 20 EeV with zenith angles up to 80°recordedbefore 2017 April 30. Sky models have been created for two distinct populations of extragalactic gamma-rayemitters: active galactic nuclei from the second catalog of hard Fermi-LAT sources (2FHL) and starburst galaxiesfrom a sample that was examined with Fermi-LAT. Flux-limited samples, which include all types of galaxies fromthe Swift-BAT and 2MASS surveys, have been investigated for comparison. The sky model of cosmic-ray densityconstructed using each catalog has two free parameters, the fraction of events correlating with astrophysicalobjects, and an angular scale characterizing the clustering of cosmic rays around extragalactic sources. Amaximum-likelihood ratio test is used to evaluate the best values of these parameters and to quantify the strength ofeach model by contrast with isotropy. It is found that the starburst model fits the data better than the hypothesis ofisotropy with a statistical significance of 4.0σ, the highest value of the test statistic being for energies above39 EeV. The three alternative models are favored against isotropy with 2.7σ?3.2σ significance. The origin of theindicated deviation from isotropy is examined and prospects for more sensitive future studies are discussed.Fil: Aab, A.. Radboud University Nijmegen; Países BajosFil: Allekotte, Ingomar. Centro Atómico Bariloche and Instituto Balseiro; ArgentinaFil: Almela, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Andrada, B.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Bertou, Xavier Pierre Louis. Centro Atómico Bariloche and Instituto Balseiro; ArgentinaFil: Botti, Ana Martina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Cancio, A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Contreras, F.. Observatorio Pierre Auger; ArgentinaFil: Etchegoyen, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Figueira, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Fuster, Alan Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Golup, Geraldina Tamara. Centro Atómico Bariloche and Instituto Balseiro; ArgentinaFil: Gómez Berisso, M.. Centro Atómico Bariloche and Instituto Balseiro; ArgentinaFil: Gómez Vitale, P. F.. Pierre Auger Observatory; ArgentinaFil: González, N.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Hampel, Matias Rolf. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Hansen, Patricia Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; ArgentinaFil: Harari, Diego Dario. Centro Atómico Bariloche and Instituto Balseiro; ArgentinaFil: Holt, E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Hulsman, Johannes. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Josebachuili Ogando, Mariela Gisele. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Kleinfeller, J.. Pierre Auger Observatory; ArgentinaFil: Lucero, A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Mollerach, Maria Silvia. Centro Atómico Bariloche and Instituto Balseiro; ArgentinaFil: Melo, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Müller, Ana Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Naranjo, I.. Centro Atómico Bariloche and Instituto Balseiro; ArgentinaFil: Roulet, Esteban. Centro Atómico Bariloche and Instituto Balseiro; ArgentinaFil: Rodriguez Rojo, J.. Pierre Auger Observatory; ArgentinaFil: Sánchez, F.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Santos, E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Sarmiento Cano, Christian Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Schmidt, D.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Sciutto, Sergio Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; ArgentinaFil: Silli, Gaia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Suarez, F.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Taborda Pulgarin, Oscar Alejandro. Centro Atómico Bariloche and Instituto Balseiro; ArgentinaFil: Wainberg, Oscar Isaac. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Wundheiler, Brian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: Yushkov, Alexey. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Tecnología en Detección y Astropartículas. Comisión Nacional de Energía Atómica. Instituto de Tecnología en Detección y Astropartículas. Universidad Nacional de San Martín. Instituto de Tecnología en Detección y Astropartículas; ArgentinaFil: The Pierre Auger Collaboration. Pierre Auger Observatory; Argentin

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study

Background: Identification of convulsive epilepsy in sub-Saharan Africa relies on access to resources that are often unavailable. Infrastructure and resource requirements can further complicate case verification. Using machine-learning techniques, we have developed and tested a region-specific questionnaire panel and predictive model to identify people who have had a convulsive seizure. These findings have been implemented into a free app for health-care workers in Kenya, Uganda, Ghana, Tanzania, and South Africa. Methods: In this retrospective case-control study, we used data from the Studies of the Epidemiology of Epilepsy in Demographic Sites in Kenya, Uganda, Ghana, Tanzania, and South Africa. We randomly split these individuals using a 7:3 ratio into a training dataset and a validation dataset. We used information gain and correlation-based feature selection to identify eight binary features to predict convulsive seizures. We then assessed several machine-learning algorithms to create a multivariate prediction model. We validated the best-performing model with the internal dataset and a prospectively collected external-validation dataset. We additionally evaluated a leave-one-site-out model (LOSO), in which the model was trained on data from all sites except one that, in turn, formed the validation dataset. We used these features to develop a questionnaire-based predictive panel that we implemented into a multilingual app (the Epilepsy Diagnostic Companion) for health-care workers in each geographical region. Findings: We analysed epilepsy-specific data from 4097 people, of whom 1985 (48·5%) had convulsive epilepsy, and 2112 were controls. From 170 clinical variables, we initially identified 20 candidate predictor features. Eight features were removed, six because of negligible information gain and two following review by a panel of qualified neurologists. Correlation-based feature selection identified eight variables that demonstrated predictive value; all were associated with an increased risk of an epileptic convulsion except one. The logistic regression, support vector, and naive Bayes models performed similarly, outperforming the decision-tree model. We chose the logistic regression model for its interpretability and implementability. The area under the receiver operator curve (AUC) was 0·92 (95% CI 0·91–0·94, sensitivity 85·0%, specificity 93·7%) in the internal-validation dataset and 0·95 (0·92–0·98, sensitivity 97·5%, specificity 82·4%) in the external-validation dataset. Similar results were observed for the LOSO model (AUC 0·94, 0·93–0·96, sensitivity 88·2%, specificity 95·3%). Interpretation: On the basis of these findings, we developed the Epilepsy Diagnostic Companion as a predictive model and app offering a validated culture-specific and region-specific solution to confirm the diagnosis of a convulsive epileptic seizure in people with suspected epilepsy. The questionnaire panel is simple and accessible for health-care workers without specialist knowledge to administer. This tool can be iteratively updated and could lead to earlier, more accurate diagnosis of seizures and improve care for people with epilepsy

Incipient Social Groups: An Analysis via In-Vivo Behavioral Tracking

Social psychology is fundamentally the study of individuals in groups, yet there remain basic unanswered questions about group formation, structure, and change. We argue that the problem is methodological. Until recently, there was no way to track who was interacting with whom with anything approximating valid resolution and scale. In the current study we describe a new method that applies recent advances in image-based tracking to study incipient group formation and evolution with experimental precision and control. In this method, which we term "in vivo behavioral tracking," we track individuals' movements with a high definition video camera mounted atop a large field laboratory. We report results of an initial study that quantifies the composition, structure, and size of the incipient groups. We also apply in-vivo spatial tracking to study participants' tendency to cooperate as a function of their embeddedness in those crowds. We find that participants form groups of seven on average, are more likely to approach others of similar attractiveness and (to a lesser extent) gender, and that participants' gender and attractiveness are both associated with their proximity to the spatial center of groups (such that women and attractive individuals are more likely than men and unattractive individuals to end up in the center of their groups). Furthermore, participants' proximity to others early in the study predicted the effort they exerted in a subsequent cooperative task, suggesting that submergence in a crowd may predict social loafing. We conclude that in vivo behavioral tracking is a uniquely powerful new tool for answering longstanding, fundamental questions about group dynamics

A large population of diverse neurons in the Drosophila central nervous system expresses short neuropeptide F, suggesting multiple distributed peptide functions

<p>Abstract</p> <p>Background</p> <p>Insect neuropeptides are distributed in stereotypic sets of neurons that commonly constitute a small fraction of the total number of neurons. However, some neuropeptide genes are expressed in larger numbers of neurons of diverse types suggesting that they are involved in a greater diversity of functions. One of these widely expressed genes, <it>snpf</it>, encodes the precursor of short neuropeptide F (sNPF). To unravel possible functional diversity we have mapped the distribution of transcript of the <it>snpf </it>gene and its peptide products in the central nervous system (CNS) of <it>Drosophila </it>in relation to other neuronal markers.</p> <p>Results</p> <p>There are several hundreds of neurons in the larval CNS and several thousands in the adult <it>Drosophila </it>brain expressing <it>snpf </it>transcript and sNPF peptide. Most of these neurons are intrinsic interneurons of the mushroom bodies. Additionally, sNPF is expressed in numerous small interneurons of the CNS, olfactory receptor neurons (ORNs) of the antennae, and in a small set of possibly neurosecretory cells innervating the corpora cardiaca and aorta. A sNPF-Gal4 line confirms most of the expression pattern. None of the sNPF immunoreactive neurons co-express a marker for the transcription factor DIMMED, suggesting that the majority are not neurosecretory cells or large interneurons involved in episodic bulk transmission. Instead a portion of the sNPF producing neurons co-express markers for classical neurotransmitters such as acetylcholine, GABA and glutamate, suggesting that sNPF is a co-transmitter or local neuromodulator in ORNs and many interneurons. Interestingly, sNPF is coexpressed both with presumed excitatory and inhibitory neurotransmitters. A few sNPF expressing neurons in the brain colocalize the peptide corazonin and a pair of dorsal neurons in the first abdominal neuromere coexpresses sNPF and insulin-like peptide 7 (ILP7).</p> <p>Conclusion</p> <p>It is likely that sNPF has multiple functions as neurohormone as well as local neuromodulator/co-transmitter in various CNS circuits, including olfactory circuits both at the level of the first synapse and at the mushroom body output level. Some of the sNPF immunoreactive axons terminate in close proximity to neurosecretory cells producing ILPs and adipokinetic hormone, indicating that sNPF also might regulate hormone production or release.</p

Proceedings of the International Cancer Imaging Society (ICIS) 16th Annual Teaching Course

Table of contents O1 Tumour heterogeneity: what does it mean? Dow-Mu Koh O2 Skeletal sequelae in adult survivors of childhood cancer Sue Creviston Kaste O3 Locoregional effects of breast cancer treatment Sarah J Vinnicombe O4 Imaging of cancer therapy-induced CNS toxicity Giovanni Morana, Andrea Rossi O5 Screening for lung cancer Christian J. Herold O6Risk stratification of lung nodules Theresa C. McLoud O7 PET imaging of pulmonary nodules Kirk A Frey O8 Transarterial tumour therapy Bernhard Gebauer O9 Interventional radiology in paediatric oncology Derek Roebuck O10 Image guided prostate interventions Jurgen J. Fütterer O11 Imaging cancer predisposition syndromes Alexander J. Towbin O12Chest and chest wall masses Thierry AG Huisman O13 Abdominal masses: good or bad? Anne MJB Smets O14 Hepatobiliary MR contrast: enhanced liver MRI for HCC diagnosis and management Giovanni Morana O15 Role of US elastography and multimodality fusion for managing patients with chronic liver disease and HCC Jeong Min Lee O16 Opportunities and challenges in imaging metastatic disease Hersh Chandarana O17 Diagnosis, treatment monitoring, and follow-up of lymphoma Marius E. Mayerhoefer, Markus Raderer, Alexander Haug O18 Managing high-risk and advanced prostate cancer Matthias Eiber O19 Immunotherapy: imaging challenges Bernhard Gebauer O20 RECIST and RECIST 1.1 Andrea Rockall O21 Challenges of RECIST in oncology imaging basics for the trainee and novice Aslam Sohaib O22 Lymphoma: PET for interim and end of treatment response assessment: a users’ guide to the Deauville Score Victoria S Warbey O23 Available resources Hebert Alberto Vargas O24 ICIS e-portal and the online learning community Dow-Mu Koh O25 Benign lesions that mimic pancreatic cancer Jay P Heiken O26 Staging and reporting pancreatic malignancies Isaac R Francis, Mahmoud, M Al-Hawary, Ravi K Kaza O27 Intraductal papillary mucinous neoplasm Giovanni Morana O28 Cystic pancreatic tumours Mirko D’Onofrio O29 Diffusion-weighted imaging of head and neck tumours Harriet C. Thoeny O30 Radiation injury in the head and neck Ann D King O31 PET/MR of paediatric brain tumours Giovanni Morana, Arnoldo Piccardo, Maria Luisa Garrè, Andrea Rossi O32 Structured reporting and beyond Hebert Alberto Vargas O33 Massachusetts General Hospital experience with structured reporting Theresa C. McLoud O34 The oncologist’s perspective: what the oncologist needs to know Nick Reed O35 Towards the cure of all children with cancer: global initiatives in pediatric oncology Carlos Rodriguez-Galindo O36 Multiparametric imaging of renal cancers Hersh Chandarana O37 Linking imaging features of renal disease and their impact on management strategies Hebert Alberto Vargas O38 Adrenals, retroperitoneum and peritoneum Isaac R Francis, Ashish P Wasnik O39 Lung and pleura Stefan Diederich O40 Advances in MRI Jurgen J. Fütterer O41 Advances in molecular imaging Wim J.G. Oyen O42 Incorporating advanced imaging, impact on treatment selection and patient outcome Cheng Lee Chaw, Nicholas van As S1 Combining ADC-histogram features improves performance of MR diffusion-weighted imaging for Lymph node characterisation in cervical cancer Igor Vieira, Frederik De Keyzer, Elleke Dresen, Sileny Han, Ignace Vergote, Philippe Moerman, Frederic Amant, Michel Koole, Vincent Vandecaveye S2 Whole-body diffusion-weighted MRI for surgical planning in patients with colorectal cancer and peritoneal metastases R Dresen, S De Vuysere, F De Keyzer, E Van Cutsem, A D’Hoore, A Wolthuis, V Vandecaveye S3 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extra capsular extension of prostate cancer. P. Pricolo ([email protected]), S. Alessi, P. Summers, E. Tagliabue, G. Petralia S4 Generating evidence for clinical benefit of PET/CT – are management studies sufficient as surrogate for patient outcome? C. Pfannenberg, B. Gückel, SC Schüle, AC Müller, S. Kaufmann, N. Schwenzer, M. Reimold,C. la Fougere, K. Nikolaou, P. Martus S5 Heterogeneity of treatment response in skeletal metastases from breast cancer with 18F-fluoride and 18F-FDG PET GJ Cook, GK Azad, BP Taylor, M Siddique, J John, J Mansi, M Harries, V Goh S6 Accuracy of suspicious breast imaging—can we tell the patient? S Seth, R Burgul, A Seth S7 Measurement method of tumour volume changes during neoadjuvant chemotherapy affects ability to predict pathological response S Waugh, N Muhammad Gowdh, C Purdie, A Evans, E Crowe, A Thompson, S Vinnicombe S8 Diagnostic yield of CT IVU in haematuria screening F. Arfeen, T. Campion, E. Goldstraw S9 Percutaneous radiofrequency ablation of unresectable locally advanced pancreatic cancer: preliminary results D’Onofrio M, Ciaravino V, Crosara S, De Robertis R, Pozzi Mucelli R S10 Iodine maps from dual energy CT improve detection of metastases in staging examinations of melanoma patients M. Uhrig, D. Simons, H. Schlemmer S11Can contrast enhanced CT predict pelvic nodal status in malignant melanoma of the lower limb? Kate Downey S12 Current practice in the investigation for suspected Paraneoplastic Neurological Syndromes (PNS) and positive malignancy yield. S Murdoch, AS Al-adhami, S Viswanathan P1 Technical success and efficacy of Pulmonary Radiofrequency ablation: an analysis of 207 ablations S Smith, P Jennings, D Bowers, R Soomal P2 Lesion control and patient outcome: prospective analysis of radiofrequency abaltion in pulmonary colorectal cancer metastatic disease S Smith, P Jennings, D Bowers, R Soomal P3 Hepatocellular carcinoma in a post-TB patient: case of tropical infections and oncologic imaging challenges TM Mutala, AO Odhiambo, N Harish P4 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extracapsular extension of prostate cancer P. Pricolo, S. Alessi, P. Summers, E. Tagliabue, G. 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Fine epitope signature of antibody neutralization breadth at the HIV-1 envelope CD4-binding site

Major advances in donor identification, antigen probe design, and experimental methods to clone pathogen-specific antibodies have led to an exponential growth in the number of newly characterized broadly neutralizing antibodies (bnAbs) that recognize the HIV-1 envelope glycoprotein. Characterization of these bnAbs has defined new epitopes and novel modes of recognition that can result in potent neutralization of HIV-1. However, the translation of envelope recognition profiles in biophysical assays into an understanding of in vivo activity has lagged behind, and identification of subjects and mAbs with potent antiviral activity has remained reliant on empirical evaluation of neutralization potency and breadth. To begin to address this discrepancy between recombinant protein recognition and virus neutralization, we studied the fine epitope specificity of a panel of CD4-binding site (CD4bs) antibodies to define the molecular recognition features of functionally potent humoral responses targeting the HIV-1 envelope site bound by CD4. Whereas previous studies have used neutralization data and machine-learning methods to provide epitope maps, here, this approach was reversed, demonstrating that simple binding assays of fine epitope specificity can prospectively identify broadly neutralizing CD4bs–specific mAbs. Building on this result, we show that epitope mapping and prediction of neutralization breadth can also be accomplished in the assessment of polyclonal serum responses. Thus, this study identifies a set of CD4bs bnAb signature amino acid residues and demonstrates that sensitivity to mutations at signature positions is sufficient to predict neutralization breadth of polyclonal sera with a high degree of accuracy across cohorts and across clades

Associations of common breast cancer susceptibility alleles with risk of breast cancer subtypes in BRCA1 and BRCA2 mutation carriers

Introduction: More than 70 common alleles are known to be involved in breast cancer (BC) susceptibility, and several exhibit significant heterogeneity in their associations with different BC subtypes. Although there are differences in the association patterns between BRCA1 and BRCA2 mutation carriers and the general population for several loci, no study has comprehensively evaluated the associations of all known BC susceptibility alleles with risk of BC subtypes in BRCA1 and BRCA2 carriers. Methods: We used data from 15,252 BRCA1 and 8,211 BRCA2 carriers to analyze the associations between approximately 200,000 genetic variants on the iCOGS array and risk of BC subtypes defined by estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and triple-negative- (TN) status; morphologic subtypes; histological grade; and nodal involvement. Results: The estimated BC hazard ratios (HRs) for the 74 known BC alleles in BRCA1 carriers exhibited moderate correlations with the corresponding odds ratios from the general population. However, their associations with ER-positive BC in BRCA1 carriers were more consistent with the ER-positive as