Design and Validation of a MR-compatible Pneumatic Manipulandum

The combination of functional MR imaging and novel robotic tools may provide unique opportunities to probe the neural systems underlying motor control and learning. Here, we describe the design and validation of a MR-compatible, 1 degree-of-freedom pneumatic manipulandum along with experiments demonstrating its safety and efficacy. We first validated the robot\u27s ability to apply computer-controlled loads about the wrist, demonstrating that it possesses sufficient bandwidth to simulate torsional spring-like loads during point-to-point flexion movements. Next, we verified the MR-compatibility of the device by imaging a head phantom during robot operation. We observed no systematic differences in two measures of MRI signal quality (signal/noise and field homogeneity) when the robot was introduced into the scanner environment. Likewise, measurements of joint angle and actuator pressure were not adversely affected by scanning. Finally, we verified device efficacy by scanning 20 healthy human subjects performing rapid wrist flexions against a wide range of spring-like loads. We observed a linear relationship between joint torque at peak movement extent and perturbation magnitude, thus demonstrating the robot\u27s ability to simulate spring-like loads in situ. fMRI revealed task-related activation in regions known to contribute to the control of movement including the left primary sensorimotor cortex and right cerebellum

Estimation of summary protective efficacy using a frailty mixture model for recurrent event time data.

Recurrent event time data are common in experimental and observational studies. The analytic strategy needs to consider three issues: within-subject event dependence, between-subject heterogeneity in event rates, and the possibility of a nonsusceptible fraction. Motivated by the need to estimate the summary protective efficacy from recurrent event time data as seen in many infectious disease clinical trials, we propose a two-part frailty mixture model that simultaneously accommodates all the three issues. In terms of vaccine action models, the proposed model is a combination of the 'all-or-none' and the 'leaky' models, and the summary protective efficacy is a unified measure of the vaccine's twofold effects in completely or partially protecting the vaccinated individuals against the study event. The model parameters of interest are estimated using the expectation-maximization algorithm with their respective variances estimated using Louis's formula for the expectation-maximization algorithm. The summary protective efficacy is estimated by a composite estimand with its variance estimated using the delta method. The performance of the proposed estimation approach is investigated by a simulation study. Data from a trial of malaria prophylaxis conducted in Ghana are reanalyzed

Information mobility in complex networks

The concept of information mobility in complex networks is introduced on the basis of a stochastic process taking place in the network. The transition matrix for this process represents the probability that the information arising at a given node is transferred to a target one. We use the fractional powers of this transition matrix to investigate the stochastic process at fractional time intervals. The mobility coefficient is then introduced on the basis of the trace of these fractional powers of the stochastic matrix. The fractional time at which a network diffuses 50% of the information contained in its nodes (1/ k50 ) is also introduced. We then show that the scale-free random networks display better spread of information than the non scale-free ones. We study 38 real-world networks and analyze their performance in spreading information from their nodes. We find that some real-world networks perform even better than the scale-free networks with the same average degree and we point out some of the structural parameters that make this possible

Developing health-related quality-of-life instruments for use in Asia: the issues.

About half of the world's population live in Asia. Mandarin (the official language of China), Hindi and Japanese are among the ten languages spoken by the largest number of primary speakers. The numbers of Tamil and Malay speakers are expected to grow rapidly in the next few decades. Most health-related quality-of-life (HR-QOL) instruments currently used in Asia are translations and/or adaptations of instruments developed in North America and Western Europe. We illustrate and discuss several major issues in the development of HR-QOL instruments for use in Asia. We have seen insufficient quality in translation and semantic equivalence, which is not a uniquely Asian problem. This problem will be alleviated by putting recently proposed guidelines for translation and adaptation of patient-reported outcomes into practice and formally conducting equivalence studies. For copyright or other reasons it is rare to see major adaptations, such as exclusion of a domain in the original instrument or inclusion of a new domain, made to existing instruments. Evidence is limited and mixed as to whether there are differences in the concepts of HR-QOL between Asian and North American/Western European cultures that are important enough to justify such major adaptations, or the development of indigenous instruments, as opposed to the translation/adaptation of existing instruments. There are substantial cultural differences concerning what questions are appropriate to ask and answer. Many HR-QOL instruments are designed for self-completion. This mode of administration is often not feasible in Asia because of low literacy rates and the presence of many different regional languages. Alternative administration methods and analytic strategies that allow for pooling data collected by different modes are needed. The availability of HR-QOL instruments in various Asian countries seems to reflect the status of economic development of the countries rather than their disease burden. For instance, many important HR-QOL instruments are available in Japanese but not in Hindi or Tamil

Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information

Dimensionality reduction and manifold learning methods such as t-Distributed Stochastic Neighbor Embedding (t-SNE) are routinely used to map high-dimensional data into a 2-dimensional space to visualize and explore the data. However, two dimensions are typically insufficient to capture all structure in the data, the salient structure is often already known, and it is not obvious how to extract the remaining information in a similarly effective manner. To fill this gap, we introduce \emph{conditional t-SNE} (ct-SNE), a generalization of t-SNE that discounts prior information from the embedding in the form of labels. To achieve this, we propose a conditioned version of the t-SNE objective, obtaining a single, integrated, and elegant method. ct-SNE has one extra parameter over t-SNE; we investigate its effects and show how to efficiently optimize the objective. Factoring out prior knowledge allows complementary structure to be captured in the embedding, providing new insights. Qualitative and quantitative empirical results on synthetic and (large) real data show ct-SNE is effective and achieves its goal

Long-term morbidity from severe pneumonia in early childhood in The Gambia, West Africa: a follow-up study

OBJECTIVE: To assess long-term outcomes in severe early childhood pneumonia in The Gambia. DESIGN: Observational cohort study of children hospitalised with severe pneumonia between 1992 and 1 04 compared to age, sex, and neigh bourhood-marched controls on measures of current general and pulmonary health. RESULTS: Of 83 children successfully traced, 68 of the 69 alive at follow-up agreed to participate. Thirteen per Cent of cases and 4% of controls had lung disease clinically or on spirometry. Another 16 (13%) participants had abnormal spirometry but did not meet the American Thoracic Society technical criteria (formally 'inconclusive'). Odds ratios of lung disease among childhood pneumonia cases were 2.93 (95 %CI 0.69-12.48, P = 0.1468) with incon-clusives omitted; 2.53 (95 %CI 0.61-10.59, P = 0.2033) with inconclusives included as normal; and 2.83 (95%CI 1.09-7.36, P = 0.0334) with inconclusives included as lung disease. Among deceased cases, most deaths were reported within weeks of discharge, suggesting a possible connection between admission and subsequent death. CONCLUSION: These African data, while not conclusive, add to previous data suggesting a link between severe early, childhood pneumonia and later chronic lung disease. While larger-scale research is needed, increased awareness of possible long-term morbidity in children with severe pneumonia is warranted to limit its impact and optimise long-term health

Supplementary feeding with fortified spread among moderately underweight 6-18-month-old rural Malawian children.

We aimed to analyse growth and recovery from undernutrition among moderately underweight ambulatory children receiving micronutrient-fortified maize-soy flour (Likuni Phala, LP) or ready-to-use fortified spread (FS) supplementary diet. One hundred and seventy-six 6-18-month-old individuals were randomized to receive 500 g LP or 350 g FS weekly for 12 weeks. Baseline and end of intervention measurements were used to calculate anthropometric gains and recovery from underweight, wasting and stunting. Mean weight-for-age increased by 0.22 (95% CI 0.07-0.37) and 0.28 (0.18-0.40) Z-score units in the LP and FS groups respectively. Comparable increase for mean weight-for-length was 0.39 (0.20-0.57) and 0.52 (0.38-0.65) Z-score units. Recovery from underweight and wasting was 20% and 93% in LP group and 16% and 75% in FS group. Few individuals recovered from stunting and mean length-for-age was not markedly changed. There were no statistically significant differences between the outcomes in the two intervention groups. In a poor food-security setting, underweight infants and children receiving supplementary feeding for 12 weeks with ready-to-use FS or maize-soy flour porridge show similar recovery from moderate wasting and underweight. Neither intervention, if limited to a 12-week duration, appears to have significant impact on the process of linear growth or stunting

Individual classification of ADHD patients by integrating multiscale neuroimaging markers and advanced pattern recognition techniques

Accurate classification or prediction of the brain state across individual subject, i.e., healthy, or with brain disorders, is generally a more difficult task than merely finding group differences. The former must be approached with highly informative and sensitive biomarkers as well as effective pattern classification/feature selection approaches. In this paper, we propose a systematic methodology to discriminate attention deficit hyperactivity disorder (ADHD) patients from healthy controls on the individual level. Multiple neuroimaging markers that are proved to be sensitive features are identified, which include multiscale characteristics extracted from blood oxygenation level dependent (BOLD) signals, such as regional homogeneity (ReHo) and amplitude of low-frequency fluctuations. Functional connectivity derived from Pearson, partial, and spatial correlation is also utilized to reflect the abnormal patterns of functional integration, or, dysconnectivity syndromes in the brain. These neuroimaging markers are calculated on either voxel or regional level. Advanced feature selection approach is then designed, including a brain-wise association study (BWAS). Using identified features and proper feature integration, a support vector machine (SVM) classifier can achieve a cross-validated classification accuracy of 76.15% across individuals from a large dataset consisting of 141 healthy controls and 98 ADHD patients, with the sensitivity being 63.27% and the specificity being 85.11%. Our results show that the most discriminative features for classification are primarily associated with the frontal and cerebellar regions. The proposed methodology is expected to improve clinical diagnosis and evaluation of treatment for ADHD patient, and to have wider applications in diagnosis of general neuropsychiatric disorders