Metabolomic analysis identifies altered metabolic pathways in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic, demyelinating disease that affects the central nervous system and is characterized by a complex pathogenesis and difficult management. The identification of new biomarkers would be clinically useful for more accurate diagnoses and disease monitoring. Metabolomics, the identification of small endogenous molecules, offers an instantaneous molecular snapshot of the MS phenotype. Here the metabolomic profiles (utilizing plasma from patients with MS) were characterized with a Gas cromatography-mass spectrometry-based platform followed by a multivariate statistical analysis and comparison with a healthy control (HC) population. The obtained partial least square discriminant analysis (PLS-DA) model identified and validated significant metabolic differences between individuals with MS and HC (R2X = 0.223, R2Y = 0.82, Q2 = 0.562; p < 0.001). Among discriminant metabolites phosphate, fructose, myo-inositol, pyroglutamate, threonate, l-leucine, l-asparagine, l-ornithine, l-glutamine, and l-glutamate were correctly identified, and some resulted as unknown. A receiver operating characteristic (ROC) curve with AUC 0.84 (p = 0.01; CI: 0.75–1) generated with the concentrations of the discriminant metabolites, supported the strength of the model. Pathway analysis indicated asparagine and citrulline biosynthesis as the main canonical pathways involved in MS. Changes in the citrulline biosynthesis pathway suggests the involvement of oxidative stress during neuronal damage. The results confirmed metabolomics as a useful approach to better understand the pathogenesis of MS and to provide new biomarkers for the disease to be used together with clinical data.     

Estimation of parameters in large offspring number models and ratios of coalescence times

The ratio of singletons to the total number of segregating sites is used to estimate a reproduction parameter in a population model of large offspring numbers without having to jointly estimate the mutation rate. For neutral genetic variation, the ratio of singletons to the total number of segregating sites is equivalent to the ratio of total length of external branches to the total length of the gene genealogy. A multinomial maximum likelihood method that takes into account more frequency classes than just the singletons is developed to estimate the parameter of another large offspring number model. The performance of these methods with regard to sample size, mutation rate, and bias, is investigated by simulation. The expected value of the ratio of the total length of external branches to the total length of the whole tree is, using simulation, shown to decrease for the Kingman coalescent as sample size increases, but can increase or decrease, depending on parameter values, for Λ coalescents. Considering ratios of tree statistics, as opposed to considering lengths of various subtrees separately, can yield better insight into the dynamics of gene genealogies.     

Indirect nontarget effects of host-specific biological control agents: Implications for biological control

Classical biological control of weeds currently operates under the assumption that biological control agents are safe (i.e., low risk) if they do not directly attack nontarget species. However, recent studies indicate that even highly host-specific biological control agents can impact nontarget species through indirect effects. This finding has profound implications for biological control. To better understand the causes of these interactions and their implications, we evaluate recent case studies of indirect nontarget effects of biological control agents in the context of theoretical work in community ecology. We find that although particular indirect nontarget effects are extremely difficult to predict, all indirect nontarget effects of host specific biological control agents derive from the nature and strength of the interaction between the biological control agent and the pest. Additionally, recent theoretical work suggests that the degree of impact of a biological control agent on nontarget species is proportional to the agent’s abundance, which will be highest for moderately successful control agents. Therefore, the key to safeguarding against indirect nontarget effects of host-specific biological control agents is to ensure the biological control agents are not only host specific, but also efficacious. Biological control agents that greatly reduce their target species while remaining host-specific will reduce their own populations through density-dependent feedbacks that minimize risks to nontarget species.     

Recent advances in plasmid-based tools for establishing novel microbial chassis

A key challenge for domesticating alternative cultivable microorganisms with biotechnological potential lies in the development of innovative technologies. Within this framework, a myriad of genetic tools has flourished, allowing the design and manipulation of complex synthetic circuits and genomes to become the general rule in many laboratories rather than the exception. More recently, with the development of novel technologies such as DNA automated synthesis/sequencing and powerful computational tools, molecular biology has entered the synthetic biology era. In the beginning, most of these technologies were established in traditional microbial models (known as chassis in the synthetic biology framework) such as Escherichia coli and Saccharomyces cerevisiae, enabling fast advances in the field and the validation of fundamental proofs of concept. However, it soon became clear that these organisms, although extremely useful for prototyping many genetic tools, were not ideal for a wide range of biotechnological tasks due to intrinsic limitations in their molecular/physiological properties. Over the last decade, researchers have been facing the great challenge of shifting from these model systems to non-conventional chassis with endogenous capacities for dealing with specific tasks. The key to address these issues includes the generation of narrow and broad host plasmid-based molecular tools and the development of novel methods for engineering genomes through homologous recombination systems, CRISPR/Cas9 and other alternative methods. Here, we address the most recent advances in plasmid-based tools for the construction of novel cell factories, including a guide for helping with “build-your-own” microbial host.     

Gyroscopic corrections improve wearable sensor data prior to measuring dynamic sway in the gait of people with Multiple Sclerosis

Accelerometers are incorporated into many consumer devices providing new ways to monitor gait, mobility, and fall risk. However, many health benefits have not been realised because of issues with data quality that results from gravitational ‘cross-talk’ when the wearable device is tilted. Here we present an adaptive filter designed to improve the quality of accelerometer data prior to measuring dynamic pelvic sway patterns during a six minute walk test in people with and without Multiple Sclerosis (MS). Optical motion capture was used as the gold standard. Improved wearable device accuracy (≤4.4% NRMSE) was achieved using gyroscopic corrections and scaling filter thresholds by step frequency. The people with MS presented significantly greater pelvis sway range to compensate for their lower limb weaknesses and joint contractures. The visualisation of asymmetric pelvic sway in people with MS illustrates the potential to better understand their mobility impairments for reducing fall risk.     

A structured decision making analysis to increase a Red-cockaded Woodpecker population and balance stakeholder objectives for a National Forest

Longleaf pine (Pinus palustris) savanna is a biodiverse ecosystem native to the southeastern United States. Due to fire suppression and timber harvest, longleaf pine has declined to 3% of its original range. The extant forest provides habitat for many threatened and endangered species, including the endangered Red-cockaded Woodpecker (Picoides borealis; RCW), a cavity-nesting bird that co-evolved with fire-maintained forest, resulting in savanna-like old-growth forest as the bird’s preferred habitat. Our study site, the Oakmulgee Ranger District of the Talladega National Forest, harbors the largest RCW population in Alabama and is managed with an emphasis on RCW conservation. The United States Forest Service (USFS) also manages the Oakmulgee for uses such as wildlife conservation, recreation, and timber harvest. Despite efforts to restore RCW habitat and install artificial cavities in the Oakmulgee, the number of RCW groups has not exceeded 123, although the Recovery Plan objective is 394 groups. Our project was motivated by the USFS expressing interest in determining why the RCW population has not exceeded 123 groups. We proposed using structured decision making (SDM) with the USFS and other stakeholders to address this problem. Our goals were to explicitly define management objectives, build a Bayesian belief network with a model of how decision alternatives are believed to affect management objectives, and use a sensitivity analysis to determine the part of the model to which RCW population growth was most sensitive. Therefore, results from the analysis were expected to give insights into 1) ecological factors limiting RCW population growth, 2) how management can overcome these limits, plus 3) the relative expected ability of different decision alternatives to satisfy multiple objectives in addition to increasing RCW group number. We held four SDM workshops with representatives from the USFS, the Animal and Plant Health Inspection Service, the Longleaf Alliance, the Birmingham Audubon Society, and local residents. Stakeholder objectives consisted of maximizing the following: RCW group number, forest health, recreational enjoyment, community economic health, and aesthetics. Cavity insert installation had the greatest probability of increasing the number of RCW groups. The number of RCW groups was most affected by cavity availability, adult survival, reproductive output, food availability, and herbaceous understory. Prescribed burning was most likely to meet the combination of stakeholder objectives, followed by midstory removal. Our findings suggest that cavity installation efforts may need to be increased in the Oakmulgee to increase RCW group number. Also it could be beneficial to investigate how RCWs select cavity tree locations with the goal of increasing the chance that RCWs use artificial cavities to form new groups. The Bayesian belief network provided insights into factors limiting RCW population growth and how management can overcome these limits. The Bayesian belief network also can be used to prioritize management methods in the Oakmulgee given stakeholder objectives and time constraints.     

Iron and copper in progressive demyelination – New lessons from Skogholt's disease

The pathophysiological mechanisms of progressive demyelinating disorders including multiple sclerosis are incompletely understood. Increasing evidence indicates a role for trace metals in the progression of several neurodegenerative disorders. The study of Skogholt disease, a recently discovered demyelinating disease affecting both the central and peripheral nervous system, might shed some light on the mechanisms underlying demyelination. Cerebrospinal fluid iron and copper concentrations are about four times higher in Skogholt patients than in controls. The transit into cerebrospinal fluid of these elements from blood probably occurs in protein bound form. We hypothesize that exchangeable fractions of iron and copper are further transferred from cerebrospinal fluid into myelin, thereby contributing to the pathogenesis of demyelination. Free or weakly bound iron and copper ions may exert their toxic action on myelin by catalyzing production of oxygen radicals. Similarities to demyelinating processes in multiple sclerosis and other myelinopathies are discussed.     

Assessment of vulnerability to climate change using a multi-criteria outranking approach with application to heat stress in Sydney

Climate change vulnerability assessment is a complex form of risk assessment which accounts for both geophysical and socio-economic components of risk. In indicator-based vulnerability assessment (IBVA), indicators are used to rank the vulnerabilities of socio-ecological systems (SESs). The predominant aggregation approach in the literature, sometimes based on multi-attribute utility theory (MAUT), typically builds a global-scale, utility function based on weighted summation, to generate rankings. However, the corresponding requirement for additive independence and complete knowledge of system interactions by analyst are rarely if ever satisfied in IBVA.We build an analogy between the structures of Multi-Criteria Decision Analysis (MCDA) and IBVA problems and show that a set of techniques called Outranking Methods, developed in MCDA to deal with criteria incommensurability, data uncertainty and preference imprecision, offer IBVA a sound alternative to additive or multiplicative aggregation. We reformulate IBVA problems within an outranking framework, define thresholds of difference and use an outranking method, ELECTRE III, to assess the relative vulnerability to heat stress of 15 local government areas in metropolitan Sydney. We find that the ranking outcomes are robust and argue that an outranking approach is better suited for assessments characterized by a mix of qualitative, semi-quantitative and quantitative indicators, threshold effects and uncertainties about the exact relationships between indicators and vulnerability.     

Hill coefficient-based stochastic switch-like signal directly governs damage-recovery dynamics in freshwater fish in response to pulse copper

Growing evidence demonstrates that fluctuating metal stressors can have profound impact on the ecophysiological responses in aquatic species. However, how environmental stochasticity affects the complex damage-recovery dynamics in organisms remains difficult to predict. The objective of this paper was to investigate the stochastic behavior in the damage-recovery dynamics in tilapia in response to pulse waterborne copper (Cu). We developed a mathematical framework that allows discrimination between damage and recovery processes in tilapia exposed to designed pulse Cu scenarios. We built deterministic nonlinear models for the damage-recovery dynamics that produce response surfaces describing killing/recovery rate–Cu-pulse interval interactions. Here we showed that the stochastic switching behavior arose from competition among killing, recovery rates, and Cu pulse frequency. This competition resulted in an ultrasensitivity appeared in whole body, gills, muscle, liver, and kidney with Hill coefficients of ≥7, 4, 7, 5, and 5, respectively, at Cu 3 mg L⁻¹, dilution rate 0.05 h⁻¹, and pulse interval 72 h, indicating that a stochastic switch-like response was generated. We argue that the role of gill-associated Hill coefficient as a direct signal of the stochastic switch-like response in the damage-recovery dynamics in response to pulse metal stressor can serve as a sensitive indicator for risk detection in fluctuating environments. Our approach constitutes a general method to identify the stochastic switch-like response for aquatic species exposed to fluctuating metal stressors, which may help to predict and, eventually, expand our understanding of the damage-recovery dynamics. Finally, we implicate that Hill coefficient-based switch-like signal and its damage with hazard response can be linked in an information theoretic framework to handle environmental stochasticity.     

The changing incidence of human papillomavirus-associated oropharyngeal cancer using multiple imputation from 2000 to 2010 at a Comprehensive Cancer Centre

Introduction Human papillomavirus (HPV) is a risk and prognostic factor for oropharyngeal cancer (OPC). Determining whether the incidence of HPV-associated OPC is rising informs health policy. Methods HPV status was ascribed using p16 immunohistochemistry in 683/1474 OPC patients identified from the Princess Margaret Hospital's Cancer Registry (from 2000 to 2010). Missing p16 data was estimated using multiple (n = 100) imputation (MI) and validated using an independent OPC cohort (n = 214). Non-OPC head and neck squamous cell carcinoma (HNSCC) (n = 3262) were also used for time-trend comparison. Regression was used to compare HNSCC subsets and time-trends. The c-index was used to measure the predictive ability of MI. Results The incidence of OPC rose from 23.3% of all HNSCC in 2000 to 31.2% in 2010 (p = 0.002). In the subset of OPC tested for p16, there was no change in p16 positivity over time (p = 0.9). However, p16 testing became more frequent over time (p < 0.0001), but was nonetheless biased, favouring never-smokers [OR 1.87 (95% CI 1.29–2.70)] and tumors of the tonsil [OR 2.30 (1.52–3.47)] or base-of-tongue [OR 1.72 (1.10–2.70)]. These same factors were also associated with p16-positivity [ORs 3.22 (1.27–8.16), 7.26 (3.50–15.1), 5.83 (2.70–12.7), respectively]. Following MI and normalization, the proportion of OPC that was p16-associated rose from 39.8% in 2000 to 65.0% in 2010, p = 0.002, fully explaining the rise in OPC in our patient population. Conclusion The rise in HNSCC referrals seen from 2000 to 2010 at our institution was driven primarily by p16-associated OPC. MI was necessary to derive reliable conclusions when cases with missing data are considerable.