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The aim of this study was to contribute to knowledge about classroom assessment by identifying profiles of teachers’ assessment of their students’ understanding of mathematics. For carrying out this study we used data of a nationwide teacher survey (N = 960) in the Netherlands. The data were collected by an online questionnaire. Through exploratory factor analyses the underlying structure of what is measured by this questionnaire was uncovered as consisting of five factors: Goal centeredness of assessment, Authentic nature of assessment, Perceived usefulness of assessment, Diversity of assessment problem format, and Allocated importance of assessing skills and knowledge. By using a latent class analysis four different assessment profiles of teachers were identified: Enthusiastic assessors, Mainstream assessors, Non-enthusiastic assessors, and Alternative assessors. The findings suggest that teachers with particular assessment profiles have qualitatively different assessment practices. The paper concludes with discussing theoretical implications of these assessment profiles and indications these profiles can offer both for designing material for professional development in classroom assessment and for evaluating changes in teachers’ classroom assessment practice. [ABSTRACT FROM AUTHOR]

Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss. [ABSTRACT FROM AUTHOR]

The vasculature of body tissues is continuously subject to remodeling processes originating at the micro-vascular level. The formation of new blood vessels (angiogenesis) is essential for a number of physiological and pathophysiological processes such as tissue regeneration, tumor development and the integration of artificial tissues. There are currently no time-lapsed in vivo imaging techniques providing information on the vascular network at the capillary level in a non-destructive, three-dimensional and high-resolution fashion. This paper presents a novel imaging framework based on contrast enhanced micro-computed tomography (micro-CT) for hierarchical in vivo quantification of blood vessels in mice, ranging from largest to smallest structures. The framework combines for the first time a standard morphometric approach with densitometric analysis. Validation tests showed that the method is precise and robust. Furthermore, the framework is sensitive in detecting different perfusion levels after the implementation of a murine ischemia-reperfusion model. Correlation with both histological data and micro-CT analysis of vascular corrosion casts confirmed accuracy of the method. The newly developed time-lapsed imaging approach shows high potential for in vivo monitoring of a number of different physiological and pathological conditions in angiogenesis and vascular development. [ABSTRACT FROM AUTHOR]

The regulation of chromosome separation during mitosis is not fully understood yet. Microtubules forming mitotic spindles are targets of treatment strategies which are aimed at (i) the triggering of the apoptosis or (ii) the interruption of uncontrolled cell division. Despite these facts, only few physical models relating to the dynamics of mitotic spindles exist up to now. In this paper, we present the first electromechanical model which enables calculation of the electromagnetic field coupled to acoustic vibrations of the mitotic spindle. This electromagnetic field originates from the electrical polarity of microtubules which form the mitotic spindle. The model is based on the approximation of resonantly vibrating microtubules by a network of oscillating electric dipoles. Our computational results predict the existence of a rapidly changing electric field which is generated by either driven or endogenous vibrations of the mitotic spindle. For certain values of parameters, the intensity of the electric field and its gradient reach values which may exert a not-inconsiderable force on chromosomes which are aligned in the spindle midzone. Our model may describe possible mechanisms of the effects of ultra-short electrical and mechanical pulses on dividing cells—a strategy used in novel methods for cancer treatment. [ABSTRACT FROM AUTHOR]

People with TB and/or HIV frequently experience severe economic barriers to health care, including out-of-pocket expenses related to diagnosis and treatment, as well as indirect costs due to loss of income. These barriers can both aggravate economic hardship and prevent or delay diagnosis, treatment and successful outcome, leading to increased transmission, morbidity and mortality. WHO, UNAIDS and the ILO argue that economic support of various kinds is essential to enable vulnerable people to protect themselves from infection, avoid delayed diagnosis and treatment, overcome barriers to adherence, and avert destitution. This paper analyses successful country proposals to the Global Fund to Fight AIDS, Tuberculosis and Malaria that include economic support in Rounds 7 and 10; 36 and 20 HIV and TB grants in Round 7 and 32 and 26, respectively, in Round 10. Of these, up to 84 percent included direct or indirect economic support for beneficiaries, although the amount constituted a very small proportion of the total grant. In TB grants, the objectives of economic support were generally clearly stated, and focused on mechanisms to improve treatment uptake and adherence, and the case was most clearly made for MDR-TB patients. In HIV grants, the objectives were much broader in scope, including mitigation of adverse economic and social effects of HIV and its treatment on both patients and families. The analysis shows that economic support is on the radar for countries developing Global Fund proposals, and a wide range of economic support activities are in place. In order to move forward in this area, the wealth of country experience that exists needs to be collated, assessed and disseminated. In addition to trials, operational research and programme evaluations, more precise guidance to countries is needed to inform evidence-based decision about activities that are cost-effective, affordable and feasible. [ABSTRACT FROM AUTHOR]

Objective: Noncompliance with scheduled ambulatory saliva sampling is common and has been associated with biased cortisol estimates in nonpregnant subjects. This study is the first to investigate in pregnant women strategies to improve ambulatory saliva-sampling compliance, and the association between sampling noncompliance and saliva cortisol estimates. Methods: We instructed 64 pregnant women to collect eight scheduled saliva samples on two consecutive days each. Objective compliance with scheduled sampling times was assessed with a Medication Event Monitoring System and self-reported compliance with a paper-and-pencil diary. In a randomized controlled study, we estimated whether a disclosure intervention (informing women about objective compliance monitoring) and a reminder intervention (use of acoustical reminders) improved compliance. A mixed model analysis was used to estimate associations between women's objective compliance and their diurnal cortisol profiles, and between deviation from scheduled sampling and the cortisol concentration measured in the related sample. Results: Self-reported compliance with a saliva-sampling protocol was 91%, and objective compliance was 70%. The disclosure intervention was associated with improved objective compliance (informed: 81%, noninformed: 60%), F(1,60)  = 17.64, p<0.001, but not the reminder intervention (reminders: 68%, without reminders: 72%), F(1,60)  = 0.78, p = 0.379. Furthermore, a woman's increased objective compliance was associated with a higher diurnal cortisol profile, F(2,64) = 8.22, p<0.001. Altered cortisol levels were observed in less objective compliant samples, F(1,705) = 7.38, p = 0.007, with delayed sampling associated with lower cortisol levels. Conclusions: The results suggest that in pregnant women, objective noncompliance with scheduled ambulatory saliva sampling is common and is associated with biased cortisol estimates. To improve sampling compliance, results suggest informing women about objective compliance monitoring but discourage use of acoustical reminders. [ABSTRACT FROM AUTHOR]

With the proliferation of social networks and blogs, the Internet is increasingly being used to disseminate personal health information rather than just as a source of information. In this paper we exploit the wealth of user-generated data, available through the micro-blogging service Twitter, to estimate and track the incidence of health conditions in society. The method is based on two stages: we start by extracting possibly relevant tweets using a set of specially crafted regular expressions, and then classify these initial messages using machine learning methods. Furthermore, we selected relevant features to improve the results and the execution times. To test the method, we considered four health states or conditions, namely flu, depression, pregnancy and eating disorders, and two locations, Portugal and Spain. We present the results obtained and demonstrate that the detection results and the performance of the method are improved after feature selection. The results are promising, with areas under the receiver operating characteristic curve between 0.7 and 0.9, and f-measure values around 0.8 and 0.9. This fact indicates that such approach provides a feasible solution for measuring and tracking the evolution of health states within the society. [ABSTRACT FROM AUTHOR]

The objective of this paper is to assess the attitude of Malaysian stakeholders to genetically modified (GM) salmon and to identify the factors that influence their acceptance of GM salmon using a structural equation model. A survey was carried out on 434 representatives from various stakeholder groups in the Klang Valley region of Malaysia. Public attitude towards GM salmon was measured using self-developed questionnaires with seven-point Likert scales. The findings of this study have confirmed that public attitudes towards GM salmon is a complex issue and should be seen as a multi-faceted process. The most important direct predictors for the encouragement of GM salmon are the specific application-linked perceptions about religious acceptability of GM salmon followed by perceived risks and benefits, familiarity, and general promise of modern biotechnology. Encouragement of GM salmon also involves the interplay among other factors such as general concerns of biotechnology, threatening the natural order of things, the need for labeling, the need for patenting, confidence in regulation, and societal values. The research findings can serve as a database that will be useful for understanding the social construct of public attitude towards GM foods in a developing country. [ABSTRACT FROM AUTHOR]

Background: Poor nutrition is harmful to one’s health as it can lead to overweight and obesity and a number of chronic diseases. Understanding consumer perceptions toward diet and nutrition is critical to advancing nutrition-related population health interventions to address such issues. The purpose of this paper was to examine Canadians’ perceived health and diet status, compared to their actual health status, and general concern about their own diet and beliefs about health. Also analyzed were some of the perceived barriers to eating “healthy” foods, with a focus on the availability of “healthy” processed foods. Methods: Two surveys were administered online to a group of Canadian panelists from all ten provinces during May 2010 to January 2011. Thirty thousand were invited; 6,665 completed the baseline survey and 5,494 completed the second survey. Panelists were selected to be nationally representative of the Canadian adult population by age, sex, province and education level, according to 2006 census data. Results: Approximately one third of Canadians perceived their health or diet to be very good while very few Canadians perceived their health or diet to be very poor. While the majority of Canadians believed food and nutrition to be very important for improving one’s health, fewer Canadians were concerned about their own diets. The majority of Canadians reported difficulty finding “healthy” processed foods (low in salt and sugar and with sufficient vitamins and minerals). Many also reported difficulty finding healthy foods that are affordable. Conclusion: Although consumers believe that nutrition is one of the most important factors for maintaining health, there are still a number of attitudinal and perceived environmental barriers to healthy eating. [ABSTRACT FROM AUTHOR]

Background: In developing countries hip osteoarthritis constitutes a major public health issue as it is highly prevalent in all age ranges of population, including the young. It often remains untreated because of the low accessibility of total hip prostheses. Hip arthrodesis still represents a major treatment option, but, for several reasons which are discussed in this paper, is nowadays infrequently performed. By means of reporting the results of a new simple technique, using a self-devised plate, the relevancy of hip arthrodesis in this particular environment is emphasized. Methods and Findings: Our series included 35 patients with painful hip osteoarthritis who underwent a hip fusion with the anterolateral arthrodesis plate. Two of them had a concurrent femoral osteotomy for correction of a vicious position of the limb and another patient had a femoral diaphysis osteotomy and placement of a Wagner elongating device in order to proceed with a limb lengthening by callotasis. The follow-up period averaged 16,9 months (9 to 34). All hips, except two, achieved solid fusion between 6 and 15 months after surgery. One failure of fusion was in the oldest patient, who presented a loosening of plate and screws due to an advanced degree of osteoporosis; the other was in a young patient who admitted having walked on his leg too soon. Patient satisfaction was high. We concluded that this technique is reliable and effective. Conclusions: The results of this study should convince the hesitant surgeon and patient to consider hip arthrodesis an acceptable treatment option for disabling hip arthritis, compared to no treatment at all. [ABSTRACT FROM AUTHOR]

Purpose: This paper describes a novel method to automatically segment the human brainstem into midbrain and pons, called LABS: Landmark-based Automated Brainstem Segmentation. LABS processes high-resolution structural magnetic resonance images (MRIs) according to a revised landmark-based approach integrated with a thresholding method, without manual interaction. Methods: This method was first tested on morphological T1-weighted MRIs of 30 healthy subjects. Its reliability was further confirmed by including neurological patients (with Alzheimer's Disease) from the ADNI repository, in whom the presence of volumetric loss within the brainstem had been previously described. Segmentation accuracies were evaluated against expert-drawn manual delineation. To evaluate the quality of LABS segmentation we used volumetric, spatial overlap and distance-based metrics. Results: The comparison between the quantitative measurements provided by LABS against manual segmentations revealed excellent results in healthy controls when considering either the midbrain (DICE measures higher that 0.9; Volume ratio around 1 and Hausdorff distance around 3) or the pons (DICE measures around 0.93; Volume ratio ranging 1.024–1.05 and Hausdorff distance around 2). Similar performances were detected for AD patients considering segmentation of the pons (DICE measures higher that 0.93; Volume ratio ranging from 0.97–0.98 and Hausdorff distance ranging 1.07–1.33), while LABS performed lower for the midbrain (DICE measures ranging 0.86–0.88; Volume ratio around 0.95 and Hausdorff distance ranging 1.71–2.15). Conclusions: Our study represents the first attempt to validate a new fully automated method for in vivo segmentation of two anatomically complex brainstem subregions. We retain that our method might represent a useful tool for future applications in clinical practice. [ABSTRACT FROM AUTHOR]

Cardiovascular malformations and cardiomyopathy are among the most common phenotypes caused by deletions of chromosome 1p36 which affect approximately 1 in 5000 newborns. Although these cardiac-related abnormalities are a significant source of morbidity and mortality associated with 1p36 deletions, most of the individual genes that contribute to these conditions have yet to be identified. In this paper, we use a combination of clinical and molecular cytogenetic data to define five critical regions for cardiovascular malformations and two critical regions for cardiomyopathy on chromosome 1p36. Positional candidate genes which may contribute to the development of cardiovascular malformations associated with 1p36 deletions include DVL1, SKI, RERE, PDPN, SPEN, CLCNKA, ECE1, HSPG2, LUZP1, and WASF2. Similarly, haploinsufficiency of PRDM16–a gene which was recently shown to be sufficient to cause the left ventricular noncompaction–SKI, PRKCZ, RERE, UBE4B and MASP2 may contribute to the development of cardiomyopathy. When treating individuals with 1p36 deletions, or providing prognostic information to their families, physicians should take into account that 1p36 deletions which overlie these cardiac critical regions may portend to cardiovascular complications. Since several of these cardiac critical regions contain more than one positional candidate gene–and large terminal and interstitial 1p36 deletions often overlap more than one cardiac critical region–it is likely that haploinsufficiency of two or more genes contributes to the cardiac phenotypes associated with many 1p36 deletions. [ABSTRACT FROM AUTHOR]

Background: Evidence about relevant outcomes is required in the evaluation of clinical interventions for children with autism spectrum disorders (ASD). However, to date, the variety of outcome measurement tools being used, and lack of knowledge about the measurement properties of some, compromise conclusions regarding the most effective interventions. Objectives: This two-stage systematic review aimed to identify the tools used in studies evaluating interventions for anxiety for high-functioning children with ASD in middle childhood, and then to evaluate the tools for their appropriateness and measurement properties. Methods: Electronic databases including Medline, PsychInfo, Embase, and the Cochrane database and registers were searched for anxiety intervention studies for children with ASD in middle childhood. Articles examining the measurement properties of the tools used were then searched for using a methodological filter in PubMed, and the quality of the papers evaluated using the COSMIN checklist. Results: Ten intervention studies were identified in which six tools measuring anxiety and one of overall symptom change were used as primary outcomes. One further tool was included as it is recommended for standard use in UK children's mental health services. Sixty three articles on the properties of the tools were evaluated for the quality of evidence, and the quality of the measurement properties of each tool was summarised. Conclusions: Overall three questionnaires were found robust in their measurement properties, the Spence Children's Anxiety Scale, its revised version – the Revised Children's Anxiety and Depression Scale, and also the Screen for Child Anxiety Related Emotional Disorders. Crucially the articles on measurement properties provided almost no evidence on responsiveness to change, nor on the validity of use of the tools for evaluation of interventions for children with ASD. PROSPERO Registration number: CRD42012002684. [ABSTRACT FROM AUTHOR]

Women experiencing greater childhood adversity exhibit faster reproductive trajectories. One possible psychological mechanism underlying this phenomenon is an increased interest in infants. Interest in infants is thought to be an adaptation important for successful rearing as it motivates the acquisition of caretaking skills. We investigated the relationships between childhood adversity, intended reproductive timing and interest in infants in a sample of English adolescent girls. Specifically we sought to investigate the relationship between 1) childhood adversity and intended reproductive timing; 2) childhood adversity and interest in infants; and 3) intended reproductive timing and interest in infants. Additionally we explored different methods of measuring interest in infants using self-reported fondness for babies, a forced choice adult versus infant paper-based preference task and a novel computer based attention task using adult and infant stimuli. In total 357 girls aged nine to 14 years participated in the study, which took place in schools. Participants completed the two interest in infants tasks before moving on to a childhood adversity questionnaire. Girls with more childhood adversity reported earlier ideal ages at parenthood. We found some evidence that, contrary to our predictions, girls with less childhood adversity were more interested in infants. There was no relationship between intended reproductive timing and interest in infants. The different measurements for interest in infants were only weakly related, if at all, highlighting the complexity of measuring this construct. Our findings suggest that rather than interest in infants being a mechanism for the effect of childhood adversity on early reproductive timing it might instead be an indicator of future reproductive strategies. [ABSTRACT FROM AUTHOR]

Because of its richness and availability, micro-blogging has become an ideal platform for conducting psychological research. In this paper, we proposed to predict active users' personality traits through micro-blogging behaviors. 547 Chinese active users of micro-blogging participated in this study. Their personality traits were measured by the Big Five Inventory, and digital records of micro-blogging behaviors were collected via web crawlers. After extracting 845 micro-blogging behavioral features, we first trained classification models utilizing Support Vector Machine (SVM), differentiating participants with high and low scores on each dimension of the Big Five Inventory. The classification accuracy ranged from 84% to 92%. We also built regression models utilizing PaceRegression methods, predicting participants' scores on each dimension of the Big Five Inventory. The Pearson correlation coefficients between predicted scores and actual scores ranged from 0.48 to 0.54. Results indicated that active users' personality traits could be predicted by micro-blogging behaviors. [ABSTRACT FROM AUTHOR]

No matching vaccine is immediately available when a novel influenza strain breaks out. Several nonvaccine-related strategies must be employed to control an influenza epidemic, including antiviral treatment, patient isolation, and immigration detection. This paper presents the development and application of two regional dynamic models of influenza with Pontryagin’s Maximum Principle to determine the optimal control strategies for an epidemic and the corresponding minimum antiviral stockpiles. Antiviral treatment was found to be the most effective measure to control new influenza outbreaks. In the case of inadequate antiviral resources, the preferred approach was the centralized use of antiviral resources in the early stage of the epidemic. Immigration detection was the least cost-effective; however, when used in combination with the other measures, it may play a larger role. The reasonable mix of the three control measures could reduce the number of clinical cases substantially, to achieve the optimal control of new influenza. [ABSTRACT FROM AUTHOR]

Obesity is an important and intractable public health problem. In addition to the well-known risk factors of behavior, diet, and genetics, gut microbial communities were recently identified as another possible source of risk and a potential therapeutic target. However, human and animal-model studies have yielded conflicting results about the precise nature of associations between microbiome composition and obesity. In this paper, we use publicly available data from the Human Microbiome Project (HMP) and MetaHIT, both surveys of healthy adults that include obese individuals, plus two smaller studies that specifically examined lean versus obese adults. We find that inter-study variability in the taxonomic composition of stool microbiomes far exceeds differences between lean and obese individuals within studies. Our analyses further reveal a high degree of variability in stool microbiome composition and diversity across individuals. While we confirm the previously published small, but statistically significant, differences in phylum-level taxonomic composition between lean and obese individuals in several cohorts, we find no association between BMI and taxonomic composition of stool microbiomes in the larger HMP and MetaHIT datasets. We explore a range of different statistical techniques and show that this result is robust to the choice of methodology. Differences between studies are likely due to a combination of technical and clinical factors. We conclude that there is no simple taxonomic signature of obesity in the microbiota of the human gut. [ABSTRACT FROM AUTHOR]

Cortical spreading depression (CSD) is a pathophysiological phenomenon, which underlies some neurological disorders, such as migraine and stroke, but its mechanisms are still not completely understood. One of the striking facts is that the spatiotemporal evolution of CSD wave is varying. Observations in experiments reveal that a CSD wave may propagate through the entire cortex, or just bypass some areas of the cortex. In this paper, we have applied a 2D reaction-diffusion equation with recovery term to study the spatiotemporal evolution of CSD. By modulating the recovery rate from CSD in the modeled cortex, CSD waves with different spatiotemporal evolutions, either bypassing some areas or propagating slowly in these areas, were present. Moreover, spiral CSD waves could also be induced in case of the transiently altered recovery rate, i.e. block release from the absolute refractory period. These results suggest that the refractory period contributes to the different propagation patterns of CSD, which may help to interpret the mechanisms of CSD propagation. [ABSTRACT FROM AUTHOR]

Sudden cardiac death is often caused by cardiac arrhythmias. Recently, special attention has been given to a certain arrhythmogenic condition, the long-QT syndrome, which occurs as a result of genetic mutations or drug toxicity. The underlying mechanisms of arrhythmias, caused by the long-QT syndrome, are not fully understood. However, arrhythmias are often connected to special excitations of cardiac cells, called early afterdepolarizations (EADs), which are depolarizations during the repolarizing phase of the action potential. So far, EADs have been studied mainly in isolated cardiac cells. However, the question on how EADs at the single-cell level can result in fibrillation at the tissue level, especially in human cell models, has not been widely studied yet. In this paper, we study wave patterns that result from single-cell EAD dynamics in a mathematical model for human ventricular cardiac tissue. We induce EADs by modeling experimental conditions which have been shown to evoke EADs at a single-cell level: by an increase of L-type Ca currents and a decrease of the delayed rectifier potassium currents. We show that, at the tissue level and depending on these parameters, three types of abnormal wave patterns emerge. We classify them into two types of spiral fibrillation and one type of oscillatory dynamics. Moreover, we find that the emergent wave patterns can be driven by calcium or sodium currents and we find phase waves in the oscillatory excitation regime. From our simulations we predict that arrhythmias caused by EADs can occur during normal wave propagation and do not require tissue heterogeneities. Experimental verification of our results is possible for experiments at the cell-culture level, where EADs can be induced by an increase of the L-type calcium conductance and by the application of I blockers, and the properties of the emergent patterns can be studied by optical mapping of the voltage and calcium. [ABSTRACT FROM AUTHOR]

Background: Coronary Heart Disease (CHD) is rising in middle income countries. Population based strategies to reduce specific CHD risk factors have an important role to play in reducing overall CHD mortality. Reducing dietary salt consumption is a potentially cost-effective way to reduce CHD events. This paper presents an economic evaluation of population based salt reduction policies in Tunisia, Syria, Palestine and Turkey. Methods and Findings: Three policies to reduce dietary salt intake were evaluated: a health promotion campaign, labelling of food packaging and mandatory reformulation of salt content in processed food. These were evaluated separately and in combination. Estimates of the effectiveness of salt reduction on blood pressure were based on a literature review. The reduction in mortality was estimated using the IMPACT CHD model specific to that country. Cumulative population health effects were quantified as life years gained (LYG) over a 10 year time frame. The costs of each policy were estimated using evidence from comparable policies and expert opinion including public sector costs and costs to the food industry. Health care costs associated with CHDs were estimated using standardized unit costs. The total cost of implementing each policy was compared against the current baseline (no policy). All costs were calculated using 2010 PPP exchange rates. In all four countries most policies were cost saving compared with the baseline. The combination of all three policies (reducing salt consumption by 30%) resulted in estimated cost savings of $235,000,000 and 6455 LYG in Tunisia; $39,000,000 and 31674 LYG in Syria; $6,000,000 and 2682 LYG in Palestine and $1,3000,000,000 and 378439 LYG in Turkey. Conclusion: Decreasing dietary salt intake will reduce coronary heart disease deaths in the four countries. A comprehensive strategy of health education and food industry actions to label and reduce salt content would save both money and lives. [ABSTRACT FROM AUTHOR]

Nowadays, brain signals are employed in various scientific and practical fields such as Medical Science, Cognitive Science, Neuroscience, and Brain Computer Interfaces. Hence, the need for robust signal analysis methods with adequate accuracy and generalizability is inevitable. The brain signal analysis is faced with complex challenges including small sample size, high dimensionality and noisy signals. Moreover, because of the non-stationarity of brain signals and the impacts of mental states on brain function, the brain signals are associated with an inherent uncertainty. In this paper, an evidence-based combining classifiers method is proposed for brain signal analysis. This method exploits the power of combining classifiers for solving complex problems and the ability of evidence theory to model as well as to reduce the existing uncertainty. The proposed method models the uncertainty in the labels of training samples in each feature space by assigning soft and crisp labels to them. Then, some classifiers are employed to approximate the belief function corresponding to each feature space. By combining the evidence raised from each classifier through the evidence theory, more confident decisions about testing samples can be made. The obtained results by the proposed method compared to some other evidence-based and fixed rule combining methods on artificial and real datasets exhibit the ability of the proposed method in dealing with complex and uncertain classification problems. [ABSTRACT FROM AUTHOR]

Lung cancer is one of the most common types of cancer and causes 1.38 million deaths annually, as of 2008 worldwide. Identifying natural anti-lung cancer agents has become very important. Gambogenic acid (GNA) is one of the active compounds of Gamboge, a traditional medicine that was used as a drastic purgative, emetic, or vermifuge for treating tapeworm. Recently, increasing evidence has indicated that GNA exerts promising anti-tumor effects; however, the underlying mechanism remains unclear. In the present paper, we found that GNA could induce the formation of vacuoles, which was linked with autophagy in A549 and HeLa cells. Further studies revealed that GNA triggers the initiation of autophagy based on the results of MDC staining, AO staining, accumulation of LC3 II, activation of Beclin 1 and phosphorylation of P70S6K. However, degradation of p62 was disrupted and free GFP could not be released in GNA treated cells, which indicated a block in the autophagy flux. Further studies demonstrated that GNA blocks the fusion between autophagosomes and lysosomes by inhibiting acidification in lysosomes. This dysfunctional autophagy plays a pro-death role in GNA-treated cells by activating p53, Bax and cleaved caspase-3 while decreasing Bcl-2. Beclin 1 knockdown greatly decreased GNA-induced cell death and the effects on p53, Bax, cleaved caspase-3 and Bcl-2. Similar results were obtained using a xenograft model. Our findings show, for the first time, that GNA can cause aberrant autophagy to induce cell death and may suggest the potential application of GNA as a tool or viable drug in anticancer therapies. [ABSTRACT FROM AUTHOR]

Knowledge of how a population of cancerous cells progress through the cell cycle is vital if the population is to be treated effectively, as treatment outcome is dependent on the phase distributions of the population. Estimates on the phase distribution may be obtained experimentally however the errors present in these estimates may effect treatment efficacy and planning. If mathematical models are to be used to make accurate, quantitative predictions concerning treatments, whose efficacy is phase dependent, knowledge of the phase distribution is crucial. In this paper it is shown that two different transition rates at the - checkpoint provide a good fit to a growth curve obtained experimentally. However, the different transition functions predict a different phase distribution for the population, but both lying within the bounds of experimental error. Since treatment outcome is effected by the phase distribution of the population this difference may be critical in treatment planning. Using an age-structured population balance approach the cell cycle is modelled with particular emphasis on the - checkpoint. By considering the probability of cells transitioning at the - checkpoint, different transition functions are obtained. A suitable finite difference scheme for the numerical simulation of the model is derived and shown to be stable. The model is then fitted using the different probability transition functions to experimental data and the effects of the different probability transition functions on the model's results are discussed. [ABSTRACT FROM AUTHOR]

Identifying patients with Mild Cognitive Impairment (MCI) who are likely to convert to dementia has recently attracted increasing attention in Alzheimer's disease (AD) research. An accurate prediction of conversion from MCI to AD can aid clinicians to initiate treatments at early stage and monitor their effectiveness. However, existing prediction systems based on the original biosignatures are not satisfactory. In this paper, we propose to fit the prediction models using pairwise biosignature interactions, thus capturing higher-order relationship among biosignatures. Specifically, we employ hierarchical constraints and sparsity regularization to prune the high-dimensional input features. Based on the significant biosignatures and underlying interactions identified, we build classifiers to predict the conversion probability based on the selected features. We further analyze the underlying interaction effects of different biosignatures based on the so-called stable expectation scores. We have used 293 MCI subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) database that have MRI measurements at the baseline to evaluate the effectiveness of the proposed method. Our proposed method achieves better classification performance than state-of-the-art methods. Moreover, we discover several significant interactions predictive of MCI-to-AD conversion. These results shed light on improving the prediction performance using interaction features. [ABSTRACT FROM AUTHOR]

Two-way selection is a common phenomenon in nature and society. It appears in the processes like choosing a mate between men and women, making contracts between job hunters and recruiters, and trading between buyers and sellers. In this paper, we propose a model of two-way selection system, and present its analytical solution for the expectation of successful matching total and the regular pattern that the matching rate trends toward an inverse proportion to either the ratio between the two sides or the ratio of the state total to the smaller group's people number. The proposed model is verified by empirical data of the matchmaking fairs. Results indicate that the model well predicts this typical real-world two-way selection behavior to the bounded error extent, thus it is helpful for understanding the dynamics mechanism of the real-world two-way selection system. [ABSTRACT FROM AUTHOR]

Background: Community-based peer support has been shown to be effective in improving exclusive breastfeeding rates in a variety of settings. Methods: We conducted a cost analysis of a community cluster randomised-controlled trial (Promise-EBF), aimed at promoting exclusive infant feeding in three sites in South Africa. The costs were considered from the perspective of health service providers. Peer supporters in this trial visited women to support exclusive infant feeding, once antenatally and four times postpartum. Results: The total economic cost of the Promise-EBF intervention was US$393 656, with average costs per woman and per visit of US$228 and US$52, respectively. The average costs per woman and visit in an operational ‘non research’ scenario were US$137 and US$32 per woman and visit, respectively. Investing in the promotion of exclusive infant feeding requires substantial financial commitment from policy makers. Extending the tasks of multi-skilled community health workers (CHWs) to include promoting exclusive infant feeding is a potential option for reducing these costs. In order to avoid efficiency losses, we recommend that the time requirements for delivering the promotion of exclusive infant feeding are considered when integrating it within the existing activities of CHWs. Discussion: This paper focuses on interventions for exclusive infant feeding, but its findings more generally illustrate the importance of documenting and quantifying factors that affect the feasibility and sustainability of community-based interventions, which are receiving increased focus in low income settings. [ABSTRACT FROM AUTHOR]

Accurate and robust brain extraction is a critical step in most neuroimaging analysis pipelines. In particular, for the large-scale multi-site neuroimaging studies involving a significant number of subjects with diverse age and diagnostic groups, accurate and robust extraction of the brain automatically and consistently is highly desirable. In this paper, we introduce population-specific probability maps to guide the brain extraction of diverse subject groups, including both healthy and diseased adult human populations, both developing and aging human populations, as well as non-human primates. Specifically, the proposed method combines an atlas-based approach, for coarse skull-stripping, with a deformable-surface-based approach that is guided by local intensity information and population-specific prior information learned from a set of real brain images for more localized refinement. Comprehensive quantitative evaluations were performed on the diverse large-scale populations of ADNI dataset with over 800 subjects (55∼90 years of age, multi-site, various diagnosis groups), OASIS dataset with over 400 subjects (18∼96 years of age, wide age range, various diagnosis groups), and NIH pediatrics dataset with 150 subjects (5∼18 years of age, multi-site, wide age range as a complementary age group to the adult dataset). The results demonstrate that our method consistently yields the best overall results across almost the entire human life span, with only a single set of parameters. To demonstrate its capability to work on non-human primates, the proposed method is further evaluated using a rhesus macaque dataset with 20 subjects. Quantitative comparisons with popularly used state-of-the-art methods, including BET, Two-pass BET, BET-B, BSE, HWA, ROBEX and AFNI, demonstrate that the proposed method performs favorably with superior performance on all testing datasets, indicating its robustness and effectiveness. [ABSTRACT FROM AUTHOR]

Murray Valley encephalitis virus (MVEV) is the most serious of the endemic arboviruses in Australia. It was responsible for six known large outbreaks of encephalitis in south-eastern Australia in the 1900s, with the last comprising 58 cases in 1974. Since then MVEV clinical cases have been largely confined to the western and central parts of northern Australia. In 2011, high-level MVEV activity occurred in south-eastern Australia for the first time since 1974, accompanied by unusually heavy seasonal MVEV activity in northern Australia. This resulted in 17 confirmed cases of MVEV disease across Australia. Record wet season rainfall was recorded in many areas of Australia in the summer and autumn of 2011. This was associated with significant flooding and increased numbers of the mosquito vector and subsequent MVEV activity. This paper documents the outbreak and adds to our knowledge about disease outcomes, epidemiology of disease and the link between the MVEV activity and environmental factors. Clinical and demographic information from the 17 reported cases was obtained. Cases or family members were interviewed about their activities and location during the incubation period. In contrast to outbreaks prior to 2000, the majority of cases were non-Aboriginal adults, and almost half (40%) of the cases acquired MVEV outside their area of residence. All but two cases occurred in areas of known MVEV activity. This outbreak continues to reflect a change in the demographic pattern of human cases of encephalitic MVEV over the last 20 years. In northern Australia, this is associated with the increasing numbers of non-Aboriginal workers and tourists living and travelling in endemic and epidemic areas, and also identifies an association with activities that lead to high mosquito exposure. This outbreak demonstrates that there is an ongoing risk of MVEV encephalitis to the heavily populated areas of south-eastern Australia. [ABSTRACT FROM AUTHOR]

Arachidonic (ARA), eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids are the most biologically active polyunsaturated fatty acids, but their biosyntheses in mammals are very limited. The biosynthesis of DHA is the most difficult, because this undergoes the Sprecher pathway–a further elongation step from docosapentaenoic acid (DPA), a Δ6-desaturase acting on a C24 fatty acid substrate followed by a peroxisomal chain shortening step. This paper reports the successful heterologous expression of two non-mammalian genes (with modification of codon usage), coding for Euglena gracilis Δ4-desaturase and Siganus canaliculatus Δ4-desaturase respectively, in mammalian cells (HEK293 cell line). Both of the Δ4-desaturases can efficiently function, directly converting DPA into DHA. Moreover, the cooperation of the E. gracilis Δ4-desaturase with C. elegans Δ15-desaturase (able to convert a number of n-6 PUFAs to their corresponding n-3 PUFAs) in transgenic HEK293 cells made a more desirable fatty acid composition – a drastically reduced n-6/n-3 PUFAs ratio and a high level of DHA as well as EPA and ARA. Our findings provide a basis for potential applications of the gene constructs for expression of Δ15/Δ4-desaturases in transgenic livestock to produce such a fatty acid profile in the related products, which certainly will bring benefit to human health. [ABSTRACT FROM AUTHOR]

In sensory neural system, external asynchronous stimuli play an important role in perceptual learning, associative memory and map development. However, the organization of structure and dynamics of neural networks induced by external asynchronous stimuli are not well understood. Spike-timing-dependent plasticity (STDP) is a typical synaptic plasticity that has been extensively found in the sensory systems and that has received much theoretical attention. This synaptic plasticity is highly sensitive to correlations between pre- and postsynaptic firings. Thus, STDP is expected to play an important role in response to external asynchronous stimuli, which can induce segregative pre- and postsynaptic firings. In this paper, we study the impact of external asynchronous stimuli on the organization of structure and dynamics of neural networks through STDP. We construct a two-dimensional spatial neural network model with local connectivity and sparseness, and use external currents to stimulate alternately on different spatial layers. The adopted external currents imposed alternately on spatial layers can be here regarded as external asynchronous stimuli. Through extensive numerical simulations, we focus on the effects of stimulus number and inter-stimulus timing on synaptic connecting weights and the property of propagation dynamics in the resulting network structure. Interestingly, the resulting feedforward structure induced by stimulus-dependent asynchronous firings and its propagation dynamics reflect both the underlying property of STDP. The results imply a possible important role of STDP in generating feedforward structure and collective propagation activity required for experience-dependent map plasticity in developing in vivo sensory pathways and cortices. The relevance of the results to cue-triggered recall of learned temporal sequences, an important cognitive function, is briefly discussed as well. Furthermore, this finding suggests a potential application for examining STDP by measuring neural population activity in a cultured neural network. [ABSTRACT FROM AUTHOR]

With great potential for assisting radiological image interpretation and decision making, content-based image retrieval in the medical domain has become a hot topic in recent years. Many methods to enhance the performance of content-based medical image retrieval have been proposed, among which the relevance feedback (RF) scheme is one of the most promising. Given user feedback information, RF algorithms interactively learn a user’s preferences to bridge the “semantic gap” between low-level computerized visual features and high-level human semantic perception and thus improve retrieval performance. However, most existing RF algorithms perform in the original high-dimensional feature space and ignore the manifold structure of the low-level visual features of images. In this paper, we propose a new method, termed dual-force ISOMAP (DFISOMAP), for content-based medical image retrieval. Under the assumption that medical images lie on a low-dimensional manifold embedded in a high-dimensional ambient space, DFISOMAP operates in the following three stages. First, the geometric structure of positive examples in the learned low-dimensional embedding is preserved according to the isometric feature mapping (ISOMAP) criterion. To precisely model the geometric structure, a reconstruction error constraint is also added. Second, the average distance between positive and negative examples is maximized to separate them; this margin maximization acts as a force that pushes negative examples far away from positive examples. Finally, the similarity propagation technique is utilized to provide negative examples with another force that will pull them back into the negative sample set. We evaluate the proposed method on a subset of the IRMA medical image dataset with a RF-based medical image retrieval framework. Experimental results show that DFISOMAP outperforms popular approaches for content-based medical image retrieval in terms of accuracy and stability. [ABSTRACT FROM AUTHOR]

Metformin, a well-known insulin-sensitizer commonly used for type 2 diabetes therapy, has recently emerged as potentially very attractive drug also in oncology. It is cheap, it is relatively safe and many reports have indicated effects in cancer prevention and therapy. These desirable features are particularly interesting for pediatric sarcomas, a group of rare tumors that have been shown to be dependent on IGF and insulin system for pathogenesis and progression. Metformin exerts anti-mitogenic activity in several cancer histotypes through several molecular mechanisms. In this paper, we analyzed its effects against osteosarcoma, Ewing sarcoma and rhabdomyosarcoma, the three most common pediatric sarcomas. Despite in vitro metformin gave remarkable antiproliferative and chemosensitizing effects both in sensitive and chemoresistant cells, its efficacy was not confirmed against Ewing sarcoma xenografts neither as single agent nor in combination with vincristine. This discrepancy between in vitro and in vivo effects may be due to hypoxia, a common feature of solid tumors. We provide evidences that in hypoxia conditions metformin was not able to activate AMPK and inhibit mTOR signaling, which likely prevents the inhibitory effects of metformin on tumor growth. Thus, although metformin may be considered a useful complement of conventional chemotherapy in normoxia, its therapeutic value in highly hypoxic tumors may be more limited. The impact of hypoxia should be considered when novel therapies are planned for pediatric sarcomas. [ABSTRACT FROM AUTHOR]

Individual behavioral response to the spreading of an epidemic plays a crucial role in the progression of the epidemic itself. The risk perception induces individuals to adopt a protective behavior, as for instance reducing their social contacts, adopting more restrictive hygienic measures or undergoing prophylaxis procedures. In this paper, starting with a previously developed lattice-gas SIR model, we construct a coupled behavior-disease model for influenza spreading with spontaneous behavioral changes. The focus is on self-initiated behavioral changes that alter the susceptibility to the disease, without altering the contact patterns among individuals. Three different mechanisms of awareness spreading are analyzed: the local spreading due to the presence in the neighborhood of infective individuals; the global spreading due to the news published by the mass media and to educational campaigns implemented at institutional level; the local spreading occurring through the “thought contagion” among aware and unaware individuals. The peculiarity of the present approach is that the awareness spreading model is calibrated on available data on awareness and concern of the population about the risk of contagion. In particular, the model is validated against the A(H1N1) epidemic outbreak in Italy during the season, by making use of the awareness data gathered by the behavioral risk factor surveillance system (PASSI). We find that, increasing the accordance between the simulated awareness spreading and the PASSI data on risk perception, the agreement between simulated and experimental epidemiological data improves as well. Furthermore, we show that, within our model, the primary mechanism to reproduce a realistic evolution of the awareness during an epidemic, is the one due to globally available information. This result highlights how crucial is the role of mass media and educational campaigns in influencing the epidemic spreading of infectious diseases. [ABSTRACT FROM AUTHOR]

In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions. [ABSTRACT FROM AUTHOR]

Breastfeeding has immense public health value for mothers, babies, and society. But there is an undesirably large gap between the number of new mothers who undertake and persist in breastfeeding compared to what would be a preferred level of accomplishment. This gap is a reflection of the many obstacles, both physical and psychological, that confront new mothers. Previous research has illuminated many of these concerns, but research on this problem is limited in part by the unavailability of a research instrument that can measure the key differences between first-time mothers and experienced mothers, with regard to the challenges they face when breastfeeding and the instructional advice they require. An instrument was designed to measure motivational complexity associated with sustained breast feeding behaviour; the Breastfeeding Motivational Measurement Scale. It contains 51 self-report items (7 point Likert scale) that cluster into four categories related to perceived value of breast-feeding, confidence to succeed, factors that influence success or failure, and strength of intentions, or goal. However, this scale has not been validated in terms of its sensitivity to profile the motivation of new mothers and experienced mothers. This issue was investigated by having 202 breastfeeding mothers (100 first time mothers) fill out the scale. The analysis reported in this paper is a three factor solution consisting of value, midwife support, and expectancies for success that explained the characteristics of first time mothers as a known group. These results support the validity of the BMM scale as a diagnostic tool for research on first time mothers who are learning to breastfeed. Further research studies are required to further test the validity of the scale in additional subgroups. [ABSTRACT FROM AUTHOR]

In modern logistics operations, large-scale logistics companies, besides active participation in profit-seeking commercial business, also play an essential role during an emergency relief process by dispatching urgently-required materials to disaster-affected areas. Therefore, an issue has been widely addressed by logistics practitioners and caught researchers' more attention as to how the logistics companies achieve maximum commercial profit on condition that emergency tasks are effectively and performed satisfactorily. In this paper, two vehicle scheduling models are proposed to solve the problem. One is a prediction-related scheme, which predicts the amounts of disaster-relief materials and commercial business and then accepts the business that will generate maximum profits; the other is a priority-directed scheme, which, firstly groups commercial and emergency business according to priority grades and then schedules both types of business jointly and simultaneously by arriving at the maximum priority in total. Moreover, computer-based simulations are carried out to evaluate the performance of these two models by comparing them with two traditional disaster-relief tactics in China. The results testify the feasibility and effectiveness of the proposed models. [ABSTRACT FROM AUTHOR]

In this paper, Choi and colleagues analyzed levels of mitochondrial DNA in two prospective observational cohort studies and found that increased mtDNA levels are associated with ICU mortality, and improve risk prediction in medical ICU patients. The data suggests that mtDNA could serve as a viable plasma biomarker in MICU patients. [ABSTRACT FROM AUTHOR]

In this paper we provide normative data along multiple cognitive and affective variable dimensions for a set of 110 sounds, including living and manmade stimuli. Environmental sounds are being increasingly utilized as stimuli in the cognitive, neuropsychological and neuroimaging fields, yet there is no comprehensive set of normative information for these type of stimuli available for use across these experimental domains. Experiment 1 collected data from 162 participants in an on-line questionnaire, which included measures of identification and categorization as well as cognitive and affective variables. A subsequent experiment collected response times to these sounds. Sounds were normalized to the same length (1 second) in order to maximize usage across multiple paradigms and experimental fields. These sounds can be freely downloaded for use, and all response data have also been made available in order that researchers can choose one or many of the cognitive and affective dimensions along which they would like to control their stimuli. Our hope is that the availability of such information will assist researchers in the fields of cognitive and clinical psychology and the neuroimaging community in choosing well-controlled environmental sound stimuli, and allow comparison across multiple studies. [ABSTRACT FROM AUTHOR]

Background: Publication of scientific research papers is important for professionals working in academic medical centres. Quantitative measures of scientific output determine status and prestige, and serve to rank universities as well as individuals. The pressure to generate maximum scientific output is high, and quantitative aspects may tend to dominate over qualitative ones. How this pressure influences professionals’ perception of science and their personal well-being is unknown. Methods and Findings: We performed an online survey inviting all medical professors (n = 1206) of the 8 academic medical centres in The Netherlands to participate. They were asked to fill out 2 questionnaires; a validated Publication Pressure Questionnaire and the Maslach Burnout Inventory. In total, 437 professors completed the questionnaires. among them, 54% judge that publication pressure ‘has become excessive’, 39% believe that publication pressure ‘affects the credibility of medical research’ and 26% judge that publication pressure has a ‘sickening effect on medical science’. The burn out questionnaire indicates that 24% of medical professors have signs of burn out. The number of years of professorship was significantly related with experiencing less publication pressure. Significant and strong associations between burn out symptoms and the level of perceived publication pressure were found. The main limitation is the possibility of response bias. Conclusion: A substantial proportion of medical professors believe that publication pressure has become excessive, and have a cynical view on the validity of medical science. These perceptions are statistically correlated to burn out symptoms. Further research should address the effects of publication pressure in more detail and identify alternative ways to stimulate the quality of medical science. [ABSTRACT FROM AUTHOR]

The clinical serial interval of an infectious disease is the time between date of symptom onset in an index case and the date of symptom onset in one of its secondary cases. It is a quantity which is commonly collected during a pandemic and is of fundamental importance to public health policy and mathematical modelling. In this paper we present a novel method for calculating the serial interval distribution for a Markovian model of household transmission dynamics. This allows the use of Bayesian MCMC methods, with explicit evaluation of the likelihood, to fit to serial interval data and infer parameters of the underlying model. We use simulated and real data to verify the accuracy of our methodology and illustrate the importance of accounting for household size. The output of our approach can be used to produce posterior distributions of population level epidemic characteristics. [ABSTRACT FROM AUTHOR]

Introduction: The Choices Programme is an internationally applicable nutrient profiling system with nutrition criteria for trans fatty acids (TFA), saturated fatty acids, sodium, added sugar and for some product groups energy and fibre. These criteria determine whether foods are eligible to carry a “healthier option” stamp. In this paper a nutrient intake modelling method is described to evaluate these nutritional criteria by investigating the potential effect on nutrient intakes. Methods: Data were combined from the 2003 Dutch food consumption survey in young adults (aged 19–30) and the Dutch food composition table into the Monte Carlo Risk Assessment model. Three scenarios were calculated: the “actual intakes” (scenario 1) were compared to scenario 2, where all foods that did not comply were replaced by similar foods that did comply with the Choices criteria. Scenario 3 was the same as scenario 2 adjusted for the difference in energy density between the original and replacement food. Additional scenarios were calculated where snacks were not or partially replaced and stratified analyses for gender, age, Body Mass Index (BMI) and education. Results: Calculated intake distributions showed that median energy intake was reduced by 16% by replacing normally consumed foods with Choices compliant foods. Intakes of nutrients with a maximal intake limit were also reduced (ranging from −23% for sodium and −62% for TFA). Effects on intakes of beneficial nutrients varied from an unintentional reduction in fat soluble vitamin intakes (−15 to −28%) to an increase of 28% for fibre and 17% calcium. Stratified analyses in this homogeneous study population showed only small differences across gender, age, BMI and education. Conclusions: This intake modelling method showed that with consumption of Choices compliant foods, nutrient intakes shift towards population intake goals for the nutrients for which nutrition criteria were defined, while effects on beneficial nutrients were diverse. [ABSTRACT FROM AUTHOR]

Graph theoretical approaches have successfully revealed abnormality in brain connectivity, in particular, for contrasting patients from healthy controls. Besides the group comparison analysis, a correlational study is also challenging. In studies with patients, for example, finding brain connections that indeed deepen specific symptoms is interesting. The correlational study is also beneficial since it does not require controls, which are often difficult to find, especially for old-age patients with cognitive impairment where controls could also have cognitive deficits due to normal ageing. However, one of the major difficulties in such correlational studies is too conservative multiple comparison correction. In this paper, we propose a novel method for identifying brain connections that are correlated with a specific cognitive behavior by employing cluster-based statistics, which is less conservative than other methods, such as Bonferroni correction, false discovery rate procedure, and extreme statistics. Our method is based on the insight that multiple brain connections, rather than a single connection, are responsible for abnormal behaviors. Given brain connectivity data, we first compute a partial correlation coefficient between every edge and the behavioral measure. Then we group together neighboring connections with strong correlation into clusters and calculate their maximum sizes. This procedure is repeated for randomly permuted assignments of behavioral measures. Significance levels of the identified sub-networks are estimated from the null distribution of the cluster sizes. This method is independent of network construction methods: either structural or functional network can be used in association with any behavioral measures. We further demonstrated the efficacy of our method using patients with subcortical vascular cognitive impairment. We identified sub-networks that are correlated with the disease severity by exploiting diffusion tensor imaging techniques. The identified sub-networks were consistent with the previous clinical findings having valid significance level, while other methods did not assert any significant findings. [ABSTRACT FROM AUTHOR]

Evidence of clinical utility is a key issue in translating pharmacogenomics into clinical practice. Appropriately designed randomized controlled trials generally provide the most robust evidence of the clinical utility, but often only data from a pharmacogenomic association study are available. This paper details a method for reframing the results of pharmacogenomic association studies in terms of the comparative treatment effect for a pharmacogenomic subgroup to provide greater insight into the likely clinical utility of a pharmacogenomic marker, its’ likely cost effectiveness, and the value of undertaking the further (often expensive) research required for translation into clinical practice. The method is based on the law of total probability, which relates marginal and conditional probability. It takes as inputs: the prevalence of the pharmacogenomic marker in the patient group of interest, prognostic effect of the pharmacogenomic marker based on observational association studies, and the unstratified comparative treatment effect based on one or more conventional randomized controlled trials. The critical assumption is that of exchangeability across the included studies. The method is demonstrated using a case study of cytochrome P450 (CYP) 2C19 genotype and the anti-platelet agent clopidogrel. Indirect subgroup analysis provided insight into relationship between the clinical utility of genotyping CYP2C19 and the risk ratio of cardiovascular outcomes between CYP2C19 genotypes for individuals using clopidogrel. In this case study the indirect and direct estimates of the treatment effect for the cytochrome P450 2C19 subgroups were similar. In general, however, indirect estimates are likely to have substantially greater risk of bias than an equivalent direct estimate. [ABSTRACT FROM AUTHOR]

Changes in electroencephalography (EEG) amplitude modulations have recently been linked with early-stage Alzheimer’s disease (AD). Existing tools available to perform such analysis (e.g., detrended fluctuation analysis), however, provide limited gains in discriminability power over traditional spectral based EEG analysis. In this paper, we explore the use of an innovative EEG amplitude modulation analysis technique based on spectro-temporal signal processing. More specifically, full-band EEG signals are first decomposed into the five well-known frequency bands and the envelopes are then extracted via a Hilbert transform. Each of the five envelopes are further decomposed into four so-called modulation bands, which were chosen to coincide with the delta, theta, alpha and beta frequency bands. Experiments on a resting-awake EEG dataset collected from 76 participants (27 healthy controls, 27 diagnosed with mild-AD, and 22 with moderate-AD) showed significant differences in amplitude modulations between the three groups. Most notably, i) delta modulation of the beta frequency band disappeared with an increase in disease severity (from mild to moderate AD), ii) delta modulation of the theta band appeared with an increase in severity, and iii) delta modulation of the beta frequency band showed to be a reliable discriminant feature between healthy controls and mild-AD patients. Taken together, it is hoped that the developed tool can be used to assist clinicians not only with early detection of Alzheimer’s disease, but also to monitor its progression. [ABSTRACT FROM AUTHOR]

Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called “iGPCR-drug”, was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug – target interaction networks. [ABSTRACT FROM AUTHOR]

The number of travel-acquired dengue infections has seen a consistent global rise over the past decade. An increased volume of international passenger air traffic originating from regions with endemic dengue has contributed to a rise in the number of dengue cases in both areas of endemicity and elsewhere. This paper reports results from a network-based risk assessment model which uses international passenger travel volumes, travel routes, travel distances, regional populations, and predictive species distribution models (for the two vector species, Aedes aegypti and Aedes albopictus) to quantify the relative risk posed by each airport in importing passengers with travel-acquired dengue infections. Two risk attributes are evaluated: (i) the risk posed by through traffic at each stopover airport and (ii) the risk posed by incoming travelers to each destination airport. The model results prioritize optimal locations (i.e., airports) for targeted dengue surveillance. The model is easily extendible to other vector-borne diseases. [ABSTRACT FROM AUTHOR]

This paper explores the effect of social relations and gender-based conflicts on the uptake of HIV testing in the South and Central provinces of Zambia. We conducted a community-based cross-sectional study of 1716 randomly selected individuals. Associations were examined using mixed-effect multivariable logistic regression. A total of 264 men (64%) and 268 women (56%) had never tested for HIV. The strongest determinants for not being tested were disruptive couple relationships (OR = 2.48 95% CI = 1.00–6.19); tolerance to gender-based violence (OR = 2.10 95% CI = 1.05–4.32) and fear of social rejection (OR = 1.48 95% CI = 1.23–1.80). In the Zambian context, unequal power relationships within the couple and the community seem to play a pivotal role in the decision to test which until now have been largely underestimated. Policies, programs and interventions to rapidly increase HIV testing need to urgently address gender-power inequity in relationships and prevent gender-based violence to reduce the negative impact on the lives of couples and families. [ABSTRACT FROM AUTHOR]

Objectives: To extend existing research on the US health disadvantage relative to Europe by studying the relationships of disability with age from midlife to old age in the US and four European regions (England/Northern and Western Europe/Southern Europe/Eastern Europe) including their wealth-related differences, using a flexible statistical approach to model the age-functions. Methods: We used data from three studies on aging, with nationally representative samples of adults aged 50 to 85 from 15 countries (N = 48225): the US-American Health and Retirement Study (HRS), the English Longitudinal Study of Ageing (ELSA) and the Survey of Health, Ageing and Retirement in Europe (SHARE). Outcomes were mobility limitations and limitations in instrumental activities of daily living. We applied fractional polynomials of age to determine best fitting functional forms for age on disability in each region, while controlling for socio-demographic characteristics and important risk factors (hypertension, diabetes, obesity, smoking, physical inactivity). Results: Findings showed high levels of disability in the US with small age-related changes between 50 and 85. Levels of disability were generally lower in Eastern Europe, followed by England and Southern Europe and lowest in Northern and Western Europe. In these latter countries age-related increases of disability, though, were steeper than in the US, especially in Eastern and Southern Europe. For all countries and at all ages, disability levels were higher among adults with low wealth compared to those with high wealth, with largest wealth-related differences among those in early old age in the USA. Conclusions: This paper illustrates considerable variations of disability and its relationship with age. It supports the hypothesis that less developed social policies and more pronounced socioeconomic inequalities are related to higher levels of disability and an earlier onset of disability. [ABSTRACT FROM AUTHOR]

In this paper we introduce a new method to expressly use live/corporeal data in quantifying differences of time series data with an underlying limit cycle attractor; and apply it using an example of gait data. Our intention is to identify gait pattern differences between diverse situations and classify them on group and individual subject levels. First we approximated the limit cycle attractors, from which three measures were calculated: δM amounts to the difference between two attractors (a measure for the differences of two movements), δD computes the difference between the two associated deviations of the state vector away from the attractor (a measure for the change in movement variation), and δF, a combination of the previous two, is an index of the change. As an application we quantified these measures for walking on a treadmill under three different conditions: normal walking, dual task walking, and walking with additional weights at the ankle. The new method was able to successfully differentiate between the three walking conditions. Day to day repeatability, studied with repeated trials approximately one week apart, indicated excellent reliability for δM (ICCave > 0.73 with no differences across days; p > 0.05) and good reliability for δD (ICCave  =  0.414 to 0.610 with no differences across days; p > 0.05). Based on the ability to detect differences in varying gait conditions and the good repeatability of the measures across days, the new method is recommended as an alternative to expensive and time consuming techniques of gait classification assessment. In particular, the new method is an easy to use diagnostic tool to quantify clinical changes in neurological patients. [ABSTRACT FROM AUTHOR]

Objectives: Increasing walking and cycling, and reducing motorised transport, are health and environmental priorities. This paper examines levels and trends in the use of different commute modes in England and Wales, both overall and with respect to small-area deprivation. It also investigates whether commute modal share can serve as a proxy for travel behaviour more generally. Methods: 23.7 million adult commuters reported their usual main mode of travelling to work in the 2011 census in England and Wales; similar data were available for 1971–2001. Indices of Multiple Deprivation were used to characterise socio-economic patterning. The National Travel Survey (2002–2010) was used to examine correlations between commute modal share and modal share of total travel time. These correlations were calculated across 150 non-overlapping populations defined by region, year band and income. Results: Among commuters in 2011, 67.1% used private motorised transport as their usual main commute mode (−1.8 percentage-point change since 2001); 17.8% used public transport (+1.8% change); 10.9% walked (−0.1% change); and 3.1% cycled (+0.1% change). Walking and, to a marginal extent, cycling were more common among those from deprived areas, but these gradients had flattened over the previous decade to the point of having essentially disappeared for cycling. In the National Travel Survey, commute modal share and total modal share were reasonably highly correlated for private motorised transport (r = 0.94), public transport (r = 0.96), walking (r = 0.88 excluding London) and cycling (r = 0.77). Conclusions: England and Wales remain car-dependent, but the trends are slightly more encouraging. Unlike many health behaviours, it is more common for socio-economically disadvantaged groups to commute using physically active modes. This association is, however, weakening and may soon reverse for cycling. At a population level, commute modal share provides a reasonable proxy for broader travel patterns, enhancing the value of the census in characterising background trends and evaluating interventions. [ABSTRACT FROM AUTHOR]