Validation of an immunoassay to measure plasminogen-activator inhibitor-1 concentrations in human saliva

Introduction We have previously shown that the concentrations of D-dimer are significantly elevated in saliva compared with plasma. Saliva offers several advantages compared with blood analysis. We hypothesised that human saliva contains plasminogen activator inhibitor-1 (PAI-1) and that the concentrations are not affected by the time of saliva collection. The aim was to adopt and validate an immunoassay to quantify PAI-1 concentrations in saliva and to determine whether saliva collection time has an influence in the measurement. Materials and methods Two saliva samples (morning and afternoon) from the same day were collected from healthy subjects (N = 40) who have had no underlying heart conditions. A customized AlphaLISA® immunoassay (PerkinElmer®, MA, USA) was adopted and used to quantify PAI-1 concentrations. We validated the analytical performance of the customized immunoassay by calculating recovery of known amount of analyte spiked in saliva. Results: The recovery (95.03%), intra- (8.59%) and inter-assay (7.52%) variations were within the acceptable ranges. The median salivary PAI-1 concentrations were 394 pg/mL (interquartile ranges (IQR) 243.4-833.1 pg/mL) in the morning and 376 (129.1-615.4) pg/mL in the afternoon and the plasma concentration was 59,000 (24,000-110,000) pg/mL. Salivary PAI-1 did not correlate with plasma (P = 0.812). Conclusions The adopted immunoassay produced acceptable assay sensitivity and specificity. The data demonstrated that saliva contains PAI-1 and that its concentration is not affected by the time of saliva collection. There is no correlation between salivary and plasma PAI-1 concentrations. Further studies are required to demonstrate the utility of salivary PAI-1 in CVD risk factor studies.

Detecting approximate clones in business process model repositories

Empirical evidence shows that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication arises for example when the repository covers multiple variants of the same processes or due to copy-pasting. Previous work has addressed the problem of efficiently retrieving exact clones that can be refactored into shared subprocess models. This article studies the broader problem of approximate clone detection in process models. The article proposes techniques for detecting clusters of approximate clones based on two well-known clustering algorithms: DBSCAN and Hi- erarchical Agglomerative Clustering (HAC). The article also defines a measure of standardizability of an approximate clone cluster, meaning the potential benefit of replacing the approximate clones with a single standardized subprocess. Experiments show that both techniques, in conjunction with the proposed standardizability measure, accurately retrieve clusters of approximate clones that originate from copy-pasting followed by independent modifications to the copied fragments. Additional experiments show that both techniques produce clusters that match those produced by human subjects and that are perceived to be standardizable.

Informal Sectors and New Industries: The Complexities of Regulating Occupational Health and Safety in Developing Countries

Focusing on paid work that blurs traditional legal boundaries and the challenge this poses to traditional forms of labour regulation, this collection of original case studies illustrates the wide range of different forms of regulation designed to provide decent work. The original case studies cover a diversity of workers from across developed and developing countries, the formal and informal economies and public and private work spaces. Each deals with the failings of traditional labour law, and several explore the capacity of different forms of regulatory techniques, such as commercial law, corporate codes of conduct, or supply chain regulation, to protect workers.

Methods for extracting genomic DNA from whole blood samples : current perspectives

Deoxyribonucleic acid (DNA) extraction has considerably evolved since it was initially performed back in 1869. It is the first step required for many of the available downstream applications used in the field of molecular biology. Whole blood samples are one of the main sources used to obtain DNA, and there are many different protocols available to perform nucleic acid extraction on such samples. These methods vary from very basic manual protocols to more sophisticated methods included in automated DNA extraction protocols. Based on the wide range of available options, it would be ideal to determine the ones that perform best in terms of cost-effectiveness and time efficiency. We have reviewed DNA extraction history and the most commonly used methods for DNA extraction from whole blood samples, highlighting their individual advantages and disadvantages. We also searched current scientific literature to find studies comparing different nucleic acid extraction methods, to determine the best available choice. Based on our research, we have determined that there is not enough scientific evidence to support one particular DNA extraction method from whole blood samples. Choosing a suitable method is still a process that requires consideration of many different factors, and more research is needed to validate choices made at facilities around the world.

The establishment of an ISO compliant cancer biobank for Jordan and its neighboring countries through knowledge transfer and training

Research studies aimed at advancing cancer prevention, diagnosis, and treatment depend on a number of key resources, including a ready supply of high-quality annotated biospecimens from diverse ethnic populations that can be used to test new drugs, assess the validity of prognostic biomarkers, and develop tailor-made therapies. In November 2011, KHCCBIO was established at the King Hussein Cancer Center (KHCC) with the support of Seventh Framework Programme (FP7) funding from the European Union (khccbio.khcc.jo). KHCCBIO was developed for the purpose of achieving an ISO accredited cancer biobank through the collection, processing, and preservation of high-quality, clinically annotated biospecimens from consenting cancer patients, making it the first cancer biobank of its kind in Jordan. The establishment of a state-of-the-art, standardized biospecimen repository of matched normal and lung tumor tissue, in addition to blood components such as serum, plasma, and white blood cells, was achieved through the support and experience of its European partners, Trinity College Dublin, Biostor Ireland, and accelopment AG. To date, KHCCBIO along with its partners, have worked closely in establishing an ISO Quality Management System (QMS) under which the biobank will operate. A Quality Policy Manual, Validation, and Training plan have been developed in addition to the development of standard operating procedures (SOPs) for consenting policies on ethical issues, data privacy, confidentiality, and biobanking bylaws. SOPs have also been drafted according to best international practices and implemented for the donation, procurement, processing, testing, preservation, storage, and distribution of tissues and blood samples from lung cancer patients, which will form the basis for the procurement of other cancer types. KHCCBIO will be the first ISO accredited cancer biobank from a diverse ethnic Middle Eastern and North African population. It will provide a unique and valuable resource of high-quality human biospecimens and anonymized clinicopathological data to the cancer research communities world-wide.

Nanostructured silver-gold bimetallic SERS substrates for selective identification of bacteria in human blood

Surface-enhanced Raman spectroscopy (SERS) is a potentially important tool in the rapid and accurate detection of pathogenic bacteria in biological fluids. However, for diagnostic application of this technique, it is necessary to develop a highly sensitive, stable, biocompatible and reproducible SERS-active substrate. In this work, we have developed a silver–gold bimetallic SERS surface by a simple potentiostatic electrodeposition of a thin gold layer on an electrochemically roughened nanoscopic silver substrate. The resultant substrate was very stable under atmospheric conditions and exhibited the strong Raman enhancement with the high reproducibility of the recorded SERS spectra of bacteria (E. coli, S. enterica, S. epidermidis, and B. megaterium). The coating of the antibiotic over the SERS substrate selectively captured bacteria from blood samples and also increased the Raman signal in contrast to the bare surface. Finally, we have utilized the antibiotic-coated hybrid surface to selectively identify different pathogenic bacteria, namely E. coli, S. enterica and S. epidermidis from blood samples.

Decline in perfluorooctane sulfonate and perfluorooctanoate serum concentrations in an Australian population from 2002 to 2011

Some perfluoroalkyl and polyfluoroalkyl substances (PFASs) have become widespread pollutants detected in human and wildlife samples worldwide. The main objective of this study was to assess temporal trends of PFAS concentrations in human blood in Australia over the last decade (2002–2011), taking into consideration age and sex trends. Pooled human sera from 2002/03 (n=26); 2008/09 (n=24) and 2010/11 (n=24) from South East Queensland, Australia were obtained from de-identified surplus pathology samples and compared with samples collected previously from 2006/07 (n=84). A total of 9775 samples in 158 pools were available for assessment of PFASs. Stratification criteria included sex and age: <16 years (2002/03 only); 0–4 (2006/07, 2008/09, 2010/11); 5–15 (2006/07, 2008/09, 2010/11); 16–30; 31–45; 46–60; and >60 years (all collection periods). Sera were analyzed using on-line solid-phase extraction coupled to high-performance liquid chromatography-isotope dilution-tandem mass spectrometry. Perfluorooctane sulfonate (PFOS) was detected in the highest concentrations ranging from 5.3–19.2 ng/ml (2008/09) to 4.4–17.4 ng/ml (2010/11). Perfluorooctanoate (PFOA) was detected in the next highest concentration ranging from 2.8–7.3 ng/ml (2008/09) to 3.1–6.5 ng/ml (2010/11). All other measured PFASs were detected at concentrations <1 ng/ml with the exception of perfluorohexane sulfonate which ranged from 1.2–5.7 ng/ml (08/09) and 1.4–5.4 ng/ml (10/11). The mean concentrations of both PFOS and PFOA in the 2010/11 period compared to 2002/03 were lower for all adult age groups by 56%. For 5-15 year olds, the decrease was 66% (PFOS) and 63% (PFOA) from 2002/03 to 2010/11. For 0-4 year olds the decrease from 2006/07 (when data were first available for this age group) was 50% (PFOS) and 22% (PFOA). This study provides strong evidence for decreasing serum PFOS and PFOA concentrations in an Australian population from 2002 through 2011. Age trends were variable and concentrations were higher in males than females. Global use has been in decline since around 2002 and hence primary exposure levels are expected to be decreasing. Further biomonitoring will allow assessment of PFAS exposures to confirm trends in exposure as primary and eventually secondary sources are depleted.

The role of other people and emotion for blood donation : an altruistic social service

Blood donation is a critical part of health services with a viable blood supply underpinning an effective health program in any country. Typically blood is provided by voluntary donations from citizens and is therefore reliant on the goodwill and altruistic commitment of donors. In Australia, like many other developed nations, there are many challenges in maintaining a sufficient and sustainable blood supply. The Australian Red Cross Blood Service Donor and Community research group aim is to understand the barriers, motivations and perceptions of donors. Blood donation is a ‘people-processing’ service (Lovelock 1983, Russell-Bennett et al 2013) with the marketing exchange relating to bodily fluid rather than money and is an altruistic social service that has no direct benefit for the customer donor rather the benefit is for other people and society (Kotler and Zaltman 1971). Emotion has been shown to be a motivator and a barrier in a variety of Blood Service studies, this is a key insight that is further explored in the current study. Other key social factors that impact blood donor behavior are classified as social because they involve perceptions of other people’s beliefs and responses (such as moral or subjective norms), peer pressure, other people’s expectations and other people as a form of support. Given that emotions are social phenomena (Parkinson 1996), this study focuses on the role of other people in the blood donation process and how other people relates to the emotional experience of blood donors. We argue in this paper that overcoming emotional barriers to blood donation by leveraging the role of other people will influence low donation rates in Australia. To date, there has been little evidence in service research that identifies. In this paper we explore how other people influence the emotional experience of donors and how, donor emotions create the need for other people as a coping resource.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

Deterrence of drug driving : the impact of the ACT drug driving legislation and detection techniques

Overarching Research Questions Are ACT motorists aware of roadside saliva based drug testing operations? What is the perceived deterrent impact of the operations? What factors are predictive of future intentions to drug drive? What are the differences between key subgroups

Identifying product families using data mining techniques in manufacturing paradigm

Identifying product families has been considered as an effective way to accommodate the increasing product varieties across the diverse market niches. In this paper, we propose a novel framework to identifying product families by using a similarity measure for a common product design data BOM (Bill of Materials) based on data mining techniques such as frequent mining and clus-tering. For calculating the similarity between BOMs, a novel Extended Augmented Adjacency Matrix (EAAM) representation is introduced that consists of information not only of the content and topology but also of the fre-quent structural dependency among the various parts of a product design. These EAAM representations of BOMs are compared to calculate the similarity between products and used as a clustering input to group the product fami-lies. When applied on a real-life manufacturing data, the proposed framework outperforms a current baseline that uses orthogonal Procrustes for grouping product families.

Demographics and survivial of a cohort of blood and breast cancer patients who developed heart failure following cancer treatment

Background/Aim: Cardiotoxicity resulting in heart failure is a devastating complication of cancer therapy. It is possible that a patient may survive cancer only to develop heart failure (HF), which is more deadly than cancer. The aim of this project was to profile the characteristics of patients at risk of cancer treatment induced heart failure. Methods: Linked Health Data Analysis of Queensland Cancer Registry (QCR) from 1996-2009, Death Registry and Hospital Administration records for HF and chemotherapy admissions were reviewed. Index heart failure admission must have occurred after the date of cancer registry entry. Results: A total of 15,987 patients were included in this analysis; 1,062 (6.6%) had chemotherapy+HF admission (51.4% Female) and 14,925 (93.4%) chemotherapy_no HF admission. Median age of chemotherapy+HF patients was 67 years (IQR 58 to 75) vs. 54 years (IQR 44 to 64) for chemotherapy_no HF admission. Chemotherapy+HF patients had increased risk of all cause mortality (HR 2.79 [95% CI 2.58-3.02] and 1.67 [95% CI, 1.54 to 1.81] after adjusting for age, sex, marital status, country of birth, cancer site and chemotherapy dose). Index HF admission occurred within one year of cancer diagnosis in 47% of HF patients with 80% of patinets having there index admission with 3 years. The number of chemotherapy cycles was not associated with significant reduction in survival time in chemotherapy+HF patients. Mean survival for heart failure patients was 5.3 years (95% CI, 4.99 - 5.62) vs.9.57 years (95% CI, 9.47-9.68) for chemotherapy_no HF admission patients. Conclusion: All-cause mortality was 67% higher in patients diagnosed with HF following chemotherapy in adjusted analysis for covariates. Methods to improve and better coordinate of the interdisciplinary care for cancer patients with HF involving cardiologists and oncologists are required, including evidence-based guidelines for the comprehensive assessment, monitoring and management of this cohort.

Recruiting, Sampling and Data Collection with Difficult Populations: Clients of Male Sex Workers.

Although there are many potential new insights to be gained through advancing research on the clients of male sex workers, significant social, ethical and methodological challenges to accessing this population exist. This research project case explores our attempts to recruit a population that does not typically form a cohesive or coherent 'community' and often avoids self-identifying to mitigate the stigma attached to buying sex. We used an arms-length recruitment campaign that focussed on directing potential participants to our study website, which could in turn lead them to participate in an anonymous telephone interview. Barriers to reaching male sex-work clients, however, demanded the evolution of our recruitment strategy. New technologies are part of the solution to accessing a hard-to-reach population, but they only work if researchers engage responsively. We also show how we conducted an in-depth interview with a client and discuss the value of using secondary data.