Predicting the legal status of recreational marijuana in U.S. states

Following decades of a war on drugs in the United States and the demonization of marijuana, a wave of recreational legalization began in 2012 with Washington state and Colorado. Recreational marijuana legalization is a novel phenomenon, both within and outside the U.S. borders. This thesis adds to the marijuana legalization research by creating prediction models that classifies observations (state-year) on whether U.S. states have legalized recreational marijuana or not in the timespan 2010 to 2018. It addresses the following research question: ‘To what extent, and how, is it possible to predict if a state has legalized recreational marijuana in the United States?’ I have drawn from theories and literature that explain why policies change, as well as from theories and literature on why individuals support marijuana legalization. My focus is on public opinion and policy responsiveness. Such theories and literature play an important role in predicting and describing states that have legalized recreational marijuana. A wide range of data sources have been used in order to create the best predictive model possible. For instance, data from such as the General Social Survey and United States Census Bureau have been used to create input variables. Furthermore, the machine learning iteration of multilevel regression with post-stratification is central in terms of this thesis’ data. This method, using the R package autoMrP, has allowed for the simulated disaggregation of the nationally representative public opinion variable in the General Social Survey. Tree-based classification algorithms, shrinkage methods and support vector machines have been used to predict the legality of marijuana. A focus on description using machine learning (ML) has been done due to what I see as necessities and to illustrate the use of ML in the social sciences – even when traditional regression models were a viable alternative. Having created multiple models, support vector machines and gradient boosting machines proved to be the best prediction algorithms. In terms of how marijuana legality is best predicted, the abstraction of individual-level determinants, and the use of public opinion and medical legalization as input variables are central aspects of creating strong predictive models of recreationally legal marijuana. This thesis concludes with the need for studying medical legalization and its relationship to recreational legalization. This is because the results show that medical legalization is important in predicting recreational legality.Master's ThesisSAMPOL350MASV-SAP

Simplified model for periodic nanoantennae: linear model and inverse design

We determine and use a minimal set of numerical simulations to create a simplified model for the spectral response of nanoantennae with respect to their geometric and modeling parameters. The simplified model is then used to rapidly obtain best-fit modeling parameters to match experimental results, accurately predict the spectral response for various geometries, and inversely design antennae to have a desired performance. This method is structure and model independent, and is applied here to both nanoantenna pair arrays and strips modeled using a 3D finite-element method and 2D spatial harmonic analysis, respectively. Typical numerical simulations may need hours per model, whereas this method, after the initial time to obtain a baseline set of simulations, requires only seconds to analyze and generate spectra for new geometries

COVID-19 risk-mitigation in reopening mass events: population-based observational study for the UK Events Research Programme in Liverpool City Region

OBJECTIVES: To understand severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission risks, perceived risks and the feasibility of risk mitigations from experimental mass cultural events before coronavirus disease 2019 (COVID-19) restrictions were lifted. DESIGN: Prospective, population-wide observational study. SETTING: Four events (two nightclubs, an outdoor music festival and a business conference) open to Liverpool City Region UK residents, requiring a negative lateral flow test (LFT) within the 36 h before the event, but not requiring social distancing or face-coverings. PARTICIPANTS: A total of 12,256 individuals attending one or more events between 28 April and 2 May 2021. MAIN OUTCOME MEASURES: SARS-CoV-2 infections detected using audience self-swabbed (5-7 days post-event) polymerase chain reaction (PCR) tests, with viral genomic analysis of cases, plus linked National Health Service COVID-19 testing data. Audience experiences were gathered via questionnaires, focus groups and social media. Indoor CO2 concentrations were monitored. RESULTS: A total of 12 PCR-positive cases (likely 4 index, 8 primary or secondary), 10 from the nightclubs. Two further cases had positive LFTs but no PCR. A total of 11,896 (97.1%) participants with scanned tickets were matched to a negative pre-event LFT: 4972 (40.6%) returned a PCR within a week. CO2 concentrations showed areas for improving ventilation at the nightclubs. Population infection rates were low, yet with a concurrent outbreak of >50 linked cases around a local swimming pool without equivalent risk mitigations. Audience anxiety was low and enjoyment high. CONCLUSIONS: We observed minor SARS-CoV-2 transmission and low perceived risks around events when prevalence was low and risk mitigations prominent. Partnership between audiences, event organisers and public health services, supported by information systems with real-time linked data, can improve health security for mass cultural events

Barcoding a Quantified Food Web: Crypsis, Concepts, Ecology and Hypotheses

The efficient and effective monitoring of individuals and populations is critically dependent on correct species identification. While this point may seem obvious, identifying the majority of the more than 100 natural enemies involved in the spruce budworm (Choristoneura fumiferana – SBW) food web remains a non-trivial endeavor. Insect parasitoids play a major role in the processes governing the population dynamics of SBW throughout eastern North America. However, these species are at the leading edge of the taxonomic impediment and integrating standardized identification capacity into existing field programs would provide clear benefits. We asked to what extent DNA barcoding the SBW food web would alter our understanding of the diversity and connectence of the food web and the frequency of generalists vs. specialists in different forest habitats. We DNA barcoded over 10% of the insects collected from the SBW food web in three New Brunswick forest plots from 1983 to 1993. For 30% of these specimens, we amplified at least one additional nuclear region. When the nodes of the food web were estimated based on barcode divergences (using molecular operational taxonomic units (MOTU) or phylogenetic diversity (PD) – the food web became much more diverse and connectence was reduced. We tested one measure of food web structure (the “bird feeder effect”) and found no difference compared to the morphologically based predictions. Many, but not all, of the presumably polyphagous parasitoids now appear to be morphologically-cryptic host-specialists. To our knowledge, this project is the first to barcode a food web in which interactions have already been well-documented and described in space, time and abundance. It is poised to be a system in which field-based methods permit the identification capacity required by forestry scientists. Food web barcoding provided an effective tool for the accurate identification of all species involved in the cascading effects of future budworm outbreaks. Integrating standardized barcodes within food webs may ultimately change the face of community ecology. This will be most poignantly felt in food webs that have not yet been quantified. Here, more accurate and precise connections will be within the grasp of any researcher for the first time

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes

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

2020 taxonomic update for phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales.

In March 2020, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. At the genus rank, 20 new genera were added, two were deleted, one was moved, and three were renamed. At the species rank, 160 species were added, four were deleted, ten were moved and renamed, and 30 species were renamed. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV

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

A prenylated dsRNA sensor protects against severe COVID-19

Inherited genetic factors can influence the severity of COVID-19, but the molecular explanation underpinning a genetic association is often unclear. Intracellular antiviral defenses can inhibit the replication of viruses and reduce disease severity. To better understand the antiviral defenses relevant to COVID-19, we used interferon-stimulated gene (ISG) expression screening to reveal that OAS1, through RNase L, potently inhibits SARS-CoV-2. We show that a common splice-acceptor SNP (Rs10774671) governs whether people express prenylated OAS1 isoforms that are membrane-associated and sense specific regions of SARS-CoV-2 RNAs, or only express cytosolic, nonprenylated OAS1 that does not efficiently detect SARS-CoV-2. Importantly, in hospitalized patients, expression of prenylated OAS1 was associated with protection from severe COVID-19, suggesting this antiviral defense is a major component of a protective antiviral response