Lessons Learned from Public Health and State Prison Collaborations during COVID-19 Pandemic and Multifacility Tuberculosis Outbreak, Washington, USA.

The large COVID-19 outbreaks in prisons in the Washington (USA) State Department of Corrections (WADOC) system during 2020 highlighted the need for a new public health approach to prevent and control COVID-19 transmission in the system's 12 facilities. WADOC and the Washington State Department of Health (WADOH) responded by strengthening partnerships through dedicated corrections-focused public health staff, improving cross-agency outbreak response coordination, implementing and developing corrections-specific public health guidance, and establishing collaborative data systems. The preexisting partnerships and trust between WADOC and WADOH, strengthened during the COVID-19 response, laid the foundation for a collaborative response during late 2021 to the largest tuberculosis outbreak in Washington State in the past 20 years. We describe challenges of a multiagency collaboration during 2 outbreak responses, as well as approaches to address those challenges, and share lessons learned for future communicable disease outbreak responses in correctional settings.

Foot injuries, playing surface and shoe design: Should we be thinking more about injury prevention.

The increasing use of artificial pitches has occurred in a multitude of sports at both professional and amateur levels. Artificial turf has become an extremely attractive option as it is felt to encourage a faster, safer and more entertaining play. However these pitches are not without controversy among sporting professionals and in the media. Foot and ankle injury in sport remains incredibly common and a significant burden on health professionals, but what impact do the new artificial surfaces have on these injuries. This review article aims to establish whether artificial turf has an impact on injury rates in the foot and ankle.

Density and distribution of western chimpanzees around a bauxite deposit in the Boé Sector, Guinea-Bissau.

The Boé sector in southeast Guinea-Bissau harbors a population of western chimpanzees (Pan troglodytes verus) that inhabits a mosaic of forest and savanna. The Boé sector contains a substantial bauxite deposit in a region called Ronde Hill, and there are plans for the construction of a mine, which may endanger the chimpanzee population. In 1-week survey in May 2013, we used the standing crop nest counts method to obtain the number of chimpanzee nests and from that estimate the density and abundance of chimpanzees. We carried out five 1-km line transects that covered the bauxite deposit and surrounding valleys. We used density surface modeling to analyze habitat preferences, then predicted chimpanzee nest density and distribution based on environmental variables. We found the projected location of the mine partially coincides with an area of high predicted abundances of chimpanzee nests and is surrounded by highly suitable areas for chimpanzees (northeast and southwest). We conclude the mine could have significant direct and indirect effects on this population of chimpanzees whose impacts must be carefully considered and properly mitigated if the mine is built.

Turbulent flow reduces oxygen consumption in the labriform swimming shiner perch, Cymatogaster aggregata.

Fish swimming energetics are often measured in laboratory environments which attempt to minimize turbulence, though turbulent flows are common in the natural environment. To test whether the swimming energetics and kinematics of shiner perch, Cymatogaster aggregata (a labriform swimmer), were affected by turbulence, two flow conditions were constructed in a swim-tunnel respirometer. A low-turbulence flow was created using a common swim-tunnel respirometry setup with a flow straightener and fine-mesh grid to minimize velocity fluctuations. A high-turbulence flow condition was created by allowing large velocity fluctuations to persist without a flow straightener or fine grid. The two conditions were tested with particle image velocimetry to confirm significantly different turbulence properties throughout a range of mean flow speeds. Oxygen consumption rate of the swimming fish increased with swimming speed and pectoral fin beat frequency in both flow conditions. Higher turbulence also caused a greater positional variability in swimming individuals (versus low-turbulence flow) at medium and high speeds. Surprisingly, fish used less oxygen in high-turbulence compared with low-turbulence flow at medium and high swimming speeds. Simultaneous measurements of swimming kinematics indicated that these reductions in oxygen consumption could not be explained by specific known flow-adaptive behaviours such as Kármán gaiting or entraining. Therefore, fish in high-turbulence flow may take advantage of the high variability in turbulent energy through time. These results suggest that swimming behaviour and energetics measured in the lab in straightened flow, typical of standard swimming respirometers, might differ from that of more turbulent, semi-natural flow conditions.

Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas.

As human activities expand beyond national jurisdictions to the high seas, there is an increasing need to consider anthropogenic impacts to species inhabiting these waters. The current scarcity of scientific observations of cetaceans in the high seas impedes the assessment of population-level impacts of these activities. We developed plausible density estimates to facilitate a quantitative assessment of anthropogenic impacts on cetacean populations in these waters. Our study region extended from a well-surveyed region within the U.S. Exclusive Economic Zone into a large region of the western North Atlantic sparsely surveyed for cetaceans. We modeled densities of 15 cetacean taxa with available line transect survey data and habitat covariates and extrapolated predictions to sparsely surveyed regions. We formulated models to reduce the extent of extrapolation beyond covariate ranges, and constrained them to model simple and generalizable relationships. To evaluate confidence in the predictions, we mapped where predictions were made outside sampled covariate ranges, examined alternate models, and compared predicted densities with maps of sightings from sources that could not be integrated into our models. Confidence levels in model results depended on the taxon and geographic area and highlighted the need for additional surveying in environmentally distinct areas. With application of necessary caution, our density estimates can inform management needs in the high seas, such as the quantification of potential cetacean interactions with military training exercises, shipping, fisheries, and deep-sea mining and be used to delineate areas of special biological significance in international waters. Our approach is generally applicable to other marine taxa and geographic regions for which management will be implemented but data are sparse.

Use of Autometallography in Studies of Nanosilver Distribution and Toxicity.

With the increasing use of and interest in nanoparticles in medicine and technology, the tissue and cell-specific localization of the particles are important considerations when the nanomaterials find their way into biological systems. This brief communication shows the utility of autometallography in determining the location of metal deposition at the light microscopic level. Although primarily focusing on studies of the toxicity and deposition of silver nanoparticles, use of autometallography to localize zinc and other metals at the tissue and subcellular localization is also recognized.

Accounting for spatial habitat and management boundaries when estimating forest bird population distribution and density: inferences from a soap film smoother.

Birds are often obligate to specific habitats which can result in study areas with complex boundaries due to sudden changes in vegetation or other features. This can result in study areas with concave arcs or that include holes of unsuitable habitat such as lakes or agricultural fields. Spatial models used to produce species' distribution and density estimates need to respect such boundaries to make informed decisions for species conservation and management. The soap film smoother is one model for complex study regions which controls the boundary behaviour, ensuring realistic values at the edges of the region. We apply the soap film smoother to account for boundary effects and compare it with thin plate regression spline (TPRS) smooth and design-based conventional distance sampling methods to produce abundance estimates from point-transect distance sampling collected data on Hawai'i 'Akepa Loxops coccineus in the Hakalau Forest Unit of the Big Island National Wildlife Refuge Complex, Hawai'i Island, USA. The soap film smoother predicted zero or near zero densities in the northern part of the domain and two hotspots (in the southern and central parts of the domain). Along the boundary the soap film model predicted relatively high densities where 'Akepa occur in the adjacent forest and near zero elsewhere. The design-based and soap film abundance estimates were nearly identical. The width of the soap film confidence interval was 16.5% and 0.8% wider than the width of the TPRS smooth and design-based confidence intervals, respectively. The peaks in predicted densities along the boundary indicates leakage by the TPRS smooth. We provide a discussion of the statistical methods, biological findings and management implications of applying soap film smoothers to estimate forest bird population status.

Increased photosynthesis during spring drought in energy-limited ecosystems.

Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there is potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of photosynthesis (gross primary productivity, GPP) to meteorological drought across the water-energy limitation spectrum. We find a consistent increase in eddy covariance GPP during spring drought in energy-limited ecosystems (83% of the energy-limited sites). Half of spring GPP sensitivity to precipitation was predicted solely from the wetness index (R2 = 0.47, p < 0.001), with weaker relationships in summer and fall. Our results suggest GPP increases during spring drought for 55% of vegetated Northern Hemisphere lands ( >30° N). We then compare these results to terrestrial biosphere model outputs and remote sensing products. In contrast to trends detected in eddy covariance data, model mean GPP always declined under spring precipitation deficits after controlling for air temperature and light availability. While remote sensing products captured the observed negative spring GPP sensitivity in energy-limited ecosystems, terrestrial biosphere models proved insufficiently sensitive to spring precipitation deficits.

Differential effects of Western diet and traumatic muscle injury on skeletal muscle metabolic regulation in male and female mice.

BACKGROUND: This study was designed to develop an understanding of the pathophysiology of traumatic muscle injury in the context of Western diet (WD; high fat and high sugar) and obesity. The objective was to interrogate the combination of WD and injury on skeletal muscle mass and contractile and metabolic function. METHODS: Male and female C57BL/6J mice were randomized into four groups based on a two-factor study design: (1) injury (uninjured vs. volumetric muscle loss [VML]) and (2) diet (WD vs. normal chow [NC]). Electrophysiology was used to test muscle strength and metabolic function in cohorts of uninjured + NC, uninjured + WD, VML + NC and VML + WD at 8 weeks of intervention. RESULTS: VML-injured male and female mice both exhibited decrements in muscle mass (-17%, P < 0.001) and muscle strength (-28%, P < 0.001); however, VML + WD females had a 28% greater muscle mass compared to VML + NC females (P = 0.034), a compensatory response not detected in males. VML-injured male and female mice both had lower carbohydrate- and fat-supported muscle mitochondrial respiration (JO2 ) and less electron conductance through the electron transport system (ETS); however, male VML-WD had 48% lower carbohydrate-supported JO2 (P = 0.014) and 47% less carbohydrate-supported electron conductance (P = 0.026) compared to male VML + NC, and this diet-injury phenotype was not present in females. ETS electron conductance starts with complex I and complex II dehydrogenase enzymes at the inner mitochondrial membrane, and male VML + WD had 31% less complex I activity (P = 0.004) and 43% less complex II activity (P = 0.005) compared to male VML + NC. This was a diet-injury phenotype not present in females. Pyruvate dehydrogenase (PDH), ß-hydroxyacyl-CoA dehydrogenase, citrate synthase, α-ketoglutarate dehydrogenase and malate dehydrogenase metabolic enzyme activities were evaluated as potential drivers of impaired JO2 in the context of diet and injury. There were notable male and female differential effects in the enzyme activity and post-translational regulation of PDH. PDH enzyme activity was 24% less in VML-injured males, independent of diet (P < 0.001), but PDH enzyme activity was not influenced by injury in females. PDH enzyme activity is inhibited by phosphorylation at serine-293 by PDH kinase 4 (PDK4). In males, there was greater total PDH, phospho-PDHser293 and phospho-PDH-to-total PDH ratio in WD mice compared to NC, independent of injury (P ≤ 0.041). In females, PDK4 was 51% greater in WD compared to NC, independent of injury (P = 0.025), and was complemented by greater phospho-PDHser293 (P = 0.001). CONCLUSIONS: Males are more susceptible to muscle metabolic dysfunction in the context of combined WD and traumatic injury compared to females, and this may be due to impaired metabolic enzyme functions.

Shipping in the north-east Atlantic: Identifying spatial and temporal patterns of change.

Maritime traffic is increasing globally, with a four-fold increase in commercial vessel movements between 1992 and 2012. Vessels contribute to noise and air pollution, provide pathways for non-native species, and collide with marine wildlife. While knowledge of shipping trends and potential environmental impacts exists at both local and global levels, key information on vessel density for regional-scale management is lacking. This study presents the first in-depth spatio-temporal analysis of shipping in the north-east Atlantic region, over three years in a five-year period. Densities increased by 34%, including in 73% of Marine Protected Areas. Western Scotland and the Bay of Biscay experienced the largest increases in vessel density, predominantly from small and slow vessels. Given well-documented impacts that shipping can have on the marine environment, it is crucial that this situation continues to be monitored - particularly in areas designated to protect vulnerable species and ecosystems which may already be under pressure.

Estimating uncertainty in density surface models.

Providing uncertainty estimates for predictions derived from species distribution models is essential for management but there is little guidance on potential sources of uncertainty in predictions and how best to combine these. Here we show where uncertainty can arise in density surface models (a multi-stage spatial modelling approach for distance sampling data), focussing on cetacean density modelling. We propose an extensible, modular, hybrid analytical-simulation approach to encapsulate these sources. We provide example analyses of fin whales Balaenoptera physalus in the California Current Ecosystem.

Extending density surface models to include multiple and double-observer survey data.

Spatial models of density and abundance are widely used in both ecological research (e.g., to study habitat use) and wildlife management (e.g., for population monitoring and environmental impact assessment). Increasingly, modellers are tasked with integrating data from multiple sources, collected via different observation processes. Distance sampling is an efficient and widely used survey and analysis technique. Within this framework, observation processes are modelled via detection functions. We seek to take multiple data sources and fit them in a single spatial model. Density surface models (DSMs) are a two-stage approach: first accounting for detectability via distance sampling methods, then modelling distribution via a generalized additive model. However, current software and theory does not address the issue of multiple data sources. We extend the DSM approach to accommodate data from multiple surveys, collected via conventional distance sampling, double-observer distance sampling (used to account for incomplete detection at zero distance) and strip transects. Variance propagation ensures that uncertainty is correctly accounted for in final estimates of abundance. Methods described here are implemented in the dsm R package. We briefly analyse two datasets to illustrate these new developments. Our new methodology enables data from multiple distance sampling surveys of different types to be treated in a single spatial model, enabling more robust abundance estimation, potentially over wider geographical or temporal domains.

A Sensitive and Cost-Effective Chemiluminescence ELISA for Measurement of Amyloid-ß 1-42 Peptide in Human Plasma.

BACKGROUND: Amyloid-ß42 (Aß42) is associated with plaque formation in the brain of patients with Alzheimer's disease (AD). Studies have suggested the potential utility of plasma Aß42 levels in the diagnosis, and in longitudinal study of AD pathology. Conventional ELISAs are used to measure Aß42 levels in plasma but are not sensitive enough to quantitate low levels. Although ultrasensitive assays like single molecule array or immunoprecipitation-mass spectrometry have been developed to quantitate plasma Aß42 levels, the high cost of instruments and reagents limit their use. OBJECTIVE: We hypothesized that a sensitive and cost-effective chemiluminescence (CL) immunoassay could be developed to detect low Aß42 levels in human plasma. METHODS: We developed a sandwich ELISA using high affinity rabbit monoclonal antibody specific to Aß42. The sensitivity of the assay was increased using CL substrate to quantitate low levels of Aß42 in plasma. We examined the levels in plasma from 13 AD, 25 Down syndrome (DS), and 50 elderly controls. RESULTS: The measurement range of the assay was 0.25 to 500 pg/ml. The limit of detection was 1 pg/ml. All AD, DS, and 45 of 50 control plasma showed measurable Aß42 levels. CONCLUSION: This assay detects low levels of Aß42 in plasma and does not need any expensive equipment or reagents. It offers a preferred alternative to ultrasensitive assays. Since the antibodies, peptide, and substrate are commercially available, the assay is well suited for academic or diagnostic laboratories, and has a potential for the diagnosis of AD or in clinical trials.

Hierarchical generalized additive models in ecology: an introduction with mgcv.

In this paper, we discuss an extension to two popular approaches to modeling complex structures in ecological data: the generalized additive model (GAM) and the hierarchical model (HGLM). The hierarchical GAM (HGAM), allows modeling of nonlinear functional relationships between covariates and outcomes where the shape of the function itself varies between different grouping levels. We describe the theoretical connection between HGAMs, HGLMs, and GAMs, explain how to model different assumptions about the degree of intergroup variability in functional response, and show how HGAMs can be readily fitted using existing GAM software, the mgcv package in R. We also discuss computational and statistical issues with fitting these models, and demonstrate how to fit HGAMs on example data. All code and data used to generate this paper are available at: github.com/eric-pedersen/mixed-effect-gams.

Generation and Partial Characterization of Rabbit Monoclonal Antibody to Pyroglutamate Amyloid-ß3-42 (pE3-Aß).

N-terminally truncated pyroglutamate amyloid-ß (Aß) peptide starting at position 3 represents a significant fraction of Aß peptides (pE3-Aß) in amyloid plaques of postmortem brains from patients with Alzheimer's disease (AD) and older persons with Down syndrome (DS). Studies in transgenic mouse models of AD also showed that pE3-Aß is a major component of plaques, and mouse monoclonal antibody to pE3-Aß appears to be a desirable therapeutic agent for AD. Since small peptides do not typically elicit a good immune response in mice, but do so favorably in rabbits, our aims were to generate and partially characterize a rabbit monoclonal antibody (RabmAb) to pE3-Aß. The generated RabmAb was found to be specific for pE3-Aß, since it showed no reactivity with Aß16, Aß40, Aß42, Aß3-11, and pE11-17 Aß peptides in an enzyme linked immunosorbent assay (ELISA). The isotype of the antibody was found to be IgG class. The antibody possesses high affinity to pE3-Aß with dissociation constant (KD) for the antibody of 1 nM. The epitope of the antibody lies within the sequence of pE3-FRHD. In dot blotting, the optimal detection of pE3-Aß was at an antibody concentration of 0.5 µg/ml. The threshold of pE3-Aß detection was 2 fmol. The antibody was sensitive enough to detect 10 pg/ml of pE3-Aß in sandwich ELISA. pE3-Aß was detected in AD and DS brain extracts in ELISA and immunoblotting. Immunohistological studies showed immunolabeling of plaques and blood vessels in brains from patients with AD, and DS showing AD pathology. Thus, the antibody can be widely applied in AD and DS research, and therapeutic applications.

Humoral immune responses to peptides derived from the beta-amyloid peptide C-terminal sequence.

There is a continuing interest in the immunochemical quantification of isoforms of amyloid beta-peptide (Abeta) in body fluids of patients with Alzheimer's disease (AD); however, at present there is no general procedure to produce and test the required antibodies. We examined various methods to generate rabbit anti-Abeta; antibodies that are specific for Abeta(38), Abeta(40) and Abeta(42), and we tested their specificity and sensitivity by ELISA and Western blotting. To produce high-affinity antibodies required repeated inoculations of small doses of peptide conjugates over a period of at least 6 months. Antibodies generated to peptides derived from the Abeta(42) sequence showed some cross-reactivity with Abeta(40), but antibodies generated to Abeta4 peptides did not cross-react with Abeta(42). The shortest peptide capable of generating antibodies of moderate affinity possessed the sequence Met(35)-Ala(42); however, antibodies raised to the peptide Gly(33)-Ala(42) possessed the greatest affinity (K(D) = 1 nM) and specificity for Abeta(42). The latter antibodies were over 50,000-fold more reactive with Abeta(42) than with Abeta(40). They can detect Abeta isoforms in extracts of normal brain, where the peptides are present at levels below one part per billion. Our results provide methods to generate and characterize the specificity and affinity of anti-Abeta antibodies. This information is necessary to develop sensitive and specific immunoassays to quantify Abeta isoforms in brain extracts and in body fluids.

Penalized nonparametric scalar-on-function regression via principal coordinates.

A number of classical approaches to nonparametric regression have recently been extended to the case of functional predictors. This paper introduces a new method of this type, which extends intermediate-rank penalized smoothing to scalar-on-function regression. In the proposed method, which we call principal coordinate ridge regression, one regresses the response on leading principal coordinates defined by a relevant distance among the functional predictors, while applying a ridge penalty. Our publicly available implementation, based on generalized additive modeling software, allows for fast optimal tuning parameter selection and for extensions to multiple functional predictors, exponential family-valued responses, and mixed-effects models. In an application to signature verification data, principal coordinate ridge regression, with dynamic time warping distance used to define the principal coordinates, is shown to outperform a functional generalized linear model.

Generation and Partial Characterization of Rabbit Monoclonal Antibody to Amyloid-ß Peptide 1-37 (Aß37).

Secreted soluble amyloid-ß 1-37 (Aß37) peptide is one of the prominent Aß forms next to Aß40, and is found in cerebrospinal fluid (CSF) and blood. Recent studies have shown the importance of quantitation of CSF Aß37 levels in combination with Aß38, Aß40, and Aß42 to support the diagnosis of patients with probable Alzheimer's disease (AD), and the value of antibody to Aß37 to facilitate drug discovery studies. However, the availability of reliable and specific monoclonal antibody to Aß37 is very limited. Our aims were: 1) to generate and partially characterize rabbit monoclonal antibody (RabmAb) to Aß37, and 2) to determine whether the antibody detects changes in Aß37 levels produced by a γ-secretase modulator (GSM). Our generated RabmAb to Aß37 was found to be specific to Aß37, since it did not react with Aß36, Aß38, Aß39, Aß40, and Aß42 in an ELISA or immunoblotting. The epitope of the antibody was contained in the seven C-terminal residues of Aß37. The antibody was sensitive enough to measure CSF and plasma Aß37 levels in ELISA. Immunohistological studies showed the presence of Aß37-positive deposits in the brain of AD, and Down syndrome persons diagnosed with AD. Our studies also showed that the antibody detected Aß37 increases in CSF and brains of rodents following treatment with a GSM. Thus, our antibody can be widely applied to AD research, and in a panel based approach it may have potential to support the diagnosis of probable AD, and in testing the effect of GSMs to target AD.

Spatial Models of Abundance and Habitat Preferences of Commerson's and Peale's Dolphin in Southern Patagonian Waters.

Commerson's dolphins (Cephalorhynchus c. commersonii) and Peale's dolphins (Lagenorhynchus australis) are two of the most common species of cetaceans in the coastal waters of southwest South Atlantic Ocean. Both species are listed as Data Deficient by the IUCN, mainly due to the lack of information about population sizes and trends. The goal of this study was to build spatially explicit models for the abundance of both species in relation to environmental variables using data collected during eight scientific cruises along the Patagonian shelf. Spatial models were constructed using generalized additive models. In total, 88 schools (212 individuals) of Commerson's dolphin and 134 schools (465 individuals) of Peale's dolphin were recorded in 8,535 km surveyed. Commerson's dolphin was found less than 60 km from shore; whereas Peale's dolphins occurred over a wider range of distances from the coast, the number of animals sighted usually being larger near or far from the coast. Fitted models indicate overall abundances of approximately 22,000 Commerson's dolphins and 20,000 Peale's dolphins in the total area studied. This work provides the first large-scale abundance estimate for Peale's dolphin in the Atlantic Ocean and an update of population size for Commerson's dolphin. Additionally, our results contribute to baseline data on suitable habitat conditions for both species in southern Patagonia, which is essential for the implementation of adequate conservation measures.

Mixture models for distance sampling detection functions.

We present a new class of models for the detection function in distance sampling surveys of wildlife populations, based on finite mixtures of simple parametric key functions such as the half-normal. The models share many of the features of the widely-used "key function plus series adjustment" (K+A) formulation: they are flexible, produce plausible shapes with a small number of parameters, allow incorporation of covariates in addition to distance and can be fitted using maximum likelihood. One important advantage over the K+A approach is that the mixtures are automatically monotonic non-increasing and non-negative, so constrained optimization is not required to ensure distance sampling assumptions are honoured. We compare the mixture formulation to the K+A approach using simulations to evaluate its applicability in a wide set of challenging situations. We also re-analyze four previously problematic real-world case studies. We find mixtures outperform K+A methods in many cases, particularly spiked line transect data (i.e., where detectability drops rapidly at small distances) and larger sample sizes. We recommend that current standard model selection methods for distance sampling detection functions are extended to include mixture models in the candidate set.