Myofiber-specific lipidomics unveil differential contributions to insulin sensitivity in individuals of African and European ancestry.

Aims: Individuals of African ancestry (AA) present with lower insulin sensitivity compared to their European counterparts (EA). Studies show ethnic differences in skeletal muscle fiber type (lower type I fibers in AA), muscle fat oxidation capacity (lower in AA), whilst no differences in total skeletal muscle lipids. However, skeletal muscle lipid subtypes have not been examined in this context. We hypothesize that lower insulin sensitivity in AA is due to a greater proportion of type II (non-oxidative) muscle fibers, and that this would result in an ancestry-specific association between muscle lipid subtypes and peripheral insulin sensitivity. To test this hypothesis, we examined the association between insulin sensitivity and muscle lipids in AA and EA adults, and in an animal model of insulin resistance with muscle-specific fiber types. Methods: In this cross-sectional study, muscle biopsies were obtained from individuals with a BMI ranging from normal to overweight with AA (N = 24) and EA (N = 19). Ancestry was assigned via genetic admixture analysis; peripheral insulin sensitivity via hyperinsulinaemic-euglycemic clamp; and myofiber content via myosin heavy chain immunohistochemistry. Further, muscle types with high (soleus) and low (vastus lateralis) type I fiber content were obtained from high-fat diet-induced insulin resistant F1 mice and littermate controls. Insulin sensitivity in mice was assessed via intraperitoneal glucose tolerance test. Mass spectrometry (MS)-based lipidomics was used to measure skeletal muscle lipid. Results: Compared to EA, AA had lower peripheral insulin sensitivity and lower oxidative type 1 myofiber content, with no differences in total skeletal muscle lipid content. Muscles with lower type I fiber content (AA and vastus from mice) showed lower levels of lipids associated with fat oxidation capacity, i.e., cardiolipins, triacylglycerols with low saturation degree and phospholipids, compared to muscles with a higher type 1 fiber content (EA and soleus from mice). Further, we found that muscle diacylglycerol content was inversely associated with insulin sensitivity in EA, who have more type I fiber, whereas no association was found in AA. Similarly, we found that insulin sensitivity in mice was associated with diacylglycerol content in the soleus (high in type I fiber), not in vastus (low in type I fiber).Conclusions; Our data suggest that the lipid contribution to altered insulin sensitivity differs by ethnicity due to myofiber composition, and that this needs to be considered to increase our understanding of underlying mechanisms of altered insulin sensitivity in different ethnic populations.

Adverse Drug Event-Related Hospital Admissions among Australian Aged Care Residents: A Cross-Sectional Study.

OBJECTIVES: To investigate the proportion, characteristics, causality, severity, preventability, and independently associated factors for adverse drug event (ADE)-related admissions in aged care residents admitted to the major public hospitals in Tasmania, Australia. DESIGN: Retrospective cross-sectional study. SETTING AND PARTICIPANTS: Residential aged care facility (RACF) patients aged ≥65 years who had an unplanned admission to one of the 4 Tasmanian public hospitals between July 1, 2018, and June 30, 2021. METHODS: We accessed the medical records of RACF patients. The ADEs were initially identified via chart review and a trigger tool. Hospitalizations attributable to ADEs were then determined by expert consensus. The causality, preventability, and severity of each ADE admission were assessed using standard criteria. RESULTS: Ninety-one residents (18.2%) of 500 randomly selected experienced potential ADE-related hospitalizations. ADEs were considered possible (n = 58, 64%) or definite/probable (n = 33, 36%). The most common ADEs were falls (n = 19, 21%), hypotension (n = 16, 18%), and confusion or delirium (n = 10, 11%). ADEs were frequently associated with renin-angiotensin system inhibitors (n = 43, 47.3%), opioids (n = 43, 47.3%), and diuretics (n = 40, 44%). Most ADEs were of moderate severity (n = 90, 99%) and considered not preventable (n = 60, 66%). Rheumatologic disease [odds ratio (OR) 1.89, 95% CI 1.09-3.30; P = .024] and previous adverse drug reaction (ADR) (OR 12.91, 95% CI 6.84-24.37; P < .001) were associated with ADE hospitalizations. CONCLUSIONS AND IMPLICATIONS: This study highlights that hospitalization for moderately severe ADEs is common among RACF residents. Opioids and antihypertensives were the common drug classes associated with harm. Rheumatologic disease (due to opioids) and previous ADR were identified as independently associated factors, which may warrant tailored interventions.

Overcoming Xenoantigen Immunity to Enable Cellular Tracking and Gene Regulation with Immune-competent "NoGlow" Mice.

The ability to temporally regulate gene expression and track labeled cells makes animal models powerful biomedical tools. However, sudden expression of xenobiotic genes [e.g., GFP, luciferase (Luc), or rtTA3] can trigger inadvertent immunity that suppresses foreign protein expression or results in complete rejection of transplanted cells. Germline exposure to foreign antigens somewhat addresses these challenges; however, native fluorescence and bioluminescence abrogates the utility of reporter proteins and highly spatiotemporally restricted expression can lead to suboptimal xenoantigen tolerance. To overcome these unwanted immune responses and enable reliable cell tracking/gene regulation, we developed a novel mouse model that selectively expresses antigen-intact but nonfunctional forms of GFP and Luc, as well as rtTA3, after CRE-mediated recombination. Using tissue-specific CREs, we observed model and sex-based differences in immune tolerance to the encoded xenoantigens, illustrating the obstacles of tolerizing animals to foreign genes and validating the utility of these "NoGlow" mice to dissect mechanisms of central and peripheral tolerance. Critically, tissue unrestricted NoGlow mice possess no detectable background fluorescence or luminescence and exhibit limited adaptive immunity against encoded transgenic xenoantigens after vaccination. Moreover, we demonstrate that NoGlow mice allow tracking and tetracycline-inducible gene regulation of triple-transgenic cells expressing GFP/Luc/rtTA3, in contrast to transgene-negative immune-competent mice that eliminate these cells or prohibit metastatic seeding. Notably, this model enables de novo metastasis from orthotopically implanted, triple-transgenic tumor cells, despite high xenoantigen expression. Altogether, the NoGlow model provides a critical resource for in vivo studies across disciplines, including oncology, developmental biology, infectious disease, autoimmunity, and transplantation. SIGNIFICANCE: Multitolerant NoGlow mice enable tracking and gene manipulation of transplanted tumor cells without immune-mediated rejection, thus providing a platform to investigate novel mechanisms of adaptive immunity related to metastasis, immunotherapy, and tolerance.

Aging and intraocular pressure homeostasis in mice.

Age and elevated intraocular pressure (IOP) are the two primary risk factors for glaucoma, an optic neuropathy that is the leading cause of irreversible blindness. In most people, IOP is tightly regulated over a lifetime by the conventional outflow tissues. However, the mechanistic contributions of age to conventional outflow dysregulation, elevated IOP and glaucoma are unknown. To address this gap in knowledge, we studied how age affects the morphology, biomechanical properties and function of conventional outflow tissues in C57BL/6 mice, which have an outflow system similar to humans. As reported in humans, we observed that IOP in mice was maintained within a tight range over their lifespan. Remarkably, despite a constellation of age-related changes to the conventional outflow tissues that would be expected to hinder aqueous drainage and impair homeostatic function (decreased cellularity, increased pigment accumulation, increased cellular senescence and increased stiffness), outflow facility, a measure of conventional outflow tissue fluid conductivity, was stable with age. We conclude that the murine conventional outflow system has significant functional reserve in healthy eyes. However, these age-related changes, when combined with other underlying factors, such as genetic susceptibility, are expected to increase risk for ocular hypertension and glaucoma.

Using in-abattoir 3-dimensional measurements from images of beef carcasses for the prediction of EUROP classification grade and carcass weight.

Imaging technology can aid the automatic extraction of measurements from beef carcasses, which can be used for objective grading. Many abattoirs, however, rely on manual grading due to the required infrastructure and cost, making technology unfeasible. This study explores 3-dimensional (3D) imaging technology, requiring limited infrastructure, and its ability to predict carcass weight, conformation class and fat class for non-invasive, objective classification. Time-of-flight near-infrared cameras captured 3-dimensional point clouds of beef carcasses, on-line in one commercial abattoir in Scotland, over a 6-month period. Thirty-five 3D images were captured per carcass and processed using machine vison software. Seventy-four measurements were extracted from each point cloud. Removal of extreme outliers resulted in 285,109 datapoints for 17,250 carcasses. Coefficients of variation (CV) for each measurement on a per-animal basis were low and consistent, and measurements were averaged across images. Using a training and validation dataset (70:30), multiple linear regression models predicted EUROP conformation class, fat class, and carcass weight. Stepwise models included fixed effects (sex, breed type, kill date (and cold carcass weight for conformation and fat class)), and 3D image measurements. Including 3D measurements resulted in prediction accuracies of 70%, 50% and 23% for cold carcass weight, conformation, and fat class respectively. Mapping predictions on the traditional EUROP grid used in the UK showed that 99% of conformation classes and 93% of fat classes were classified within the correct or neighbouring grade. The results of this study indicate the potential for non-invasive, in-abattoir technology requiring limited infrastructure to predict carcass traits objectively.

Aging and intraocular pressure homeostasis in mice.

Age and elevated intraocular pressure (IOP) are the two primary risk factors for glaucoma, an optic neuropathy that is the leading cause of irreversible blindness. In most people, IOP is tightly regulated over a lifetime by the conventional outflow tissues. However, the mechanistic contributions of age to conventional outflow dysregulation, elevated IOP and glaucoma are unknown. To address this gap in knowledge, we studied how age affects the morphology, biomechanical properties and function of conventional outflow tissues in C57BL/6 mice, which have an outflow system similar to humans. As reported in humans, we observed that IOP in mice was maintained within a tight range over their lifespan. Remarkably, despite a constellation of age-related changes to the conventional outflow tissues that would be expected to hinder aqueous drainage and impair homeostatic function (decreased cellularity, increased pigment accumulation, increased cellular senescence and increased stiffness), outflow facility, a measure of conventional outflow tissue fluid conductivity, was stable with age. We conclude that the murine conventional outflow system has significant functional reserve in healthy eyes. However, these age-related changes, when combined with other underlying factors, such as genetic susceptibility, are expected to increase risk for ocular hypertension and glaucoma.

The WUR0000125 PRRS resilience SNP had no apparent effect on pigs' infectivity and susceptibility in a novel transmission trial.

BACKGROUND: Porcine reproductive and respiratory syndrome (PRRS) remains one of the most important infectious diseases for the pig industry. A novel small-scale transmission experiment was designed to assess whether the WUR0000125 (WUR for Wageningen University and Research) PRRS resilience single nucleotide polymorphism (SNP) confers lower susceptibility and infectivity to pigs under natural porcine reproductive and respiratory syndrome virus (PRRSV-2) transmission. METHODS: Commercial full- and half-sib piglets (n = 164) were assigned as either Inoculation, Shedder, or Contact pigs. Pigs were grouped according to their relatedness structure and WUR genotype, with R- and R+ referring to pigs with zero and one copy of the dominant WUR resilience allele, respectively. Barcoding of the PRRSV-2 strain (SD09-200) was applied to track pig genotype-specific transmission. Blood and nasal swab samples were collected and concentrations of PRRSV-2 were determined by quantitative (q)-PCR and cell culture and expressed in units of median tissue culture infectious dose (TCID50). The Log10TCID50 at each sampling event, derived infection status, and area under the curve (AUC) were response variables in linear and generalized linear mixed models to infer WUR genotype differences in Contact pig susceptibility and Shedder pig infectivity. RESULTS: All Shedder and Contact pigs, except one, became infected through natural transmission. There was no significant (p > 0.05) effect of Contact pig genotype on any virus measures that would indicate WUR genotype differences in susceptibility. Contact pigs tended to have higher serum AUC (p = 0.017) and log10TCID50 (p = 0.034) when infected by an R+ shedder, potentially due to more infectious R+ shedders at the early stages of the transmission trial. However, no significant Shedder genotype effect was found in serum (p = 0.274) or nasal secretion (p = 0.951) that would indicate genotype differences in infectivity. CONCLUSIONS: The novel design demonstrated that it is possible to estimate genotype effects on Shedder pig infectivity and Contact pig susceptibility that are not confounded by family effects. The study, however, provided no supportive evidence that genetic selection on WUR genotype would affect PRRSV-2 transmission. The results of this study need to be independently validated in a larger trial using different PRRSV strains before dismissing the effects of the WUR marker or the previously detected GBP5 gene on PRRSV transmission.

Genetic differentiation following recent domestication events: A study of farmed Nile tilapia (Oreochromis niloticus) populations.

Nile tilapia (Oreochromis niloticus) is among the most farmed finfish worldwide, distributed across different environmental conditions. Its wide distribution has mainly been facilitated by several breeding programs and widespread dissemination of genetically improved strains. In the first Nile tilapia study exploiting a whole-genome pooled sequencing (Poolseq) approach, we identified the genetic structure and signatures of selection in diverse, farmed Nile tilapia populations, with a particular focus on the GIFT strain, developed in the 1980s, and currently managed by WorldFish (GIFTw). We also investigated important farmed strains from The Philippines and Africa. Using both SNP array data and Poolseq SNPs, we characterized the population structure of these samples. We observed the greatest separation between the Asian and African populations and greater admixture in the Asian populations than in the African ones. We also established that the SNP array data were able to successfully resolve relationships between these diverse Nile tilapia populations. The Poolseq data identified genomic regions with high levels of differentiation (F ST) between GIFTw and the other populations. Gene ontology terms associated with mesoderm development were significantly enriched in the genes located in these regions. A region on chromosome Oni06 was genetically differentiated in pairwise comparisons between GIFTw and all other populations. This region contains genes associated with muscle-related traits and overlaps with a previously published QTL for fillet yield, suggesting that these traits may have been direct targets for selection on GIFT. A nearby region was also identified using XP-EHH to detect genomic differentiation using the SNP array data. Genomic regions with high or extended homozygosity within each population were also identified. This study provides putative genomic landmarks associated with the recent domestication process in several Nile tilapia populations, which could help to inform their genetic management and improvement.

Exploring the value of genomic predictions to simultaneously improve production potential and resilience of farmed animals.

Sustainable livestock production requires that animals have a high production potential but are also highly resilient to environmental challenges. The first step to simultaneously improve these traits through genetic selection is to accurately predict their genetic merit. In this paper, we used simulations of sheep populations to assess the effect of genomic data, different genetic evaluation models and phenotyping strategies on prediction accuracies and bias for production potential and resilience. In addition, we also assessed the effect of different selection strategies on the improvement of these traits. Results show that estimation of both traits greatly benefits from taking repeated measurements and from using genomic information. However, the prediction accuracy for production potential is compromised, and resilience estimates tends to be upwards biased, when families are clustered in groups even when genomic information is used. The prediction accuracy was also found to be lower for both traits, resilience and production potential, when the environment challenge levels are unknown. Nevertheless, we observe that genetic gain in both traits can be achieved even in the case of unknown environmental challenge, when families are distributed across a large range of environments. Simultaneous genetic improvement in both traits however greatly benefits from the use of genomic evaluation, reaction norm models and phenotyping in a wide range of environments. Using models without the reaction norm in scenarios where there is a trade-off between resilience and production potential, and phenotypes are collected from a narrow range of environments may result in a loss for one trait. The study demonstrates that genomic selection coupled with reaction-norm models offers great opportunities to simultaneously improve productivity and resilience of farmed animals even in the case of a trade-off.

The First Interchangeable Biosimilar Insulin: Insulin Glargine-yfgn.

On March 23, 2020, all insulin products were reclassified as biologics instead of drugs under the Biological Price Competition and Innovation (BPCI) Act of 2009. This allows biosimilar insulin products to be manufactured when the patent expires for the reference biologic, sometimes called the originator or brand name product. A biosimilar product may not be substituted for the reference biologic at the pharmacy counter unless the biosimilar undergoes further switch trials to earn the designation as an interchangeable biosimilar. Insulin glargine-yfgn 100 units/mL is the first biosimilar insulin to attain interchangeable status with the reference insulin glargine. In the INSTRIDE 1 and INSTRIDE 2 trials, insulin glargine-yfgn has proven noninferiority regarding blood glucose reduction and adverse effect profile versus reference insulin glargine; even in the INSTRIDE 3 trial in which treatment of diabetes was switched between insulin glargine-yfgn and reference insulin glargine throughout the trial without statistically significant changes to glucose levels or adverse effects. Insulin glargine-yfgn may be substituted at the pharmacy counter without consultation with the prescriber, in accordance with state laws. In suit with other biosimilars, insulin glargine-yfgn's list price is significantly lower than other insulin glargine products. This increases market competition leading to decreases in costs of other insulin glargine products. Many patients who could not previously afford insulin therapy may now have significantly improved access to treatment. Providers will need education to increase awareness of these new biosimilars and interchangeable biosimilar insulin products, cost benefits, and substitution allowances.

Applying genetic technologies to combat infectious diseases in aquaculture.

Disease and parasitism cause major welfare, environmental and economic concerns for global aquaculture. In this review, we examine the status and potential of technologies that exploit genetic variation in host resistance to tackle this problem. We argue that there is an urgent need to improve understanding of the genetic mechanisms involved, leading to the development of tools that can be applied to boost host resistance and reduce the disease burden. We draw on two pressing global disease problems as case studies-sea lice infestations in salmonids and white spot syndrome in shrimp. We review how the latest genetic technologies can be capitalised upon to determine the mechanisms underlying inter- and intra-species variation in pathogen/parasite resistance, and how the derived knowledge could be applied to boost disease resistance using selective breeding, gene editing and/or with targeted feed treatments and vaccines. Gene editing brings novel opportunities, but also implementation and dissemination challenges, and necessitates new protocols to integrate the technology into aquaculture breeding programmes. There is also an ongoing need to minimise risks of disease agents evolving to overcome genetic improvements to host resistance, and insights from epidemiological and evolutionary models of pathogen infestation in wild and cultured host populations are explored. Ethical issues around the different approaches for achieving genetic resistance are discussed. Application of genetic technologies and approaches has potential to improve fundamental knowledge of mechanisms affecting genetic resistance and provide effective pathways for implementation that could lead to more resistant aquaculture stocks, transforming global aquaculture.

The cost of host genetic resistance on body condition: Evidence from divergently selected sheep.

Trade-offs between host resistance to parasites and host growth or reproduction can occur due to allocation of limited available resources between competing demands. To predict potential trade-offs arising from genetic selection for host resistance, a better understanding of the associated nutritional costs is required. Here, we studied resistance costs by using sheep from lines divergently selected on their resistance to a common blood-feeding gastro-intestinal parasite (Haemonchus contortus). First, we assessed the effects of selection for high or low host resistance on condition traits (body weight, back fat, and muscle thickness) and infection traits (parasite fecal egg excretion and loss in blood haematocrit) at various life stages, in particular during the periparturient period when resource allocation to immunity may limit host resistance. Second, we analysed the condition-infection relationship to detect a possible trade-off, in particular during the periparturient period. We experimentally infected young females in four stages over their first 2 years of life, including twice around parturition (at 1 year and at 2 years of age). Linear mixed-model analyses revealed a large and consistent between-line difference in infection traits during growth and outside of the periparturient period, whereas this difference was strongly attenuated during the periparturient period. Despite their different responses to infection, lines had similar body condition traits. Using covariance decomposition, we then found that the phenotypic relationship between infection and condition was dominated by direct infection costs arising from parasite development within the host. Accounting for these within-individual effects, a cost of resistance on body weight was detected among ewes during their first reproduction. Although this cost and the reproductive constraint on resistance are unlikely to represent a major concern for animal breeding in nutrient-rich environments, this study provides important new insights regarding the nutritional costs of parasite resistance at different lifestages and how these may affect response to selection.

Optimal experimental designs for estimating genetic and non-genetic effects underlying infectious disease transmission.

BACKGROUND: The spread of infectious diseases in populations is controlled by the susceptibility (propensity to acquire infection), infectivity (propensity to transmit infection), and recoverability (propensity to recover/die) of individuals. Estimating genetic risk factors for these three underlying host epidemiological traits can help reduce disease spread through genetic control strategies. Previous studies have identified important 'disease resistance single nucleotide polymorphisms (SNPs)', but how these affect the underlying traits is an unresolved question. Recent advances in computational statistics make it now possible to estimate the effects of SNPs on host traits from epidemic data (e.g. infection and/or recovery times of individuals or diagnostic test results). However, little is known about how to effectively design disease transmission experiments or field studies to maximise the precision with which these effects can be estimated. RESULTS: In this paper, we develop and validate analytical expressions for the precision of the estimates of SNP effects on the three above host traits for a disease transmission experiment with one or more non-interacting contact groups. Maximising these expressions leads to three distinct 'experimental' designs, each specifying a different set of ideal SNP genotype compositions across groups: (a) appropriate for a single contact-group, (b) a multi-group design termed "pure", and (c) a multi-group design termed "mixed", where 'pure' and 'mixed' refer to groupings that consist of individuals with uniformly the same or different SNP genotypes, respectively. Precision estimates for susceptibility and recoverability were found to be less sensitive to the experimental design than estimates for infectivity. Whereas the analytical expressions suggest that the multi-group pure and mixed designs estimate SNP effects with similar precision, the mixed design is preferred because it uses information from naturally-occurring rather than artificial infections. The same design principles apply to estimates of the epidemiological impact of other categorical fixed effects, such as breed, line, family, sex, or vaccination status. Estimation of SNP effect precisions from a given experimental setup is implemented in an online software tool SIRE-PC. CONCLUSIONS: Methodology was developed to aid the design of disease transmission experiments for estimating the effect of individual SNPs and other categorical variables that underlie host susceptibility, infectivity and recoverability. Designs that maximize the precision of estimates were derived.

Ecological and evolutionary dynamics of multi-strain RNA viruses.

Potential interactions among co-circulating viral strains in host populations are often overlooked in the study of virus transmission. However, these interactions probably shape transmission dynamics by influencing host immune responses or altering the relative fitness among co-circulating strains. In this Review, we describe multi-strain dynamics from ecological and evolutionary perspectives, outline scales in which multi-strain dynamics occur and summarize important immunological, phylogenetic and mathematical modelling approaches used to quantify interactions among strains. We also discuss how host-pathogen interactions influence the co-circulation of pathogens. Finally, we highlight outstanding questions and knowledge gaps in the current theory and study of ecological and evolutionary dynamics of multi-strain viruses.

Genetic Associations of Novel Behaviour Traits Derived from Social Network Analysis with Growth, Feed Efficiency, and Carcass Characteristics in Pigs.

Reducing harmful aggressive behaviour remains a major challenge in pig production. Social network analysis (SNA) showed the potential in providing novel behavioural traits that describe the direct and indirect role of individual pigs in pen-level aggression. Our objectives were to (1) estimate the genetic parameters of these SNA traits, and (2) quantify the genetic associations between the SNA traits and commonly used performance measures: growth, feed intake, feed efficiency, and carcass traits. The animals were video recorded for 24 h post-mixing. The observed fighting behaviour of each animal was used as input for the SNA. A Bayesian approach was performed to estimate the genetic parameters of SNA traits and their association with the performance traits. The heritability estimates for all SNA traits ranged from 0.01 to 0.35. The genetic correlations between SNA and performance traits were non-significant, except for weighted degree with hot carcass weight, and for both betweenness and closeness centrality with test daily gain, final body weight, and hot carcass weight. Our results suggest that SNA traits are amenable for selective breeding. Integrating these traits with other behaviour and performance traits may potentially help in building up future strategies for simultaneously improving welfare and performance in commercial pig farms.

Estimation of age-stratified contact rates during the COVID-19 pandemic using a novel inference algorithm.

Well parameterized epidemiological models including accurate representation of contacts are fundamental to controlling epidemics. However, age-stratified contacts are typically estimated from pre-pandemic/peace-time surveys, even though interventions and public response likely alter contacts. Here, we fit age-stratified models, including re-estimation of relative contact rates between age classes, to public data describing the 2020-2021 COVID-19 outbreak in England. This data includes age-stratified population size, cases, deaths, hospital admissions and results from the Coronavirus Infection Survey (almost 9000 observations in all). Fitting stochastic compartmental models to such detailed data is extremely challenging, especially considering the large number of model parameters being estimated (over 150). An efficient new inference algorithm ABC-MBP combining existing approximate Bayesian computation (ABC) methodology with model-based proposals (MBPs) is applied. Modified contact rates are inferred alongside time-varying reproduction numbers that quantify changes in overall transmission due to pandemic response, and age-stratified proportions of asymptomatic cases, hospitalization rates and deaths. These inferences are robust to a range of assumptions including the values of parameters that cannot be estimated from available data. ABC-MBP is shown to enable reliable joint analysis of complex epidemiological data yielding consistent parametrization of dynamic transmission models that can inform data-driven public health policy and interventions. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Estropause, Sex Hormones and Metal Homeostasis in the Mouse Brain.

Alterations in brain metal ion homeostasis have been reported with aging and are implicated in the pathogenesis of neurodegenerative diseases. To assess whether age-related changes in hypothalamic-pituitary-gonadal (HPG) hormones might be involved in modulating brain metal ion homeostasis, we treated 7.5-month intact, sham-ovariecomized and ovariectomized C57B6SJL mice with vehicle or leuprolide acetate (for 9-months) to differentiate between whether sex steroids or gonadotropins might modulate brain metal ion concentrations. Unlike other aging mammals, there was no increase in plasma luteinizing hormone (LH) and follicle-stimulating hormone (FSH) concentrations following estropause in mice, suggesting there was sufficient residual production by the follicle depleted ovary, of sex steroids like estrogens and protein hormones like the inhibins, in order to suppress pituitary LH/FSH production. Castration on the other hand induced significant increases in circulating LH and FSH. Modulation of plasma sex steroid and gonadotropin levels did not significantly alter the concentrations of brain metals tested (Fe, Zn, Cu, Mn, Co, Ni, Al, Li), although there was a tendency for a decrease in all brain metals following ovariectomy (low estrogens and progesterone, high gonadotropins), a response that was reversed with leuprolide acetate treatment (low sex steroids, low gonadotropins). Brain Cu concentration was the only metal correlated with plasma LH (-0.37, n = 30, p < 0.05) and FSH (-0.42, n = 29, p < 0.01). This study demonstrates that sex hormones do not markedly alter brain metal ion homeostasis, unlike previously reported studies of circulating metal ion homeostasis. The role of gonadotropins in regulating metal ion homeostasis does however warrant further study.

Genetic Analysis of Novel Behaviour Traits in Pigs Derived from Social Network Analysis.

Social network analysis (SNA) has provided novel traits that describe the role of individual pigs in aggression. The objectives were to (1) estimate the genetic parameters for these SNA traits, (2) quantify the genetic association between SNA and skin lesion traits, and (3) investigate the possible response to selection for SNA traits on skin lesion traits. Pigs were video recorded for 24 h post-mixing. The observed fight and bullying behaviour of each animal was used as input for the SNA. Skin lesions were counted on different body parts at 24 h (SL24h) and 3 weeks (SL3wk) post-mixing. A Bayesian approach estimated the genetic parameters of SNA traits and their association with skin lesions. SNA traits were heritable (h2 = 0.09 to 0.26) and strongly genetically correlated (rg > 0.88). Positive genetic correlations were observed between all SNA traits and anterior SL24h, except for clustering coefficient. Our results suggest that selection for an index that combines the eigenvector centrality and clustering coefficient could potentially decrease SL24h and SL3wk compared to selection for each trait separately. This study provides a first step towards potential integration of SNA traits into a multi-trait selection index for improving pigs' welfare.

Modeling suggests gene editing combined with vaccination could eliminate a persistent disease in livestock.

Recent breakthroughs in gene-editing technologies that can render individual animals fully resistant to infections may offer unprecedented opportunities for controlling future epidemics in farm animals. Yet, their potential for reducing disease spread is poorly understood as the necessary theoretical framework for estimating epidemiological effects arising from gene-editing applications is currently lacking. Here, we develop semistochastic modeling approaches to investigate how the adoption of gene editing may affect infectious disease prevalence in farmed animal populations and the prospects and time scale for disease elimination. We apply our models to the porcine reproductive and respiratory syndrome (PRRS), one of the most persistent global livestock diseases to date. Whereas extensive control efforts have shown limited success, recent production of gene-edited pigs that are fully resistant to the PRRS virus have raised expectations for eliminating this deadly disease. Our models predict that disease elimination on a national scale would be difficult to achieve if gene editing was used as the only disease control. However, from a purely epidemiological perspective, disease elimination may be achievable within 3 to 6 y, if gene editing were complemented with widespread and sufficiently effective vaccination. Besides strategic distribution of genetically resistant animals, several other key determinants underpinning the epidemiological impact of gene editing were identified.

A laboratory and simulation platform to integrate individual life history traits and population dynamics.

Understanding populations is important because they are a fundamental level of biological organization. Individual traits such as aging and lifespan interact in complex ways to determine birth and death and thereby influence population dynamics. However, we lack a deep understanding of the relationships between individual traits and population dynamics. To address this challenge, we established a laboratory population using the model organism C. elegans and an individual-based computational simulation informed by measurements of real worms. The simulation realistically models individual worms and the behavior of the laboratory population. To elucidate the role of aging in population dynamics, we analyzed old age as a cause of death and showed, using computer simulations, that it was influenced by maximum lifespan, rate of adult culling, and progeny number/food stability. Notably, populations displayed a tipping point for aging as the primary cause of adult death. Our work establishes a conceptual framework that could be used for better understanding why certain animals die of old age in the wild.