Tunable “Nano-Shearing” : A physical mechanism to displace nonspecific cell adhesion during rare cell detection

We report a tunable alternating current electrohydrodynamic (ac-EHD) force which drives lateran fluid motion within a few nanometers of an electrode surface. Because the magnitude of this fluid shear force can be tuned externally (e.g., via the application of an ac electric field), it provides a new capability to physically displace weakly (nonspecifically) bound cellular analytes. To demonstrate the utility of the tunable nanoshearing phenomenon, we present data on purpose-built microfluidic devices that employ ac-EHD force to remove nonspecific adsorption of molecular and cellular species. Here, we show that an ac-EHD device containing asymmetric planar and microtip electrode pairs resulted in a 4-fold reduction in nonspecific adsorption of blood cells and also captured breast cancer cells in blood, with high efficiency (approximately 87%) and specificity. We therefore feel that this new capability of externally tuning and manipulating fluid flow could have wide applications as an innovative approach to enhance the specific capture of rare cells such as cancer cells in blood.

Condition monitoring and fault diagnosis of diesel engines using instantaneous angular speed analysis

Continuous monitoring of diesel engine performance is critical for early detection of fault developments in an engine before they materialize into a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few nonintrusive condition monitoring techniques that can be utilized for such a task. Furthermore, the technique is more suitable for mass industry deployments than other non-intrusive methods such as vibration and acoustic emission techniques due to the low instrumentation cost, smaller data size and robust signal clarity since IAS is not affected by the engine operation noise and noise from the surrounding environment. A combination of IAS and order analysis was employed in this experimental study and the major order component of the IAS spectrum was used for engine loading estimation and fault diagnosis of a four-stroke four-cylinder diesel engine. It was shown that IAS analysis can provide useful information about engine speed variation caused by changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectra directly associated with the engine firing frequency (at twice the mean shaft rotating speed) can be utilized to estimate engine loading condition regardless of whether the engine is operating at healthy condition or with faults. The amplitude of this order component follows a distinctive exponential curve as the loading condition changes. A mathematical relationship was then established in the paper to estimate the engine power output based on the amplitude of this order component of the IAS spectrum. It was further illustrated that IAS technique can be employed for the detection of a simulated exhaust valve fault in this study.

The benefits and challenges of conducting an overview of systematic reviews in public health: a focus on physical activity

Introduction The ultimate aim of Cochrane systematic reviews is to inform policy and practice decisions for better health outcomes. However, due to the increasing numbers of scientific publications, wading through the available evidence of both individual studies and systematic reviews can be challenging and overwhelming even for avid authors and readers. This paper briefly describes the first overview (a systematic review of reviews) of the Cochrane Public Health Group (CPHG) in development and proposes a way forward for the methodologies under consideration.

The impact of diabetic ketoacidosis and age on behavior six months post-diagnosis in children with type 1 diabetes

Objectives: Children with type 1 diabetes mellitus (DM1) may be at increased risk of psychosocial and adjustment difficulties. We examined behavioral outcomes six months post-diagnosis in a group of children with newly diagnosed DM1. Methods: This study formed part of a larger longitudinal project examining pathophysiology and neuropsychological outcomes in diabetic patients with or without diabetic ketoacidosis (DKA). Participants were 61 children (mean age 11.8 years, SD 2.7 years) who presented with a new diagnosis of DM1 at the Royal Children’s Hospital, Melbourne. Twenty-three (11 female) presented in DKA and 38 (14 female) without DKA. Parents completed the behavior assessment system for children, second edition six months post-diagnosis. Results: There was a non-linear relationship between age and behavior. Internalising problems (i.e. anxiety depression, withdrawal) peaked in the transition from childhood to adolescence; children aged 10–13 years had elevated rates relative to the normal population (t = 2.55, P = 0.018). There was a non-significant trend for children under 10 to display internalising problems (P = 0.052), but rates were not elevated in children over 13 (P = 0.538). Externalising problems were not significantly elevated in any age group. Interestingly, children who presented in DKA were at lower risk of internalising problems than children without DKA (t = 3.83, P < 0.001). There was no effect of DKA on externalising behaviors. Conclusions: Children transitioning from childhood to adolescence are at significant risk for developing internalising problems such as anxiety and lowered mood after diagnosis of DM1. Somewhat counter-intuitively, parents of children presenting in DKA reported fewer internalising symptoms than parents of children without DKA. These results highlight the importance of monitoring and supporting psychosocial adjustment in newly diagnosed children even when they seem physically well.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Physical activity, walking and quality of life in women with depressive symptoms

Background Physical activity (PA) has a positive association with health-related quality of life (HRQL) in the general population. The association between PA and HRQL in those with poor mental health is less clear. Purpose To examine the concurrent and prospective dose-response relationships between total physical activity (TPA) and walking only with HRQL in women aged 50-55 with depressive symptoms in 2001. Methods Participants were 1904 women born in 1946-1951 who completed mailed surveys for the Australian Longitudinal Study on Women's Health in 2001, 2004, 2007 and 2010 and who, in 2001, reported depressive symptoms. At each time point, they reported their weekly minutes of walking, moderate PA, and vigorous PA. A summary TPA score was created that accounted for differences in energy expenditure among the three PA types. Mixed models were used to examine associations between TPA and HRQL (SF-36 component and subscale scores) and between walking and HRQL, for women who reported walking as their only PA. Analyses were conducted in 2013-2014. Results Concurrently, higher levels of TPA and walking were associated with better HRQL (p<0.05). The strongest associations were found for physical functioning, vitality, and social functioning subscales. In prospective models, associations were attenuated, yet compared with women doing no TPA or walking, women doing “sufficient” TPA or walking had significantly better HRQL over time for most SF-36 scales. Conclusions This study extends previous work by demonstrating trends between both TPA and walking and HRQL in women reporting depressive symptoms.

Age, physical inactivity, obesity, health conditions, and health-related quality of life among patients receiving conservative management for musculoskeletal disorders

Background Musculoskeletal conditions and insufficient physical activity have substantial personal and economic costs among contemporary aging societies. This study examined the age distribution, comorbid health conditions, body mass index (BMI), self-reported physical activity levels, and health-related quality of life of patients accessing ambulatory hospital clinics for musculoskeletal disorders. The study also investigated whether comorbidity, BMI, and self-reported physical activity were associated with patients’ health-related quality of life after adjusting for age as a potential confounder. Methods A cross-sectional survey was undertaken in three ambulatory hospital clinics for musculoskeletal disorders. Participants (n=224) reported their reason for referral, age, comorbid health conditions, BMI, physical activity levels (Active Australia Survey), and health-related quality of life (EQ-5D). Descriptive statistics and linear modeling were used to examine the associations between age, comorbidity, BMI, intensity and duration of physical activity, and health-related quality of life. Results The majority of patients (n=115, 51.3%) reported two or more comorbidities. In addition to other musculoskeletal conditions, common comorbidities included depression (n=41, 18.3%), hypertension (n=40, 17.9%), and diabetes (n=39, 17.4%). Approximately one-half of participants (n=110, 49.1%) self-reported insufficient physical activity to meet minimum recommended guidelines and 150 (67.0%) were overweight (n=56, 23.2%), obese (n=64, 28.6%), severely obese (n=16, 7.1%), or very severely obese (n=14, 6.3%), with a higher proportion of older patients affected. A generalized linear model indicated that, after adjusting for age, self-reported physical activity was positively associated (z=4.22, P<0.001), and comorbidities were negatively associated (z=-2.67, P<0.01) with patients’ health-related quality of life. Conclusion Older patients were more frequently affected by undesirable clinical attributes of comorbidity, obesity, and physical inactivity. However, findings from this investigation are compelling for the care of patients of all ages. Potential integration of physical activity behavior change or other effective lifestyle interventions into models of care for patients with musculoskeletal disorders is worthy of further investigation.