SARS-CoV-2 Disrupts Splicing, Translation, and Protein Trafficking to Suppress Host Defenses.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a recently identified coronavirus that causes the respiratory disease known as coronavirus disease 2019 (COVID-19). Despite the urgent need, we still do not fully understand the molecular basis of SARS-CoV-2 pathogenesis. Here, we comprehensively define the interactions between SARS-CoV-2 proteins and human RNAs. NSP16 binds to the mRNA recognition domains of the U1 and U2 splicing RNAs and acts to suppress global mRNA splicing upon SARS-CoV-2 infection. NSP1 binds to 18S ribosomal RNA in the mRNA entry channel of the ribosome and leads to global inhibition of mRNA translation upon infection. Finally, NSP8 and NSP9 bind to the 7SL RNA in the signal recognition particle and interfere with protein trafficking to the cell membrane upon infection. Disruption of each of these essential cellular functions acts to suppress the interferon response to viral infection. Our results uncover a multipronged strategy utilized by SARS-CoV-2 to antagonize essential cellular processes to suppress host defenses.

Coexistence of many species under a random competition-colonization trade-off.

The competition-colonization (CC) trade-off is a well-studied coexistence mechanism for metacommunities. In this setting, it is believed that the coexistence of all species requires their traits to satisfy restrictive conditions limiting their similarity. To investigate whether diverse metacommunities can assemble in a CC trade-off model, we study their assembly from a probabilistic perspective. From a pool of species with parameters (corresponding to traits) sampled at random, we compute the probability that any number of species coexist and characterize the set of species that emerges through assembly. Remarkably, almost exactly half of the species in a large pool typically coexist, with no saturation as the size of the pool grows, and with little dependence on the underlying distribution of traits. Through a mix of analytical results and simulations, we show that this unlimited niche packing emerges as assembly actively moves communities toward overdispersed configurations in niche space. Our findings also apply to a realistic assembly scenario where species invade one at a time from a fixed regional pool. When diversity arises de novo in the metacommunity, richness still grows without bound, but more slowly. Together, our results suggest that the CC trade-off can support the robust emergence of diverse communities, even when coexistence of the full species pool is exceedingly unlikely.

Rigorous benchmarking of T-cell receptor repertoire profiling methods for cancer RNA sequencing.

The ability to identify and track T-cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The available high-throughput method to profile TCR repertoires is generally referred to as TCR sequencing (TCR-Seq). However, the available TCR-Seq data are limited compared with RNA sequencing (RNA-Seq). In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across 4 cancer cohorts including both T-cell-rich and T-cell-poor tissue types. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as provide relative frequencies of clonotypes in T-cell-rich tissues and low-diversity repertoires. However, RNA-Seq-based TCR profiling methods have limited power in T-cell-poor tissues, especially in highly diverse repertoires of T-cell-poor tissues. The results of our benchmarking provide an additional appealing argument to incorporate RNA-Seq into the immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq.

Clinical dimensions along the non-fluent variant primary progressive aphasia spectrum.

It is debated whether primary progressive apraxia of speech (PPAOS) and progressive agrammatic aphasia (PAA) belong to the same clinical spectrum, traditionally termed non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), or exist as two completely distinct syndromic entities with specific pathologic/prognostic correlates. We analysed speech, language and disease severity features in a comprehensive cohort of patients with progressive motor speech impairment and/or agrammatism to ascertain evidence of naturally occurring, clinically meaningful non-overlapping syndromic entities (e.g. PPAOS and PAA) in our data. We also assessed if data-driven latent clinical dimensions with aetiologic/prognostic value could be identified. We included 98 participants, 43 of whom had an autopsy-confirmed neuropathological diagnosis. Speech pathologists assessed motor speech features indicative of dysarthria and apraxia of speech (AOS). Quantitative expressive/receptive agrammatism measures were obtained and compared with healthy controls. Baseline and longitudinal disease severity was evaluated using the Clinical Dementia Rating Sum of Boxes (CDR-SB). We investigated the data's clustering tendency and cluster stability to form robust symptom clusters and employed principal component analysis to extract data-driven latent clinical dimensions (LCD). The longitudinal CDR-SB change was estimated using linear mixed-effects models. Of the participants included in this study, 93 conformed to previously reported clinical profiles (75 with AOS and agrammatism, 12 PPAOS and six PAA). The remaining five participants were characterized by non-fluent speech, executive dysfunction and dysarthria without apraxia of speech or frank agrammatism. No baseline clinical features differentiated between frontotemporal lobar degeneration neuropathological subgroups. The Hopkins statistic demonstrated a low cluster tendency in the entire sample (0.45 with values near 0.5 indicating random data). Cluster stability analyses showed that only two robust subgroups (differing in agrammatism, executive dysfunction and overall disease severity) could be identified. Three data-driven components accounted for 71% of the variance [(i) severity-agrammatism; (ii) prominent AOS; and (iii) prominent dysarthria]. None of these data-driven LCDs allowed an accurate prediction of neuropathology. The severity-agrammatism component was an independent predictor of a faster CDR-SB increase in all the participants. Higher dysarthria severity, reduced words per minute and expressive and receptive agrammatism severity at baseline independently predicted accelerated disease progression. Our findings indicate that PPAOS and PAA, rather than exist as completely distinct syndromic entities, constitute a clinical continuum. In our cohort, splitting the nfvPPA spectrum into separate clinical phenotypes did not improve clinical-pathological correlations, stressing the need for new biological markers and consensus regarding updated terminology and clinical classification.

Neural basis of speech and grammar symptoms in non-fluent variant primary progressive aphasia spectrum.

The non-fluent/agrammatic variant of primary progressive aphasia (nfvPPA) is a neurodegenerative syndrome primarily defined by the presence of apraxia of speech (AoS) and/or expressive agrammatism. In addition, many patients exhibit dysarthria and/or receptive agrammatism. This leads to substantial phenotypic variation within the speech-language domain across individuals and time, in terms of both the specific combination of symptoms as well as their severity. How to resolve such phenotypic heterogeneity in nfvPPA is a matter of debate. 'Splitting' views propose separate clinical entities: 'primary progressive apraxia of speech' when AoS occurs in the absence of expressive agrammatism, 'progressive agrammatic aphasia' (PAA) in the opposite case, and 'AOS + PAA' when mixed motor speech and language symptoms are clearly present. While therapeutic interventions typically vary depending on the predominant symptom (e.g. AoS versus expressive agrammatism), the existence of behavioural, anatomical and pathological overlap across these phenotypes argues against drawing such clear-cut boundaries. In the current study, we contribute to this debate by mapping behaviour to brain in a large, prospective cohort of well characterized patients with nfvPPA (n = 104). We sought to advance scientific understanding of nfvPPA and the neural basis of speech-language by uncovering where in the brain the degree of MRI-based atrophy is associated with inter-patient variability in the presence and severity of AoS, dysarthria, expressive agrammatism or receptive agrammatism. Our cross-sectional examination of brain-behaviour relationships revealed three main observations. First, we found that the neural correlates of AoS and expressive agrammatism in nfvPPA lie side by side in the left posterior inferior frontal lobe, explaining their behavioural dissociation/association in previous reports. Second, we identified a 'left-right' and 'ventral-dorsal' neuroanatomical distinction between AoS versus dysarthria, highlighting (i) that dysarthria, but not AoS, is significantly influenced by tissue loss in right-hemisphere motor-speech regions; and (ii) that, within the left hemisphere, dysarthria and AoS map onto dorsally versus ventrally located motor-speech regions, respectively. Third, we confirmed that, within the large-scale grammar network, left frontal tissue loss is preferentially involved in expressive agrammatism and left temporal tissue loss in receptive agrammatism. Our findings thus contribute to define the function and location of the epicentres within the large-scale neural networks vulnerable to neurodegenerative changes in nfvPPA. We propose that nfvPPA be redefined as an umbrella term subsuming a spectrum of speech and/or language phenotypes that are closely linked by the underlying neuroanatomy and neuropathology.

Metapopulations with habitat modification.

Across the tree of life, organisms modify their local environment, rendering it more or less hospitable for other species. Despite the ubiquity of these processes, simple models that can be used to develop intuitions about the consequences of widespread habitat modification are lacking. Here, we extend the classic Levins metapopulation model to a setting where each of n species can colonize patches connected by dispersal, and when patches are vacated via local extinction, they retain a "memory" of the previous occupant-modeling habitat modification. While this model can exhibit a wide range of dynamics, we draw several overarching conclusions about the effects of modification and memory. In particular, we find that any number of species may potentially coexist, provided that each is at a disadvantage when colonizing patches vacated by a conspecific. This notion is made precise through a quantitative stability condition, which provides a way to unify and formalize existing conceptual models. We also show that when patch memory facilitates coexistence, it generically induces a positive relationship between diversity and robustness (tolerance of disturbance). Our simple model provides a portable, tractable framework for studying systems where species modify and react to a shared landscape.

Habitat Heterogeneity, Environmental Feedbacks, and Species Coexistence across Timescales.

AbstractClassic ecological theory explains species coexistence in variable environments. While spatial variation is often treated as an intrinsic feature of a landscape, it may be shaped and even generated by the resident community. All species modify their local environment to some extent, driving changes that can feed back to affect the composition and coexistence of the community, potentially over timescales very different from population dynamics. We introduce a simple nested modeling framework for community dynamics in heterogeneous environments, including the possible evolution of heterogeneity over time due to community-environment feedbacks. We use this model to derive analytical conditions for species coexistence in environments where heterogeneity is either fixed or shaped by feedbacks. Among other results, our approach reveals how dispersal and environmental specialization interact to shape realized patterns of habitat association and demonstrates that environmental feedbacks can tune landscape conditions to allow the stable coexistence of any number of species. Our flexible modeling framework helps explain feedback dynamics that arise in a wide range of ecosystems and offers a generic platform for exploring the interplay between species and landscape diversity.

Combined Multiharmonic Frequency Analysis for Improved Dynamic Energy Measurements and Accuracy in Charge Detection Mass Spectrometry.

The ability to determine ion energies in electrostatic ion-trap-based charge detection mass spectrometry (CDMS) experiments is important for the accurate measurement of individual ion m/z, charge, and mass. Dynamic energy measurements throughout the time an ion is trapped take advantage of the relationship between ion energy and the harmonic amplitude ratio (HAR) composed from the fundamental and second harmonic amplitudes in the Fourier transform of the ion signal. This method eliminates the need for energy-filtering optics in CDMS and makes it possible to measure energy lost in collisions and changes in ion masses due to dissociation. However, the accuracy of the energy measurement depends on the signal-to-noise ratio (S/N) of the amplitudes used to determine the HAR. Here, a major improvement to this HAR-based dynamic energy measurement method is achieved using HARs composed of higher-order harmonics in addition to the fundamental and second harmonic to determine ion energies. This combined harmonic amplitude ratios for precision energy refinement (CHARPER) method is applied to the analysis of a 103 nm polystyrene nanoparticle ion (359.7 MDa, m/z = 308,300) and the energy resolution (3140) and effective mass resolution (730) achieved are the best yet demonstrated in electrostatic ion-trap-based CDMS. The CHARPER method applied to an ensemble of several thousand adeno-associated virus ion signals also results in higher mass resolution compared to the basic HAR method, making it possible to resolve additional features in the composite mass histogram.

Dynamic Energy Measurements in Charge Detection Mass Spectrometry Eliminate Adverse Effects of Ion-Ion Interactions.

Ion-ion interactions in charge detection mass spectrometers that use electrostatic traps to measure masses of individual ions have not been reported previously, although ion trajectory simulations have shown that these types of interactions affect ion energies and thereby degrade measurement performance. Here, examples of interactions between simultaneously trapped ions that have masses ranging from ca. 2 to 350 MDa and ca. 100 to 1000 charges are studied in detail using a dynamic measurement method that makes it possible to track the evolution of the mass, charge, and energy of individual ions over their trapping lifetimes. Signals from ions that have similar oscillation frequencies can have overlapping spectral leakage artifacts that result in slightly increased uncertainties in the mass determination, but these effects can be mitigated by the careful choice of parameters used in the short-time Fourier transform analysis. Energy transfers between physically interacting ions are also observed and quantified with individual ion energy measurement resolution as high as ∼950. The mass and charge of interacting ions do not change, and their corresponding measurement uncertainties are equivalent to ions that do not undergo physical interactions. Simultaneous trapping of multiple ions in CDMS can greatly decrease the acquisition time necessary to accumulate a statistically meaningful number of individual ion measurements. These results demonstrate that while ion-ion interactions can occur when multiple ions are trapped, they have negligible effects on mass accuracy when using the dynamic measurement method.

Distinct neurophysiology during nonword repetition in logopenic and non-fluent variants of primary progressive aphasia.

Overlapping clinical presentations in primary progressive aphasia (PPA) variants present challenges for diagnosis and understanding pathophysiology, particularly in the early stages of the disease when behavioral (speech) symptoms are not clearly evident. Divergent atrophy patterns (temporoparietal degeneration in logopenic variant lvPPA, frontal degeneration in nonfluent variant nfvPPA) can partially account for differential speech production errors in the two groups in the later stages of the disease. While the existing dogma states that neurodegeneration is the root cause of compromised behavior and cortical activity in PPA, the extent to which neurophysiological signatures of speech dysfunction manifest independent of their divergent atrophy patterns remain unknown. We test the hypothesis that nonword deficits in lvPPA and nfvPPA arise from distinct patterns of neural oscillations that are unrelated to atrophy. We use a novel structure-function imaging approach integrating magnetoencephalographic imaging of neural oscillations during a non-word repetition task with voxel-based morphometry-derived measures of gray matter volume to isolate neural oscillation abnormalities independent of atrophy. We find reduced beta band neural activity in left temporal regions associated with the late stages of auditory encoding unique to patients with lvPPA and reduced high-gamma neural activity over left frontal regions associated with the early stages of motor preparation in patients with nfvPPA. Neither of these patterns of reduced cortical oscillations was explained by cortical atrophy in our statistical model. These findings highlight the importance of structure-function imaging in revealing neurophysiological sequelae in early stages of dementia when neither structural atrophy nor behavioral deficits are clinically distinct.

Network anatomy in logopenic variant of primary progressive aphasia.

The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through predetermined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal structural MRI data from individuals with lvPPA to derive the epicenter-seeded resting-state networks most relevant to lvPPA symptomatology and ascertain whether functional connectivity in these networks predicts longitudinal atrophy spread in lvPPA. Our results show that two partially distinct brain networks anchored to the left anterior angular and posterior superior temporal gyri epicenters were preferentially associated with sentence repetition and naming skills in lvPPA. Critically, the strength of connectivity within these two networks in the neurologically-intact brain significantly predicted longitudinal atrophy progression in lvPPA. Taken together, our findings indicate that atrophy progression in lvPPA, starting from inferior parietal and temporoparietal junction regions, predominantly follows at least two partially nonoverlapping pathways, which may influence the heterogeneity in clinical presentation and prognosis.

Motion compensated self supervised deep learning for highly accelerated 3D ultrashort Echo time pulmonary MRI.

PURPOSE: To investigate motion compensated, self-supervised, model based deep learning (MBDL) as a method to reconstruct free breathing, 3D pulmonary UTE acquisitions. THEORY AND METHODS: A self-supervised eXtra dimension MBDL architecture (XD-MBDL) was developed that combined respiratory states to reconstruct a single high-quality 3D image. Non-rigid motion fields were incorporated into this architecture by estimating motion fields from a lower resolution motion resolved (XD-GRASP) reconstruction. Motion compensated XD-MBDL was evaluated on lung UTE datasets with and without contrast and compared to constrained reconstructions and variants of self-supervised MBDL that do not account for dynamic respiratory states or leverage motion correction. RESULTS: Images reconstructed using XD-MBDL demonstrate improved image quality as measured by apparent SNR (aSNR), contrast to noise ratio (CNR), and visual assessment relative to self-supervised MBDL approaches that do not account for dynamic respiratory states, XD-GRASP and a recently proposed motion compensated iterative reconstruction strategy (iMoCo). Additionally, XD-MBDL reduced reconstruction time relative to both XD-GRASP and iMoCo. CONCLUSION: A method was developed to allow self-supervised MBDL to combine multiple respiratory states to reconstruct a single image. This method was combined with graphics processing unit (GPU)-based image registration to further improve reconstruction quality. This approach showed promising results reconstructing a user-selected respiratory phase from free breathing 3D pulmonary UTE acquisitions.

Stability criteria for the consumption and exchange of essential resources.

Models of consumer effects on a shared resource environment have helped clarify how the interplay of consumer traits and resource supply impact stable coexistence. Recent models generalize this picture to include the exchange of resources alongside resource competition. These models exemplify the fact that although consumers shape the resource environment, the outcome of consumer interactions is context-dependent: such models can have either stable or unstable equilibria, depending on the resource supply. However, these recent models focus on a simplified version of microbial metabolism where the depletion of resources always leads to consumer growth. Here, we model an arbitrarily large system of consumers governed by Liebig's law, where species require and deplete multiple resources, but each consumer's growth rate is only limited by a single one of these resources. Resources that are taken up but not incorporated into new biomass are leaked back into the environment, possibly transformed by intracellular reactions, thereby tying the mismatch between depletion and growth to cross-feeding. For this set of dynamics, we show that feasible equilibria can be either stable or unstable, again depending on the resource environment. We identify special consumption and production networks which protect the community from instability when resources are scarce. Using simulations, we demonstrate that the qualitative stability patterns derived analytically apply to a broader class of network structures and resource inflow profiles, including cases where multiple species coexist on only one externally supplied resource. Our stability criteria bear some resemblance to classic stability results for pairwise interactions, but also demonstrate how environmental context can shape coexistence patterns when resource limitation and exchange are modeled directly.

Amyloid, tau and metabolic PET correlates of cognition in early and late-onset Alzheimer's disease.

Early-onset (age < 65) Alzheimer's disease is associated with greater non-amnestic cognitive symptoms and neuropathological burden than late-onset disease. It is not fully understood whether these groups also differ in the associations between molecular pathology, neurodegeneration and cognitive performance. We studied amyloid-positive patients with early-onset (n = 60, mean age 58 ± 4, MMSE 21 ± 6, 58% female) and late-onset (n = 53, mean age 74 ± 6, MMSE 23 ± 5, 45% female) Alzheimer's disease who underwent neurological evaluation, neuropsychological testing, 11C-Pittsburgh compound B PET (amyloid-PET) and 18F-flortaucipir PET (tau-PET). 18F-fluorodeoxyglucose PET (brain glucose metabolism PET) was also available in 74% (n = 84) of participants. Composite scores for episodic memory, semantic memory, language, executive function and visuospatial domains were calculated based on cognitively unimpaired controls. Voxel-wise regressions evaluated correlations between PET biomarkers and cognitive scores and early-onset versus late-onset differences were tested with a PET × Age group interaction. Mediation analyses estimated direct and indirect (18F-fluorodeoxyglucose mediated) local associations between 18F-flortaucipir binding and cognitive scores in domain-specific regions of interest. We found that early-onset patients had higher 18F-flortaucipir binding in parietal, lateral temporal and lateral frontal cortex; more severe 18F-fluorodeoxyglucose hypometabolism in the precuneus and angular gyrus; and greater 11C-Pittsburgh compound B binding in occipital regions compared to late-onset patients. In our primary analyses, PET-cognition correlations did not meaningfully differ between age groups.18F-flortaucipir and 18F-fluorodeoxyglucose, but not 11C-Pittsburgh compound B, were significantly associated with cognition in expected domain-specific patterns in both age groups (e.g. left perisylvian/language, frontal/executive, occipital/visuospatial). 18F-fluorodeoxyglucose mediated the relationship between 18F-flortaucipir and cognition in both age groups across all domains except episodic memory in late-onset patients. Additional direct effects of 18F-flortaucipir were observed for executive function in all age groups, language in early-onset Alzheimer's disease and in the total sample and visuospatial function in the total sample. In conclusion, tau and neurodegeneration, but not amyloid, were similarly associated with cognition in both early and late-onset Alzheimer's disease. Tau had an association with cognition independent of neurodegeneration in language, executive and visuospatial functions in the total sample. Our findings support tau PET as a biomarker that captures both the clinical severity and molecular pathology specific to Alzheimer's disease across the broad spectrum of ages and clinical phenotypes in Alzheimer's disease.

Right temporal degeneration and socioemotional semantics: semantic behavioural variant frontotemporal dementia.

Focal anterior temporal lobe degeneration often preferentially affects the left or right hemisphere. While patients with left-predominant anterior temporal lobe atrophy show severe anomia and verbal semantic deficits and meet criteria for semantic variant primary progressive aphasia and semantic dementia, patients with early right anterior temporal lobe atrophy are more difficult to diagnose as their symptoms are less well understood. Focal right anterior temporal lobe atrophy is associated with prominent emotional and behavioural changes, and patients often meet, or go on to meet, criteria for behavioural variant frontotemporal dementia. Uncertainty around early symptoms and absence of an overarching clinico-anatomical framework continue to hinder proper diagnosis and care of patients with right anterior temporal lobe disease. Here, we examine a large, well-characterized, longitudinal cohort of patients with right anterior temporal lobe-predominant degeneration and propose new criteria and nosology. We identified individuals from our database with a clinical diagnosis of behavioural variant frontotemporal dementia or semantic variant primary progressive aphasia and a structural MRI (n = 478). On the basis of neuroimaging criteria, we defined three patient groups: right anterior temporal lobe-predominant atrophy with relative sparing of the frontal lobes (n = 46), frontal-predominant atrophy with relative sparing of the right anterior temporal lobe (n = 79) and left-predominant anterior temporal lobe-predominant atrophy with relative sparing of the frontal lobes (n = 75). We compared the clinical, neuropsychological, genetic and pathological profiles of these groups. In the right anterior temporal lobe-predominant group, the earliest symptoms were loss of empathy (27%), person-specific semantic impairment (23%) and complex compulsions and rigid thought process (18%). On testing, this group exhibited greater impairments in Emotional Theory of Mind, recognition of famous people (from names and faces) and facial affect naming (despite preserved face perception) than the frontal- and left-predominant anterior temporal lobe-predominant groups. The clinical symptoms in the first 3 years of the disease alone were highly sensitive (81%) and specific (84%) differentiating right anterior temporal lobe-predominant from frontal-predominant groups. Frontotemporal lobar degeneration-transactive response DNA binding protein (84%) was the most common pathology of the right anterior temporal lobe-predominant group. Right anterior temporal lobe-predominant degeneration is characterized by early loss of empathy and person-specific knowledge, deficits that are caused by progressive decline in semantic memory for concepts of socioemotional relevance. Guided by our results, we outline new diagnostic criteria and propose the name, 'semantic behavioural variant frontotemporal dementia', which highlights the underlying cognitive mechanism and the predominant symptomatology. These diagnostic criteria will facilitate early identification and care of patients with early, focal right anterior temporal lobe degeneration as well as in vivo prediction of frontotemporal lobar degeneration-transactive response DNA binding protein pathology.

Support for management actions to protect night sky quality: Insights from visitors to state and national park units in the U.S.

Light pollution is a global phenomenon where anthropogenic light sources continue to grow unabated, affecting both social and ecological systems. This is leaving parks and protected areas as some of the last vestiges of naturally dark environments for protecting views of the night sky. Yet, even parks and protected areas have outdoor lighting. Alternative lighting practices are needed to reduce or prevent light pollution from within parks. However, making parks darker may not be desirable for some visitors if they believe it will reduce navigability, safety, or restrict how they recreate (e.g., requiring the use of red-light flashlights after dark and before dawn). How visitors will respond to alternative lighting practices that park managers can implement is still unknown. We used an on-site intercept survey at nine state and national park units in Utah, U.S., to investigate nighttime visitors' support or opposition to management actions to protect night sky quality and their interest in learning about topics related to night skies. Further, this study also segmented visitors into two groups: those 'dependent' on the dark sky as a resource and those whose activities did not depend on a dark sky. Defining what a 'dark sky dependent' visitor is, which has yet to be done in the literature, is a fundamental step to furthering night sky research and management efforts. Across nine parks and protected areas, 62% of nighttime visitors participated in dark sky dependent activities. Findings indicate broad support for management actions designed to improve night sky quality, with between 74% and 89% of all visitors supporting seven different management actions. There was stronger support from dark sky dependent visitors for some elements of alternative lighting practices, but there was still strong support for those who do not participate in dark sky dependent outdoor recreation. Additionally, between 57% and 75% of visitors were interested in learning more about topics related to night skies. This research indicates most visitors would welcome actions to preserve the quality of the rapidly dwindling naturally dark experiences offered by parks and protected areas.

Show-Me Resilience: Assessing and Reconciling Rural Leaders' Perceptions of Climate Resilience in Missouri.

Rural areas of the United States play a vital role in coping with, adapting to and mitigating climate change, yet they often lag urban areas in climate planning and action. Rural leaders-e.g., policymakers, state/federal agency professionals, non-profit organization leadership, and scholars - are pivotal for driving the programs and policies that support resilient practices, but our understanding of their perspectives on climate resilience writ large is limited. We conducted semi-structured interviews with 23 rural leaders in Missouri to elucidate their conceptualizations of climate resilience and identify catalysts and constraints for climate adaptation planning and action across rural landscapes. We investigated participants' perceptions of the major vulnerabilities of rural communities and landscapes, threats to rural areas, and potential steps for making rural Missouri more resilient in the face of climate change. We found that most rural leaders conceptualized climate resilience as responding to hazardous events rather than anticipating or planning for hazardous trends. The predominant threats identified were flooding and drought, which aligns with climate projections for the Midwest. Participants proposed a wide variety of specific steps to enhance resilience but had the highest agreement about the utility of expanding existing programs. The most comprehensive suite of solutions was offered by participants who conceptualized resilience as involving social, ecological, and economic systems, underscoring the importance of broad thinking for developing more holistic solutions to climate-associated threats and the potential impact of greater collaboration across domains. We highlight and discuss a Missouri-based levee setback project that was identified by participants as a showcase of collaborative resilience-building.

Motion-corrected 4D-Flow MRI for neurovascular applications.

Neurovascular 4D-Flow MRI has emerged as a powerful tool for comprehensive cerebrovascular hemodynamic characterization. Clinical studies in at risk populations such as aging adults indicate hemodynamic markers can be confounded by motion-induced bias. This study develops and characterizes a high fidelity 3D self-navigation approach for retrospective rigid motion correction of neurovascular 4D-Flow data. A 3D radial trajectory with pseudorandom ordering was combined with a multi-resolution low rank regularization approach to enable high spatiotemporal resolution self-navigators from extremely undersampled data. Phantom and volunteer experiments were performed at 3.0T to evaluate the ability to correct for different amounts of induced motions. In addition, the approach was applied to clinical-research exams from ongoing aging studies to characterize performance in the clinical setting. Simulations, phantom and volunteer experiments with motion correction produced images with increased vessel conspicuity, reduced image blurring, and decreased variability in quantitative measures. Clinical exams revealed significant changes in hemodynamic parameters including blood flow rates, flow pulsatility index, and lumen areas after motion correction in probed cerebral arteries (Flow: P<0.001 Lt ICA, P=0.002 Rt ICA, P=0.004 Lt MCA, P=0.004 Rt MCA; Area: P<0.001 Lt ICA, P<0.001 Rt ICA, P=0.004 Lt MCA, P=0.004 Rt MCA; flow pulsatility index: P=0.042 Rt ICA, P=0.002 Lt MCA). Motion induced bias can lead to significant overestimation of hemodynamic markers in cerebral arteries. The proposed method reduces measurement bias from rigid motion in neurovascular 4D-Flow MRI in challenging populations such as aging adults.

No robust multispecies coexistence in a canonical model of plant-soil feedbacks.

Plant-soil feedbacks (PSFs) are considered a key mechanism generating frequency-dependent dynamics in plant communities. Negative feedbacks, in particular, are often invoked to explain coexistence and the maintenance of diversity in species-rich communities. However, the primary modelling framework used to study PSFs considers only two plant species, and we lack clear theoretical expectations for how these complex interactions play out in communities with natural levels of diversity. Here, we extend this canonical model of PSFs to include an arbitrary number of plant species and analyse the dynamics. Surprisingly, we find that coexistence of more than two species is virtually impossible, suggesting that alternative theoretical frameworks are needed to describe feedbacks observed in diverse natural communities. Drawing on our analysis, we discuss future directions for PSF models and implications for experimental study of PSF-mediated coexistence in the field.

Effects of Molecular Size on Resolution in Charge Detection Mass Spectrometry.

Instrumental resolution of Fourier transform-charge detection mass spectrometry instruments with electrostatic ion trap detection of individual ions depends on the precision with which ion energy is determined. Energy can be selected using ion optic filters or from harmonic amplitude ratios (HARs) that provide Fellgett's advantage and eliminate the necessity of ion transmission loss to improve resolution. Unlike the ion energy-filtering method, the resolution of the HAR method increases with charge (improved S/N) and thus with mass. An analysis of the HAR method with current instrumentation indicates that higher resolution can be obtained with the HAR method than the best resolution demonstrated for instruments with energy-selective optics for ions in the low MDa range and above. However, this gain is typically unrealized because the resolution obtainable with molecular systems in this mass range is limited by sample heterogeneity. This phenomenon is illustrated with both tobacco mosaic virus (0.6-2.7 MDa) and AAV9 (3.7-4.7 MDa) samples where mass spectral resolution is limited by the sample, including salt adducts, and not by instrument resolution. Nevertheless, the ratio of full to empty AAV9 capsids and the included genome mass can be accurately obtained in a few minutes from 1× PBS buffer solution and an elution buffer containing 300+ mM nonvolatile content despite extensive adduction and lower resolution. Empty and full capsids adduct similarly indicating that salts encrust the complexes during late stages of droplet evaporation and that mass shifts can be calibrated in order to obtain accurate analyte masses even from highly salty solutions.