Smallpox and Bioterrorism: Why the Plan to Protect the Nation Is Stalled and What to Do

The Iraq war is over, no weapons of mass destruction (WMD) have yet been found, and the president's smallpox plan, though sound, is running out of steam. Instead of being well on the way to protecting the nation's civilian population by vaccinating up to 10 million health, emergency, and public safety workers, we are stalled at 37,971 vaccinated civilians while the military has successfully and safely vaccinated more than 450,000 people. Moreover, whether or not WMD are found in Iraq, it is only one of a number of nations on the list of suspects. Of all biological weapons, smallpox has the greatest potential for doing widespread harm. Given that the risk of death or serious harm to anyone from any form of terrorism is very low, we should live our daily lives normally, not in fear. However, to do that we need to be sure that our government is taking effective steps to reduce the chances of terrorism and, when it occurs, to minimize its consequences. Even though there is enough vaccine for everyone, we are ill prepared to rapidly contain smallpox after a bioterrorist release. Although Centers for Disease Control and Prevention (CDC) guidelines have recently improved, they continue to overstate the risk of side effects of the vaccine and erroneously suggest that, after an attack, the techniques used decades ago to eradicate smallpox will work well today. Medicine and public health are very risk-averse professions in our risk-averse culture. We have not yet realized the complexity and difficulty of vaccinating millions of Americans rapidly after an attack. Nor have we come to grips with the need to make rapid, possibly draconian, post-attack decisions based on limited data of uncertain quality. That type of decisionmaking runs counter to the culture of public health. The Bush administration needs to revitalize our preparations for a smallpox bioterrorist event

Bird communities across different levels of human settlement: A comparative analysis from two northern Amazonian ecoregions

Urban ecosystems are increasingly dominating landscapes globally, so it is critical to understand the effects of human settlements on biodiversity. Bird communities are effective indicators because they are impacted by the size and expansion of human settlements, exemplified by changes in their habitat use, breeding and foraging behaviours, as well as patterns of richness and abundance. Existing studies on bird community responses to human settlements have mainly focused on single ecoregions and large cities, leaving a gap in comparative research on how differently sized human settlements affect bird communities across various ecoregions. To address this gap, we examine species richness, bird abundances and community composition in human settlements, which exhibit variable sizes, populations, landscape configurations, and overall intensity of settlement in two tropical ecoregions in Guyana, Amazonia: forest and savannah. In each ecoregion we explored how different groupings of urban tolerance in birds responded to human settlements of differing population size and building densities. Overall, we found significant differences in bird communities across the varying levels of human settlement intensity in both ecoregions, with greater differences in bird community composition in the forest ecoregion than the savannah region. In both ecoregions, species richness and abundance were highest at the medium level of settlement of human settlement. Our findings suggest that bird tolerance to human settlements varies based on ecoregion and site-level factors. In the savannah, built features may be benefitting birds from all urban tolerance levels, but they have a negative impact on less urban-tolerant species in the forest ecoregion. Our comparative analysis reveals for the first time that the impact of human settlements on avian communities in northern Amazonia varies among ecoregions, indicating that species evolved to live in a savannah may be more tolerant to human settlements than those more evolved to a forest system

DNA replication stress restricts ribosomal DNA copy number

Ribosomal RNAs (rRNAs) in budding yeast are encoded by ~100–200 repeats of a 9.1kb sequence arranged in tandem on chromosome XII, the ribosomal DNA (rDNA) locus. Copy number of rDNA repeat units in eukaryotic cells is maintained far in excess of the requirement for ribosome biogenesis. Despite the importance of the repeats for both ribosomal and non-ribosomal functions, it is currently not known how “normal” copy number is determined or maintained. To identify essential genes involved in the maintenance of rDNA copy number, we developed a droplet digital PCR based assay to measure rDNA copy number in yeast and used it to screen a yeast conditional temperature-sensitive mutant collection of essential genes. Our screen revealed that low rDNA copy number is associated with compromised DNA replication. Further, subculturing yeast under two separate conditions of DNA replication stress selected for a contraction of the rDNA array independent of the replication fork blocking protein, Fob1. Interestingly, cells with a contracted array grew better than their counterparts with normal copy number under conditions of DNA replication stress. Our data indicate that DNA replication stresses select for a smaller rDNA array. We speculate that this liberates scarce replication factors for use by the rest of the genome, which in turn helps cells complete DNA replication and continue to propagate. Interestingly, tumors from mini chromosome maintenance 2 (MCM2)-deficient mice also show a loss of rDNA repeats. Our data suggest that a reduction in rDNA copy number may indicate a history of DNA replication stress, and that rDNA array size could serve as a diagnostic marker for replication stress. Taken together, these data begin to suggest the selective pressures that combine to yield a “normal” rDNA copy number

HacA-Independent Functions of the ER Stress Sensor IreA Synergize with the Canonical UPR to Influence Virulence Traits in Aspergillus fumigatus

Endoplasmic reticulum (ER) stress is a condition in which the protein folding capacity of the ER becomes overwhelmed by an increased demand for secretion or by exposure to compounds that disrupt ER homeostasis. In yeast and other fungi, the accumulation of unfolded proteins is detected by the ER-transmembrane sensor IreA/Ire1, which responds by cleaving an intron from the downstream cytoplasmic mRNA HacA/Hac1, allowing for the translation of a transcription factor that coordinates a series of adaptive responses that are collectively known as the unfolded protein response (UPR). Here, we examined the contribution of IreA to growth and virulence in the human fungal pathogen Aspergillus fumigatus. Gene expression profiling revealed that A. fumigatus IreA signals predominantly through the canonical IreA-HacA pathway under conditions of severe ER stress. However, in the absence of ER stress IreA controls dual signaling circuits that are both HacA-dependent and HacA-independent. We found that a ΔireA mutant was avirulent in a mouse model of invasive aspergillosis, which contrasts the partial virulence of a ΔhacA mutant, suggesting that IreA contributes to pathogenesis independently of HacA. In support of this conclusion, we found that the ΔireA mutant had more severe defects in the expression of multiple virulence-related traits relative to ΔhacA, including reduced thermotolerance, decreased nutritional versatility, impaired growth under hypoxia, altered cell wall and membrane composition, and increased susceptibility to azole antifungals. In addition, full or partial virulence could be restored to the ΔireA mutant by complementation with either the induced form of the hacA mRNA, hacAi, or an ireA deletion mutant that was incapable of processing the hacA mRNA, ireAΔ10. Together, these findings demonstrate that IreA has both HacA-dependent and HacA-independent functions that contribute to the expression of traits that are essential for virulence in A. fumigatus

Multiple pathways of SARS-CoV-2 nosocomial transmission uncovered by integrated genomic and epidemiological analyses during the second wave of the COVID-19 pandemic in the UK

INTRODUCTION: Throughout the global COVID-19 pandemic, nosocomial transmission has represented a major concern for healthcare settings and has accounted for many infections diagnosed within hospitals. As restrictions ease and novel variants continue to spread, it is important to uncover the specific pathways by which nosocomial outbreaks occur to understand the most suitable transmission control strategies for the future. METHODS: In this investigation, SARS-CoV-2 genome sequences obtained from 694 healthcare workers and 1,181 patients were analyzed at a large acute NHS hospital in the UK between September 2020 and May 2021. These viral genomic data were combined with epidemiological data to uncover transmission routes within the hospital. We also investigated the effects of the introduction of the highly transmissible variant of concern (VOC), Alpha, over this period, as well as the effects of the national vaccination program on SARS-CoV-2 infection in the hospital. RESULTS: Our results show that infections of all variants within the hospital increased as community prevalence of Alpha increased, resulting in several outbreaks and super-spreader events. Nosocomial infections were enriched amongst older and more vulnerable patients more likely to be in hospital for longer periods but had no impact on disease severity. Infections appeared to be transmitted most regularly from patient to patient and from patients to HCWs. In contrast, infections from HCWs to patients appeared rare, highlighting the benefits of PPE in infection control. The introduction of the vaccine at this time also reduced infections amongst HCWs by over four-times. DISCUSSION: These analyses have highlighted the importance of control measures such as regular testing, rapid lateral flow testing alongside polymerase chain reaction (PCR) testing, isolation of positive patients in the emergency department (where possible), and physical distancing of patient beds on hospital wards to minimize nosocomial transmission of infectious diseases such as COVID-19

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Spike patterning in oxytocin neurons:Capturing physiological behaviour with Hodgkin-Huxley and integrate-and-fire models

Integrate-and-fire (IF) models can provide close matches to the discharge activity of neurons, but do they oversimplify the biophysical properties of the neurons? A single compartment Hodgkin-Huxley (HH) model of the oxytocin neuron has previously been developed, incorporating biophysical measurements of channel properties obtained in vitro. A simpler modified integrate-and-fire model has also been developed, which can match well the characteristic spike patterning of oxytocin neurons as observed in vivo. Here, we extended the HH model to incorporate synaptic input, to enable us to compare spike activity in the model with experimental data obtained in vivo. We refined the HH model parameters to closely match the data, and then matched the same experimental data with a modified IF model, using an evolutionary algorithm to optimise parameter matching. Finally we compared the properties of the modified HH model with those of the IF model to seek an explanation for differences between spike patterning in vitro and in vivo. We show that, with slight modifications, the original HH model, like the IF model, is able to closely match both the interspike interval (ISI) distributions of oxytocin neurons and the observed variability of spike firing rates in vivo and in vitro. This close match of both models to data depends on the presence of a slow activity-dependent hyperpolarisation (AHP); this is represented in both models and the parameters used in the HH model representation match well with optimal parameters of the IF model found by an evolutionary algorithm. The ability of both models to fit data closely also depends on a shorter hyperpolarising after potential (HAP); this is explicitly represented in the IF model, but in the HH model, it emerges from a combination of several components. The critical elements of this combination are identified

Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences

Abstract: Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental datasets, that these types of designs usually give less biased estimates than simpler observational designs. We propose a model-based approach to combine study estimates that may suffer from different levels of study design bias, discuss the implications for evidence synthesis, and how to facilitate the use of more credible study designs