Showing papers by "University of Saskatchewan published in 2016"

Changing disturbance regimes, ecological memory, and forest resilience

Abstract: Ecological memory is central to how ecosystems respond to disturbance and is maintained by two types of legacies – information and material. Species life-history traits represent an adaptive response to disturbance and are an information legacy; in contrast, the abiotic and biotic structures (such as seeds or nutrients) produced by single disturbance events are material legacies. Disturbance characteristics that support or maintain these legacies enhance ecological resilience and maintain a “safe operating space” for ecosystem recovery. However, legacies can be lost or diminished as disturbance regimes and environmental conditions change, generating a “resilience debt” that manifests only after the system is disturbed. Strong effects of ecological memory on post-disturbance dynamics imply that contingencies (effects that cannot be predicted with certainty) of individual disturbances, interactions among disturbances, and climate variability combine to affect ecosystem resilience. We illustrate these concepts and introduce a novel ecosystem resilience framework with examples of forest disturbances, primarily from North America. Identifying legacies that support resilience in a particular ecosystem can help scientists and resource managers anticipate when disturbances may trigger abrupt shifts in forest ecosystems, and when forests are likely to be resilient.

Significance of HbA1c Test in Diagnosis and Prognosis of Diabetic Patients

Abstract: Diabetes is a global endemic with rapidly increasing prevalence in both developing and developed countries. The American Diabetes Association has recommended glycated hemoglobin (HbA1c) as a possible substitute to fasting blood glucose for diagnosis of diabetes. HbA1c is an important indicator of long-term glycemic control with the ability to reflect the cumulative glycemic history of the preceding two to three months. HbA1c not only provides a reliable measure of chronic hyperglycemia but also correlates well with the risk of long-term diabetes complications. Elevated HbA1c has also been regarded as an independent risk factor for coronary heart disease and stroke in subjects with or without diabetes. The valuable information provided by a single HbA1c test has rendered it as a reliable biomarker for the diagnosis and prognosis of diabetes. This review highlights the role of HbA1c in diagnosis and prognosis of diabetes patients.

Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?

Abstract: Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

SourcererCC: scaling code clone detection to big-code

Abstract: Despite a decade of active research, there has been a marked lack in clone detection techniques that scale to large repositories for detecting near-miss clones. In this paper, we present a token-based clone detector, SourcererCC, that can detect both exact and near-miss clones from large inter-project repositories using a standard workstation. It exploits an optimized inverted-index to quickly query the potential clones of a given code block. Filtering heuristics based on token ordering are used to significantly reduce the size of the index, the number of code-block comparisons needed to detect the clones, as well as the number of required token-comparisons needed to judge a potential clone. We evaluate the scalability, execution time, recall and precision of SourcererCC, and compare it to four publicly available and state-of-the-art tools. To measure recall, we use two recent benchmarks: (1) a big benchmark of real clones, BigCloneBench, and (2) a Mutation/Injection-based framework of thousands of fine-grained artificial clones. We find SourcererCC has both high recall and precision, and is able to scale to a large inter-project repository (25K projects, 250MLOC) using a standard workstation.

Maltreatment in childhood substantially increases the risk of adult depression and anxiety in prospective cohort studies: systematic review, meta-analysis, and proportional attributable fractions

Abstract: BACKGROUND: Literature supports a strong relationship between childhood maltreatment and mental illness but most studies reviewed are cross-sectional and/or use recall to assess maltreatment and are thus prone to temporality and recall bias. Research on the potential prospective impact of maltreatment reduction on the incidence of psychiatric disorders is scarce. METHOD: Electronic databases and grey literature from 1990 to 2014 were searched for English-language cohort studies with criteria for depression and/or anxiety and non-recall measurement of childhood maltreatment. Systematic review with meta-analysis synthesized the results. Study quality, heterogeneity, and publication bias were examined. Initial screening of titles and abstracts resulted in 199 papers being reviewed. Eight high-quality articles met eligibility criteria. Population attributable fractions (PAFs) estimated potential preventive impact. RESULTS: The pooled odds ratio (OR) between any type of maltreatment and depression was 2.03 [95% confidence interval (CI) 1.37-3.01] and 2.70 (95% CI 2.10-3.47) for anxiety. For specific types of maltreatment and depression or anxiety disorders, the ORs were: physical abuse (OR 2.00, 95% CI 1.25-3.19), sexual abuse (OR 2.66, 95% CI 1.88-3.75), and neglect (OR 1.74, 95% CI 1.35-2.23). PAFs suggest that over one-half of global depression and anxiety cases are potentially attributable to self-reported childhood maltreatment. A 10-25% reduction in maltreatment could potentially prevent 31.4-80.3 million depression and anxiety cases worldwide. CONCLUSION: This review provides robust evidence of childhood maltreatment increasing the risk for depression and anxiety, and reinforces the need for effective programs and policies to reduce its occurrence. Language: en

Blockchain as a Service for IoT

Abstract: A blockchain is a distributed and decentralized ledger that contains connected blocks of transactions. Unlike other ledger approaches, blockchain guarantees tamper proof storage of approved transactions. Due to its distributed and decentralized organization, blockchain is beeing used within IoT e.g. to manage device configuration, store sensor data and enable micro-payments. This paper presents the idea of using blockchain as a service for IoT and evaluates the performance of a cloud and edge hosted blockchain implementation.

A review on machine learning principles for multi-view biological data integration.

Abstract: Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.

Stratospheric Aerosol--Observations, Processes, and Impact on Climate

Abstract: Interest in stratospheric aerosol and its role in climate have increased over the last decade due to the observed increase in stratospheric aerosol since 2000 and the potential for changes in the sulfur cycle induced by climate change. This review provides an overview about the advances in stratospheric aerosol research since the last comprehensive assessment of stratospheric aerosol was published in 2006. A crucial development since 2006 is the substantial improvement in the agreement between in situ and space-based inferences of stratospheric aerosol properties during volcanically quiescent periods. Furthermore, new measurement systems and techniques, both in situ and space based, have been developed for measuring physical aerosol properties with greater accuracy and for characterizing aerosol composition. However, these changes induce challenges to constructing a long-term stratospheric aerosol climatology. Currently, changes in stratospheric aerosol levels less than 20% cannot be confidently quantified. The volcanic signals tend to mask any nonvolcanically driven change, making them difficult to understand. While the role of carbonyl sulfide as a substantial and relatively constant source of stratospheric sulfur has been confirmed by new observations and model simulations, large uncertainties remain with respect to the contribution from anthropogenic sulfur dioxide emissions. New evidence has been provided that stratospheric aerosol can also contain small amounts of nonsulfate matter such as black carbon and organics. Chemistry-climate models have substantially increased in quantity and sophistication. In many models the implementation of stratospheric aerosol processes is coupled to radiation and/or stratospheric chemistry modules to account for relevant feedback processes.

Lean interventions in healthcare: do they actually work? A systematic literature review.

Abstract: Purpose: Lean is a widely used quality improvement methodology initially developed and used in the automotive and manufacturing industries but recently expanded to the healthcare sector. This systematic literature review seeks to independently assess the effect of Lean or Lean interventions on worker and patient satisfaction, health and process outcomes, and financial costs. Data sources: We conducted a systematic literature review of Medline, PubMed, Cochrane Library, CINAHL, Web of Science, ABI/Inform, ERIC, EMBASE and SCOPUS. Study selection: Peer reviewed articles were included if they examined a Lean intervention and included quantitative data. Methodological quality was assessed using validated critical appraisal checklists. Publically available data collected by the Saskatchewan Health Quality Council and the Saskatchewan Union of Nurses were also analysed and reported separately. Data extraction: Data on design, methods, interventions and key outcomes were extracted and collated. Results of data synthesis: Our electronic search identified 22 articles that passed methodological quality review. Among the accepted studies, 4 were exclusively concerned with health outcomes, 3 included both health and process outcomes and 15 included process outcomes. Our study found that Lean interventions have: (i) no statistically significant association with patient satisfaction and health outcomes; (ii) a negative association with financial costs and worker satisfaction and (iii) potential, yet inconsistent, benefits on process outcomes like patient flow and safety. Conclusion: While some may strongly believe that Lean interventions lead to quality improvements in healthcare, the evidence to date simply does not support this claim. More rigorous, higher quality and better conducted scientific research is required to definitively ascertain the impact and effectiveness of Lean in healthcare settings.

Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm

Abstract: Motivation: Drug repositioning, which aims to identify new indications for existing drugs, offers a promising alternative to reduce the total time and cost of traditional drug development. Many computational strategies for drug repositioning have been proposed, which are based on similarities among drugs and diseases. Current studies typically use either only drug-related properties (e.g. chemical structures) or only disease-related properties (e.g. phenotypes) to calculate drug or disease similarity, respectively, while not taking into account the influence of known drug–disease association information on the similarity measures. Results: In this article, based on the assumption that similar drugs are normally associated with similar diseases and vice versa, we propose a novel computational method named MBiRW, which utilizes some comprehensive similarity measures and Bi-Random walk (BiRW) algorithm to identify potential novel indications for a given drug. By integrating drug or disease features information with known drug–disease associations, the comprehensive similarity measures are firstly developed to calculate similarity for drugs and diseases. Then drug similarity network and disease similarity network are constructed, and they are incorporated into a heterogeneous network with known drug–disease interactions. Based on the drug–disease heterogeneous network, BiRW algorithm is adopted to predict novel potential drug–disease associations. Computational experiment results from various datasets demonstrate that the proposed approach has reliable prediction performance and outperforms several recent computational drug repositioning approaches. Moreover, case studies of five selected drugs further confirm the superior performance of our method to discover potential indications for drugs practically. Availability and Implementation: http://github.com//bioinfomaticsCSU/MBiRW . Contact: jxwang@mail.csu.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.

World's soils are under threat

Abstract: . The Intergovernmental Technical Panel on Soils has completed the first State of the World's Soil Resources Report. Globally soil erosion was identified as the gravest threat, leading to deteriorating water quality in developed regions and to lowering of crop yields in many developing regions. We need to increase nitrogen and phosphorus fertilizer use in infertile tropical and semi-tropical soils – the regions where the most food insecurity among us are found – while reducing global use of these products overall. Stores of soil organic carbon are critical in the global carbon balance, and national governments must set specific targets to stabilize or ideally increase soil organic carbon stores. Finally the quality of soil information available for policy formulation must be improved – the regional assessments in the State of the World's Soil Resources Report frequently base their evaluations on studies from the 1990s based on observations made in the 1980s or earlier.

Biochar as an exceptional bioresource for energy, agronomy, carbon sequestration, activated carbon and specialty materials.

Abstract: Biofuels and biomaterials are gaining increased attention because of their ecofriendly nature and renewable precursors. Biochar is a recalcitrant carbonaceous product obtained from pyrolysis of biomass and other biogenic wastes. Biochar has found many notable applications in diverse areas because of its versatile physicochemical properties. Some of the promising biochar applications discussed in this paper include char gasification and combustion for energy production, soil remediation, carbon sequestration, catalysis, as well as development of activated carbon and specialty materials with biomedical and industrial uses. The pyrolysis temperature and heating rates are the limiting factors that determine the biochar properties such as fixed carbon, volatile matter, mineral phases, surface area, porosity and pore size distribution, alkalinity, electrical conductivity, cation-exchange capacity, etc. A broad investigation of these properties determining biochar application is rare in literature. With this objective, this paper comprehensively reviews the evolution of biochar from several lignocellulosic biomasses influenced by pyrolysis temperature and heating rate. Lower pyrolysis temperatures produce biochar with higher yields, and greater levels of volatiles, electrical conductivity and cation-exchange capacity. Conversely, higher temperatures generate biochar with a greater extent of aromatic carbon, alkalinity and surface area with microporosity. Nevertheless, this coherent review summarizes the valorization potentials of biochar for various environmental, industrial and biomedical applications.

A review of the open charm and open bottom systems

Abstract: Since the discovery of the first charmed meson in 1976, many open-charm and open-bottom hadrons were observed. In 2003 two narrow charm-strange states $D_{s0}^*(2317)$ and $D_{s1}(2460)$ were discovered by the BaBar and CLEO Collaborations, respectively. After that, more excited heavy hadrons were reported. In this work, we review the experimental and theoretical progress in this field.

Anthropogenic noise increases fish mortality by predation

Abstract: Noise-generating human activities affect hearing, communication and movement in terrestrial and aquatic animals, but direct evidence for impacts on survival is rare. We examined effects of motorboat noise on post-settlement survival and physiology of a prey fish species and its performance when exposed to predators. Both playback of motorboat noise and direct disturbance by motorboats elevated metabolic rate in Ambon damselfish (Pomacentrus amboinensis), which when stressed by motorboat noise responded less often and less rapidly to simulated predatory strikes. Prey were captured more readily by their natural predator (dusky dottyback, Pseudochromis fuscus) during exposure to motorboat noise compared with ambient conditions, and more than twice as many prey were consumed by the predator in field experiments when motorboats were passing. Our study suggests that a common source of noise in the marine environment has the potential to impact fish demography, highlighting the need to include anthropogenic noise in management plans.

Substantial proportion of global streamflow less than three months old

Abstract: Streamflow is a mixture of precipitation of various ages. Oxygen isotope data suggests that a third of global river discharge is sourced from rainfall within the past few months, which accounts for less than 0.1% of global groundwater.

Circular RNAs as potential biomarkers for cancer diagnosis and therapy.

Abstract: Circular RNAs (circRNAs) are a naturally occurring type of universal and diverse endogenous noncoding RNAs which unlike linear RNAs, have covalently linked ends. They are usually stable, abundant, conserved RNA molecules and often exhibit tissue/developmental-stage specific expression. Functional circRNAs have been identified to act as microRNA sponges and RNA-binding protein (RBP) sequestering agents as well as transcriptional regulators. These multiple functional roles elicit a great potential for circRNAs in biological applications. Emerging evidence shows that circRNAs play important roles in several diseases, particularly in cancer where they act through regulating protein expression of the pivotal genes that are critical for carcinogenesis. The presence of abundant circRNAs in saliva, exosomes and clinical standard blood samples will make them potential diagnostic or predictive biomarkers for diseases, particularly for cancer development, progression and prognosis. Here, we review the current literature and provide evidence for the impact of circRNAs in cancers and their potential significance in cancer prognosis and clinical treatment.

Weight loss intervention adherence and factors promoting adherence: a meta-analysis.

Abstract: Background Adhering to weight loss interventions is difficult for many people. The majority of those who are overweight or obese and attempt to lose weight are simply not successful. The objectives of this study were 1) to quantify overall adherence rates for various weight loss interventions and 2) to provide pooled estimates for factors associated with improved adherence to weight loss interventions.

The Prevalence and Incidence of Dementia Due to Alzheimer's Disease: a Systematic Review and Meta-Analysis.

Abstract: Background Updated information on the epidemiology of dementia due to Alzheimer’s disease (AD) is needed to ensure that adequate resources are available to meet current and future healthcare needs. We conducted a systematic review and meta-analysis of the incidence and prevalence of AD. Methods The MEDLINE and EMBASE databases were searched from 1985 to 2012, as well as the reference lists of selected articles. Included articles had to provide an original population-based estimate for the incidence and/or prevalence of AD. Two individuals independently performed abstract and full-text reviews, data extraction and quality assessments. Random-effects models were employed to generate pooled estimates stratified by age, sex, diagnostic criteria, location (i.e., continent) and time (i.e., when the study was done). Results Of 16,066 abstracts screened, 707 articles were selected for full-text review. A total of 119 studies met the inclusion criteria. In community settings, the overall point prevalence of dementia due to AD among individuals 60+ was 40.2 per 1000 persons (CI 95% : 29.1-55.6), and pooled annual period prevalence was 30.4 per 1000 persons (CI 95% : 15.6-59.1). In community settings, the overall pooled annual incidence proportion of dementia due to AD among individuals 60+ was 34.1 per 1000 persons (CI 95% : 16.4-70.9), and the incidence rate was 15.8 per 1000 person-years (CI 95% : 12.9-19.4). Estimates varied significantly with age, diagnostic criteria used and location (i.e., continent). Conclusions The burden of AD dementia is substantial. Significant gaps in our understanding of its epidemiology were identified, even in a high-income country such as Canada. Future studies should assess the impact of using such newer clinical diagnostic criteria for AD dementia such as those of the National Institute on Aging–Alzheimer’s Association and/or incorporate validated biomarkers to confirm the presence of Alzheimer pathology to produce more precise estimates of the global burden of AD.

Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire: an expert assessment

Abstract: As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release w ...

Bird and bat predation services in tropical forests and agroforestry landscapes

Abstract: Understanding distribution patterns and multitrophic interactions is critical for managing bat- and bird-mediated ecosystem services such as the suppression of pest and non-pest arthropods Despite the ecological and economic importance of bats and birds in tropical forests, agroforestry systems, and agricultural systems mixed with natural forest, a systematic review of their impact is still missing A growing number of bird and bat exclosure experiments has improved our knowledge allowing new conclusions regarding their roles in food webs and associated ecosystem services Here, we review the distribution patterns of insectivorous birds and bats, their local and landscape drivers, and their effects on trophic cascades in tropical ecosystems We report that for birds but not bats community composition and relative importance of functional groups changes conspicuously from forests to habitats including both agricultural areas and forests, here termed 'forest-agri' habitats, with reduced representation of insectivores in the latter In contrast to previous theory regarding trophic cascade strength, we find that birds and bats reduce the density and biomass of arthropods in the tropics with effect sizes similar to those in temperate and boreal communities The relative importance of birds versus bats in regulating pest abundances varies with season, geography and management Birds and bats may even suppress tropical arthropod outbreaks, although positive effects on plant growth are not always reported As both bats and birds are major agents of pest suppression, a better understanding of the local and landscape factors driving the variability of their impact is needed

Fostering Intrinsic Motivation through Avatar Identification in Digital Games

Abstract: Fostering intrinsic motivation with interactive applications can increase the enjoyment that people experience when using technology, but can also translate into more invested effort. We propose that identifying with an avatar in a game will increase the intrinsic motivation of the player. We analyzed data from 126 participants playing a custom endless runner game and show that similarity identification, embodied identification, and wishful identification increases autonomy, immersion, invested effort, enjoyment, and positive affect. We also show that greater identification translates into motivated behaviour as operationalized by the time that players spent in an unending version of the infinite runner. Important for the design of games for entertainment and serious purposes, we discuss how identification with an avatar can be facilitated to cultivate intrinsic motivation within and beyond games.

LDAP: a web server for lncRNA-disease association prediction

Abstract: Motivation Increasing evidences have demonstrated that long noncoding RNAs (lncRNAs) play important roles in many human diseases. Therefore, predicting novel lncRNA-disease associations would contribute to dissect the complex mechanisms of disease pathogenesis. Some computational methods have been developed to infer lncRNA-disease associations. However, most of these methods infer lncRNA-disease associations only based on single data resource. Results In this paper, we propose a new computational method to predict lncRNA-disease associations by integrating multiple biological data resources. Then, we implement this method as a web server for lncRNA-disease association prediction (LDAP). The input of the LDAP server is the lncRNA sequence. The LDAP predicts potential lncRNA-disease associations by using a bagging SVM classifier based on lncRNA similarity and disease similarity. Availability and implementation The web server is available at http://bioinformatics.csu.edu.cn/ldap Contact jxwang@mail.csu.edu.cn. Supplimentary information Supplementary data are available at Bioinformatics online.

Legacy effects of soil moisture on microbial community structure and N2O emissions

Abstract: Soil moisture is a strong determinant of microbial activity exerting dominant control over gaseous and liquid diffusion rates and affecting O2 and substrate availability. Often, measures of microbial community structure and soil moisture status fail to inform our understanding of soil processes, particularly those that are governed by complex feedbacks between substrate availability and environmental conditions (e.g. nitrogen transformations). Nitrous oxide (N2O) emissions, although conceptually regulated by soil moisture, are notoriously difficult to predict based on soil water content and nutrient status. Here, we studied agricultural soils under wetting, drying, and static moisture conditions to assess the impact of current and previous moisture on bacterial 16S rRNA composition; transcription of amoA, hao, norB, and nosZ; and net N2O production. Microbial community composition was dependent on previous moisture. As soils dried, bacterial rRNA contained fewer and more evenly distributed genera. We hypothesize that this was linked to the evenness of resource distribution as controlled by differences in substrate diffusion in wetting vs. drying conditions. N2O flux depended on previous, as well as current, soil moisture status and this legacy effect was greatest at 80% water filled pore space. Overall, we found that previous moisture affected microbial activity, transcription, composition and ultimately, N2O emissions. Our study demonstrates that, for soil microorganisms and processes, it is not only what soil moisture is, but also what it was that is important.