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Abstract Wildlife tagging provides critical insights into animal movement ecology, physiology, and behavior amid global ecosystem changes. However, the stress induced by capture, handling, and tagging can impact post-release locomotion and activity and, consequently, the interpretation of study results. Here, we analyze post-tagging effects on 1585 individuals of 42 terrestrial mammal species using collar-collected GPS and accelerometer data. Species-specific displacements and overall dynamic body acceleration, as a proxy for activity, were assessed over 20 days post-release to quantify disturbance intensity, recovery duration, and speed. Differences were evaluated, considering species-specific traits and the human footprint of the study region. Over 70% of the analyzed species exhibited significant behavioral changes following collaring events. Herbivores traveled farther with variable activity reactions, while omnivores and carnivores were initially less active and mobile. Recovery duration proved brief, with alterations diminishing within 4–7 tracking days for most species. Herbivores, particularly males, showed quicker displacement recovery (4 days) but slower activity recovery (7 days). Individuals in high human footprint areas displayed faster recovery, indicating adaptation to human disturbance. Our findings emphasize the necessity of extending tracking periods beyond 1 week and particular caution in remote study areas or herbivore-focused research, specifically in smaller mammals.

Abstract Comparative genomics has revealed the rapid expansion of multiple gene families involved in immunity. Members within each gene family often evolved distinct roles in immunity. However, less is known about the evolution of their epigenome and cis-regulation. Here we systematically profile the epigenome of the recently expanded murine Ly49 gene family that mainly encode either inhibitory or activating surface receptors on natural killer cells. We identify a set of cis-regulatory elements (CREs) for activating Ly49 genes. In addition, we show that in mice, inhibitory and activating Ly49 genes are regulated by two separate sets of proximal CREs, likely resulting from lineage-specific losses of CRE activity. Furthermore, we find that some Ly49 genes are cross-regulated by the CREs of other Ly49 genes, suggesting that the Ly49 family has begun to evolve a concerted cis-regulatory mechanism. Collectively, we demonstrate the different modes of cis-regulatory evolution for a rapidly expanding gene family.

Melancholia represents a particular subtype of depressive symptomatology. Unlike Major Depressive Disorder (MDD), Melancholia has not been conclusively associated with peripheral inflammation, although there may be some methodological reasons confounding that finding. To overcome some of those methodological limitations, the correlation between one index of peripheral inflammation (C-Reactive Protein: CRP) and Melancholia was investigated in a community sample of 40 male and 51 female participants (aged 18–75 years) who provided a blood sample and self-report data on an established measure of Melancholia (MEL). Results indicated that females had significantly higher concentrations of CRP than males, and that there were different patterns of association between the MEL items and CRP for males and females. Although the predominant differences were for the MEL symptoms of cognitive confusion (females only) and feelings of low self-worth (males only), each sex had distinct networks of associations between CRP and the eight MEL items used here. These findings may provide some explanation of the lack of clear results regarding the CRP-Melancholia link in the previous literature, and also argue for development of clinical assessment and treatment approaches that differ for males and females.

Abstract Infections in early life can elicit substantially different immune responses and pathogenesis than infections in adulthood. Here, we investigate the consequences of murine cytomegalovirus infection in newborn mice on NK cells. We show that infection severely compromised NK cell maturation and functionality in newborns. This effect was not due to compromised virus control. Inflammatory responses to infection dysregulated the expression of major transcription factors governing NK cell fate, such as Eomes, resulting in impaired NK cell function. Most prominently, NK cells from perinatally infected mice have a diminished ability to produce IFN-γ due to the downregulation of long non-coding RNA Ifng-as1 expression. Moreover, the bone marrow’s capacity to efficiently generate new NK cells is reduced, explaining the prolonged negative effects of perinatal infection on NK cells. This study demonstrates that viral infections in early life can profoundly impact NK cell biology, including long-lasting impairment in NK cell functionality.

The genus Colletotrichum includes nine major clades with 252 species and 15 major phylogenetic lineages, also known as species complexes. Colletotrichum spp. are one of the top fungal plant pathogens causing anthracnose and pre- and postharvest fruit rots worldwide. Apple orchards are imperiled by devastating losses from apple bitter rot, ranging from 24 to 98%, which is a serious disease caused by several Colletotrichum species. Bitter rot is also a major postharvest rot disease, with C. fioriniae causing from 2 to 14% of unmarketable fruit in commercial apple storages. Dominant species causing apple bitter rot in the Mid-Atlantic United States are C. fioriniae from the Colletotrichum acutatum species complex and C. chrysophilum and C. noveboracense from the C. gloeosporioides species complex (CGSC). C. fioriniae is the dominant species causing apple bitter rot in the Northeastern and Mid-Atlantic states. C. chrysophilum was first identified on banana and cashew but has been recently found as the second most dominant species causing apple bitter rot in the Mid-Atlantic. As the third most dominant pathogen, C. noveboracense MB 836581 was identified as a novel species in the CGSC, causing apple bitter rot in the Mid-Atlantic. C. nupharicola is a sister group to C. fructicola and C. noveboracense, also causing bitter rot on apple. We deliver the resources of 10 new genomes, including two isolates of C. fioriniae, three isolates of C. chrysophilum, three isolates of C. noveboracense, and two isolates of C. nupharicola collected from apple fruit, yellow waterlily, and Juglans nigra. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Abstract Remote aerial sensing provides a non‐invasive, large geographical‐scale technology for avian monitoring, but the manual processing of images limits its development and applications. Artificial Intelligence (AI) methods can be used to mitigate this manual image processing requirement. The implementation of AI methods, however, has several challenges: (1) imbalanced (i.e., long‐tailed) data distribution, (2) annotation uncertainty in categorization, and (3) dataset discrepancies across different study sites. Here we use aerial imagery data of waterbirds around Cape Cod and Lake Michigan in the United States to examine how these challenges limit avian recognition performance. We review existing solutions and demonstrate as use cases how methods like Label Distribution Aware Marginal Loss with Deferred Re‐Weighting, hierarchical classification, and FixMatch address the three challenges. We also present a new approach to tackle the annotation uncertainty challenge using a Soft‐fine Pseudo‐Label methodology. Finally, we aim with this paper to increase awareness in the ecological remote sensing community of these challenges and bridge the gap between ecological applications and state‐of‐the‐art computer science, thereby opening new doors to future research.

The bitter rot of apple is caused by Colletotrichum spp. and is a serious pre-harvest disease that can manifest in postharvest losses on harvested fruit. In this study, we obtained genome sequences from four different species, C. chrysophilum, C. noveboracense, C. nupharicola, and C. fioriniae, that infect apple and cause diseases on other fruits, vegetables, and flowers. Our genomic data were obtained from isolates/species that have not yet been sequenced and represent geographic-specific regions. Genome sequencing allowed for the construction of phylogenetic trees, which corroborated the overall concordance observed in prior MLST studies. Bioinformatic pipelines were used to discover CAZyme, effector, and secondary metabolic (SM) gene clusters in all nine Colletotrichum isolates. We found redundancy and a high level of similarity across species regarding CAZyme classes and predicted cytoplastic and apoplastic effectors. SM gene clusters displayed the most diversity in type and the most common cluster was one that encodes genes involved in the production of alternapyrone. Our study provides a solid platform to identify targets for functional studies that underpin pathogenicity, virulence, and/or quiescence that can be targeted for the development of new control strategies. With these new genomics resources, exploration via omics-based technologies using these isolates will help ascertain the biological underpinnings of their widespread success and observed geographic dominance in specific areas throughout the country.

Penicillium spp. occupy many diverse biological niches that include plant pathogens, opportunistic human pathogens, saprophytes, indoor air contaminants, and those selected specifically for industrial applications to produce secondary metabolites and lifesaving antibiotics. Recent phylogenetic studies have established Penicillium fuscoglaucum as a synonym for Penicillium commune, which is an indoor air contaminant and toxin producer and can infect apple fruit during storage. During routine culturing on selective media in the lab, we obtained an isolate of P. fuscoglaucum Pf_T2 and sequenced its genome. The Pf_T2 genome is far superior to available genomic resources for the species. Our assembly exhibits a length of 35.1 Mb, a BUSCO score of 97.9% complete, and consists of five scaffolds/contigs representing the four expected chromosomes. It was determined that the Pf_T2 genome was colinear with a type specimen P. fuscoglaucum and contained a lineage-specific, intact cyclopiazonic acid (CPA) gene cluster. For comparison, a highly virulent postharvest apple pathogen, P. expansum strain TDL 12.1, was included and showed a similar growth pattern in culture to our Pf_T2 isolate but was far more aggressive in apple fruit than P. fuscoglaucum. The genome of Pf_T2 serves as a major improvement over existing resources, has superior annotation, and can inform forthcoming omics-based work and functional genetic studies to probe secondary metabolite production and disparities in aggressiveness during apple fruit decay.

Abstract Background The distribution of resources can affect animal range sizes, which in turn may alter infectious disease dynamics in heterogenous environments. The risk of pathogen exposure or the spatial extent of outbreaks may vary with host range size. This study examined the range sizes of herbivorous anthrax host species in two ecosystems and relationships between spatial movement behavior and patterns of disease outbreaks for a multi-host environmentally transmitted pathogen. Methods We examined range sizes for seven host species and the spatial extent of anthrax outbreaks in Etosha National Park, Namibia and Kruger National Park, South Africa, where the main host species and outbreak sizes differ. We evaluated host range sizes using the local convex hull method at different temporal scales, within-individual temporal range overlap, and relationships between ranging behavior and species contributions to anthrax cases in each park. We estimated the spatial extent of annual anthrax mortalities and evaluated whether the extent was correlated with case numbers of a given host species. Results Range size differences among species were not linearly related to anthrax case numbers. In Kruger the main host species had small range sizes and high range overlap, which may heighten exposure when outbreaks occur within their ranges. However, different patterns were observed in Etosha, where the main host species had large range sizes and relatively little overlap. The spatial extent of anthrax mortalities was similar between parks but less variable in Etosha than Kruger. In Kruger outbreaks varied from small local clusters to large areas and the spatial extent correlated with case numbers and species affected. Secondary host species contributed relatively few cases to outbreaks; however, for these species with large range sizes, case numbers positively correlated with outbreak extent. Conclusions Our results provide new information on the spatiotemporal structuring of ranging movements of anthrax host species in two ecosystems. The results linking anthrax dynamics to host space use are correlative, yet suggest that, though partial and proximate, host range size and overlap may be contributing factors in outbreak characteristics for environmentally transmitted pathogens.

Abstract Background Movement is central to understanding the ecology of animals. The most robustly definable segments of an individual’s lifetime track are its diel activity routines (DARs). This robustness is due to fixed start and end points set by a 24-h clock that depends on the individual’s quotidian schedule. An analysis of day-to-day variation in the DARs of individuals, their comparisons among individuals, and the questions that can be asked, particularly in the context of lunar and annual cycles, depends on the relocation frequency and spatial accuracy of movement data. Here we present methods for categorizing the geometry of DARs for high frequency (seconds to minutes) movement data. Methods Our method involves an initial categorization of DARs using data pooled across all individuals. We approached this categorization using a Ward clustering algorithm that employs four scalar “whole-path metrics” of trajectory geometry: 1. net displacement (distance between start and end points), 2. maximum displacement from start point, 3. maximum diameter, and 4. maximum width. We illustrate the general approach using reverse-GPS data obtained from 44 barn owls, Tyto alba, in north-eastern Israel. We conducted a principle components analysis (PCA) to obtain a factor, PC1, that essentially captures the scale of movement. We then used a generalized linear mixed model with PC1 as the dependent variable to assess the effects of age and sex on movement. Results We clustered 6230 individual DARs into 7 categories representing different shapes and scale of the owls nightly routines. Five categories based on size and elongation were classified as closed (i.e. returning to the same roost), one as partially open (returning to a nearby roost) and one as fully open (leaving for another region). Our PCA revealed that the DAR scale factor, PC1, accounted for 86.5% of the existing variation. It also showed that PC2 captures the openness of the DAR and accounted for another 8.4% of the variation. We also constructed spatio-temporal distributions of DAR types for individuals and groups of individuals aggregated by age, sex, and seasonal quadrimester, as well as identify some idiosyncratic behavior of individuals within family groups in relation to location. Finally, we showed in two ways that DARs were significantly larger in young than adults and in males than females. Conclusion Our study offers a new method for using high-frequency movement data to classify animal diel movement routines. Insights into the types and distributions of the geometric shape and size of DARs in populations may well prove to be more invaluable for predicting the space-use response of individuals and populations to climate and land-use changes than other currently used movement track methods of analysis.

Abstract Human stroke serum (HSS) has been shown to impair cerebrovascular function, likely by factors released into the circulation after ischemia. 20 nm gold nanoparticles (GNPs) have demonstrated anti‐inflammatory properties, with evidence that they decrease pathologic markers of ischemic severity. Whether GNPs affect cerebrovascular function, and potentially protect against the damaging effects of HSS on the cerebral circulation remains unclear. HSS obtained 24 h poststroke was perfused through the lumen of isolated and pressurized third‐order posterior cerebral arteries (PCAs) from male Wistar rats with and without GNPs (~2 × 109 GNP/ml), or GNPs in vehicle, in an arteriograph chamber (n = 8/group). All vessels were myogenically reactive ≥60 mmHg intravascular pressure; however, vessels containing GNPs had significantly less myogenic tone. GNPs increased vasoreactivity to small and intermediate conductance calcium activated potassium channel activation via NS309; however, reduced vasoconstriction to nitric oxide synthase inhibition. Hydraulic conductivity and transvascular filtration, were decreased by GNPs, suggesting a protective effect on the blood–brain barrier. The stress–strain curves of PCAs exposed to GNPs were shifted leftward, indicating increased vessel stiffness. This study provides the first evidence that GNPs affect the structure and function of the cerebrovasculature, which may be important for their development and use in biomedical applications.

PATHMAP (Pathogen And Tree fruit Health MAP) is a smartphone application (app) and interactive dashboard developed specifically for support specialists, extension personnel, and university scientists supporting the tree fruit industry. The PATHMAP app collects detailed information about observed diseases, insect pests, and disorders and provides the option to attach photos. The data are then visualized using a graphical interface dashboard displaying an interactive color-coded map. Prior to the development of PATHMAP, abundant tree fruit disorder data were collected each year, but a central interactive repository for archiving data and facilitating communication of field observations did not exist. PATHMAP has been beta tested by university extension personnel, private consultants, and university scientists to ensure usability and functionality. PATHMAP will be used within the tree fruit industry for monitoring known pest patterns, occurrences, and outbreaks of emerging pathogens. It will augment existing extension diagnosis listservs that have value in visual diagnosis but are cumbersome and have no archiving capabilities. Data obtained through the tool can be used in epidemiological meta-analyses and to develop new predictive models, and can serve as a platform to track emerging pathogens, insects, and disorders for a variety of cropping systems. [Graphic: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2022.

Abstract Migration is one of the most physical and energetically demanding periods in an individual bird’s life. The composition of the bird’s gut or cloacal microbiota can temporarily change during migration, likely due to differences in diets, habitats and other environmental conditions experienced en route. However, how physiological condition, migratory patterns, and other drivers interact to affect microbiota composition of migratory birds is still unclear. We sampled the cloacal bacterial microbiota of a long-distance migrant, the steppe buzzard (Buteo buteo vulpinus), at an important spring stopover bottleneck in Eilat, Israel, after crossing the ca. 1800 km Sahara Desert. We examined whether diversity and composition of the cloacal microbiota varied with body condition, sex, movement patterns (i.e., arrival time and migration distance), and survival. Early arrival to Eilat was associated with better body condition, longer post-Eilat spring migration distance, higher microbial α-diversity, and differences in microbiota composition. Specifically, early arrivals had higher abundance of the phylum Synergistota and five genera, including Jonquetella and Peptococcus, whereas the phylum Proteobacteria and genus Escherichia-Shigella (as well as three other genera) were more abundant in later arrivals. While the differences in α-diversity and Escherichia-Shigella seem to be mainly driven by body condition, other compositional differences associated with arrival date could be indicators of longer migratory journeys (e.g., pre-fueling at wintering grounds or stopover habitats along the way) or migratory performance. No significant differences were found between the microbiota of surviving and non-surviving individuals. Overall, our results indicate that variation in steppe buzzard microbiota is linked to variation in migratory patterns (i.e., capture/arrival date) and body condition, highlighting the importance of sampling the microbiota of GPS-tracked individuals on multiple occasions along their migration routes to gain a more detailed understanding of the links between migration, microbiota, and health in birds.

Abstract This paper lays out a hierarchical, appropriate-complexity framework for conceptualizing movement-path segments at different spatiotemporal scales in a way that facilitates comparative analyses and bridges behavior and mathematical concepts. It then outlines a process for generating a multimode, multiscale stochastic simulation model that can be used to test animal movement hypotheses and make predictions of movement responses to management and global change. Many methods for analyzing movement data begin by generating step-length (SL) and turning-angle (TA) distributions from relocation time-series data, some of which are linked to ecological, landscape, and environmental covariates. The frequency at which these data are collected may vary from sub-seconds to several hours. The kinds of questions that may be asked of these data, however, are very much scale dependent. The hierarchical path-segmentation (HPS) framework presented here clarifies how the scale at which SL and TA data are collected relates to other sub- and super-diel scales. Difficulties arise because the information contained in SL and TA time series are often not directly relatable to the physiological, ecological, and sociological factors that drive the structure of movement paths at longer scales. These difficulties are overcome by anchoring the classification of movement types around the concept of fixed-period (24 h) diel activity routines and providing a bridge between behavioral/ecological and stochastic-walk concepts (means, variances, correlations, individual-state and local environmental covariates). This bridge is achieved through the generation of relatively short segments conceived as characteristic sequences of fundamental movement elements. These short segments are then used to characterize longer canonical-activity-mode segments that emerge through movement at behaviorally relevant sub-diel scales. HPS thus provides a novel system for integrating sub-minute movement sequences into canonical activity modes (CAMs) that, in turn, can be strung together into various types of diel activity routines (DARs). These DARs both vary among individuals within a given day, and for any given individual across time and under the influence of landscape factors. An understanding of how DARs are influenced by environmental inputs will help us predict the response of supra-diel lifetime movement phases (LiMPs) of individuals, as well as their complete lifetime tracks (LiTs), to anthropogenically induced global change.

Abstract Background An understanding of epidemiological dynamics, once confined to mathematical epidemiologists and applied mathematicians, can be disseminated to a non-mathematical community of health care professionals and applied biologists through simple-to-use simulation applications. We used Numerus Model Builder RAMP Ⓡ (Runtime Alterable Model Platform) technology, to construct deterministic and stochastic versions of compartmental SIR (Susceptible, Infectious, Recovered with immunity) models as simple-to-use, freely available, epidemic simulation application programs. Results We take the reader through simulations used to demonstrate the following concepts: 1) disease prevalence curves of unmitigated outbreaks have a single peak and result in epidemics that ‘burn’ through the population to become extinguished when the proportion of the susceptible population drops below a critical level; 2) if immunity in recovered individuals wanes sufficiently fast then the disease persists indefinitely as an endemic state, with possible dampening oscillations following the initial outbreak phase; 3) the steepness and initial peak of the prevalence curve are influenced by the basic reproductive value R 0, which must exceed 1 for an epidemic to occur; 4) the probability that a single infectious individual in a closed population (i.e. no migration) gives rise to an epidemic increases with the value of R 0>1; 5) behavior that adaptively decreases the contact rate among individuals with increasing prevalence has major effects on the prevalence curve including dramatic flattening of the prevalence curve along with the generation of multiple prevalence peaks; 6) the impacts of treatment are complicated to model because they effect multiple processes including transmission, recovery and mortality; 7) the impacts of vaccination policies, constrained by a fixed number of vaccination regimens and by the rate and timing of delivery, are crucially important to maximizing the ability of vaccination programs to reduce mortality. Conclusion Our presentation makes transparent the key assumptions underlying SIR epidemic models. Our RAMP simulators are meant to augment rather than replace classroom material when teaching epidemiological dynamics. They are sufficiently versatile to be used by students to address a range of research questions for term papers and even dissertations.

The methods used for predicting space use and geographic distribution adaptations of animals in response to global change have relied on fitting statistical and machine learning models to environmentally-contextualized movement and spatial distribution data. These predictions, however, are made at particular spatiotemporal scales (from home range to species distribution), but no comprehensive methods have been proposed for predicting how changes to subdiel segments of individual movement tracks may lead to emergent changes in the lifetime tracks of individuals, and hence in the redistribution of species under global change. In this article, we discuss in terms of a hierarchical movement track segmentation framework that, anchored by diel activity routines (DARs), how adaptions in the canonical activity modes (CAMs) of movement can be used to assess space use adaptations to landscape and climate change at scales ranging from subdiel movement segments to the lifetime tracks (LiTs) of individuals.

IntroductionAlthough depression is widespread carries a major disease burden, current treatments remain non-universally effective, arguably due to the heterogeneity of depression, and leading to the consideration of depressive “subtypes” or “depressive behavior subtypes.” One such model of depressive behavior (DB) subtypes was investigated for its associations with frontal lobe asymmetry (FLA), using a different data analytic procedure than in previous research in this field.Methods100 community volunteers (54 males, 46 females) aged between 18 yr. and 75 years (M = 32.53 yr., SD = 14.13 yr) completed the Zung Self-rating Depression Scale (SDS) and underwent 15 min of eyes closed EEG resting data collection across 10 frontal lobe sites. DB subtypes were defined on the basis of previous research using the SDS, and alpha-wave (8-13 Hz) data produced an index of FLA. Data were examined via network analysis.ResultsSeveral network analyses were conducted, producing two models of the association between DB subtypes and FLA, confirming unique neurophysiological profiles for each of the four DB subtypes.DiscussionAs well as providing a firm basis for using these DB subtypes in clinical settings, these findings provide a reasonable explanation for the inconsistency in previous FLA-depression research.

Although alpha asymmetry has been found to correlate with depression, there is some inconsistency across the wider literature, suggesting the influence of other factors. Some of these may be the presence of peripheral inflammation, age, and sex of participants. To test the interaction of these factors in terms of the association between alpha asymmetry and depression in a community sample, in this study, data were collected on resting frontal alpha asymmetry (FAA) under eyes closed and eyes open conditions, serum C-reactive protein (CRP), age, and self-rated depression in a sample of 44 males and 56 females aged from 18 to 75 years (M = 32.5 yr, SD = 14.1 yr). Using regression models, the results indicated a complex set of associations. FAA values across the FP2-FP1 sites predicted depression in the eyes open condition, but not for any other pairing of sites. Increases in CRP concentration predicted increases in depression for women but not for men. CRP predicted FAA across two frontal sites (F8-F7) under the eyes open condition only. As CRP increased, FAA favoured the left hemisphere for that pair of frontal sites, a result found more strongly for males. Age did not influence these associations. By reflecting a complex, multi-factor interaction, these findings may tentatively provide some explanation for the inconsistency in the wider literature for the FAA–depression hypothesis.

Blue mold, a postharvest disease of pome fruits, is caused by the filamentous fungus Penicillium expansum. In addition to the economic losses caused by P. expansum, food safety can be compromised, as this pathogen is mycotoxigenic. In this study, forward and reverse genetic approaches were used to identify genes involved in blue mold infection in apple fruits. For this, we generated a random T-DNA insertional mutant library. A total of 448 transformants were generated and screened for the reduced decay phenotype on apples. Of these mutants, six (T-193, T-275, T-434, T-588, T-625, and T-711) were selected for continued studies and five unique genes were identified of interest. In addition, two deletion mutants (Δt-625 and Δt-588) and a knockdown strain (t-434KD) were generated for three loci. Data show that the ∆t-588 mutant phenocopied the T-DNA insertion mutant and had virulence penalties during apple fruit decay. We hypothesize that this locus encodes a glyoxalase due to bioinformatic predictions, thus contributing to reduced colony diameter when grown in methylglyoxal (MG). This work presents novel members of signaling networks and additional genetic factors that regulate fungal virulence in the blue mold fungus during apple fruit decay.

Blue mold is an economically significant postharvest disease of pome fruit that is primarily caused by Penicillium expansum. To manage this disease and sustain product quality, novel decay intervention strategies are needed that also maintain long-term efficacy. Biocontrol organisms and natural products are promising tools for managing postharvest diseases. Here, two Penicillium chrysogenum isolates, 404 and 413, were investigated as potential biocontrol agents against P. expansum in apple. Notably, 404 and 413 were non-pathogenic in apple, yet they grew vigorously in vitro when compared to the highly aggressive P. expansum R19 and Pe21 isolates. Whole-genome sequencing and species-specific barcoding identified both strains as P. chrysogenum. Each P. chrysogenum strain was inoculated in apple with the subsequent co-inoculation of R19 or Pe21 simultaneously, 3, or 7 days after prior inoculation with 404 or 413. The co-inoculation of these isolates showed reduced decay incidence and severity, with the most significant reduction from the longer establishment of P. chrysogenum. In vitro growth showed no antagonism between species, further suggesting competitive niche colonization as the mode of action for decay reduction. Both P. chrysogenum isolates had incomplete patulin gene clusters but tolerated patulin treatment. Finally, hygromycin resistance was observed for both P. chrysogenum isolates, yet they are not multiresistant to apple postharvest fungicides. Overall, we demonstrate the translative potential of P. chrysogenum to serve as an effective biocontrol agent against blue mold decay in apples, pending practical optimization and formulation.

Abstract Movement behavior is an important contributor to habitat selection and its incorporation in disease risk models has been somewhat neglected. The habitat preferences of host individuals affect their probability of exposure to pathogens. If preference behavior can be incorporated in ecological niche models (ENMs) when data on pathogen distributions are available, then variation in such behavior may dramatically impact exposure risk. Here we use data from the anthrax endemic system of Etosha National Park, Namibia, to demonstrate how integrating inferred movement behavior alters the construction of disease risk maps. We used a Maximum Entropy (MaxEnt) model that associated soil, bioclimatic, and vegetation variables with the best available pathogen presence data collected at anthrax carcass sites to map areas of most likely Bacillus anthracis (the causative bacterium of anthrax) persistence. We then used a hidden Markov model (HMM) to distinguish foraging and non-foraging behavioral states along the movement tracks of nine zebra (Equus quagga) during the 2009 and 2010 anthrax seasons. The resulting tracks, decomposed on the basis of the inferred behavioral state, formed the basis of step-selection functions (SSFs) that used the MaxEnt output as a potential predictor variable. Our analyses revealed different risks of exposure during different zebra behavioral states, which were obscured when the full movement tracks were analyzed without consideration of the underlying behavioral states of individuals. Pathogen (or vector) distribution models may be misleading with regard to the actual risk faced by host animal populations when specific behavioral states are not explicitly accounted for in selection analyses. To more accurately evaluate exposure risk, especially in the case of environmentally transmitted pathogens, selection functions could be built for each identified behavioral state and then used to assess the comparative exposure risk across relevant states. The scale of data collection and analysis, however, introduces complexities and limitations for consideration when interpreting results.

Introduction Despitehigh rates ofrecanalizationafter mechanical thrombectomy(MT),only 33–71% of patients achieve functional independence at 90 days.Experimental ischemia hashighlightedthe complexity of several pathophysiological events occurring at the level of the neurovascular unit and has revealed potential targets for neuroprotection. Apossible target is to increasebloodflow in the collateral circulationwhile delivering high levels of oxygen in the ischemic area.Hemoglobin based oxygen carriers (HBOC) as a transfusion media that can treat ischemic tissue have been investigatedfor a decade. More recently, a polyethylene glycol modifiedHBOCin the carboxy state (PP‐007)increases blood flow in the collateral circulationinrat modelsof middle cerebral artery occlusion (MCAO).PP‐007 may deliver more oxygen than Hb contained in RBCs because of increased diffusional surface area in plasma, and by facilitation of oxygen transport from RBC to endothelium.In addition,dilation ofcollateral circulationby diffusion of CO mayslow down infarct expansion andimprove the efficacy of reperfusion. Methods HEMERA 1 is a phase 1 safety clinical trialof PP‐007 in patient with acute ischemic strokewith LVO (ClinicalTrials.gov NCT04677777). Inclusion criteria are patients with Intracranial ICA and/or MCA‐M1 or M2 occlusion,baseline NIHSS ≥ 6, Baseline ASPECTS score ≥ 5 on NCCT and/or Core Volumes 50mL on CT perfusion (CTP), time fromlast seen well to start ofPP‐007infusion ≤ 24 hours,pre‐MorbidmRS< 2, and ineligibility for intravenous thrombolysis. The trial plans to enroll approximately 16–20 subjectswith3:1 randomizationtoPP‐007 (320 mg/kg with 30 min bolus + 2‐hour infusion) plus MT versus MT alone. Results Tenpatients have been enrolled so far.Mean age was 76.1 (STD±11.6), ASPECT score = 7.8 (±1.8), NIHSS at baseline = 17.3 (±5.6),TICI 2b or c in 7, TICI 3 in 3. Seven patients were randomized PP‐007 and received the complete infusion. Two patients were randomized to standard of care (MT only) and1was randomized to PP‐007 but not treated.Three patients had elevation of Partial Prothrombin Time (PTT) after the PP‐007 infusion that however had no clinical consequences. Conclusions HEMERA 1 isphase 1 clinical trialcurrently enrolling patients.No safety concerns were identified so far.

Depression is associated with frontal alpha asymmetry (FAA) and Psychological Resilience (PR), although in different ways. Only cursory attention has been given to how these three constructs interact despite the possible clinical and research implications of those associations. One limitation of recent research into these associations has been conceptualising PR as a unitary construct, whereas it has been shown to be multi-component. This study investigated the underlying components of PR, their correlations with FAA, and the effect that participants’ depressive status had upon those correlations in a community sample of 54 males and 46 females aged between 18 yr and 75 years. Results confirmed the overall inverse association between total PR and depression for four of the original five PR components and for one of the two components found in this sample. Similarly, there were differences between the ways that FAA and PR components were associated, depending upon the depressive status of participants. Source localisation data indicated that the PR components were not uniformly correlated with alpha activity in the same brain regions. These findings of content, efficacy, and neurophysiological differences between the five components of PR and their associations with FAA argue against consideration of PR as a unitary construct.

A brief review of 50 studies from the last 10 years indicated that it is often accepted practice to apply log transformation processes to raw EEG data. This practice is based upon the assumptions that (a) EEG data do not resemble a normal distribution, (b) applying a transformation will produce an acceptably normal distribution, (c) the logarithmic transformation is the most valid form of transformation for these data, and (d) the statistical procedures intended to be used are not robust to non-normality. To test those assumptions, EEG data from 100 community participants were analysed for their normality by reference to their skewness and kurtosis, the Kolmogorov–Smirnov and Shapiro–Wilk statistics, and shapes of histograms. Where non-normality was observed, several transformations were applied, and the data again tested for normality to identify the most appropriate method. To test the effects of normalisation from all these processes, Pearson and Spearman correlations between the raw and normalised EEG alpha asymmetry data and depression were calculated to detect any variation in the significance of the resultant statistic.

Abstract Background The role of viral infection in Alzheimer Disease (AD) pathogenesis is an area of great interest in recent years. Several studies have suggested an association between the human roseoloviruses, HHV-6 and HHV-7, and AD. Amyloid-β (Aβ) plaques are a hallmark neuropathological finding of AD and were recently proposed to have an antimicrobial function in response to infection. Identifying a causative and mechanistic role of human roseoloviruses in AD has been confounded by limitations in performing in vivo studies. Recent -omics based approaches have demonstrated conflicting associations between human roseoloviruses and AD. Murine roseolovirus (MRV) is a natural murine pathogen that is highly-related to the human roseoloviruses, providing an opportunity to perform well-controlled studies of the impact of roseolovirus on Aβ deposition. Methods We utilized the 5XFAD mouse model to test whether MRV induces Aβ deposition in vivo. We also evaluated viral load and neuropathogenesis of MRV infection. To evaluate Aβ interaction with MRV, we performed electron microscopy. RNA-sequencing of a cohort of AD brains compared to control was used to investigate the association between human roseolovirus and AD. Results We found that 5XFAD mice were susceptible to MRV infection and developed neuroinflammation. Moreover, we demonstrated that Aβ interacts with viral particles in vitro and, subsequent to this interaction, can disrupt infection. Despite this, neither peripheral nor brain infection with MRV increased or accelerated Aβ plaque formation. Moreover, −omics based approaches have demonstrated conflicting associations between human roseoloviruses and AD. Our RNA-sequencing analysis of a cohort of AD brains compared to controls did not show an association between roseolovirus infection and AD. Conclusion Although MRV does infect the brain and cause transient neuroinflammation, our data do not support a role for murine or human roseoloviruses in the development of Aβ plaque formation and AD.

Pseudomonas aeruginosa causes a wide range of severe infections. Ceftazidime, a cephalosporin, is a key antibiotic for treating infections but a significant proportion of isolates are ceftazidime-resistant. The aim of this research was to identify mutations that contribute to resistance, and to quantify the impacts of individual mutations and mutation combinations. Thirty-five mutants with reduced susceptibility to ceftazidime were evolved from two antibiotic-sensitive P. aeruginosa reference strains PAO1 and PA14. Mutations were identified by whole genome sequencing. The evolved mutants tolerated ceftazidime at concentrations between 4 and 1000 times that of the parental bacteria, with most mutants being ceftazidime resistant (minimum inhibitory concentration [MIC] ≥ 32 mg/L). Many mutants were also resistant to meropenem, a carbapenem antibiotic. Twenty-eight genes were mutated in multiple mutants, with dacB and mpl being the most frequently mutated. Mutations in six key genes were engineered into the genome of strain PAO1 individually and in combinations. A dacB mutation by itself increased the ceftazidime MIC by 16-fold although the mutant bacteria remained ceftazidime sensitive (MIC < 32 mg/L). Mutations in ampC, mexR, nalC or nalD increased the MIC by 2- to 4-fold. The MIC of a dacB mutant was increased when combined with a mutation in ampC, rendering the bacteria resistant, whereas other mutation combinations did not increase the MIC above those of single mutants. To determine the clinical relevance of mutations identified through experimental evolution, 173 ceftazidime-resistant and 166 sensitive clinical isolates were analysed for the presence of sequence variants that likely alter function of resistance-associated genes. dacB and ampC sequence variants occur most frequently in both resistant and sensitive clinical isolates. Our findings quantify the individual and combinatorial effects of mutations in different genes on ceftazidime susceptibility and demonstrate that the genetic basis of ceftazidime resistance is complex and multifactorial.

Resource partitioning promotes coexistence among guild members, and carnivores reduce interference competition through behavioral mechanisms that promote spatio-temporal separation. We analyzed sympatric lion and spotted hyena movements and activity patterns to ascertain the mechanisms facilitating their coexistence within semi-arid and wetland ecosystems. We identified recurrent high-use (revisitation) and extended stay (duration) areas within home ranges, as well as correlated movement-derived measures of inter- and intraspecific interactions with environmental variables. Spatial overlaps among lions and hyenas expanded during the wet season, and occurred at edges of home ranges, around water-points, along pathways between patches of high-use areas. Lions shared more of their home ranges with spotted hyenas in arid ecosystems, but shared more of their ranges with conspecifics in mesic environments. Despite shared space use, we found evidence for subtle temporal differences in the nocturnal movement and activity patterns between the two predators, suggesting a fine localized-scale avoidance strategy. Revisitation frequency and duration within home ranges were influenced by interspecific interactions, after land cover categories and diel cycles. Intraspecific interactions were also important for lions and, important for hyenas were moon illumination and ungulates attracted to former anthrax carcass sites in Etosha, with distance to water in Chobe/Linyanti. Recursion and duration according to locales of competitor probabilities were similar among female lions and both sexes of hyenas, but different for male lions. Our results suggest that lions and spotted hyenas mediate the potential for interference competition through subtle differences in temporal activity, fine-scale habitat use differentiation, and localized reactive-avoidance behaviors. These findings enhance our understanding of the potential effects of interspecific interactions among large carnivore space-use patterns within an apex predator system and show adaptability across heterogeneous and homogeneous environments. Future conservation plans should emphasize the importance of inter- and intraspecific competition within large carnivore communities, particularly moderating such effects within increasingly fragmented landscapes.

Abstract Anguillid eel populations have declined dramatically over the last 50 years in many regions of the world, and numerous species are now under threat. A critical life-history phase is migration from freshwater to distant oceans, culminating in a single life-time spawning event. For many anguillids, especially those in the southern hemisphere, mystery still shrouds their oceanic spawning migrations. We investigated the oceanic spawning migrations of the Australasian short-finned eel (Anguilla australis) using pop-up satellite archival tags. Eels were collected from river estuaries (38° S, 142° E) in south-eastern temperate Australia. In 2019, 16 eels were tracked for up to about 5 months, ~ 2620 km from release, and as far north as the tropical Coral Sea (22° S, 155° E) off the north-east coast of Australia. Eels from southern Australia appeared to access deep water off the Australian coast via two main routes: (i) directly east via Bass Strait, or (ii) south-east around Tasmania, which is the shortest route to deep water. Tagged eels exhibited strong diel vertical migrations, alternating between the warm euphotic zone (~ 100–300 m, 15–20 °C) at night and the mesopelagic zone (~ 700–900 m, 6–8 °C) during the day. Marine predators, probably lamnid sharks, tuna, or marine mammals, ended many eel migrations (at least ~ 30%), largely before the eels had left the Australian continental shelf. The long and risky marine migrations of Australasian eels highlight the need for better information on the processes contributing to eel mortality throughout the life cycle, including the impacts of future changes to oceanic currents, predator abundance and direct anthropogenic disturbances.

The role of NK cells against HIV-1 infections remains to be elucidated in vivo. While humanized mouse models potentially could be used to directly evaluate human NK cell responses during HIV-1 infection, improved functional development of human NK cells in these hosts is needed. Here, we report the humanized MISTRG-6-15 mouse model, in which NK cells were quick to expand and exhibit degranulation, cytotoxicity, and proinflammatory cytokine production in nonlymphoid organs upon HIV-1 infection but had reduced functionality in lymphoid organs. Although HIV-1 infection induced functional impairment of NK cells, antiretroviral therapy reinvigorated NK cells in response to HIV-1 rebound after analytic treatment interruption. Moreover, a broadly neutralizing antibody, PGT121, enhanced NK cell function in vivo, consistent with antibody-dependent cellular cytotoxicity. Monoclonal antibody depletion of NK cells resulted in higher viral loads in multiple nonlymphoid organs. Overall, our results in humanized MISTRG-6-15 mice demonstrated that NK cells provided direct anti–HIV-1 responses in vivo but were limited in their responses in lymphoid organs.

We investigated the initial outbreak rates and subsequent social distancing behaviour over the initial phase of the COVID-19 pandemic across 29 Combined Statistical Areas (CSAs) of the United States. We used the Numerus Model Builder Data and Simulation Analysis (NMB-DASA) web application to fit the exponential phase of a SCLAIV+D (Susceptible, Contact, Latent, Asymptomatic infectious, symptomatic Infectious, Vaccinated, Dead) disease classes model to outbreaks, thereby allowing us to obtain an estimate of the basic reproductive number R0 for each CSA. Values of R0 ranged from 1.9 to 9.4, with a mean and standard deviation of 4.5±1.8. Fixing the parameters from the exponential fit, we again used NMB-DASA to estimate a set of social distancing behaviour parameters to compute an epidemic flattening index cflatten. Finally, we applied hierarchical clustering methods using this index to divide CSA outbreaks into two clusters: those presenting a social distancing response that was either weaker or stronger. We found cflatten to be more influential in the clustering process than R0. Thus, our results suggest that the behavioural response after a short initial exponential growth phase is likely to be more determinative of the rise of an epidemic than R0 itself.

Ecological responses to changing riverine flows are often evaluated by describing the relationship between river discharge and response. However, aquatic organisms experience the hydraulics (i.e. velocity, shear stress, depth) of a river, not its discharge. Hydraulic characterizations of riverine habitats may improve our ability to predict ecological responses. We used two-dimensional hydraulic models to translate river discharge into flow velocity. We used discharge and reach-averaged velocity, along with water temperature and 8 years of field observations of fish spawning, to develop predictive models of the spawning of golden perch (Macquaria ambigua) in the Goulburn River, south-east Australia. Probability of spawning was positively related to both discharge and reach-averaged velocity. Water temperature was critical for enabling the flow response, and antecedent flows prior to spawning had a weak positive effect. Against expectations, there was little difference in predictive uncertainty for the effect of flows when reach-averaged velocity was used as the main predictor rather than discharge. The lower Goulburn River has a relatively simple channel and so discharge and velocity are monotonically related over most flows. We expect that in a more geomorphically complex environment, improvement in predictive ability would be substantial. This research only explores one example of a hydraulic parameter being used as a predictor of ecological response; many others are possible. The extra effort and expense involved in hydraulic characterization of river flows is only justified if our understanding of flow-ecology relationships is substantially improved. Further research to understand which environmental responses might be best understood through different hydraulic parameters, and how to better characterize hydraulic characteristics relevant to riverine biota, would help inform decisions regarding investment in hydraulic models. Regardless, hydraulics offers a more process-based assessment of ecological responses to changing flows, has the potential to facilitate mechanistic understanding rather than just associations, and provides the opportunity to translate hydraulic metrics that drive ecological responses across river systems of differing sizes. However, while considering ecological responses in terms of river hydraulics is more physically realistic, our results suggest that average hydraulic conditions may not result in an improved ability to predict the effects of changing flows.

Human cytomegalovirus (HCMV) infections develop into CMV diseases that result in various forms of manifestations in local organs. CMV-retinitis is a form of CMV disease that develops in immunocompromised hosts with CMV-viremia after viruses in the peripheral circulation have entered the eye. In the HCMV genome, extensive diversification of the UL40 gene has produced peptide sequences that modulate NK cell effector functions when loaded onto HLA-E and are subsequently recognized by the NKG2A and NKG2C receptors. Notably, some HCMV strains carry UL40 genes that encode peptide sequences identical to the signal peptide sequences of specific HLA-A and HLA-C allotypes, which enables these CMV strains to escape HLA-E-restricted CD8+T cell responses. Variations in UL40 sequences have been studied mainly in the peripheral blood of CMV-viremia cases. In this study, we sought to investigate how ocular CMV disease develops from CMV infections. CMV gene sequences were compared between the intraocular fluids and peripheral blood of 77 clinical cases. UL40 signal peptide sequences were more diverse, and multiple sequences were typically present in CMV-viremia blood compared to intraocular fluid. Significantly stronger NK cell suppression was induced by UL40-derived peptides from intraocular HCMV compared to those identified only in peripheral blood. HCMV present in intraocular fluids were limited to those carrying a UL40 peptide sequence corresponding to the leader peptide sequence of the host’s HLA class I, while UL40-derived peptides from HCMV found only in the peripheral blood were disparate from any HLA class I allotype. Overall, our analyses of CMV-retinitis inferred that specific HCMV strains with UL40 signal sequences matching the host’s HLA signal peptide sequences were those that crossed the blood–ocular barrier to enter the intraocular space. UL40 peptide repertoires were the same in the intraocular fluids of all ocular CMV diseases, regardless of host immune status, implying that virus type is likely to be a common determinant in ocular CMV disease development. We thus propose a mechanism for ocular CMV disease development, in which particular HCMV types in the blood exploit peripheral and central HLA-E-mediated tolerance mechanisms and, thus, escape the antivirus responses of both innate and adaptive immunity.

BTB domain And CNC Homolog 2 (Bach2) is a transcription repressor that actively participates in T and B lymphocyte development, but it is unknown if Bach2 is also involved in the development of innate immune cells, such as natural killer (NK) cells. Here, we followed the expression of Bach2 during murine NK cell development, finding that it peaked in immature CD27+CD11b+ cells and decreased upon further maturation. Bach2 showed an organ and tissue-specific expression pattern in NK cells. Bach2 expression positively correlated with the expression of transcription factor TCF1 and negatively correlated with genes encoding NK effector molecules and those involved in the cell cycle. Lack of Bach2 expression caused changes in chromatin accessibility of corresponding genes. In the end, Bach2 deficiency resulted in increased proportions of terminally differentiated NK cells with increased production of granzymes and cytokines. NK cell-mediated control of tumor metastasis was also augmented in the absence of Bach2. Therefore, Bach2 is a key checkpoint protein regulating NK terminal maturation.

Proclaimed in 1907, Etosha National Park in northern Namibia is an iconic dryland system with a rich history of wildlife conservation and research. A recent research symposium on wildlife conservation in the Greater Etosha Landscape (GEL) highlighted increased concern of how intensification of global change will affect wildlife conservation based on participant responses to a questionnaire. The GEL includes Etosha and surrounding areas, the latter divided by a veterinary fence into large, private farms to the south and communal areas of residential and farming land to the north. Here, we leverage our knowledge of this ecosystem to provide insight into the broader challenges facing wildlife conservation in this vulnerable dryland environment. We first look backward, summarizing the history of wildlife conservation and research trends in the GEL based on a literature review, providing a broad-scale understanding of the socioecological processes that drive dryland system dynamics. We then look forward, focusing on eight key areas of challenge and opportunity for this ecosystem: climate change, water availability and quality, vegetation and fire management, adaptability of wildlife populations, disease risk, human-wildlife conflict, wildlife crime, and human dimensions of wildlife conservation. Using this model system, we summarize key lessons and identify critical threats highlighting future research needs to support wildlife management. Research in the GEL has followed a trajectory seen elsewhere reflecting an increase in complexity and integration across biological scales over time. Yet, despite these trends, a gap exists between the scope of recent research efforts and the needs of wildlife conservation to adapt to climate and land-use changes. Given the complex nature of climate change, in addition to locally existing system stressors, a framework of forward-thinking adaptive management to address these challenges, supported by integrative and multidisciplinary research could be beneficial. One critical area for growth is to better integrate research and wildlife management across land-use types. Such efforts have the potential to support wildlife conservation efforts and human development goals, while building resilience against the impacts of climate change. While our conclusions reflect the specifics of the GEL ecosystem, they have direct relevance for other African dryland systems impacted by global change.

Mutations of the X-linked gene encoding methyl-CpG-binding protein 2 (MECP2) cause classical forms of Rett syndrome (RTT) in girls. A subset of patients who are recognized to have an overlapping neurological phenotype with RTT but are lacking a mutation in a gene that causes classical or atypical RTT can be described as having a ‘Rett-syndrome-like phenotype (RTT-L). Here, we report eight patients from our cohort diagnosed as having RTT-L who carry mutations in genes unrelated to RTT. We annotated the list of genes associated with RTT-L from our patient cohort, considered them in the light of peer-reviewed articles on the genetics of RTT-L, and constructed an integrated protein–protein interaction network (PPIN) consisting of 2871 interactions connecting 2192 neighboring proteins among RTT- and RTT-L-associated genes. Functional enrichment analysis of RTT and RTT-L genes identified a number of intuitive biological processes. We also identified transcription factors (TFs) whose binding sites are common across the set of RTT and RTT-L genes and appear as important regulatory motifs for them. Investigation of the most significant over-represented pathway analysis suggests that HDAC1 and CHD4 likely play a central role in the interactome between RTT and RTT-L genes.

Abstract Streptococcus pyogenes (Spy) Cas9 has potential as a component of gene therapeutics for incurable diseases. One of its limitations is its large size, which impedes its formulation and delivery in therapeutic applications. Smaller Cas9s are an alternative, but lack robust activity or specificity and frequently recognize longer PAMs. Here, we investigated four uncharacterized, smaller Cas9s and found three employing a “GG” dinucleotide PAM similar to SpyCas9. Protein engineering generated synthetic RNA-guided nucleases (sRGNs) with editing efficiencies and specificities exceeding even SpyCas9 in vitro and in human cell lines on disease-relevant targets. sRGN mRNA lipid nanoparticles displayed manufacturing advantages and high in vivo editing efficiency in the mouse liver. Finally, sRGNs, but not SpyCas9, could be packaged into all-in-one AAV particles with a gRNA and effected robust in vivo editing of non-human primate (NHP) retina photoreceptors. Human gene therapy efforts are expected to benefit from these improved alternatives to existing CRISPR nucleases.

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a communicable disease spread through close contact. It is known to disproportionately impact certain communities due to both biological susceptibility and inequitable exposure. In this study, we investigate the most important health, social, and environmental factors impacting the early phases (before July, 2020) of per capita COVID-19 transmission and per capita all-cause mortality in US counties. We aggregate county-level physical and mental health, environmental pollution, access to health care, demographic characteristics, vulnerable population scores, and other epidemiological data to create a large feature set to analyze per capita COVID-19 outcomes. Because of the high-dimensionality, multicollinearity, and unknown interactions of the data, we use ensemble machine learning and marginal prediction methods to identify the most salient factors associated with several COVID-19 outbreak measure. Our variable importance results show that measures of ethnicity, public transportation and preventable diseases are the strongest predictors for both per capita COVID-19 incidence and mortality. Specifically, the CDC measures for minority populations, CDC measures for limited English, and proportion of Black- and/or African-American individuals in a county were the most important features for per capita COVID-19 cases within a month after the pandemic started in a county and also at the latest date examined. For per capita all-cause mortality at day 100 and total to date, we find that public transportation use and proportion of Black- and/or African-American individuals in a county are the strongest predictors. The methods predict that, keeping all other factors fixed, a 10% increase in public transportation use, all other factors remaining fixed at the observed values, is associated with increases mortality at day 100 of 2012 individuals (95% CI [1972, 2356]) and likewise a 10% increase in the proportion of Black- and/or African-American individuals in a county is associated with increases total deaths at end of study of 2067 (95% CI [1189, 2654]). Using data until the end of study, the same metric suggests ethnicity has double the association as the next most important factors, which are location, disease prevalence, and transit factors. Our findings shed light on societal patterns that have been reported and experienced in the U.S. by using robust methods to understand the features most responsible for transmission and sectors of society most vulnerable to infection and mortality. In particular, our results provide evidence of the disproportionate impact of the COVID-19 pandemic on minority populations. Our results suggest that mitigation measures, including how vaccines are distributed, could have the greatest impact if they are given with priority to the highest risk communities.

Pain management is an important consideration for Head and Neck Cancer (HNC) patients as they are at an increased risk of developing chronic opioid use, which can negatively impact both quality of life and survival outcomes. This retrospective cohort study aimed to evaluate pain, opioid use and opioid prescriptions following HNC surgery. Participants included patients undergoing resection of a head and neck tumor from 2019–2020 at a single academic center with a length of admission (LOA) of at least 24 h. Exclusion criteria were a history of chronic pain, substance-use disorder, inability to tolerate multimodal analgesia or a significant post-operative complication. Subjects were compared by primary surgical site: Neck (neck dissection, thyroidectomy or parotidectomy), Mucosal (resection of tumor of upper aerodigestive tract, excluding oropharynx), Oropharyngeal (OP) and Free flap (FF). Average daily pain and total daily opioid consumption (as morphine milligram equivalents, MME) and quantity of opioids prescribed at discharge were compared. A total of 216 patients met criteria. Pain severity and daily opioid consumption were comparable across groups on post-operative day 1, but both metrics were significantly greater in the OP group on the day prior to discharge (DpDC) (5.6 (1.9–8.6), p < 0.05; 49 ± 44 MME/day, p < 0.01). The quantity of opioids prescribed at discharge was associated with opioid consumption on the DpDC only in the Mucosal and FF groups, which had longer LOA (6–7 days) than the Neck and OP groups (1 day, p < 0.001). Overall, 65% of patients required at least one dose of an opioid on the DpDC, yet 76% of patients received a prescription for an opioid medication at discharge. A longer LOA (aOR = 0.82, 95% CI: 0.63–0.98) and higher Charlson Comorbidity Index (aOR = 0.08, 95% CI: 0.01–0.48) were negatively associated with receiving an opioid prescription at the time of discharge despite no opioid use on the DpDC, respectively. HNC patients, particularly those with shorter LOA, may be prescribed opioids in excess of their post-operative needs, highlighting the need the for improved pain management algorithms in this patient population. Future work aims to use prospective surveys to better define post-operative and outpatient pain and opioid requirements following HNC surgery.

Abstract Background No versatile web app exists that allows epidemiologists and managers around the world to comprehensively analyze the impacts of COVID-19 mitigation. The http://covid-webapp.numerusinc.com/ web app presented here fills this gap. Methods Our web app uses a model that explicitly identifies susceptible, contact, latent, asymptomatic, symptomatic and recovered classes of individuals, and a parallel set of response classes, subject to lower pathogen-contact rates. The user inputs a CSV file of incidence and, if of interest, mortality rate data. A default set of parameters is available that can be overwritten through input or online entry, and a user-selected subset of these can be fitted to the model using maximum-likelihood estimation (MLE). Model fitting and forecasting intervals are specifiable and changes to parameters allow counterfactual and forecasting scenarios. Confidence or credible intervals can be generated using stochastic simulations, based on MLE values, or on an inputted CSV file containing Markov chain Monte Carlo (MCMC) estimates of one or more parameters. Results We illustrate the use of our web app in extracting social distancing, social relaxation, surveillance or virulence switching functions (i.e., time varying drivers) from the incidence and mortality rates of COVID-19 epidemics in Israel, South Africa, and England. The Israeli outbreak exhibits four distinct phases: initial outbreak, social distancing, social relaxation, and a second wave mitigation phase. An MCMC projection of this latter phase suggests the Israeli epidemic will continue to produce into late November an average of around 1500 new case per day, unless the population practices social-relaxation measures at least 5-fold below the level in August, which itself is 4-fold below the level at the start of July. Our analysis of the relatively late South African outbreak that became the world’s fifth largest COVID-19 epidemic in July revealed that the decline through late July and early August was characterised by a social distancing driver operating at more than twice the per-capita applicable-disease-class (pc-adc) rate of the social relaxation driver. Our analysis of the relatively early English outbreak, identified a more than 2-fold improvement in surveillance over the course of the epidemic. It also identified a pc-adc social distancing rate in early August that, though nearly four times the pc-adc social relaxation rate, appeared to barely contain a second wave that would break out if social distancing was further relaxed. Conclusion Our web app provides policy makers and health officers who have no epidemiological modelling or computer coding expertise with an invaluable tool for assessing the impacts of different outbreak mitigation policies and measures. This includes an ability to generate an epidemic-suppression or curve-flattening index that measures the intensity with which behavioural responses suppress or flatten the epidemic curve in the region under consideration.

Abstract Objectives To evaluate the impact of age on overall survival (OS), freedom from distant metastasis (FDM), rates of therapeutic intervention (TI), and quality of life (QOL) in active surveillance (AS) prostate cancer patients. Materials and methods Three hundred and five consecutive, prospectively evaluated AS patients who underwent a staging transperineal template‐guided mapping biopsy (TTMB) prior to enrollment on AS were evaluated and stratified by age. Evaluated outcomes included OS, FDM, TI, and QOL to include urinary, bowel, sexual function, and depression. Post void residual (PVR) urine measurements were also followed. Repeat biopsy was based on PSA kinetics, abnormal digital rectal examination or patient preference. Results Of the 305 patients, 290 (95.1%) were Gleason 3 + 3 and 15 patients (4.9%) were Gleason 3 + 4. The median follow‐up was 5.5 years (range 1‐14 years). At 10 years, TI was 0%, 1.0%, and 11.4% for patients ≤59, 60‐69, and ≥70 years of age (P

Abstract Scavenging of carrion shapes ecological landscapes by influencing scavenger population demography, increasing inter- and intra-specific interactions, and generating ecosystem services such as nutrient cycling and disease moderation. Previous research found the cues promoting, or the constraints limiting, an individual’s propensity or ability to scavenge vary widely, depending on anthropogenic and environmental factors. Here we investigated differences in scavenging patterns in a complex scavenger guild in Southwestern Montana. We used camera traps established at 13 carcass sites to monitor carcass detection, visitation, and consumption times, during 2016–2018 and generalized linear models to explore the influence of carcass characteristics, habitat features, and seasonality, on carcass selection and scavenging efficiency. We found that scavenger species diversity was higher at higher elevations and in grassland habitats. Scavenging efficiency was influenced inter alia by seasonality, distance to water, and elevation. We found that most carcass consumption was via facultative scavengers (bears, wolves, magpies, Corvus spp.) rather than turkey vultures, the only obligate scavengers in the study area. However, growing populations of turkey vultures may lead to increased competition with facultative scavengers over carrion, and could have cascading effects on food webs in this ecosystem.