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Abstract Freshwater ecosystems are biologically important habitats that provide many ecosystem services. Calcium concentration and pH are two key variables that are linked to multiple chemical processes in these environments, influence the biology of organisms from diverse taxa, and can be important factors affecting the distribution of native and non-native species. However, it can be challenging to obtain high-resolution data for these variables at regional and national scales. To address this data gap, water quality data for lakes and rivers in Canada and the continental USA were compiled and used to generate high-resolution (10 × 10 km) interpolated raster layers, after comparing multiple spatial interpolation approaches. This is the first time that such data have been made available at this scale and resolution, providing a valuable resource for research, including projects evaluating risks from environmental change, pollution, and invasive species. This will aid the development of conservation and management strategies for these vital habitats.

Abstract Habitat structural complexity (HSC) is a key variable to help interpret ecological patterns and processes among different ecosystems. Existing metrics used to quantify HSC often, however, result in insufficient or biased representation of structural complexity. As such, our understanding of how HSC affects biodiversity and related ecological patterns is often limited by these measures. Recent advances in photogrammetry and computer vision have enabled the ability to reconstruct 3D habitats with high efficiency and accuracy. Point clouds, for example, better represent the structural properties of target objects with reduced sampling bias as compared to traditional formats like 2.5D raster (i.e. DEM, DSM, DTM). The analysis of point clouds is, however, limited by the lack of readily available packages with mathematically well‐defined metrics for ecologists to help interpret relevant HSC properties. To address this gap, novel metrics are provided in the present Python package HSC3D version 0.2.0, which allows quantification of structural complexity of targeted habitats based on photogrammetry point clouds. This package is designed to help ecologists better describe the structural characteristics of a specific habitat and is bundled with visualisation functions to help interpret the computational processes used. To demonstrate functions implemented in HSC3D we use a case study that compares the structural complexity differences formed by two intertidal ecosystem engineers, mussels and oysters. Results indicate that HSC3D is a versatile and easily adapted package, which can provide both ecological and analytical insights on photogrammetry point clouds which should prove a useful tool for ecologists wanting to quantify HSC.

BACKGROUND: During the 2010 Deepwater Horizon (DWH) disaster, in-situ burning and flaring were conducted to remove oil from the water. Workers near combustion sites were potentially exposed to burning-related fine particulate matter (PM2.5). Exposure to PM2.5 has been linked to increased risk of coronary heart disease (CHD), but no study has examined the relationship among oil spill workers. OBJECTIVES: To investigate the association between estimated PM2.5 from burning/flaring of oil/gas and CHD risk among the DWH oil spill workers. METHODS: We included workers who participated in response and cleanup activities on the water during the DWH disaster (N = 9091). PM2.5 exposures were estimated using a job-exposure matrix that linked modelled PM2.5 concentrations to detailed DWH spill work histories provided by participants. We ascertained CHD events as the first self-reported physician-diagnosed CHD or a fatal CHD event that occurred after each workers last day of burning exposure. We estimated hazard ratios (HR) and 95% confidence intervals (95%CI) for the associations between categories of average or cumulative daily maximum PM2.5 exposure (versus a referent category of water workers not near controlled burning) and subsequent CHD. We assessed exposure-response trends by examining continuous exposure parameters in models. RESULTS: We observed increased CHD hazard among workers with higher levels of average daily maximum exposure (low vs. referent: HR = 1.26, 95% CI: 0.93, 1.70; high vs. referent: HR = 2.11, 95% CI: 1.08, 4.12; per 10 μg/m3 increase: HR = 1.10, 95% CI: 1.02, 1.19). We also observed suggestively elevated HRs among workers with higher cumulative daily maximum exposure (low vs. referent: HR = 1.19, 95% CI: 0.68, 2.08; medium vs. referent: HR = 1.38, 95% CI: 0.88, 2.16; high vs. referent: HR = 1.44, 95% CI: 0.96, 2.14; per 100 μg/m3-d increase: HR = 1.03, 95% CI: 1.00, 1.05). CONCLUSIONS: Among oil spill workers, exposure to PM2.5 from flaring/burning of oil/gas was associated with increased risk of CHD.

In recent years, the complex evolution of the highly pathogenic avian influenza (HPAI) situation reflects a change in the eco-epidemiology of the causative agent which, among other demands, renews the need for better understanding of the connectivity between countries through the main virus reservoirs to improve prevention, early warning and mitigate the associated risks. Our objective was to determine migratory connectivity of Blue-winged Teal and evaluate the risk of AIV introduction to Cuba by this species. The stable hydrogen isotope (δ2H) value in flight feathers was analyzed. Individuals were sampled during the migratory season of 2021 (N=126) and winter residence of 2020 (N=152), in western and central Cuba, respectively. Based on banding records from 1955 to 2018, the transition probabilities from 3 breeding areas in North America to 9 wintering areas was estimated with a Burnham’s live-recapture dead-recovery modeling framework. A map of likely origin in North America of the individuals sampled for each season was generated, combining the isotopic information and transition probabilities. Evidence of an age-related and phenological pattern in migratory origins was identified. Individuals harvested in the migratory season in western Cuba were most likely from molt or natal areas in the prairies and forest regions from United States and southern Canada. Alternatively, individuals harvested in winter in the center of Cuba had the most likely origin in the U.S. prairie region. The spatial-temporal pattern of AIV prevalence in the estimated region was analyzed and suggestions are made to assist the Cuban system of active AIV surveillance of wild birds.

Living donor liver transplantation has expanded in recent years, particularly in North America. As experience with this procedure has matured over the last 25 years, centers are increasingly faced with potential living donors who are more medically complex. As donors move through the evaluation process, completing the informed consent process continues to be challenged by a paucity of granular data demonstrating long-term outcomes and overall safety specifically in the otherwise "healthy" living liver donor population. Two recently published studies examined long-term outcomes post-living liver donation using Korean registry data and reported similar results, with excellent overall survival when compared to appropriately matched controls. However, the authors of these studies were presented differently, with one reporting an alarmist view based on one aspect of a suboptimal analysis approach using an inappropriate comparator group. Herein, the North American Living Liver Donor Innovation Group (NALLDIG) consortium discusses these two studies and their potential impact on living liver donation in North America, ultimately highlighting the importance of scientific integrity in data presentation and dissemination when using transplant registry data.

The Society of Nuclear Medicine and Molecular Imaging (SNMMI) has publicly commented that they do not support the reporting of large extravasations to patients or regulatory bodies. The comment cites recently published articles suggesting that extravasations are infrequent and not severe. The comment stresses the importance of ensuring patients are not apprehensive or resistant to nuclear medicine procedures because of “radiation paranoia” and a “chilling effect” that can result from misinformation. Radiation paranoia and chilling effect are not defined, and there are no references to specific misinformation. Our experiences and this case suggest the comment may be incongruent with real-world clinical experiences. Our severe case, at a center with a long-standing focus on reducing radiopharmaceutical extravasation, suggests these events can still happen, can be significant, and should be shared with our patients. Our experiences also suggest that being transparent with patients builds trust. We are concerned that a reluctance to recognize the true frequency of extravasations and their severity may create distrust in the relationship between the nuclear medicine community and patients.

Background: Studies are increasingly examining the relationship between the neighborhood environment and cognitive decline; yet, few have investigated associations between multiple neighborhood features and Alzheimer's disease and related dementias (ADRD). Objective: We investigated the relationship between neighborhood features and ADRD cumulative incidence from 2010 to 2014 in the South Carolina Alzheimer's Disease Registry (SCADR). Methods: Diagnosed ADRD cases [greater than or equal to] 50 years of age were ascertained from the SCADR by ZIP code and census tract. Neighborhood features from multiple secondary sources included poverty, air pollution [particulate matter with a diameter of 2.5 micrometers or less (P[M.sub.2.5])], and rurality at the census-tract level and access to healthy food, recreation facilities, and diabetes screening at the county level. In addition to using Poisson generalized linear regression to estimate ADRD incident rate ratios (IRR) with 95% confidence intervals (CIs), we applied integrated nested Laplace approximations and stochastic partial differential equations (INLA-SPDE) to address disparate spatial scales. We estimated associations between neighborhood features and ADRD cumulative incidence. Results: The average annual ADRD cumulative incidence was 690 per 100,000 people per census tract (95% CI: 660, 710). The analysis was limited to 98% of census tracts with a population [greater than or equal to]50 years old (i.e., 1,081 of 1,103). The average percent of families living below the federal poverty line per census tract was 18.8%, and ~20% of census tracts were considered rural. The average percent of households with limited access to healthy food was 6.4%. In adjusted models, every 5 [micro]g/[m.sup.3]) increase of P[M.sub.2.5] was associated with 65% higher ADRD cumulative incidence (IRR = 1.65; 95% CI: 1.30, 2.09), where P[M.sub.2.5] at or below 12 [micro]g/[m.sup.3] is considered healthy. Compared to large urban census tracts, rural and small urban tracts had 10% (IRR = 1.10; 95% CI: 1.00, 1.23) and 5% (IRR = 1.05; 95% CI: 0.96, 1.16) higher ADRD, respectively. For every percent increase of the county population with limited access to healthy food, ADRD was 2% higher (IRR= 1.02; 95% CI: 1.01, 1.04). Conclusions: Neighborhood environment features, such as higher air pollution levels, were associated with higher neighborhood ADRD incidence. The INLA-SPDE method could have broad applicability to data collected across disparate spatial scales. https://doi.org/10.1289/EHP13183, Introduction Alzheimer's disease (AD) impacts an estimated 5.7 million adults in the US (1) and is ranked, along with other forms of dementia, as the sixth leading cause of death. [...]

The small genomes of most viruses make it difficult to fully capture viral diversity in metagenomes dominated by DNA from cellular organisms. Viral size fraction metagenomics (viromics) protocols facilitate the enrichment of viral DNA from environmental samples, and these protocols typically include DNase treatment of the post-0.2-μm-filtered viromic fraction to remove contaminating free DNA prior to virion lysis. However, DNase may also remove desirable viral genomic DNA (e.g., contained in virions compromised due to frozen storage or laboratory processing), suggesting that DNase-untreated viromes might be useful in some cases. In order to understand how virome preparation with and without DNase treatment influences the resultant data, here, we compared 15 soil viromes (7 DNase treated and 8 untreated) from 8 samples collected from agricultural fields prior to tomato planting. DNase-treated viromes yielded significantly more assembled viral contigs, contained significantly less nonviral microbial DNA, and recovered more viral populations (viral operational taxonomic units [vOTUs]) through read mapping. However, DNase-treated and untreated viromes were statistically indistinguishable in terms of ecological patterns across viral communities. Although the results suggest that DNase treatment is preferable where possible, in comparison to previously reported total metagenomes from the same samples, both DNase-treated and untreated viromes were significantly enriched in viral signatures by all metrics compared, including a 225-times-higher proportion of viral reads in untreated viromes compared to total metagenomes. Thus, even without DNase treatment, viromics was preferable to total metagenomics for capturing viral diversity in these soils, suggesting that preparation of DNase-untreated viromes can be worthwhile when DNase treatment is not possible. IMPORTANCE Viromics is becoming an increasingly popular method for characterizing soil viral communities. DNase treatment of the viral size fraction prior to DNA extraction is meant to reduce contaminating free DNA and is a common step within viromics protocols to ensure that sequences are of viral origin. However, some samples may not be amenable to DNase treatment due to viral particles being compromised either in storage (i.e., frozen) or during other sample processing steps. To date, the effect of DNase treatment on the recovery of viruses and downstream ecological interpretations of soil viral communities is not thoroughly understood. This work sheds light on these questions and indicates that while DNase treatment of soil viromes improves the recovery of viral populations, this improvement is modest in comparison to the gains made by viromics over total soil metagenomics. Furthermore, DNase treatment may not be necessary to observe the ecological patterns structuring soil viral communities.

BackgroundPeatlands are expected to experience sustained yet fluctuating higher temperatures due to climate change, leading to increased microbial activity and greenhouse gas emissions. Despite mounting evidence for viral contributions to these processes in peatlands underlain with permafrost, little is known about viruses in other peatlands. More generally, soil viral biogeography and its potential drivers are poorly understood at both local and global scales. Here, 87 metagenomes and five viral size-fraction metagenomes (viromes) from a boreal peatland in northern Minnesota (the SPRUCE whole-ecosystem warming experiment and surrounding bog) were analyzed for dsDNA viral community ecological patterns, and the recovered viral populations (vOTUs) were compared with our curated PIGEON database of 266,125 vOTUs from diverse ecosystems.ResultsWithin the SPRUCE experiment, viral community composition was significantly correlated with peat depth, water content, and carbon chemistry, including CH4 and CO2 concentrations, but not with temperature during the first 2 years of warming treatments. Peat vOTUs with aquatic-like signatures (shared predicted protein content with marine and/or freshwater vOTUs) were significantly enriched in more waterlogged surface peat depths. Predicted host ranges for SPRUCE vOTUs were relatively narrow, generally within a single bacterial genus. Of the 4326 SPRUCE vOTUs, 164 were previously detected in other soils, mostly peatlands. None of the previously identified 202,371 marine and freshwater vOTUs in our PIGEON database were detected in SPRUCE peat, but 0.4% of 80,714 viral clusters (VCs, grouped by predicted protein content) were shared between soil and aquatic environments. On a per-sample basis, vOTU recovery was 32 times higher from viromes compared with total metagenomes.ConclusionsResults suggest strong viral "species" boundaries between terrestrial and aquatic ecosystems and to some extent between peat and other soils, with differences less pronounced at higher taxonomic levels. The significant enrichment of aquatic-like vOTUs in more waterlogged peat suggests that viruses may also exhibit niche partitioning on more local scales. These patterns are presumably driven in part by host ecology, consistent with the predicted narrow host ranges. Although more samples and increased sequencing depth improved vOTU recovery from total metagenomes, the substantially higher per-sample vOTU recovery after viral particle enrichment highlights the utility of soil viromics. Video abstract The importance of Minnesota peat viromes in revealing terrestrial and aquatic niche partitioning for viral populations.