Ultra-trace detection of diagnostically important biomarkers using functionalised-Surface Enhanced Raman Spectroscopy (SERS)

Here we report an ultrasensitive method for detecting bio-active compounds in biological samples by means of functionalised nanoparticles interrogated by surface enhanced Raman spectroscopy (SERS). This method is applicable to the recovery and detection of many diagnostically important peptidyl analytes such as insulin, human growth hormone, growth factors (IGFs) and erythropoietin (EPO), as well as many small molecule analytes and metabolites. Our method, developed to detect EPO, demonstrates its utility in a complex yet well defined biological system. Recombinant human EPO (rhEPO) and EPO analogues have successfully been used to treat anaemia in end-stage renal failure, chronic disorders and infections, cancer and AIDS. Current methods for EPO testing are lengthy, laborious and relatively insensitive to low concentrations. In our rapid screening methodology, gold nanoparticles were functionalised with anti-EPO antibodies to provide very high selectivity towards the EPO protein in urine. These “smart sensor” nanoparticles interact with and trap EPO. Subsequent SERS screening allows for the detection and quantisation of ultra trace amounts (<<10-15 M) of EPO in urine samples with minimal sample preparation. We present data showing that the SERS spectrum differentiates between human endogenous EPO and rhEPO in unpurified urine, and potentially distinguishes between purified EPO isoforms. The elimination of sample preparation and direct screening in biological fluids significantly reduces the time required by current methods. Antibody recognition against a variety of biological targets and the availability of portable commercial SERS analysers for rapid onsite testing suggest broad diagnostic applicability in a flexible analytical platform.

Monitoring and benchmarking government policies and actions to improve the healthiness of food environments : a proposed Government Healthy Food Environment Policy Index

Government action is essential to increase the healthiness of food environments and reduce obesity, diet-related non-communicable diseases (NCDs), and their related inequalities. This paper proposes a monitoring framework to assess government policies and actions for creating healthy food environments. Recommendations from relevant authoritative organizations and expert advisory groups for reducing obesity and NCDs were examined, and pertinent components were incorporated into a comprehensive framework for monitoring government policies and actions. A Government Healthy Food Environment Policy Index (Food-EPI) was developed, which comprises a ‘policy’ component with seven domains on specific aspects of food environments, and an ‘infrastructure support’ component with seven domains to strengthen systems to prevent obesity and NCDs. These were revised through a week-long consultation process with international experts. Examples of good practice statements are proposed within each domain, and these will evolve into benchmarks established by governments at the forefront of creating and implementing food policies for good health. A rating process is proposed to assess a government's level of policy implementation towards good practice. The Food-EPI will be pre-tested and piloted in countries of varying size and income levels. The benchmarking of government policy implementation has the potential to catalyse greater action to reduce obesity and NCDs.

Modal flexibility method for structural damage detection in suspension bridges

Suspension bridges meet the steadily growing demand for lighter and longer bridges in today’s infrastructure systems. These bridges are designed to have long life spans, but with age, their main cables and hangers could suffer from corrosion and fatigue. There is a need for a simple and reliable procedure to detect and locate such damage, so that appropriate retrofitting can be carried out to prevent bridge failure. Damage in a structure causes changes in its properties (mass, damping and stiffness) which in turn will cause changes in its vibration characteristics (natural frequencies, modal damping and mode shapes). Methods based on modal flexibility, which depends on both the natural frequencies and mode shapes, have the potential for damage detection. They have been applied successfully to beam and plate elements, trusses and simple structures in reinforced concrete and steel. However very limited applications for damage detection in suspension bridges have been identified to date. This paper examines the potential of modal flexibility methods for damage detection and localization of a suspension bridge under different damage scenarios in the main cables and hangers using numerical simulation techniques. Validated finite element model (FEM) of a suspension bridge is used to acquire mass normalized mode shape vectors and natural frequencies at intact and damaged states. Damage scenarios will be simulated in the validated FE models by varying stiffness of the damaged structural members. The capability of damage index based on modal flexibility to detect and locate damage is evaluated. Results confirm that modal flexibility based methods have the ability to successfully identify damage in suspension bridge main cables and hangers.

Damage detection in cable structures using vibration characteristics

Cable structures find many applications such as in power transmission, in anchors and especially in bridges. They serve as major load bearing elements in suspension bridges, which are capable of spanning long distances. All bridges, including suspension bridges, are designed to have long service lives. However, during this long life, they become vulnerable to damage due to changes in loadings, deterioration with age and random action such as impacts. The main cables are more vulnerable to corrosion and fatigue, compared to the other bridge components, and consequently reduces the serviceability and ultimate capacity of the bridge. Detecting and locating such damage at the earliest stage is challenging in the current structural health monitoring (SHM) systems of long span suspension bridges. Damage or deterioration of a structure alters its stiffness, mass and damping properties which in turn modify its vibration characteristics. This phenomenon can therefore be used to detect damage in a structure. The modal flexibility, which depends on the vibration characteristics of a structure, has been identified as a successful damage indicator in beam and plate elements, trusses and simple structures in reinforced concrete and steel. Successful application of the modal flexibility phenomenon to detect and locate the damage in suspension bridge main cables has received limited attention in recent research work. This paper, therefore examines the potential of the modal flexibility based Damage Index (DI) for detecting and locating damage in the main cable of a suspension bridge under four different damage scenarios. Towards this end, a numerical model of a suspension bridge cable was developed to extract the modal parameters at both damaged and undamaged states. Damage scenarios considered in this study with varied location and severity were simulated by changing stiffness at particular locations of the cable model. Results confirm that the DI has the potential to successfully detect and locate damage in suspension bridge main cables. This simple method can therefore enable bridge engineers and managers to detect and locate damage in suspension bridges at an early stage, minimize expensive retrofitting and prevent bridge collapse.

Internet-based surveillance systems for monitoring emerging infectious diseases

Emerging infectious diseases present a complex challenge to public health officials and governments; these challenges have been compounded by rapidly shifting patterns of human behaviour and globalisation. The increase in emerging infectious diseases has led to calls for new technologies and approaches for detection, tracking, reporting, and response. Internet-based surveillance systems offer a novel and developing means of monitoring conditions of public health concern, including emerging infectious diseases. We review studies that have exploited internet use and search trends to monitor two such diseases: influenza and dengue. Internet-based surveillance systems have good congruence with traditional surveillance approaches. Additionally, internet-based approaches are logistically and economically appealing. However, they do not have the capacity to replace traditional surveillance systems; they should not be viewed as an alternative, but rather an extension. Future research should focus on using data generated through internet-based surveillance and response systems to bolster the capacity of traditional surveillance systems for emerging infectious diseases.

A systematic review of community-based interventions for emerging zoonotic diseases in Southeast Asia

Background Southeast Asia has been at the epicentre of recent epidemics of emerging and re-emerging zoonotic diseases. Community-based surveillance and control interventions have been heavily promoted but the most effective interventions have not been identified. Objectives This review evaluated evidence for the effectiveness of community-based surveillance interventions at monitoring and identifying emerging infectious disease; the effectiveness of community-based control interventions at reducing rates of emerging infectious disease; and contextual factors that influence intervention effectiveness. Inclusion criteria Participants Communities in Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Viet Nam. Types of intervention(s) Non-pharmaceutical, non-vaccine, and community-based surveillance or prevention and control interventions targeting rabies, Nipah virus , dengue, SARS or avian influenza. Types of outcomes Primary outcomes: measures: of infection or disease; secondary outcomes: measures of intervention function. Types of studies Original quantitative studies published in English. Search strategy Databases searched (1980 to 2011): PubMed, CINAHL, ProQuest, EBSCOhost, Web of Science, Science Direct, Cochrane database of systematic reviews, WHOLIS, British Development Library, LILACS, World Bank (East Asia), Asian Development Bank. Methodological quality Two independent reviewers critically appraised studies using standard Joanna Briggs Institute instruments. Disagreements were resolved through discussion. Data extraction A customised tool was used to extract quantitative data on intervention(s), populations, study methods, and primary and secondary outcomes; and qualitative contextual information or narrative evidence about interventions. Data synthesis Data was synthesised in a narrative summary with the aid of tables. Meta-analysis was used to statistically pool quantitative results. Results Fifty-seven studies were included. Vector control interventions using copepods, environmental cleanup and education are effective and sustainable at reducing dengue in rural and urban communities, whilst insecticide spraying is effective in urban outbreak situations. Community-based surveillance interventions can effectively identify avian influenza in backyard flocks, but have not been broadly applied. Outbreak control interventions for Nipah virus and SARS are effective but may not be suitable for ongoing control. Canine vaccination and education is more acceptable than culling, but still fails to reach coverage levels required to effectively control rabies. Contextual factors were identified that influence community engagement with, and ultimately effectiveness of, interventions. Conclusion Despite investment in community-based disease control and surveillance in Southeast Asia, published evidence evaluating interventions is limited in quantity and quality. Nonetheless this review identified a number of effective interventions, and several contextual factors influencing effectiveness. Identification of the best programs will require comparative evidence of effectiveness acceptability, cost-effectiveness and sustainability.

Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

Systematic Review Protocol : "Are community-based interventions effective in identifying and responding to emerging zoonotic infectious diseases?"

Review question/objective The objective of this review is to identify the effectiveness of surveillance systems and community-based interventions in identifying and responding to emerging and re-emerging zoonotic infections in Southeast Asia (SE Asia). More specifically the research questions are: 1. What is the effectiveness of community-based surveillance interventions designed to identify emerging zoonotic infectious diseases? 2. What is the effectiveness of non-pharmaceutical community-based interventions designed to prevent transmission of emerging zoonotic infectious diseases? 3. How do factors related to the emergence and management of emerging zoonotic infectious diseases impact the effectiveness of interventions designed to identify and respond to them?

Detection of rain in acoustic recordings of the environment

Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.

Can skin cancer prevention and early detection be improved via mobile phone text messaging? a randomised, attention-control trial.

Objective. To test the impact of a theory-based, SMS (text message)-delivered behavioural intervention (Healthy Text) targeting sun protection or skin self-examination behaviours compared to attention-control. Method. Overall, 546 participants aged 18–42 years were randomised using a computer-generated number list to the skin self-examination (N = 176), sun protection (N = 187), or attention-control (N = 183) text messages group. Each group received 21 text messages about their assigned topic over 12 months (12 weekly messages for three months, then monthly messages for the next nine months). Data was collected via telephone survey at baseline, three-, and 12-months across Queensland from January 2012 to August 2013. Results. One year after baseline, the sun protection (mean change 0.12; P = 0.030) and skin self-examination groups (mean change 0.12; P = 0.035) had significantly greater improvement in their sun protection habits (SPH) index compared to the attention-control group (reference mean change 0.02). The increase in the proportion of participants who reported any skin self-examination from baseline to 12 months was significantly greater in the skin self-examination intervention group (103/163; 63%; P < 0.001) than the sun protection (83/173; 48%), or attention-control (65/165; 36%) groups. There was no significant effect of the intervention for participants who self-reported whole-body skin self-examination, sun tanning behaviour, or sunburn behaviours. Conclusion. The Healthy Text intervention was effective in inducing significant improvements in sun protection and any type of skin self-examination behaviours.

Poverty and non-communicable diseases in South Africa

Background: High levels of wealth inequality with improved health statistics in South Africa (SA) provide an important opportunity to investigate non-communicable diseases (NCDs) among the poor. Aims: This paper uses two distinct national data sets to contrast patterns of mortality in rich and poor areas and explore the associations between poverty, risk factors, health care and selected NCDs diseases in South African adults. Methods: Causes of premature mortality in 1996 experienced in the poorest magisterial districts are compared with those in the richest, using average household wealth to classify districts. Logistic and multinomial regression are used to investigate the association of a household asset index and selected chronic conditions, related risk factors and healthcare indicators using data from the 1998 South African Demographic and Health Survey. Results: NCDs accounted for 39% and 33% of premature mortality in rich and poor districts respectively. The household survey data showed that the risk factors hypertension and obesity increased with increasing wealth, while most of the lifestyle factors, such as light smoking, domestic exposure to ``smoky'' fuels and alcohol dependence were associated with poverty. Treatment status for hypertension and asthma was worse for poor people than for rich people. Conclusions: The study suggests that NCDs and lifestyle-related risk factors are prevalent among the poor in SA and treatment for chronic diseases is lacking for poor people. The observed increase in hypertension and obesity with wealth suggests that unless comprehensive health promotion strategies are implemented, there will be an unmanageable chronic disease epidemic with future socioeconomic development in SA.

Green-fluorescent protein facilitates rapid in vivo detection of genetically transformed plant cells

Early detection of plant transformation events is necessary for the rapid establishment and optimization of plant transformation protocols. We have assessed modified versions of the green fluorescent protein (GFP) from Aequorea victoria as early reporters of plant transformation using a dissecting fluorescence microscope with appropriate filters. Gfp-expressing cells from four different plant species (sugarcane, maize, lettuce, and tobacco) were readily distinguished, following either Agrobacterium-mediated or particle bombardment-mediated transformation. The identification of gfp-expressing sugarcane cells allowed for the elimination of a high proportion of non-expressing explants and also enabled visual selection of dividing transgenic cells, an early step in the generation of transgenic organisms. The recovery of transgenic cell clusters was streamlined by the ability to visualize gfp-expressing tissues in vitro.

A nationwide web-based automated system for early outbreak detection and rapid response in China

Timely reporting, effective analyses and rapid distribution of surveillance data can assist in detecting the aberration of disease occurrence and further facilitate a timely response. In China, a new nationwide web-based automated system for outbreak detection and rapid response was developed in 2008. The China Infectious Disease Automated-alert and Response System (CIDARS) was developed by the Chinese Center for Disease Control and Prevention based on the surveillance data from the existing electronic National Notifiable Infectious Diseases Reporting Information System (NIDRIS) started in 2004. NIDRIS greatly improved the timeliness and completeness of data reporting with real time reporting information via the Internet. CIDARS further facilitates the data analysis, aberration detection, signal dissemination, signal response and information communication needed by public health departments across the country. In CIDARS, three aberration detection methods are used to detect the unusual occurrence of 28 notifiable infectious diseases at the county level and to transmit that information either in real-time or on a daily basis. The Internet, computers and mobile phones are used to accomplish rapid signal generation and dissemination, timely reporting and reviewing of the signal response results. CIDARS has been used nationwide since 2008; all Centers for Disease Control and Prevention (CDC) in China at the county, prefecture, provincial and national levels are involved in the system. It assists with early outbreak detection at the local level and prompts reporting of unusual disease occurrences or potential outbreaks to CDCs throughout the country.

Microscopy for the detection, identification and quantification of malaria parasites on stained thick and thin blood films in research settings

Summary This manual was developed to guide a move towards common standards for undertaking and reporting research microscopy for malaria parasite detection, identification and quantification. It contains procedures based on agreed quality assurance standards for research malaria microscopy defined at a consultation of: TDR, the Special Programme for Research and Training in Tropical Diseases; the Worldwide Antimalarial Resistance Network (WWARN), United Kingdom; the Foundation for Innovative New Diagnostics (FIND), Switzerland; the Centers for Disease Control and Prevention (CDC), USA; the Kenya Medical Research Institute (KEMRI) and later expanded to include Amref Health Africa (Kenya); the Eijkman-Oxford Clinical Research Unit (EOCRU), Indonesia; Institut Pasteur du Cambodge (IPC); Institut de recherche pour le Développement (IRD), Senegal; the Global Good and Intellectual Ventures Laboratory (GG-IVL), USA; the Mahidol-Oxford Tropical Medicine Research Unit (MORU), Thailand; Queensland University of Technology (QUT), Australia, and the Shoklo Malaria Research Unit (SMRU), Thailand. These collaborating institutions commit to adhering to these standards in published research studies. It is hoped that they will form a solid basis for the wider adoption of standardized reference microscopy protocols for malaria research.

Gender-specific differences of interaction between obesity and air pollution on stroke and cardiovascular diseases in Chinese adults from a high pollution range area: A large population based cross sectional study

Background Little information exists regarding the interaction effects of obesity with long-term air pollution exposure on cardiovascular diseases (CVDs) and stroke in areas of high pollution. The aim of the present study is to examine whether obesity modifies CVD-related associations among people living in an industrial province of northeast China. Methods We studied 24,845 Chinese adults, aged 18 to 74 years old, from three Northeastern Chinese cities in 2009 utilizing a cross-sectional study design. Body weight and height were measured by trained observers. Overweight and obesity were defined as a body mass index (BMI) between 25–29.9 and ≥ 30 kg/m2, respectively. Prevalence rate and related risk factors of cardiovascular and cerebrovascular diseases were investigated by a questionnaire. Three-year (2006–2008) average concentrations of particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxides (NO2), and ozone (O3) were measured by fixed monitoring stations. All the participants lived within 1 km of air monitoring sites. Two-level logistic regression (personal level and district-specific pollutant level) was used to examine these effects, controlling for covariates. Results We observed significant interactions between exposure and obesity on CVDs and stroke. The associations between annual pollutant concentrations and CVDs and stroke were strongest in obese subjects (OR 1.15–1.47 for stroke, 1.33–1.59 for CVDs), less strong in overweight subjects (OR 1.22–1.35 for stroke, 1.07–1.13 for CVDs), and weakest in normal weight subjects (OR ranged from 0.98–1.01 for stroke, 0.93–1.15 for CVDs). When stratified by gender, these interactions were significant only in women. Conclusions Study findings indicate that being overweight and obese may enhance the effects of air pollution on the prevalence of CVDs and stroke in Northeastern metropolitan China. Further studies will be needed to investigate the temporality of BMI relative to exposure and onset of disease.