Effects of historic and projected climate change on the range and impacts of an emerging wildlife disease.

The global trend of increasing environmental temperatures is often predicted to result in more severe disease epidemics. However, unambiguous evidence that temperature is a driver of epidemics is largely lacking, because it is demanding to demonstrate its role among the complex interactions between hosts, pathogens, and their shared environment. Here, we apply a three-pronged approach to understand the effects of temperature on ranavirus epidemics in UK common frogs, combining in vitro, in vivo, and field studies. Each approach suggests that higher temperatures drive increasing severity of epidemics. In wild populations, ranavirosis incidents were more frequent and more severe at higher temperatures, and their frequency increased through a period of historic warming in the 1990s. Laboratory experiments using cell culture and whole animal models showed that higher temperature increased ranavirus propagation, disease incidence, and mortality rate. These results, combined with climate projections, predict severe ranavirosis outbreaks will occur over wider areas and an extended season, possibly affecting larval recruitment. Since ranaviruses affect a variety of ectothermic hosts (amphibians, reptiles, and fish), wider ecological damage could occur. Our three complementary lines of evidence present a clear case for direct environmental modulation of these epidemics and suggest management options to protect species from disease.

Regional variability of imaging biomarkers in autosomal dominant Alzheimer's disease.

Major imaging biomarkers of Alzheimer's disease include amyloid deposition [imaged with [(11)C]Pittsburgh compound B (PiB) PET], altered glucose metabolism (imaged with [(18)F]fluro-deoxyglucose PET), and structural atrophy (imaged by MRI). Recently we published the initial subset of imaging findings for specific regions in a cohort of individuals with autosomal dominant Alzheimer's disease. We now extend this work to include a larger cohort, whole-brain analyses integrating all three imaging modalities, and longitudinal data to examine regional differences in imaging biomarker dynamics. The anatomical distribution of imaging biomarkers is described in relation to estimated years from symptom onset. Autosomal dominant Alzheimer's disease mutation carrier individuals have elevated PiB levels in nearly every cortical region 15 y before the estimated age of onset. Reduced cortical glucose metabolism and cortical thinning in the medial and lateral parietal lobe appeared 10 and 5 y, respectively, before estimated age of onset. Importantly, however, a divergent pattern was observed subcortically. All subcortical gray-matter regions exhibited elevated PiB uptake, but despite this, only the hippocampus showed reduced glucose metabolism. Similarly, atrophy was not observed in the caudate and pallidum despite marked amyloid accumulation. Finally, before hypometabolism, a hypermetabolic phase was identified for some cortical regions, including the precuneus and posterior cingulate. Additional analyses of individuals in which longitudinal data were available suggested that an accelerated appearance of volumetric declines approximately coincides with the onset of the symptomatic phase of the disease.

Partial volume correction in quantitative amyloid imaging.

Amyloid imaging is a valuable tool for research and diagnosis in dementing disorders. As positron emission tomography (PET) scanners have limited spatial resolution, measured signals are distorted by partial volume effects. Various techniques have been proposed for correcting partial volume effects, but there is no consensus as to whether these techniques are necessary in amyloid imaging, and, if so, how they should be implemented. We evaluated a two-component partial volume correction technique and a regional spread function technique using both simulated and human Pittsburgh compound B (PiB) PET imaging data. Both correction techniques compensated for partial volume effects and yielded improved detection of subtle changes in PiB retention. However, the regional spread function technique was more accurate in application to simulated data. Because PiB retention estimates depend on the correction technique, standardization is necessary to compare results across groups. Partial volume correction has sometimes been avoided because it increases the sensitivity to inaccuracy in image registration and segmentation. However, our results indicate that appropriate PVC may enhance our ability to detect changes in amyloid deposition.

Arctic cyanobacterial mat community diversity decreases with latitude across the Canadian Arctic.

Cyanobacterial mats are commonly reported as hotspots of microbial diversity across polar environments. These thick, multilayered microbial communities provide a refuge from extreme environmental conditions, with many species able to grow and coexist despite the low allochthonous nutrient inputs. The visibly dominant phototrophic biomass is dependent on internal nutrient recycling by heterotrophic organisms within the mats; however, the specific contribution of heterotrophic protists remains little explored. In this study, mat community diversity was examined along a latitudinal gradient (55-83°N), spanning subarctic taiga, tundra, polar desert, and the High Arctic ice shelves. The prokaryotic and eukaryotic communities were targeted, respectively, by V4 16S ribosomal RNA (rRNA) and V9 18S rRNA gene amplicon high-throughput sequencing. Prokaryotic and eukaryotic richness decreased, in tandem with decreasing temperatures and shorter seasons of light availability, from the subarctic to the High Arctic. Taxonomy-based annotation of the protist community revealed diverse phototrophic, mixotrophic, and heterotrophic genera in all mat communities, with fewer parasitic taxa in High Arctic communities. Co-occurrence network analysis identified greater heterogeneity in eukaryotic than prokaryotic community structure among cyanobacterial mats across the Canadian Arctic. Our findings highlight the sensitivity of microbial eukaryotes to environmental gradients across northern high latitudes.

In situ observations of large-amplitude Alfvén waves heating and accelerating the solar wind.

After leaving the Sun's corona, the solar wind continues to accelerate and cools, but more slowly than expected for a freely expanding adiabatic gas. Alfvén waves are perturbations of the interplanetary magnetic field that transport energy. We use in situ measurements from the Parker Solar Probe and Solar Orbiter spacecraft to investigate a stream of solar wind as it traverses the inner heliosphere. The observations show heating and acceleration of the plasma between the outer edge of the corona and near the orbit of Venus, along with the presence of large-amplitude Alfvén waves. We calculate that the damping and mechanical work performed by the Alfvén waves are sufficient to power the heating and acceleration of the fast solar wind in the inner heliosphere.

Multi-source connectivity as the driver of solar wind variability in the heliosphere.

The ambient solar wind that fills the heliosphere originates from multiple sources in the solar corona and is highly structured. It is often described as high-speed, relatively homogeneous, plasma streams from coronal holes and slow-speed, highly variable, streams whose source regions are under debate. A key goal of ESA/NASA's Solar Orbiter mission is to identify solar wind sources and understand what drives the complexity seen in the heliosphere. By combining magnetic field modelling and spectroscopic techniques with high-resolution observations and measurements, we show that the solar wind variability detected in situ by Solar Orbiter in March 2022 is driven by spatio-temporal changes in the magnetic connectivity to multiple sources in the solar atmosphere. The magnetic field footpoints connected to the spacecraft moved from the boundaries of a coronal hole to one active region (12961) and then across to another region (12957). This is reflected in the in situ measurements, which show the transition from fast to highly Alfvénic then to slow solar wind that is disrupted by the arrival of a coronal mass ejection. Our results describe solar wind variability at 0.5 au but are applicable to near-Earth observatories.

Transmission of SARS-CoV-2 from humans to animals and potential host adaptation.

SARS-CoV-2, the causative agent of the COVID-19 pandemic, can infect a wide range of mammals. Since its spread in humans, secondary host jumps of SARS-CoV-2 from humans to multiple domestic and wild populations of mammals have been documented. Understanding the extent of adaptation to these animal hosts is critical for assessing the threat that the spillback of animal-adapted SARS-CoV-2 into humans poses. We compare the genomic landscapes of SARS-CoV-2 isolated from animal species to that in humans, profiling the mutational biases indicative of potentially different selective pressures in animals. We focus on viral genomes isolated from mink (Neovison vison) and white-tailed deer (Odocoileus virginianus) for which multiple independent outbreaks driven by onward animal-to-animal transmission have been reported. We identify five candidate mutations for animal-specific adaptation in mink (NSP9_G37E, Spike_F486L, Spike_N501T, Spike_Y453F, ORF3a_L219V), and one in deer (NSP3a_L1035F), though they appear to confer a minimal advantage for human-to-human transmission. No considerable changes to the mutation rate or evolutionary trajectory of SARS-CoV-2 has resulted from circulation in mink and deer thus far. Our findings suggest that minimal adaptation was required for onward transmission in mink and deer following human-to-animal spillover, highlighting the 'generalist' nature of SARS-CoV-2 as a mammalian pathogen.

Association of Pretreatment Hippocampal Volume With Neurocognitive Function in Patients Treated With Hippocampal Avoidance Whole Brain Radiation Therapy for Brain Metastases: Secondary Analysis of NRG Oncology/RTOG 0933.

Purpose: Hippocampal volume (HV) is an established predicting factor for neurocognitive function (NCF) in neurodegenerative disease. Whether the same phenomenon exists with hippocampal-avoidant whole brain radiation therapy is not known; therefore, we assessed the association of baseline HV with NCF among patients enrolled on RTOG 0933. Methods and Materials: Hippocampal volume and total brain volume were calculated from the radiation therapy plan. Hippocampal volume was correlated with baseline and 4-month NCF scores (Hopkins Verbal Learning Test-Revised [HVLT-R] Total Recall [TR], Immediate Recognition, and Delayed Recall [DR]) using Pearson correlation. Deterioration in NCF was defined per the primary endpoint of RTOG 0933(mean 4-month relative decline in HVLT-R DR). Comparisons between patients with deteriorated and nondeteriorated NCF were made using the Wilcoxon test. Results: Forty-two patients were evaluable. The median age was 56.5 years (range, 28-83 years), and 81% had a class II recursive partitioning analysis. The median total, right, and left HVs were 5.4 cm3 (range, 1.9-7.4 cm3), 2.8 cm3 (range, 0.9-4.0 cm3), and 2.7 cm3 (range, 1.0-3.7 cm3), respectively. The median total brain volume was 1343 cm3 (range, 1120.5-1738.8 cm3). For all measures of corrected HV, increasing HV was associated with higher baseline HVLT-R TR and DR scores (ρ: range, 0.35-0.40; P-value range, .009-.024) and 4-month TR and DR scores (ρ: range, 0.29-0.40; P-value range, .009-.04), with the exception of right HV and 4-month DR scores (ρ: 0.29; P = .059). There was no significant association between HV and NCF change between baseline and 4 months. Fourteen patients (33.3%) developed NCF deterioration per the primary endpoint of RTOG 0933. There was no significant difference in HV between patients with deteriorated and nondeteriorated NCF, although in all instances, patients with deteriorated NCF had numerically lower HV. Conclusions: Larger HV was positively associated with improved performance on baseline and 4-month HVLT-R TR and DR scores in patients with brain metastases undergoing hippocampal-avoidant whole brain radiation therapy but was not associated with a change in NCF.

Pre-existing T cell-mediated cross-reactivity to SARS-CoV-2 cannot solely be explained by prior exposure to endemic human coronaviruses.

T-cell-mediated immunity to SARS-CoV-2-derived peptides in individuals unexposed to SARS-CoV-2 has been previously reported. This pre-existing immunity was suggested to largely derive from prior exposure to 'common cold' endemic human coronaviruses (HCoVs). To test this, we characterised the sequence homology of SARS-CoV-2-derived T-cell epitopes reported in the literature across the full proteome of the Coronaviridae family. 54.8% of these epitopes had no homology to any of the HCoVs. Further, the proportion of SARS-CoV-2-derived epitopes with any level of sequence homology to the proteins encoded by any of the coronaviruses tested is well-predicted by their alignment-free phylogenetic distance to SARS-CoV-2 (Pearson's r = -0.958). No coronavirus in our dataset showed a significant excess of T-cell epitope homology relative to the proportion of expected random matches, given their genetic similarity to SARS-CoV-2. Our findings suggest that prior exposure to human or animal-associated coronaviruses cannot completely explain the T-cell repertoire in unexposed individuals that recognise SARS-CoV-2 cross-reactive epitopes.

Emergence of genomic diversity and recurrent mutations in SARS-CoV-2.

SARS-CoV-2 is a SARS-like coronavirus of likely zoonotic origin first identified in December 2019 in Wuhan, the capital of China's Hubei province. The virus has since spread globally, resulting in the currently ongoing COVID-19 pandemic. The first whole genome sequence was published on January 5 2020, and thousands of genomes have been sequenced since this date. This resource allows unprecedented insights into the past demography of SARS-CoV-2 but also monitoring of how the virus is adapting to its novel human host, providing information to direct drug and vaccine design. We curated a dataset of 7666 public genome assemblies and analysed the emergence of genomic diversity over time. Our results are in line with previous estimates and point to all sequences sharing a common ancestor towards the end of 2019, supporting this as the period when SARS-CoV-2 jumped into its human host. Due to extensive transmission, the genetic diversity of the virus in several countries recapitulates a large fraction of its worldwide genetic diversity. We identify regions of the SARS-CoV-2 genome that have remained largely invariant to date, and others that have already accumulated diversity. By focusing on mutations which have emerged independently multiple times (homoplasies), we identify 198 filtered recurrent mutations in the SARS-CoV-2 genome. Nearly 80% of the recurrent mutations produced non-synonymous changes at the protein level, suggesting possible ongoing adaptation of SARS-CoV-2. Three sites in Orf1ab in the regions encoding Nsp6, Nsp11, Nsp13, and one in the Spike protein are characterised by a particularly large number of recurrent mutations (>15 events) which may signpost convergent evolution and are of particular interest in the context of adaptation of SARS-CoV-2 to the human host. We additionally provide an interactive user-friendly web-application to query the alignment of the 7666 SARS-CoV-2 genomes.

Correction: Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer's Disease: Results from the DIAN Study Group.

[This corrects the article DOI: 10.1371/journal.pone.0152082.].

Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer's Disease: Results from the DIAN Study Group.

Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer's Network (DIAN), an autosomal dominant Alzheimer's disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer's disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted.

The geometric factor of electrostatic plasma analyzers: a case study from the Fast Plasma Investigation for the Magnetospheric Multiscale mission.

We report our findings comparing the geometric factor (GF) as determined from simulations and laboratory measurements of the new Dual Electron Spectrometer (DES) being developed at NASA Goddard Space Flight Center as part of the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission. Particle simulations are increasingly playing an essential role in the design and calibration of electrostatic analyzers, facilitating the identification and mitigation of the many sources of systematic error present in laboratory calibration. While equations for laboratory measurement of the GF have been described in the literature, these are not directly applicable to simulation since the two are carried out under substantially different assumptions and conditions, making direct comparison very challenging. Starting from first principles, we derive generalized expressions for the determination of the GF in simulation and laboratory, and discuss how we have estimated errors in both cases. Finally, we apply these equations to the new DES instrument and show that the results agree within errors. Thus we show that the techniques presented here will produce consistent results between laboratory and simulation, and present the first description of the performance of the new DES instrument in the literature.