Modulation of cold-induced shivering activity by intermittent and continuous voluntary suppression.

This investigation assessed the physiological effects of voluntary suppression of shivering thermogenesis in response to whole body cooling. Eleven healthy volunteers underwent passive air cooling (10°C), across three visits: NO_SUP, where participants allowed their body to freely regulate against the cold; FULL_SUP, where participants constantly suppressed shivering; INT_SUP, where participants intermittently suppressed shivering (5 min phases), interspersed with 5 min free regulation. Shivering was assessed via electromyography (EMG), mechanomyography (MMG), and whole body oxygen uptake (V̇o2), whereas body temperature and heat exchange were assessed via skin temperature, rectal temperature, and heat flux sensors. A 29% increase was observed in shivering onset time in the FULL_SUP trial compared with NO_SUP (P = 0.032). Assessing shivering intensity, EMG activity decreased by 29% (P = 0.034), MMG activity decreased by 35% (P = 0.031), whereas no difference was observed in V̇o2 (P = 0.091) in the FULL_SUP trial compared with NO_SUP. Partitioning the no-suppression and suppression phases of the INT_SUP trial, acute voluntary suppression significantly decreased V̇o2 (P = 0.001), EMG (P < 0.001), and MMG (P = 0.012) activity compared with the no-suppression phases. Shivering activity was restored in the no-suppression phases, equivalent to that in the NO_SUP trial (P > 0.3). No difference was observed in thermal metrics between conditions up to 60 min (P > 0.4). Humans can both constantly and periodically suppress shivering activity, leading to a delay in shivering onset and a reduction in shivering intensity. Following suppression, regular shivering is resumed.

Mood and activity changes during the COVID-19 pandemic in rural and urban Veterans and their cohabitants.

OBJECTIVES: We aimed to examine the impact of COVID-19 pandemic-related stay-at-home orders on weekly reports of mood and activity before and during COVID-19 in a sample of older Veterans and their cohabitants. METHODS: Urban and rural Veterans and their cohabitants living in the Pacific Northwest ≥62 years old were enrolled as part of the Collaborative Aging Research Using Technology initiative (n = 100, age = 71.2 ± 6.5, 41% women). Participants reported frequency of social activities (e.g., travel away), physical illness, and mood (blue mood and loneliness) via weekly online health forms. RESULTS: A total of 2,441 weekly online health forms (OHFs) were collected from 100 participants. During the COVID-19 pandemic, blue mood (OR = 4.4, p < .0001) and loneliness (OR = 7.2, p < .0001) were significantly higher than before the pandemic, and travel away from home was significantly lower (OR = 0.5, p < .0001). Prevalence of blue mood and loneliness were not associated with rurality. CONCLUSIONS: The current study established that blue mood and loneliness were significantly more prevalent in older Veterans following COVID-19 stay-at-home orders regardless of rurality. CLINICAL IMPLICATIONS: The COVID-19 pandemic associated health precautions, while necessary to curb acute health risks, have created a unique situation that places vulnerable populations at increased risk of low mood.

Black and White individuals differ in dementia prevalence, risk factors, and symptomatic presentation.

INTRODUCTION: Although dementia prevalence differs by race, it remains unclear whether cognition and neuropsychiatric symptom severity differ between Black and White individuals with dementia. METHODS: Using National Alzheimer's Coordinating Center (NACC) data, we evaluated dementia prevalence in non-Hispanic Black and White participants and compared their clinicodemographic characteristics. We examined race differences in cognition, neuropsychiatric symptoms, and functional abilities in participants with dementia using multivariable linear and logistic regression models. RESULTS: We included 5,700 Black and 31,225 White participants across 39 Alzheimer's Disease Research Centers. Of these, 1,528 (27%) Black and 11,267 (36%) White participants had dementia diagnoses. Despite having lower dementia prevalence, risk factors were more prevalent among Black participants. Black participants with dementia showed greater cognitive deficits, neuropsychiatric symptoms/severity, and functional dependence. DISCUSSION: Despite lower dementia prevalence, Black participants with dementia had more dementia risk factors, as well as greater cognitive impairment and neuropsychiatric symptom severity than White participants.

Magnetic resonance-guided focused ultrasound for Parkinson's disease since ExAblate, 2016-2019: a systematic review.

INTRODUCTION: ExAblate received FDA approval for treatment of a range of movement disorders in 2016, including tremor-dominant Parkinson's disease (TDPD), dyskinetic PD, and essential tremor. This incisionless device allows for magnetic resonance-guided focused ultrasound (MRgFUS) for ablation of several regions of interest. Current studies should aim to measure pre- and post-operative neurocognitive functioning to better understand MRgFUS in PD and how it compares to deep brain stimulation, which has known cognitive risks among certain populations. METHODS: PubMed, CINAHL, PsycINFO, and Cochrane Library databases were searched from January 2016 to January 2020. Guidelines for Preferred Reporting Items for Systematic Review and Meta-Analyses were used to review clinical trials comprehensively assessing pre- and post-operative neurocognitive functioning in PD patients undergoing MRgFUS. Due to limited extant literature in this area, TDPD was expanded to PD with severe dyskinesia. RESULTS: Twenty-two abstracts were reviewed following removal of duplicates. After full-text review of eight articles, only two studies included comprehensive neuropsychological evaluations of PD patients undergoing MRgFUS thalamotomy or pallidotomy. Most excluded studies used only brief cognitive screeners to assess functioning. Cognitive declines appear to be minimal following MRgFUS in PD, with exceptions in verbal fluency and inhibition. These results are limited by sample size and sample diversity. CONCLUSIONS: Significant methodological gaps were inadvertently discovered. Few studies to-date have administered comprehensive neuropsychological batteries to ascertain MRgFUS risks to neurocognitive functioning in PD. Studies must extend beyond brief screeners when assessing PD populations vulnerable to decline. Furthermore, consensus on a comprehensive battery would better serve replicability and the ability to engage in useful meta-analyses.

Neurologic and Immunologic Complications of COVID-19: Potential Long-Term Risk Factors for Alzheimer's Disease.

The COVID-19 pandemic has been met with studies on risk factors, characteristics, and clinical course. Among these characteristics are neurologic symptoms, which may provide improved insight into the mechanisms of this novel virus and the brain's susceptibility to infectious diseases. This article aims to discuss 1) findings related to neurologic complications, 2) how they connect to and are bidirectionally impacted by bioimmunology, 3) how this combination of biological mechanisms impact and are impacted by psychosocial stressors, and 4) the importance of considering potential neurodegenerative consequences of COVID-19. Longitudinal studies on neuropathology and cognition are critical to avoiding premature conclusions related to long-term neurologic effects.

What lies ahead: Elevated concerns for the ongoing suicide pandemic.

The genesis and global spread of coronavirus disease 2019 (COVID-19) has resulted in significant health concerns amid societies that were ill-equipped for such a formidable opponent. The COVID-19 pandemic has illuminated systemic health disparities and weaknesses within our health care and political systems. With aggressive but necessary interventions to thwart the instantaneous reproduction number, we have simultaneously introduced risk factors for new and exacerbated mental health concerns. Suicide, an ongoing pandemic whose rates are higher than they have been in the past 50 years, is one of these concerns as we navigate COVID-19 deaths and fears surrounding its spread. This article aims to briefly describe in retrospect some of the historical pandemics and their downstream consequences as well as present what may lie ahead in terms of anxiety, depression, and suicidal behaviors. This applies not only to frontline health care workers but also the public at large, who may very well experience long-term stressor- and trauma-related consequences through ongoing exposure to a virus that is not only potentially fatal but may have taken the lives of loved ones. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Unintentional injury fatalities in the context of rising U.S. suicide rates: A five-year review of the web-based injury statistics query and reporting system.

This archival study focuses specifically on suicide fatalities in relation to unintentional and undetermined injury fatalities in an effort to determine whether or not these rates are rising consistently. This question may serve to inform whether or not suicides are being accurately reported and documented. Data from all 50 states from the years 2012-2016 were obtained from the Web-based Injury Statistics Query and Reporting System (WISQARS) developed by the Centers for Disease Control and Prevention. A total of 213,726 suicide fatalities, 702,176 unintentional injury fatalities, and 24,533 undetermined injury fatalities comprised the dataset. Injury fatality rates depicted annual increases in both suicide and unintentional injury fatalities but variability in undetermined injury fatalities. Bivariate analyses discovered a statistically significant association between annual suicide fatality rates and unintentional (nonsuicidal) injury fatality rates. It would be suspected, ceteris paribus, that calculated rate changes over these years would follow suit. However, this was not observed. Given the trends and increasing stigma surrounding suicide, it is worth considering the degree to which suicides may be underreported or -documented and the epidemiological and translational ramifications of these trends as they pertain to future suicide research.

Etiopathogenesis of Suicide: A Conceptual Analysis of Risk and Prevention Within a Comprehensive, Deterministic Model.

Suicide is a rising global health concern receiving disproportionate attention in comparison to other health conditions. In spite of substantial technological and scientific advancements, suicide research has continued to move slowly in terms of clinical translation due to the complexity of neural mechanisms, and subjective experiences that seem to underpin this complex human behavior. This paper analyzes the concepts of risk and prevention in the context of suicide in an attempt to bridge the large methodological and theoretical gaps between the biological, psychological, and sociological dimensions. This paper aims to accomplish the following objectives: (1) operationalize the concepts of suicide risk and prevention as they relate to current knowledge and capabilities; (2) synthesize and integrate suicide research across biological, psychological, and sociological dimensions; (3) discuss limitations of each dimension in isolation; (4) suggest a model of etiopathogenesis that incorporates extant literature and bridges unnecessary gaps between dimensions; and (5) suggest future directions for multidimensional research through the inclusion of principles from the physical sciences. Ultimately, this paper provides a basis for a comprehensive model of suicide within a deterministic, chaotic system.

Serotonergic system, cognition, and BPSD in Alzheimer's disease.

Behavioral and Psychological Symptoms of Dementia (BPSD), present in almost 90% of patients with Alzheimer's Disease (AD), cause extensive impairment leading to reduced independence and inability to complete activities of daily living. Though BPSD includes a wide range of symptoms, such as agitation, aggression, disinhibition, anxiety, depression, apathy, delusions, and hallucinations. Certain BPSD in AD co-present and can be clustered into distinct domains based on their frequency of co-occurrence. As these BPSD are so pervasive in any stages of AD, the disease may be better characterized as a disorder of heterogeneous degenerative symptoms across a number of symptom domains, with the most prominent domain comprising memory and cognitive deficits. Importantly, there are no FDA-approved drugs to treat these BPSD, and new approaches must be considered to develop effective treatments for AD patients. The biogenic monoamine 5-hydroxytryptamine (5-HT), or serotonin, works as both a neurotransmitter and neuromodulator, which has been tied to cognitive decline and multiple BPSD domains. This review summarizes the evidence for specific serotonergic system alterations across some of the well-studied cognitive, behavioral, and psychiatric domains. Though differences in overall serotonergic transmission occur in AD, circuit-specific alterations in individual 5-HT receptors (5-HTRs) are likely linked to the heterogeneous presentation of BPSD in AD.

Does functional homogenization accompany taxonomic homogenization of British birds and how do biotic factors and climate affect these processes?

Environmental change has reshuffled communities often causing taxonomic homogenization rather than differentiation. Some studies suggest that this increasing similarity of species composition between communities is accompanied by an increase in similarity of trait composition-functional homogenization-although different methodologies have failed to come to any consistent conclusions. Functional homogenization could have a large effect on ecosystem functioning and stability. Here, we use the general definition of homogenization as "reduced spatial turnover over time" to compare changes in Simpson's beta diversity (taxonomic turnover) with changes in Rao's quadratic entropy beta diversity (functional turnover) in British breeding birds at three spatial scales. Using biotic and climatic variables, we identify which factors may predispose a site to homogenization. The change in turnover measures between two time periods, 20 years apart, was calculated. A null model approach was taken to identify occurrences of functional homogenization and differentiation independent of changes in taxonomic turnover. We used conditional autoregressive models fitted using integrated nested Laplace approximations to determine how environmental drivers and factors relating to species distributions affect changes in spatial turnover of species and functional diversity. The measurement of functional homogenization affects the chance of rejection of the null models, with many sites showing taxonomic homogenization unaccompanied by functional homogenization, although occurrence varies with spatial scale. At the smallest scale, while temperature-related variables drive changes in taxonomic turnover, changes in functional turnover are associated with variation in growing degree days; however, changes in functional turnover become more difficult to predict at larger spatial scales. Our results highlight the multifactorial processes underlying taxonomic and functional homogenization and that redundancy in species traits may allow ecosystem functioning to be maintained in some areas despite changes in species composition.

Contribution of local rarity and climatic suitability to local extinction and colonization varies with species traits.

Changes in species distributions through local extinction and colonization events are a major consequence of climate change. The mechanisms underlying these processes, however, are yet to be fully understood. We investigate the effects of climatic suitability and local rarity on local extinction and colonization of British birds. We test the hypothesis that local extinction and colonization on decadal scales are driven by both climatic suitability and the prevalence of the species within an area and that the balance between these two is affected by species traits. We use spatially explicit conditional autoregressive models to determine the effect size of local rarity and climatic suitability (extracted from climate envelope models) on local extinction and colonization events. We then use phylogenetically constrained, generalized least-square models to estimate the association of extinction and colonization predictors with body mass, clutch size and national range of each species. Both local rarity and climatic suitability of an area contributed to local extinctions and colonizations, but the importance of these predictors varied between species. This interspecific variation was explained, in part, by species traits, in particular national range, which influenced the importance of local rarity and climatic suitability to both local extinction and colonization. These results further our knowledge of the mechanisms underlying changes in species occupancy due to climate change. This can inform predictive models as well as contribute to more focussed avian conservation efforts.

Temperature rise and parasitic infection interact to increase the impact of an invasive species.

Invasive species often detrimentally impact native biota, e.g. through predation, but predicting such impacts is difficult due to multiple and perhaps interacting abiotic and biotic context dependencies. Higher mean and peak temperatures, together with parasites, might influence the impact of predatory invasive host species additively, synergistically or antagonistically. Here, we apply the comparative functional response methodology (relationship between resource consumption rate and resource supply) in one experiment and conduct a second scaled-up mesocosm experiment to assess any differential predatory impacts of the freshwater invasive amphipod Gammarus pulex, when uninfected and infected with the acanthocephalan Echinorhynchus truttae, at three temperatures representative of current and future climate. Individual G. pulex showed Type II predatory functional responses. In both experiments, infection was associated with higher maximum feeding rates, which also increased with increasing temperatures. Additionally, infection interacted with higher temperatures to synergistically elevate functional responses and feeding rates. Parasitic infection also generally increased Q10 values. We thus suggest that the differential metabolic responses of the host and parasite to increasing temperatures drives the synergy between infection and temperature, elevating feeding rates and thus enhancing the ecological impact of the invader.

Species composition of coastal dune vegetation in Scotland has proved resistant to climate change over a third of a century.

Climate change is expected to have an impact on plant communities as increased temperatures are expected to drive individual species' distributions polewards. The results of a revisitation study after c. 34 years of 89 coastal sites in Scotland, UK, were examined to assess the degree of shifts in species composition that could be accounted for by climate change. There was little evidence for either species retreat northwards or for plots to become more dominated by species with a more southern distribution. At a few sites where significant change occurred, the changes were accounted for by the invasion, or in one instance the removal, of woody species. Also, the vegetation types that showed the most sensitivity to change were all early successional types and changes were primarily the result of succession rather than climate-driven changes. Dune vegetation appears resistant to climate change impacts on the vegetation, either as the vegetation is inherently resistant to change, management prevents increased dominance of more southerly species or because of dispersal limitation to geographically isolated sites.

Protected area networks and savannah bird biodiversity in the face of climate change and land degradation.

The extent to which climate change might diminish the efficacy of protected areas is one of the most pressing conservation questions. Many projections suggest that climate-driven species distribution shifts will leave protected areas impoverished and species inadequately protected while other evidence suggests that intact ecosystems within protected areas will be resilient to change. Here, we tackle this problem empirically. We show how recent changes in distribution of 139 Tanzanian savannah bird species are linked to climate change, protected area status and land degradation. We provide the first evidence of climate-driven range shifts for an African bird community. Our results suggest that the continued maintenance of existing protected areas is an appropriate conservation response to the challenge of climate and environmental change.

Incorporating uncertainty in predictive species distribution modelling.

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

Trait assembly in plant assemblages and its modulation by productivity and disturbance.

Understanding how communities assemble is a key challenge in ecology. Conflicting hypotheses suggest that plant traits within communities should show divergence to reflect strategies to reduce competition or convergence to reflect strong selection for the environmental conditions operating. Further hypotheses suggest that plant traits related to productivity show convergence within communities, but those related to disturbance show divergence. Data on functional diversity (FD(var)) of 12 traits from 30 communities ranging from arable fields, mown and grazed grasslands to moorland and woodland were employed to test this using randomisations tests and correlation and regression analysis. No traits showed consistent significant convergence or divergence in functional diversity. When correlated to measures of the environment, the most common pattern was for functional diversity to decline (7 out of 12 traits) and the degree of convergence (7 out of 12 traits) to increase as the levels of productivity (measured as primary productivity, soil nitrogen release and vegetation C:N) and disturbance increased. Convergence or a relationship between functional diversity and the environment was not seen for a number of important traits, such as LDMC and SLA, which are considered as key predictors of ecosystem function. The analysis indicates that taking into account functional diversity within a system may be a necessary part of predicting the relationship between plant traits and ecosystem function, and that this may be of particular importance within less productive and less disturbed systems.

Spatial and temporal ecology of Scots pine ectomycorrhizas.

Spatial analysis was used to explore the distribution of individual species in an ectomycorrhizal (ECM) fungal community to address: whether mycorrhizas of individual ECM fungal species were patchily distributed, and at what scale; and what the causes of this patchiness might be. Ectomycorrhizas were extracted from spatially explicit samples of the surface organic horizons of a pine plantation. The number of mycorrhizas of each ECM fungal species was recorded using morphotyping combined with internal transcribed spacer (ITS) sequencing. Semivariograms, kriging and cluster analyses were used to determine both the extent and scale of spatial autocorrelation in species abundances, potential interactions between species, and change over time. The mycorrhizas of some, but not all, ECM fungal species were patchily distributed and the size of patches differed between species. The relative abundance of individual ECM fungal species and the position of patches of ectomycorrhizas changed between years. Spatial and temporal analysis revealed a dynamic ECM fungal community with many interspecific interactions taking place, despite the homogeneity of the host community. The spatial pattern of mycorrhizas was influenced by the underlying distribution of fine roots, but local root density was in turn influenced by the presence of specific fungal species.

Regression analysis of spatial data.

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.