A latent class analysis of risk factors for acquiring HIV among men who have sex with men: implications for implementing pre-exposure prophylaxis programs

Current Centers for Disease Control and Prevention (CDC) guidelines for prescribing pre-exposure prophylaxis (PrEP) to prevent HIV transmission are broad. In order to better characterize groups who may benefit most from PrEP, we reviewed demographics, behaviors, and clinical outcomes for individuals presenting to a publicly-funded sexually transmitted diseases (STD) clinic in Providence, Rhode Island, from 2012 to 2014. Latent class analysis (LCA) was used to identify subgroups of men who have sex with men (MSM) at highest risk for contracting HIV. A total of 1723 individuals presented for testing (75% male; 31% MSM). MSM were more likely to test HIV positive than heterosexual men or women. Among 538 MSM, we identified four latent classes. Class 1 had the highest rates of incarceration (33%), forced sex (24%), but had no HIV infections. Class 2 had <5 anal sex partners in the previous 12 months, the lowest rates of drug/alcohol use during sex and lower HIV prevalence (3%). Class 3 had the highest prevalence of HIV (7%) and other STDs (16%), > 10 anal sex partners in the previous 12 months (69%), anonymous partners (100%), drug/alcohol use during sex (76%), and prior STDs (40%). Class 4 had similar characteristics and HIV prevalence as Class 2. In this population, MSM who may benefit most from PrEP include those who have >10 sexual partners per year, anonymous partners, drug/alcohol use during sex and prior STDs. LCA is a useful tool for identifying clusters of characteristics that may place individuals at higher risk for HIV infection and who may benefit most from PrEP in clinical practice

Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network.

Grid cells fire in sequences that represent rapid trajectories in space. During locomotion, theta sequences encode sweeps in position starting slightly behind the animal and ending ahead of it. During quiescence and slow wave sleep, bouts of synchronized activity represent long trajectories called replays, which are well-established in place cells and have been recently reported in grid cells. Theta sequences and replay are hypothesized to facilitate many cognitive functions, but their underlying mechanisms are unknown. One mechanism proposed for grid cell formation is the continuous attractor network. We demonstrate that this established architecture naturally produces theta sequences and replay as distinct consequences of modulating external input. Driving inhibitory interneurons at the theta frequency causes attractor bumps to oscillate in speed and size, which gives rise to theta sequences and phase precession, respectively. Decreasing input drive to all neurons produces traveling wavefronts of activity that are decoded as replays

Exile Vol. XXXVII No. 2

Once and for All by Michael Payne 1 Alone Over The Trees by John Stoddard 2 Caught You by Nancy Booth 3 Mother\u27s Words by Julie Green 4-10 His Token by Donna Marie Voldness 11-12 Global Warming by Eric Franzon 13-14 Amish Mystery by Shannon Salser 15 For Peace by Robin Schneider 16-18 Elvis, the Lizard King, and Me by Stewart Engesser 19-22 Norpell Woods by Brandon Pfeiffer 23 Blue Suit, Red Dog by Jack Beck 24 I Am Without My List of Excusses [sic] by Douglas George 25 Somtimes - Satre Would Not Be Proud by Dana Wells 26 The Flock by Carter Holland 27-33 Dance of Alabaster by Jay Speiden 34 Winter Solstice by K. Lynn Rogers 35-36 Fish Story by Jim Dixon 37-42 Slumming by Stewart Engesser 43 Beached by Chris Dealy 44 The Missing Man by Tom Ream 45-47 Elegy by Scott Dexter 48 Close Range by Jay Speiden 49 No Longer by Shannon Salser 50 In A Bar In Georgetown, Colorado 1990 by John Stoddard 51 untitled by Brian Wills 52 Editorial decision is shared equally among the Editorial Board. -i Cover: Megan Doyle -i NOTE: I Am Without My List of Excusses [sic] by Douglas George 25 is listed as I Am Without My List of Excuses on page 25. The published table of contents is followed here

The SPARC Toroidal Field Model Coil Program

The SPARC Toroidal Field Model Coil (TFMC) Program was a three-year effort between 2018 and 2021 that developed novel Rare Earth Yttrium Barium Copper Oxide (REBCO) superconductor technologies and then successfully utilized these technologies to design, build, and test a first-in-class, high-field (~20 T), representative-scale (~3 m) superconducting toroidal field coil. With the principal objective of demonstrating mature, large-scale, REBCO magnets, the project was executed jointly by the MIT Plasma Science and Fusion Center (PSFC) and Commonwealth Fusion Systems (CFS). The TFMC achieved its programmatic goal of experimentally demonstrating a large-scale high-field REBCO magnet, achieving 20.1 T peak field-on-conductor with 40.5 kA of terminal current, 815 kN/m of Lorentz loading on the REBCO stacks, and almost 1 GPa of mechanical stress accommodated by the structural case. Fifteen internal demountable pancake-to-pancake joints operated in the 0.5 to 2.0 nOhm range at 20 K and in magnetic fields up to 12 T. The DC and AC electromagnetic performance of the magnet, predicted by new advances in high-fidelity computational models, was confirmed in two test campaigns while the massively parallel, single-pass, pressure-vessel style coolant scheme capable of large heat removal was validated. The REBCO current lead and feeder system was experimentally qualified up to 50 kA, and the crycooler based cryogenic system provided 600 W of cooling power at 20 K with mass flow rates up to 70 g/s at a maximum design pressure of 20 bar-a for the test campaigns. Finally, the feasibility of using passive, self-protection against a quench in a fusion-scale NI TF coil was experimentally assessed with an intentional open-circuit quench at 31.5 kA terminal current.Comment: 17 pages 9 figures, overview paper and the first of a six-part series of papers covering the TFMC Progra

Manganese Superoxide Dismutase: Guardian of the Powerhouse

The mitochondrion is vital for many metabolic pathways in the cell, contributing all or important constituent enzymes for diverse functions such as β-oxidation of fatty acids, the urea cycle, the citric acid cycle, and ATP synthesis. The mitochondrion is also a major site of reactive oxygen species (ROS) production in the cell. Aberrant production of mitochondrial ROS can have dramatic effects on cellular function, in part, due to oxidative modification of key metabolic proteins localized in the mitochondrion. The cell is equipped with myriad antioxidant enzyme systems to combat deleterious ROS production in mitochondria, with the mitochondrial antioxidant enzyme manganese superoxide dismutase (MnSOD) acting as the chief ROS scavenging enzyme in the cell. Factors that affect the expression and/or the activity of MnSOD, resulting in diminished antioxidant capacity of the cell, can have extraordinary consequences on the overall health of the cell by altering mitochondrial metabolic function, leading to the development and progression of numerous diseases. A better understanding of the mechanisms by which MnSOD protects cells from the harmful effects of overproduction of ROS, in particular, the effects of ROS on mitochondrial metabolic enzymes, may contribute to the development of novel treatments for various diseases in which ROS are an important component

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages