Use of genetically modified muscle and fat grafts to repair defects in bone and cartilage

We report a novel technology for the rapid healing of large osseous and chondral defects, based upon the genetic modification of autologous skeletal muscle and fat grafts. These tissues were selected because they not only possess mesenchymal progenitor cells and scaffolding properties, but also can be biopsied, genetically modified and returned to the patient in a single operative session. First generation adenovirus vector carrying cDNA encoding human bone morphogenetic protein-2 (Ad.BMP-2) was used for gene transfer to biopsies of muscle and fat. To assess bone healing, the genetically modified (“gene activated”) tissues were implanted into 5mm-long critical size, mid-diaphyseal, stabilized defects in the femora of Fischer rats. Unlike control defects, those receiving gene-activated muscle underwent rapid healing, with evidence of radiologic bridging as early as 10 days after implantation and restoration of full mechanical strength by 8 weeks. Histologic analysis suggests that the grafts rapidly differentiated into cartilage, followed by efficient endochondral ossification. Fluorescence in situ hybridization detection of Y-chromosomes following the transfer of male donor muscle into female rats demonstrated that at least some of the osteoblasts of the healed bone were derived from donor muscle. Gene activated fat also healed critical sized defects, but less quickly than muscle and with more variability. Anti-adenovirus antibodies were not detected. Pilot studies in a rabbit osteochondral defect model demonstrated the promise of this technology for healing cartilage defects. Further development of these methods should provide ways to heal bone and cartilage more expeditiously, and at lower cost, than is presently possible.

Second-order elastic finite element analysis of structures using a single element per member

Finite element frame analysis programs targeted for design office application necessitate algorithms which can deliver reliable numerical convergence in a practical timeframe with comparable degrees of accuracy, and a highly desirable attribute is the use of a single element per member to reduce computational storage, as well as data preparation and the interpretation of the results. To this end, a higher-order finite element method including geometric non-linearity is addressed in the paper for the analysis of elastic frames for which a single element is used to model each member. The geometric non-linearity in the structure is handled using an updated Lagrangian formulation, which takes the effects of the large translations and rotations that occur at the joints into consideration by accumulating their nodal coordinates. Rigid body movements are eliminated from the local member load-displacement relationship for which the total secant stiffness is formulated for evaluating the large member deformations of an element. The influences of the axial force on the member stiffness and the changes in the member chord length are taken into account using a modified bowing function which is formulated in the total secant stiffness relationship, for which the coupling of the axial strain and flexural bowing is included.

A meshfree-based local Galerkin method with condensation of degree of freedom for elastic dynamic analysis

Condensation technique of degree of freedom is first proposed to improve the computational efficiency of meshfree method with Galerkin weak form for elastic dynamic analysis. In the present method, scattered nodes without connectivity are divided into several subsets by cells with arbitrary shape. Local discrete equation is established over each cell by using moving Kriging interpolation, in which the nodes that located in the cell are used for approximation. Then local discrete equations can be simplified by condensation of degree of freedom, which transfers equations of inner nodes to equations of boundary nodes based on cells. The global dynamic system equations are obtained by assembling all local discrete equations and are solved by using the standard implicit Newmark’s time integration scheme. In the scheme of present method, the calculation of each cell is carried out by meshfree method, and local search is implemented in interpolation. Numerical examples show that the present method has high computational efficiency and good accuracy in solving elastic dynamic problems.

Feeding beliefs and practices of Chinese immigrant mothers : validation of a modified version of the child feeding questionnaire

The Child Feeding Questionnaire (CFQ) developed by Birch and colleagues (2001) is a widely used tool for measuring parental feeding beliefs, attitudes and practices. However, the appropriateness of the CFQ for use with Chinese populations is unknown. This study tested the construct validity of a novel Chinese version of the CFQ using confirmatory factor analysis (CFA). Participants included a convenience sample of 254 Chinese-Australian mothers of children aged 1-4 years. Prior to testing, the questionnaire was translated into Chinese using a translation-back-translation method, one item was re-worded to be culturally appropriate, a new item was added (monitoring), and five items that were not age-appropriate for the sample were removed. Based on previous literature, both a 7-factor and an 8-factor model were assessed via CFA. Results showed that the 8-factor model, which separated restriction and use of food rewards, improved the conceptual clarity of the constructs and provided a good fit to the data. Internal consistency of all eight factors was acceptable (Cronbach’s α: .60−.93). This modified 8-factor CFQ appears to be a linguistically and culturally appropriate instrument for assessing feeding beliefs and practices in Chinese-Australian mothers of young children.

Dietary flavonoids from modified apple reduce inflammation markers and modulate gut microbiota in mice

Apples are rich in polyphenols, which provide antioxidant properties, mediation of cellular processes such as inflammation, and modulation of gut microbiota. In this study we compared genetically engineered apples with increased flavonoids [myeloblastis transcription factor 10 (MYB10)] with nontransformed apples from the same genotype, "Royal Gala" (RG), and a control diet with no apple. Compared with the RG diet, the MYB10 diet contained elevated concentrations of the flavonoid subclasses anthocyanins, flavanol monomers (epicatechin) and oligomers (procyanidin B2), and flavonols (quercetin glycosides), but other plant secondary metabolites were largely unaltered. We used these apples to investigate the effects of dietary flavonoids on inflammation and gut microbiota in 2 mouse feeding trials. In trial 1, male mice were fed a control diet or diets supplemented with 20% MYB10 apple flesh and peel (MYB-FP) or RG apple flesh and peel (RG-FP) for 7 d. In trial 2, male mice were fed MYB-FP or RG-FP diets or diets supplemented with 20% MYB10 apple flesh or RG apple flesh for 7 or 21 d. In trial 1, the transcription levels of inflammation-linked genes in mice showed decreases of >2-fold for interleukin-2 receptor (Il2rb), chemokine receptor 2 (Ccr2), chemokine ligand 10 (Cxcl10), and chemokine receptor 10 (Ccr10) at 7 d for the MYB-FP diet compared with the RG-FP diet (P <0.05). In trial 2, the inflammation marker prostaglandin E2 (PGE2) in the plasma of mice fed the MYB-FP diet at 21 d was reduced by 10-fold (P < 0.01) compared with the RG-FP diet. In colonic microbiota, the number of total bacteria for mice fed the MYB-FP diet was 6% higher than for mice fed the control diet at 21 d (P = 0.01). In summary, high-flavonoid apple was associated with decreases in some inflammation markers and changes in gut microbiota when fed to healthy mice.

Analysis of genetically modified red-fleshed apples reveals effects on growth and consumer attributes

Consumers of whole foods, such as fruits, demand consistent high quality and seek varieties with enhanced health properties, convenience or novel taste. We have raised the polyphenolic content of apple by genetic engineering of the anthocyanin pathway using the apple transcription factor MYB10. These apples have very high concentrations of foliar, flower and fruit anthocyanins, especially in the fruit peel. Independent lines were examined for impacts on tree growth, photosynthesis and fruit characteristics. Fruit were analysed for changes in metabolite and transcript levels. Fruit were also used in taste trials to study the consumer perception of such a novel apple. No negative taste attributes were associated with the elevated anthocyanins. Modification with this one gene provides near isogenic material and allows us to examine the effects on an established cultivar, with a view to enhancing consumer appeal independently of other fruit qualities. © 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd.

RNA interference silencing of CHS greatly alters the growth pattern of apple (Malus x domestica)

Plants produce a vast array of phenolic compounds which are essential for their survival on land. One major class of polyphenols are the flavonoids and their formation is dependent on the enzyme chalcone synthase (CHS). In a recent study we silenced the CHS genes of apple (Malus × domestica Borkh.) and observed a loss of pigmentation in the fruit skin, flowers and stems. More surprisingly, highly silenced lines were significantly reduced in size, with small leaves and shortened internode lengths. Chemical analysis also revealed that the transgenic shoots contained greatly reduced concentrations of flavonoids which are known to modulate auxin flow. An auxin transport study verified this, with an increased auxin transport in the CHS-silenced lines. Overall, these findings suggest that auxin transport in apple has adapted to take place in the presence of high endogenous concentrations of flavonoids. Removal of these compounds therefore results in abnormal auxin movement and a highly disrupted growth pattern. © 2013 Landes Bioscience.

Ozone-Induced Dissociation on a Modified Tandem Linear Ion-Trap : Observations of Different Reactivity for Isomeric Lipids

Ozone-induced dissociation (OzID) exploits the gas-phase reaction between mass-selected lipid ions and ozone vapor to determine the position(s) of unsaturation In this contribution, we describe the modification of a tandem linear ion-trap mass spectrometer specifically for OzID analyses wherein ozone vapor is supplied to the collision cell This instrumental configuration provides spatial separation between mass-selection, the ozonolysis reaction, and mass-analysis steps in the OzID process and thus delivers significant enhancements in speed and sensitivity (ca 30-fold) These improvements allow spectra revealing the double-bond position(s) within unsaturated lipids to be acquired within 1 s significantly enhancing the utility of OzID in high-throughput lipidomic protocols The stable ozone concentration afforded by this modified instrument also allows direct comparison of relative reactivity of isomeric lipids and reveals reactivity trends related to (1) double-bond position, (2) substitution position on the glycerol backbone, and (3) stereochemistry For cis- and trans-isomers, differences were also observed in the branching ratio of product ions arising from the gas-phase ozonolysis reaction, suggesting that relative ion abundances could be exploited as markers for double-bond geometry Additional activation energy applied to mass-selected lipid ions during injection into the collision cell (with ozone present) was found to yield spectra containing both OzID and classical-CID fragment ions This combination CID-OzID acquisition on an ostensibly simple monounsaturated phosphatidylcholine within a cow brain lipid extract provided evidence for up to four structurally distinct phospholipids differing in both double-bond position and sn-substitution U Am Soc Mass Spectrom 2010, 21, 1989-1999) (C) 2010 American Society for Mass Spectrometry

Do left and right asymmetries of hemispheric preference interact with attention to predict local and global performance in applied tasks?

Many cognitive neuroscience studies show that the ability to attend to and identify global or local information is lateralised between the two hemispheres in the human brain; the left hemisphere is biased towards the local level, whereas the right hemisphere is biased towards the global level. Results of two studies show attention-focused people with a right ear preference (biased towards the left hemisphere) are better at local tasks, whereas people with a left ear preference (biased towards the right hemisphere) are better at more global tasks. In a third study we determined if right hemisphere-biased followers who attend to global stimuli are likely to have a stronger relationship between attention and globally based supervisor ratings of performance. Results provide evidence in support of this hypothesis. Our research supports our model and suggests that the interaction between attention and lateral preference is an important and novel predictor of work-related outcomes.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Psychometric properties of the modified RESIDE physical activity questionnaire among low-income overweight women

Objectives This study explored the criterion-related validity and test-retest reliability of the modified RESIDential Environment physical activity questionnaire and whether the instrument's validity varied by body mass index, education, race/ethnicity, or employment status. Design Validation study using baseline data collected for randomized trial of a weight loss intervention. Methods Participants recruited from health departments wore an ActiGraph accelerometer and self-reported non-occupational walking, moderate and vigorous physical activity on the modified RESIDential Environment questionnaire. We assessed validity (n = 152) using Spearman correlation coefficients, and reliability (n = 57) using intraclass correlation coefficients. Results When compared to steps, moderate physical activity, and bouts of moderate/vigorous physical activity measured by accelerometer, these questionnaire measures showed fair evidence for validity: recreational walking (Spearman correlation coefficients 0.23–0.36), total walking (Spearman correlation coefficients 0.24–0.37), and total moderate physical activity (Spearman correlation coefficients 0.18–0.36). Correlations for self-reported walking and moderate physical activity were higher among unemployed participants and women with lower body mass indices. Generally no other variability in the validity of the instrument was found. Evidence for reliability of RESIDential Environment measures of recreational walking, total walking, and total moderate physical activity was substantial (intraclass correlation coefficients 0.56–0.68). Conclusions Evidence for questionnaire validity and reliability varied by activity domain and was strongest for walking measures. The questionnaire may capture physical activity less accurately among women with higher body mass indices and employed participants. Capturing occupational activity, specifically walking at work, may improve questionnaire validity.

Multi-shot person re-identification via relational stein divergence

Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.

Improved image set classification via joint sparse approximated nearest subspaces

Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).

Unsteady natural convection within a porous enclosure of sinusoidal corrugated side walls

Numerically investigation of free convection within a porous cavity with differential heating has been performed using modified corrugated side walls. Sinusoidal hot left and cold right walls are assumed to receive sudden differentially heating where top and bottom walls are insulated. Air is considered as working fluid and is quiescent, initially. Numerical experiments reveal 3 distinct stages of developing pattern including initial stage, oscillatory intermediate and finally steady state condition. Implicit Finite Volume Method with TDMA solver is used to solve the governing equations. This study has been performed for the Rayleigh numbers ranging from 100 to 10,000. Outcomes have been reported in terms of isotherms, streamline, velocity and temperature plots and average Nusselt number for various Ra, corrugation frequency and corrugation amplitude. The effects of sudden differential heating and its resultant transient behavior on fluid flow and heat transfer characteristics have been shown for the range of governing parameters. The present results show that the transient phenomena are enormously influenced by the variation of the Rayleigh Number with corrugation amplitude and frequency.

Calculate excess mortality during heatwaves using Hilbert-Huang transform algorithm

Background Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data. Methods Special R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series. Results The Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors. Conclusions The HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.