Ectopic expression of murine CD163 enables cell-culture isolation of lactate dehydrogenase-elevating virus 63 years after its discovery.

IMPORTANCE: Mouse models of viral infection play an especially large role in virology. In 1960, a mouse virus, lactate dehydrogenase-elevating virus (LDV), was discovered and found to have the peculiar ability to evade clearance by the immune system, enabling it to persistently infect an individual mouse for its entire lifespan without causing overt disease. However, researchers were unable to grow LDV in culture, ultimately resulting in the demise of this system as a model of failed immunity. We solve this problem by identifying the cell-surface molecule CD163 as the critical missing component in cell-culture systems, enabling the growth of LDV in immortalized cell lines for the first time. This advance creates abundant opportunities for further characterizing LDV in order to study both failed immunity and the family of viruses to which LDV belongs, Arteriviridae (aka, arteriviruses).

Conditional Loss of MEF2C Expression in Osteoclasts Leads to a Sex-Specific Osteopenic Phenotype.

Myocyte enhancement factor 2C (MEF2C) is a transcription factor studied in the development of skeletal and smooth muscles. Bone resorption studies have exhibited that the reduced expression of MEF2C contributes to osteopetrosis and the dysregulation of pathological bone remodeling. Our current study aims to determine how MEF2C contributes to osteoclast differentiation and to analyze the skeletal phenotype of Mef2c-cKO mice (Cfms-cre; Mef2cfl/fl). qRT-PCR and Western blot demonstrated that Mef2c expression is highest during the early days of osteoclast differentiation. Osteoclast genes, including c-Fos, c-Jun, Dc-stamp, Cathepsin K, and Nfatc1, had a significant reduction in expression, along with a reduction in osteoclast size. Despite reduced CTX activity, female Mef2c cKO mice were osteopenic, with decreased bone formation as determined via a P1NP ELISA, and a reduced number of osteoblasts. There was no difference between male WT and Mef2c-cKO mice. Our results suggest that Mef2c is critical for osteoclastogenesis, and that its dysregulation leads to a sex-specific osteopenic phenotype.

Cardiorespiratory Optimisation By Arteriovenous fistula Ligation after renal Transplantation (COBALT): study protocol for a multicentre randomised interventional feasibility trial.

INTRODUCTION: Cardiovascular events are a major cause of mortality following successful kidney transplantation.Arteriovenous fistulas (AVFs) are considered the best option for haemodialysis, but may contribute to this excess mortality because they promote adverse cardiac remodelling and ventricular hypertrophy. This raises the question whether recipients with a well-functioning kidney transplant should undergo elective AVF ligation. METHODS AND ANALYSIS: The COBALT feasibility study is a multicentre interventional randomised controlled trial (RCT) that will randomise renal transplant patients with stable graft function and a working AVF on a 1:1 basis to standard care (continued conservative management) or to AVF ligation. All patients will perform cardiopulmonary exercise testing (CPET) on recruitment and 6 months later. Daily functioning and quality of life will be additionally assessed by questionnaire completion and objective measure of physical activity. The primary outcome-the proportion of approached patients who complete the study (incorporating rates of consent, receipt of allocated intervention and completion of both CPETs without withdrawal)-will determine progression to a full-scale RCT. Design of the proposed RCT will be informed by an embedded qualitative assessment of participant and healthcare professional involvement. ETHICS AND DISSEMINATION: This study has been approved by the East Midlands-Derby Research Ethics Committee (22/EM/0002) and the Health Research Authority. The results of this work will be disseminated academically through presentation at national and international renal meetings and via open access, peer-reviewed outputs. Existing networks of renal patient groups will also be used to disseminate the study findings to other key stakeholders. TRIAL REGISTRATION NUMBER: ISRCTN49033491.

Estrogen regulation of myokines that enhance osteoclast differentiation and activity.

Osteoporosis and sarcopenia are maladies of aging that negatively affect more women than men. In recent years, it has become apparent that bone and muscle are coupled not only mechanically as muscle pulls on bone, but also at a higher level with myokines, biochemical and molecular signaling occurring between cells of the two tissues. However, how estrogen deficiency in females impacts the chemical crosstalk between bone and muscle cells is not understood. We hypothesize that changes in estrogen signaling alters myokine expression and intensifies bone loss in women. In our present study, we demonstrate that conditioned media from ovariectomized or skeletal muscle deficient in estrogen receptor α (ERα) expression enhances osteoclast differentiation and activity. Using a cytokine array, we identified myokines that have altered expressions in response to loss of estrogen signaling in muscle. Lastly, we demonstrate that conditional deletion of ERα in skeletal muscle results in osteopenia due to an increase in the osteoclast surface per bone surface. Our results suggest that estrogen signaling modulates expression of myokines that regulate osteoclast differentiation and activity.

Phlpp1 is induced by estrogen in osteoclasts and its loss in Ctsk-expressing cells does not protect against ovariectomy-induced bone loss.

Prior studies demonstrated that deletion of the protein phosphatase Phlpp1 in Ctsk-Cre expressing cells enhances bone mass, characterized by diminished osteoclast activity and increased coupling to bone formation. Due to non-specific expression of Ctsk-Cre, the definitive mechanism for this observation was unclear. To further define the role of bone resorbing osteoclasts, we performed ovariectomy (Ovx) and Sham surgeries on Phlpp1 cKOCtsk and WT mice. Micro-CT analyses confirmed enhanced bone mass of Phlpp1 cKOCtsk Sham females. In contrast, Ovx induced bone loss in both groups, with no difference between Phlpp1 cKOCtsk and WT mice. Histomorphometry demonstrated that Ovx mice lacked differences in osteoclasts per bone surface, suggesting that estradiol (E2) is required for Phlpp1 deficiency to have an effect. We performed high throughput unbiased transcriptional profiling of Phlpp1 cKOCtsk osteoclasts and identified 290 differentially expressed genes. By cross-referencing these differentially expressed genes with all estrogen response element (ERE) containing genes, we identified IGFBP4 as potential estrogen-dependent target of Phlpp1. E2 induced PHLPP1 expression, but reduced IGFBP4 levels. Moreover, genetic deletion or chemical inhibition of Phlpp1 was correlated with IGFBP4 levels. We then assessed IGFBP4 expression by osteoclasts in vivo within intact 12-week-old females. Modest IGFBP4 immunohistochemical staining of TRAP+ osteoclasts within WT females was observed. In contrast, TRAP+ bone lining cells within intact Phlpp1 cKOCtsk females robustly expressed IGFBP4, but levels were diminished within TRAP+ bone lining cells following Ovx. These results demonstrate that effects of Phlpp1 conditional deficiency are lost following Ovx, potentially due to estrogen-dependent regulation of IGFBP4.

Tissue selective effects of bazedoxifene on the musculoskeletal system in female mice.

The actions of selective estrogen receptor modulators are tissue dependent. The primary objective of the current study was to determine the tissue selective effects of bazedoxifene (BZA) on the musculoskeletal system of ovariectomized (OVX) female mice, focusing on the strengths of muscle-bone pairs in the lower hindlimb. Treatment with BZA after ovariectomy (OVX+BZA) did not prevent body or fat mass gains (P < 0.05). In vivo plantarflexor muscle isometric torque was not affected by treatment with BZA (P = 0.522). Soleus muscle peak isometric, concentric and eccentric tetanic force production were greater in OVX+BZA mice compared to OVX+E2 mice (P ≤ 0.048) with no effect on maximal isometric specific force (P = 0.228). Tibia from OVX+BZA mice had greater cortical cross-sectional area and moment of inertia than OVX mice treated with placebo (P < 0.001), but there was no impact of BZA treatment on cortical bone mineral density, cortical thickness, tibial bone ultimate load or stiffness (P ≥ 0.086). Overall, these results indicate that BZA may be an estrogen receptor agonist in skeletal muscle, as it has previously been shown in bone, providing minor benefits to the musculoskeletal system.

Hdac3 deletion in myeloid progenitor cells enhances bone healing in females and limits osteoclast fusion via Pmepa1.

Previous studies examining the role of the histone deacetylase Hdac3 within myeloid cells demonstrated that Hdac3 promotes M2 activation and tissue healing in inflammatory conditions. Since myeloid lineage cells are required for proper bone formation and regeneration, in this study we examined the functions of Hdac3 during bone healing. Conditional deletion of Hdac3 within myeloid progenitors accelerates healing of cortical bone defects. Moreover, reduced osteoclast numbers within the defect site are correlated with Hdac3 suppression. Ex vivo osteoclastogenesis assays further demonstrate that Hdac3 deficiency limits osteoclastogenesis, the number of nuclei per cell and bone resorption, suggesting a defect in cell fusion. High throughput RNA sequencing identified the transmembrane protein Pmepa1 as a differentially expressed gene within osteoclast progenitor cells. Knockdown of Pmepa1 partially restores defects in osteoclastogenesis induced by Hdac3 deficiency. These results show that Hdac3 is required for optimal bone healing and osteoclast fusion, potentially via its regulation of Pmepa1 expression.

FastSK: fast sequence analysis with gapped string kernels.

MOTIVATION: Gapped k-mer kernels with support vector machines (gkm-SVMs) have achieved strong predictive performance on regulatory DNA sequences on modestly sized training sets. However, existing gkm-SVM algorithms suffer from slow kernel computation time, as they depend exponentially on the sub-sequence feature length, number of mismatch positions, and the task's alphabet size. RESULTS: In this work, we introduce a fast and scalable algorithm for calculating gapped k-mer string kernels. Our method, named FastSK, uses a simplified kernel formulation that decomposes the kernel calculation into a set of independent counting operations over the possible mismatch positions. This simplified decomposition allows us to devise a fast Monte Carlo approximation that rapidly converges. FastSK can scale to much greater feature lengths, allows us to consider more mismatches, and is performant on a variety of sequence analysis tasks. On multiple DNA transcription factor binding site prediction datasets, FastSK consistently matches or outperforms the state-of-the-art gkmSVM-2.0 algorithms in area under the ROC curve, while achieving average speedups in kernel computation of ∼100× and speedups of ∼800× for large feature lengths. We further show that FastSK outperforms character-level recurrent and convolutional neural networks while achieving low variance. We then extend FastSK to 7 English-language medical named entity recognition datasets and 10 protein remote homology detection datasets. FastSK consistently matches or outperforms these baselines. AVAILABILITY AND IMPLEMENTATION: Our algorithm is available as a Python package and as C++ source code at https://github.com/QData/FastSK. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Epigenetic Regulators Involved in Osteoclast Differentiation.

Age related changes to the skeleton, such as osteoporosis, increase the risk of fracture and morbidity in the elderly population. In osteoporosis, bone remodeling becomes unbalanced with an increase in bone resorption and a decrease in bone formation. Osteoclasts are large multinucleated cells that secrete acid and proteases to degrade and resorb bone. Understanding the molecular mechanisms that regulate osteoclast differentiation and activity will provide insight as to how hyper-active osteoclasts lead to pathological bone loss, contributing to diseases such as osteoporosis. Reversible modifications to the DNA such as histone acetylation, methylation, phosphorylation and ubiquitylation alters the access of transcriptional machinery to DNA and regulates gene expression and osteoclast differentiation and activity. It is critical for the management of bone related diseases to understand the role of these chromatin modifying proteins during osteoclast differentiation, as potential therapies targeting these proteins are currently under development.

Loss of myocyte enhancer factor 2 expression in osteoclasts leads to opposing skeletal phenotypes.

Osteoclasts are multinuclear cells that resorb bone. Osteoclast differentiation is regulated by multiple transcription factors which may be acting in a single or multiple factor complex to regulate gene expression. Myocyte enhancer factor 2 (MEF2) is a family of transcription factors whose role during osteoclast differentiation has not been well characterized. Because MEF2A and MEF2D are the family members most highly expressed during osteoclast differentiation, we created conditional knockout mice models for MEF2A and/or MEF2D. In vitro cultures of A- and D-KO osteoclasts were smaller and less numerous than wild type cultures, while AD-KO osteoclasts were almost completely devoid of TRAP positive mononuclear cells. Female A-KO mice are osteopetrotic while male A- and D-KO mice of either sex had no significant in vivo skeletal phenotype, suggesting a sex-specific regulation of osteoclasts by MEF2A. Lastly, in vivo male AD-KO mice are osteopenic, indicating while MEF2 is required for M-CSF and RANKL-stimulated osteoclastogenesis in vitro, osteoclasts can form in the absence of MEF2 in vivo via a RANKL-alternative pathway.

Male mice with elevated C-type natriuretic peptide-dependent guanylyl cyclase-B activity have increased osteoblasts, bone mass and bone strength.

C-type natriuretic peptide (CNP) activation of guanylyl cyclase (GC)-B, also known as NPR2, stimulates cGMP synthesis and bone elongation. CNP activation requires the phosphorylation of multiple GC-B residues and dephosphorylation inactivates the receptor. GC-B7E/7E knockin mice, expressing a glutamate-substituted, "pseudophosphorylated," form of GC-B, exhibit increased CNP-dependent GC activity. Since mutations that constitutively activate GC-B in the absence of CNP result in low bone mineral density in humans, we determined the skeletal phenotype of 9-week old male GC-B7E/7E mice. Unexpectedly, GC-B7E/7E mice have significantly greater tibial and L5 vertebral trabecular bone volume fraction, tibial trabecular number, and tibial bone mineral density. Cortical cross-sectional area, cortical thickness, periosteal diameter and cortical cross-sectional moment of inertia were also significantly increased in GC-B7E/7E tibiae. Three-point bending measurements demonstrated that the mutant tibias and femurs had greater ultimate load, stiffness, energy to ultimate load, and energy to failure. No differences in microhardness indicated similar bone quality at the tissue level between the mutant and wildtype bones. Procollagen 1 N-terminal propeptide and osteocalcin were elevated in serum, and osteoblast number per bone perimeter and osteoid width per bone perimeter were elevated in tibias from the mutant mice. In contrast to mutations that constitutively activate GC-B, we report that mutations that enhance GC-B activity only in the presence of its natural ligand, increase bone mass, bone strength, and the number of active osteoblasts at the bone surface.

Harnessing employment-based social assistance programmes to scale up nature-based climate action.

As the severity of the triple challenges of global inequality, climate change and biodiversity loss becomes clearer, governments and international development institutions must find effective policy instruments to respond. We examine the potential of social assistance policies in this context. Social assistance refers to transfers to poor, vulnerable and marginalized groups to reduce their vulnerability and livelihood risks, and to enhance their rights and status. Substantial public funds support social assistance programmes globally. Collectively, lower- and middle-income countries spend approximately 1.5% of their GDP on social assistance annually. We focus on the potential of paid employment schemes to promote effective ecosystem stewardship. Available evidence suggests such programmes can offer multiple benefits in terms of improvements in local ecosystems and natural capital, carbon sequestration and local biodiversity conservation. We review evidence from three key case studies: in India (the Mahatma Gandhi National Rural Employment Guarantee Scheme), Ethiopia (the Productive Safety Nets Programme) and Mexico (the Temporary Employment Programme). We conclude that, to realize the potential of employment-based social assistance for ecosystem benefits it will be necessary to address two challenges: first, the weak design and maintenance of local public works outputs in many schemes, and second, the concern that social protection schemes may become less effective if they are overburdened with additional objectives. Overcoming these challenges requires an evolution of institutional systems for delivering social assistance to enable a more effective combination of social and environmental objectives. This article is part of the theme issue 'Climate change and ecosystems: threats, opportunities and solutions'.

Economic and environmental efficiency of UK and Ireland water companies: Influence of exogenous factors and rurality.

For water companies, benchmarking their performance relative to other companies can be an effective way to identify the scope for efficiency gains to be made through infrastructure investment and operational improvements. However, a key limitation to benchmarking is the confounding effect of exogenous factors, which may not be factored in to benchmarking methodologies. The purpose of this study was to provide an unbiased comparison of efficiency across a sample of water and sewage companies, accounting for important exogenous factors. Bias-corrected economic and environmental efficiency estimates with explanatory factors were evaluated for a sample of 13 water and sewage companies in the UK and Ireland, using a double-bootstrap data envelopment analysis (DEA) approach. Bias correction for economic and environmental efficiency changed the rankings of nine and eight companies, respectively. On average, companies could reduce economic inputs by 19% and carbon outputs by 16% if they performed at the efficiency frontier. Variables explaining efficiency were: source of water, leakage rate, per capita consumption and population density. Population density showed statistical significance with both economic (p-value 0.002) and environmental (p-value 0.001) efficiency. Consequently, a rurality factor was defined for each company's operational area, which was then regressed against normalised water company performance data. More rural water companies spend more per property (R2 of 0.633), in part reflecting a larger number of smaller sewage treatment works serving rural populations (R2 of 0.823). These findings provide new insight into methods for benchmarking, and factors affecting, water company efficiency, pertinent for both regulators and water companies.

The importance of growing up: juvenile environment influences dispersal of individuals and their neighbours.

Dispersal is a key ecological process that is strongly influenced by both phenotype and environment. Here, we show that juvenile environment influences dispersal not only by shaping individual phenotypes, but also by changing the phenotypes of neighbouring conspecifics, which influence how individuals disperse. We used a model system (Tribolium castaneum, red flour beetles) to test how the past environment of dispersing individuals and their neighbours influences how they disperse in their current environment. We found that individuals dispersed especially far when exposed to a poor environment as adults if their phenotype, or even one-third of their neighbours' phenotypes, were shaped by a poor environment as juveniles. Juvenile environment therefore shapes dispersal both directly, by influencing phenotype, as well as indirectly, by influencing the external social environment. Thus, the juvenile environment of even a minority of individuals in a group can influence the dispersal of the entire group.

A Bayesian state-space model using age-at-harvest data for estimating the population of black bears (Ursus americanus) in Wisconsin.

Population estimation is essential for the conservation and management of fish and wildlife, but accurate estimates are often difficult or expensive to obtain for cryptic species across large geographical scales. Accurate statistical models with manageable financial costs and field efforts are needed for hunted populations and using age-at-harvest data may be the most practical foundation for these models. Several rigorous statistical approaches that use age-at-harvest and other data to accurately estimate populations have recently been developed, but these are often dependent on (a) accurate prior knowledge about demographic parameters of the population, (b) auxiliary data, and (c) initial population size. We developed a two-stage state-space Bayesian model for a black bear (Ursus americanus) population with age-at-harvest data, but little demographic data and no auxiliary data available, to create a statewide population estimate and test the sensitivity of the model to bias in the prior distributions of parameters and initial population size. The posterior abundance estimate from our model was similar to an independent capture-recapture estimate from tetracycline sampling and the population trend was similar to the catch-per-unit-effort for the state. Our model was also robust to bias in the prior distributions for all parameters, including initial population size, except for reporting rate. Our state-space model created a precise estimate of the black bear population in Wisconsin based on age-at-harvest data and potentially improves on previous models by using little demographic data, no auxiliary data, and not being sensitive to initial population size.

Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality.

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause-of-death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.

Isolation and Analysis of Proteoglycans and Glycosaminoglycans from Archaeological Bones and Teeth.

We have developed methods for isolating proteoglycans and glycosaminoglycans from archaeological bones and teeth. These methods have been previously published (Coulson- Thomas et al., 2015 ) and are described here in more detail. In the case of glycosaminoglycans, the method was a previously described method ( Nader et al., 1999 ) which we optimized for archeological samples.

Environmental Factors Influencing White-Tailed Deer (Odocoileus virginianus) Exposure to Livestock Pathogens in Wisconsin.

White-tailed deer (Odocoileus virginianus) are commonly exposed to disease agents that affect livestock but environmental factors that predispose deer to exposure are unknown for many pathogens. We trapped deer during winter months on two study areas (Northern Forest and Eastern Farmland) in Wisconsin from 2010 to 2013. Deer were tested for exposure to six serovars of Leptospira interrogans (grippotyphosa, icterohaemorrhagiae, canicola, bratislava, pomona, and hardjo), bovine viral diarrhea virus (BVDV-1 and BVDV-2), infectious bovine rhinotracheitis virus (IBR), and parainfluenza 3 virus (PI3). We used logistic regression to model potential intrinsic (e.g., age, sex) and extrinsic (e.g., land type, study site, year, exposure to multiple pathogens) variables we considered biologically meaningful to exposure of deer to livestock pathogens. Deer sampled in 2010-2011 did not demonstrate exposure to BVDV, so we did not test for BVDV in subsequent years. Deer had evidence of exposure to PI3 (24.7%), IBR (7.9%), Leptospira interrogans serovar pomona (11.7%), L. i. bratislava (1.0%), L. i. grippotyphosa (2.5%) and L. i. hardjo (0.3%). Deer did not demonstrate exposure to L. interrogans serovars canicola and icterohaemorrhagiae. For PI3, we found that capture site and year influenced exposure. Fawns (n = 119) were not exposed to L. i. pomona, but land type was an important predictor of exposure to L. i. pomona for older deer. Our results serve as baseline exposure levels of Wisconsin white-tailed deer to livestock pathogens, and helped to identify important factors that explain deer exposure to livestock pathogens.

The identification of proteoglycans and glycosaminoglycans in archaeological human bones and teeth.

Bone tissue is mineralized dense connective tissue consisting mainly of a mineral component (hydroxyapatite) and an organic matrix comprised of collagens, non-collagenous proteins and proteoglycans (PGs). Extracellular matrix proteins and PGs bind tightly to hydroxyapatite which would protect these molecules from the destructive effects of temperature and chemical agents after death. DNA and proteins have been successfully extracted from archaeological skeletons from which valuable information has been obtained; however, to date neither PGs nor glycosaminoglycan (GAG) chains have been studied in archaeological skeletons. PGs and GAGs play a major role in bone morphogenesis, homeostasis and degenerative bone disease. The ability to isolate and characterize PG and GAG content from archaeological skeletons would unveil valuable paleontological information. We therefore optimized methods for the extraction of both PGs and GAGs from archaeological human skeletons. PGs and GAGs were successfully extracted from both archaeological human bones and teeth, and characterized by their electrophoretic mobility in agarose gel, degradation by specific enzymes and HPLC. The GAG populations isolated were chondroitin sulfate (CS) and hyaluronic acid (HA). In addition, a CSPG was detected. The localization of CS, HA, three small leucine rich PGs (biglycan, decorin and fibromodulin) and glypican was analyzed in archaeological human bone slices. Staining patterns were different for juvenile and adult bones, whilst adolescent bones had a similar staining pattern to adult bones. The finding that significant quantities of PGs and GAGs persist in archaeological bones and teeth opens novel venues for the field of Paleontology.