An Introduction to the Chandra Carina Complex Project

The Great Nebula in Carina provides an exceptional view into the violent massive star formation and feedback that typifies giant HII regions and starburst galaxies. We have mapped the Carina star-forming complex in X-rays, using archival Chandra data and a mosaic of 20 new 60ks pointings using the Chandra X-ray Observatory's Advanced CCD Imaging Spectrometer, as a testbed for understanding recent and ongoing star formation and to probe Carina's regions of bright diffuse X-ray emission. This study has yielded a catalog of properties of >14,000 X-ray point sources; >9800 of them have multiwavelength counterparts. Using Chandra's unsurpassed X-ray spatial resolution, we have separated these point sources from the extensive, spatially-complex diffuse emission that pervades the region; X-ray properties of this diffuse emission suggest that it traces feedback from Carina's massive stars. In this introductory paper, we motivate the survey design, describe the Chandra observations, and present some simple results, providing a foundation for the 15 papers that follow in this Special Issue and that present detailed catalogs, methods, and science results.Comment: Accepted for the ApJS Special Issue on the Chandra Carina Complex Project (CCCP), scheduled for publication in May 2011. All 16 CCCP Special Issue papers are available at http://cochise.astro.psu.edu/Carina_public/special_issue.html through 2011 at least. 43 pages; 18 figure

Correction for Johansson et al., An open challenge to advance probabilistic forecasting for dengue epidemics.

Correction for “An open challenge to advance probabilistic forecasting for dengue epidemics,” by Michael A. Johansson, Karyn M. Apfeldorf, Scott Dobson, Jason Devita, Anna L. Buczak, Benjamin Baugher, Linda J. Moniz, Thomas Bagley, Steven M. Babin, Erhan Guven, Teresa K. Yamana, Jeffrey Shaman, Terry Moschou, Nick Lothian, Aaron Lane, Grant Osborne, Gao Jiang, Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, Roni Rosenfeld, Justin Lessler, Nicholas G. Reich, Derek A. T. Cummings, Stephen A. Lauer, Sean M. Moore, Hannah E. Clapham, Rachel Lowe, Trevor C. Bailey, Markel García-Díez, Marilia Sá Carvalho, Xavier Rodó, Tridip Sardar, Richard Paul, Evan L. Ray, Krzysztof Sakrejda, Alexandria C. Brown, Xi Meng, Osonde Osoba, Raffaele Vardavas, David Manheim, Melinda Moore, Dhananjai M. Rao, Travis C. Porco, Sarah Ackley, Fengchen Liu, Lee Worden, Matteo Convertino, Yang Liu, Abraham Reddy, Eloy Ortiz, Jorge Rivero, Humberto Brito, Alicia Juarrero, Leah R. Johnson, Robert B. Gramacy, Jeremy M. Cohen, Erin A. Mordecai, Courtney C. Murdock, Jason R. Rohr, Sadie J. Ryan, Anna M. Stewart-Ibarra, Daniel P. Weikel, Antarpreet Jutla, Rakibul Khan, Marissa Poultney, Rita R. Colwell, Brenda Rivera-García, Christopher M. Barker, Jesse E. Bell, Matthew Biggerstaff, David Swerdlow, Luis Mier-y-Teran-Romero, Brett M. Forshey, Juli Trtanj, Jason Asher, Matt Clay, Harold S. Margolis, Andrew M. Hebbeler, Dylan George, and Jean-Paul Chretien, which was first published November 11, 2019; 10.1073/pnas.1909865116. The authors note that the affiliation for Xavier Rodó should instead appear as Catalan Institution for Research and Advanced Studies (ICREA) and Climate and Health Program, Barcelona Institute for Global Health (ISGlobal). The corrected author and affiliation lines appear below. The online version has been corrected

Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models

Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18–34°C with maximal transmission occurring in a range from 26–29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones

2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales.

Correction to: 2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales. Archives of Virology (2021) 166:3567–3579. https://doi.org/10.1007/s00705-021-05266-wIn March 2021, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by four families (Aliusviridae, Crepuscuviridae, Myriaviridae, and Natareviridae), three subfamilies (Alpharhabdovirinae, Betarhabdovirinae, and Gammarhabdovirinae), 42 genera, and 200 species. Thirty-nine species were renamed and/or moved and seven species were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.This work was supported in part through Laulima Government Solutions, LLC prime contract with the US National Institute of Allergy and Infectious Diseases (NIAID) under Contract No. HHSN272201800013C. J.H.K. performed this work as an employee of Tunnell Government Services (TGS), a subcontractor of Laulima Government Solutions, LLC under Contract No. HHSN272201800013C. This work was also supported in part with federal funds from the National Cancer Institute (NCI), National Institutes of Health (NIH), under Contract No. 75N91019D00024, Task Order No. 75N91019F00130 to I.C., who was supported by the Clinical Monitoring Research Program Directorate, Frederick National Lab for Cancer Research. This work was also funded in part by Contract No. HSHQDC-15-C-00064 awarded by DHS S&T for the management and operation of The National Biodefense Analysis and Countermeasures Center, a federally funded research and development center operated by the Battelle National Biodefense Institute (V.W.); and NIH contract HHSN272201000040I/HHSN27200004/D04 and grant R24AI120942 (N.V., R.B.T.). S.S. acknowledges partial support from the Special Research Initiative of Mississippi Agricultural and Forestry Experiment Station (MAFES), Mississippi State University, and the National Institute of Food and Agriculture, US Department of Agriculture, Hatch Project 1021494. Part of this work was supported by the Francis Crick Institute which receives its core funding from Cancer Research UK (FC001030), the UK Medical Research Council (FC001030), and the Wellcome Trust (FC001030).S

An open challenge to advance probabilistic forecasting for dengue epidemics.

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue

2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales.

In March 2021, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by four families (Aliusviridae, Crepuscuviridae, Myriaviridae, and Natareviridae), three subfamilies (Alpharhabdovirinae, Betarhabdovirinae, and Gammarhabdovirinae), 42 genera, and 200 species. Thirty-nine species were renamed and/or moved and seven species were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV

Developmental Regulation of Early Serotonergic Neuronal Differentiation: The Role of Brain-Derived Neurotrophic Factor and Membrane Depolarization

AbstractThe RN46A cell line was derived from Embryonic Day 13 rat medullary raphe cells by infection with a retrovirus encoding the temperature-sensitive mutant of SV40 large T antigen. This cell line is neuronally restricted and constitutively differentiates following a shift to nonpermissive temperature. Undifferentiated RN46A cells express low levels of tryptophan hydroxylase (TPH), low-affinity neurotrophin receptor (p75NTR), and trkB immunoreactivities, but no detectable levels of serotonin (5HT) immunoreactivity. TrkB, p75NTR, and TPH, but not 5HT, expressions increase with differentiation and treatment with brain-derived neurotrophic factor (BDNF). 5HT synthesis in RN46A cells requires initial treatment with BDNF, followed by growth under partial membrane depolarizing conditions. Embryonic raphe cultures treated similarly with BDNF and partial depolarizing conditions also demonstrate increased 5HT synthesis. The sodium-dependent transporter for 5HT reuptake is present in undifferentiated RN46A cells, and the apparent Km and Bmax are unchanged by differentiation or BDNF treatment and membrane depolarization. The high-affinity 5HT1A receptor is present in both undifferentiated and differentiated RN46A cells, and while the Kd is unaffected by differentiation or BDNF/membrane depolarization, the Bmax increases 20-fold after differentiation and 3.5-fold further with BDNF under depolarizing conditions. The expression of the synaptic vesicular monoamine transporter, as determined by the binding of [125I]iodovinyltetrabenazine, also increases in RN46A cells with differentiation. However, 5HT release is constitutive and is independent of acute membrane depolarization. Collectively these data indicate that distinct aspects of serotonin metabolism are differentially regulated during development and suggest that 5HT may function as a developmental signal in an autocrine loop during early serotonergic differentiation

Society for Immunotherapy of Cancer (SITC) clinical practice guideline on immunotherapy for the treatment of gastrointestinal cancer

Gastrointestinal (GI) cancers, including esophageal, gastroesophageal junction, gastric, duodenal and distal small bowel, biliary tract, pancreatic, colon, rectal, and anal cancer, comprise a heterogeneous group of malignancies that impose a significant global burden. Immunotherapy has transformed the treatment landscape for several GI cancers, offering some patients durable responses and prolonged survival. Specifically, immune checkpoint inhibitors (ICIs) directed against programmed cell death protein 1 (PD-1), either as monotherapies or in combination regimens, have gained tissue site-specific regulatory approvals for the treatment of metastatic disease and in the resectable setting. Indications for ICIs in GI cancer, however, have differing biomarker and histology requirements depending on the anatomic site of origin. Furthermore, ICIs are associated with unique toxicity profiles compared with other systemic treatments that have long been the mainstay for GI cancer, such as chemotherapy. With the goal of improving patient care by providing guidance to the oncology community, the Society for Immunotherapy of Cancer (SITC) convened a panel of experts to develop this clinical practice guideline on immunotherapy for the treatment of GI cancer. Drawing from published data and clinical experience, the expert panel developed evidence- and consensus-based recommendations for healthcare professionals using ICIs to treat GI cancers, with topics including biomarker testing, therapy selection, and patient education and quality of life considerations, among others

High throughput detection of miRNAs and gene-specific mRNA at the single-cell level by flow cytometry

Fluorescent in situ hybridization (FISH) is a method that uses fluorescent probes to detect specific nucleic acid sequences at the single cell level. Here we describe optimized protocols that exploit a highly sensitive FISH method based on branched DNA technology to detect mRNA and miRNA in human leukocytes. This technique can be multiplexed and combined with fluorescent antibody protein staining to addressa variety of questions in heterogeneous cell populations. We demonstrate antigen-specific upregulation of IFNγ and IL-2 mRNAs in HIV- and CMV-specific T cells. We show simultaneous detection of cytokine mRNA and corresponding protein in single cells. We apply this method to detect mRNAs for which flow antibodies against the corresponding proteins are poor or are not available. We use this technique to show modulation of a microRNA critical for T cell function, miR-155. We adapt this assay for simultaneous detection of mRNA and proteins by Image Stream technology