Co-distribution and co-infection of chikungunya and dengue viruses

BACKGROUND Chikungunya and dengue infections are spatio-temporally related. The current review aims to determine the geographic limits of chikungunya, dengue and the principal mosquito vectors for both viruses and to synthesise current epidemiological understanding of their co-distribution. METHODS Three biomedical databases (PubMed, Scopus and Web of Science) were searched from their inception until May 2015 for studies that reported concurrent detection of chikungunya and dengue viruses in the same patient. Additionally, data from WHO, CDC and Healthmap alerts were extracted to create up-to-date global distribution maps for both dengue and chikungunya. RESULTS Evidence for chikungunya-dengue co-infection has been found in Angola, Gabon, India, Madagascar, Malaysia, Myanmar, Nigeria, Saint Martin, Singapore, Sri Lanka, Tanzania, Thailand and Yemen; these constitute only 13 out of the 98 countries/territories where both chikungunya and dengue epidemic/endemic transmission have been reported. CONCLUSIONS Understanding the true extent of chikungunya-dengue co-infection is hampered by current diagnosis largely based on their similar symptoms. Heightened awareness of chikungunya among the public and public health practitioners in the advent of the ongoing outbreak in the Americas can be expected to improve diagnostic rigour. Maps generated from the newly compiled lists of the geographic distribution of both pathogens and vectors represent the current geographical limits of chikungunya and dengue, as well as the countries/territories at risk of future incursion by both viruses. These describe regions of co-endemicity in which lab-based diagnosis of suspected cases is of higher priority.

What are the driving factors influencing the size distribution of airborne synthetic clay particles emitted from a jet milling process?

In the field of workplace air quality, measuring and analyzing the size distribution of airborne particles to identify their sources and apportion their contribution has become widely accepted, however, the driving factors that influence this parameter, particularly for nanoparticles (< 100 nm), have not been thoroughly determined. Identification of driving factors, and in turn, general trends in size distribution of emitted particles would facilitate the prediction of nanoparticles’ emission behavior and significantly contribute to their exposure assessment. In this study, a comprehensive analysis of the particle number size distribution data, with a particular focus on the ultrafine size range of synthetic clay particles emitted from a jet milling machine was conducted using the multi-lognormal fitting method. The results showed relatively high contribution of nanoparticles to the emissions in many of the tested cases, and also, that both surface treatment and feed rate of the machine are significant factors influencing the size distribution of the emitted particles of this size. In particular, applying surface treatments and increasing the machine feed rate have the similar effect of reducing the size of the particles, however, no general trend was found in variations of size distribution across different surface treatments and feed rates. The findings of our study demonstrate that for this process and other activities, where no general trend is found in the size distribution of the emitted airborne particles due to dissimilar effects of the driving factors, each case must be treated separately in terms of workplace exposure assessment and regulations.

Reputation model based on rating data and application in recommender systems

This thesis introduced two novel reputation models to generate accurate item reputation scores using ratings data and the statistics of the dataset. It also presented an innovative method that incorporates reputation awareness in recommender systems by employing voting system methods to produce more accurate top-N item recommendations. Additionally, this thesis introduced a personalisation method for generating reputation scores based on users' interests, where a single item can have different reputation scores for different users. The personalised reputation scores are then used in the proposed reputation-aware recommender systems to enhance the recommendation quality.

LRP5 regulates human body fat distribution by modulating adipose progenitor biology in a dose- and depot-specific fashion

Summary Common variants in WNT pathway genes have been associated with bone mass and fat distribution, the latter predicting diabetes and cardiovascular disease risk. Rare mutations in the WNT co-receptors LRP5 and LRP6 are similarly associated with bone and cardiometabolic disorders. We investigated the role of LRP5 in human adipose tissue. Subjects with gain-of-function LRP5 mutations and high bone mass had enhanced lower-body fat accumulation. Reciprocally, a low bone mineral density-associated common LRP5 allele correlated with increased abdominal adiposity. Ex vivo LRP5 expression was higher in abdominal versus gluteal adipocyte progenitors. Equivalent knockdown of LRP5 in both progenitor types dose-dependently impaired β-catenin signaling and led to distinct biological outcomes: diminished gluteal and enhanced abdominal adipogenesis. These data highlight how depot differences in WNT/β-catenin pathway activity modulate human fat distribution via effects on adipocyte progenitor biology. They also identify LRP5 as a potential pharmacologic target for the treatment of cardiometabolic disorders. © 2015 The Authors.

The reproducibility of acquiring three dimensional gait and plantar pressure data using established protocols in participants with and without type 2 diabetes and foot ulcers

Background Several prospective studies have suggested that gait and plantar pressure abnormalities secondary to diabetic peripheral neuropathy contributes to foot ulceration. There are many different methods by which gait and plantar pressures are assessed and currently there is no agreed standardised approach. This study aimed to describe the methods and reproducibility of three-dimensional gait and plantar pressure assessments in a small subset of participants using pre-existing protocols. Methods Fourteen participants were conveniently sampled prior to a planned longitudinal study; four patients with diabetes and plantar foot ulcers, five patients with diabetes but no foot ulcers and five healthy controls. The repeatability of measuring key biomechanical data was assessed including the identification of 16 key anatomical landmarks, the measurement of seven leg dimensions, the processing of 22 three-dimensional gait parameters and the analysis of four different plantar pressures measures at 20 foot regions. Results The mean inter-observer differences were within the pre-defined acceptable level (<7 mm) for 100 % (16 of 16) of key anatomical landmarks measured for gait analysis. The intra-observer assessment concordance correlation coefficients were > 0.9 for 100 % (7 of 7) of leg dimensions. The coefficients of variations (CVs) were within the pre-defined acceptable level (<10 %) for 100 % (22 of 22) of gait parameters. The CVs were within the pre-defined acceptable level (<30 %) for 95 % (19 of 20) of the contact area measures, 85 % (17 of 20) of mean plantar pressures, 70 % (14 of 20) of pressure time integrals and 55 % (11 of 20) of maximum sensor plantar pressure measures. Conclusion Overall, the findings of this study suggest that important gait and plantar pressure measurements can be reliably acquired. Nearly all measures contributing to three-dimensional gait parameter assessments were within predefined acceptable limits. Most plantar pressure measurements were also within predefined acceptable limits; however, reproducibility was not as good for assessment of the maximum sensor pressure. To our knowledge, this is the first study to investigate the reproducibility of several biomechanical methods in a heterogeneous cohort.

Data-aware task scheduling for all-to-all comparison problems in heterogeneous distributed systems

Solving large-scale all-to-all comparison problems using distributed computing is increasingly significant for various applications. Previous efforts to implement distributed all-to-all comparison frameworks have treated the two phases of data distribution and comparison task scheduling separately. This leads to high storage demands as well as poor data locality for the comparison tasks, thus creating a need to redistribute the data at runtime. Furthermore, most previous methods have been developed for homogeneous computing environments, so their overall performance is degraded even further when they are used in heterogeneous distributed systems. To tackle these challenges, this paper presents a data-aware task scheduling approach for solving all-to-all comparison problems in heterogeneous distributed systems. The approach formulates the requirements for data distribution and comparison task scheduling simultaneously as a constrained optimization problem. Then, metaheuristic data pre-scheduling and dynamic task scheduling strategies are developed along with an algorithmic implementation to solve the problem. The approach provides perfect data locality for all comparison tasks, avoiding rearrangement of data at runtime. It achieves load balancing among heterogeneous computing nodes, thus enhancing the overall computation time. It also reduces data storage requirements across the network. The effectiveness of the approach is demonstrated through experimental studies.

Prevalence, codetection and seasonal distribution of upper airway viruses and bacteria in children with acute respiratory illnesses with cough as a symptom

Most studies exploring the role of upper airway viruses and bacteria in paediatric acute respiratory infections (ARI) focus on specific clinicaldiagnoses and/or do not account for virus–bacteria interactions. We aimed to describe the frequency and predictors of virus and bacteria codetection in children with ARI and cough, irrespective of clinical diagnosis. Bilateral nasal swabs, demographic, clinical and risk factor data were collected at enrollment in children aged <15 years presenting to an emergency department with an ARI and where cough was a symptom. Swabs were tested by polymerase chain reaction for 17 respiratory viruses and seven respiratory bacteria. Logistic regression was used to investigate associations between child characteristics and codetection of the organisms of interest. Between December 2011 and August 2014, swabs were collected from 817 (93.3%) of 876 enrolled children, median age 27.7 months (interquartile range13.9–60.3 months). Overall, 740 (90.6%) of 817 specimens were positive for any organism. Both viruses and bacteria were detected in 423 specimens (51.8%). Factors associated with codetection were age (adjusted odds ratio (aOR) for age <12 months = 4.9, 95% confidence interval (CI) 3.0, 7.9; age 12 to <24 months = 6.0, 95% CI 3.7, 9.8; age 24 to <60 months = 2.4, 95% CI 1.5, 3.9), male gender (aOR 1.46; 95% CI 1.1, 2.0), child care attendance (aOR 2.0; 95% CI 1.4, 2.8) and winter enrollment (aOR 2.0; 95% CI 1.3, 3.0). Haemophilus influenzae dominated the virus–bacteria pairs. Virus–H. influenzae interactions in ARI should be investigated further, especially as the contribution of nontypeable H. influenzae to acute and chronic respiratory diseases is being increasingly recognized.

Statistical tools for analyzing water quality data

Water quality data are often collected at different sites over time to improve water quality management. Water quality data usually exhibit the following characteristics: non-normal distribution, presence of outliers, missing values, values below detection limits (censored), and serial dependence. It is essential to apply appropriate statistical methodology when analyzing water quality data to draw valid conclusions and hence provide useful advice in water management. In this chapter, we will provide and demonstrate various statistical tools for analyzing such water quality data, and will also introduce how to use a statistical software R to analyze water quality data by various statistical methods. A dataset collected from the Susquehanna River Basin will be used to demonstrate various statistical methods provided in this chapter. The dataset can be downloaded from website http://www.srbc.net/programs/CBP/nutrientprogram.htm.

Revisiting Coptotermes (Isoptera: Rhinotermitidae): a global taxonomic road map for species validity and distribution of an economically important subterranean termite genus

Coptotermes Wasmann (Isoptera: Rhinotermitidae) is one of the most economically important subterranean termite genera and some species are successful invaders. However, despite its important pest status, the taxonomic validity of many named Coptotermes species remains unclear. In this study, we reviewed all named species within the genus and investigated evidence supporting the validity of each named species. Species were systematically scrutinized according to the region of their original description: Southeast Asia, India, China, Africa, the Neotropics, and Australia. We estimate that of the currently 69 named species described by accepted nomenclatural rules, only 21 taxa have solid evidence for validity, 44 names have uncertain status, and the remaining species names should be synonymized or were made unavailable. Species with high degrees of invasiveness may be known under additional junior synonyms due to independent parochial descriptions. Molecular data for a vast majority of species are scarce and significant effort is needed to complete the taxonomic and phylogenetic revision of the genus. Because of the wide distribution of Coptotermes, we advocate for an integrative taxonomic effort to establish the distribution of each putative species, provide specimens and corresponding molecular data, check original descriptions and type specimens (if available), and provide evidence for a more robust phylogenetic position of each species. This study embodies both consensus and contention of those studying Coptotermes and thus pinpoints the current uncertainty of many species. This project is intended to be a roadmap for identifying those Coptotermes species names that need to be more thoroughly investigated, as an incentive to complete a necessary revision process.