Recovery of transverse strain in high–stress tendons following exercise

Background. This study evaluated the time course of recovery of transverse strain in the Achilles and patellar tendons following a bout of resistance exercise. Methods. Seventeen healthy adults underwent sonographic examination of the right patellar (n = 9) or Achilles (n = 8) tendons immediately prior to and following 90 repetitions of weight–bearing exercise. Quadriceps and gastrocnemius exercise were performed against an effective resistance of 175% and 250% body weight, respectively. Sagittal tendon thickness was determined 20 mm from the tendon enthesis and transverse strain was repeatedly monitored over a 24 hour recovery period. Results. Resistance exercise resulted in an immediate decrease in Achilles (t7 = 10.6, P<.01) and patellar (t8 = 8.9, P<.01) tendon thickness, resulting in an average transverse strain of 0.14 ± 0.04 and 0.18 ± 0.05. While the average strain was not significantly different between tendons, older age was associated with a reduced transverse strain response (r=0.63, P<.01). Recovery of transverse strain, in contrast, was prolonged compared with the duration of loading and exponential in nature. The mean primary recovery time was not significantly different between Achilles (6.5 ± 3.2 hours) and patellar (7.1 ± 3.2 hours) tendons and body weight accounted for 62% and 64% of the variation in recovery time, respectively. Discussion. Despite structural and biochemical differences between the Achilles and patellar tendons [1], the mechanisms underlying transverse creep–recovery in vivo appear similar and are highly time dependent. Primary recovery required about 7 hours in healthy tendons, with full recovery requiring up to 24 hours. These in vivo recovery times are similar to those reported for axial creep recovery of the vertebral disc in vitro [2], and may be used clinically to guide physical activity to rest ratios in healthy adults. Optimal ratios for high–stress tendons in clinical populations, however, remain unknown and require further attention in light of the knowledge gained in this study.

Donating blood and organs : using an extended theory of planned behavior perspective to identify similarities and differences in individual motivations to donate

Due to the critical shortage and continued need of blood and organ donations (ODs), research exploring similarities and differences in the motivational determinants of these behaviors is needed. In a sample of 258 university students, we used a cross-sectional design to test the utility of an extended theory of planned behavior (TPB) including moral norm, self-identity and in-group altruism (family/close friends and ethnic group), to predict people’s blood and OD intentions. Overall, the extended TPB explained 77.0% and 74.6% of variance in blood and OD intentions, respectively. In regression analyses, common contributors to intentions across donation contexts were attitude, self-efficacy and self-identity. Normative influences varied with subjective norm as a significant predictor related to OD intentions but not blood donation intentions at the final step of regression analyses. Moral norm did not contribute significantly to blood or OD intentions. In-group altruism (family/close friends) was significantly related to OD intentions only in regressions. Future donation strategies should increase confidence to donate, foster a perception of self as the type of person who donates blood and/or organs, and address preferences to donate organs to in-group members only.

An evaluation of different features and learning models for anomalous event detection

The huge amount of CCTV footage available makes it very burdensome to process these videos manually through human operators. This has made automated processing of video footage through computer vision technologies necessary. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned ‘normal’ model. There is no precise and exact definition for an abnormal activity; it is dependent on the context of the scene. Hence there is a requirement for different feature sets to detect different kinds of abnormal activities. In this work we evaluate the performance of different state of the art features to detect the presence of the abnormal objects in the scene. These include optical flow vectors to detect motion related anomalies, textures of optical flow and image textures to detect the presence of abnormal objects. These extracted features in different combinations are modeled using different state of the art models such as Gaussian mixture model(GMM) and Semi- 2D Hidden Markov model(HMM) to analyse the performances. Further we apply perspective normalization to the extracted features to compensate for perspective distortion due to the distance between the camera and objects of consideration. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Construct design for efficient, effective and high-throughput gene silencing in plants

Post-transcriptional silencing of plant genes using anti-sense or co-suppression constructs usually results in only a modest proportion of silenced individuals. Recent work has demonstrated the potential for constructs encoding self-complementary 'hairpin' RNA (hpRNA) to efficiently silence genes. In this study we examine design rules for efficient gene silencing, in terms of both the proportion of independent transgenic plants showing silencing, and the degree of silencing. Using hpRNA constructs containing sense/anti-sense arms ranging from 98 to 853 nt gave efficient silencing in a wide range of plant species, and inclusion of an intron in these constructs had a consistently enhancing effect. Intron-containing constructs (ihpRNA) generally gave 90-100% of independent transgenic plants showing silencing. The degree of silencing with these constructs was much greater than that obtained using either co-suppression or anti-sense constructs. We have made a generic vector, pHANNIBAL, that allows a simple, single PCR product from a gene of interest to be easily converted into a highly effective ihpRNA silencing construct. We have also created a high-throughput vector, pHELLSGATE, that should facilitate the cloning of gene libraries or large numbers of defined genes, such as those in EST collections, using an in vitro recombinase system. This system may facilitate the large-scale determination and discovery of plant gene functions in the same way as RNAi is being used to examine gene function in Caenorhabditis elegans.

Quality based frame selection for face clustering in news video

Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance.

A methodology for estimating exposure-controlled crash risk using traffic Police crash data

Exposure control or case-control methodologies are common techniques for estimating crash risks, however they require either observational data on control cases or exogenous exposure data, such as vehicle-kilometres travelled. This study proposes an alternative methodology for estimating crash risk of road user groups, whilst controlling for exposure under a variety of roadway, traffic and environmental factors by using readily available police-reported crash data. In particular, the proposed method employs a combination of a log-linear model and quasi-induced exposure technique to identify significant interactions among a range of roadway, environmental and traffic conditions to estimate associated crash risks. The proposed methodology is illustrated using a set of police-reported crash data from January 2004 to June 2009 on roadways in Queensland, Australia. Exposure-controlled crash risks of motorcyclists—involved in multi-vehicle crashes at intersections—were estimated under various combinations of variables like posted speed limit, intersection control type, intersection configuration, and lighting condition. Results show that the crash risk of motorcycles at three-legged intersections is high if the posted speed limits along the approaches are greater than 60 km/h. The crash risk at three-legged intersections is also high when they are unsignalized. Dark lighting conditions appear to increase the crash risk of motorcycles at signalized intersections, but the problem of night time conspicuity of motorcyclists at intersections is lessened on approaches with lower speed limits. This study demonstrates that this combined methodology is a promising tool for gaining new insights into the crash risks of road user groups, and is transferrable to other road users.

The potential role of lycopene for the prevention and therapy of prostate cancer : from molecular mechanisms to clinical evidence

Lycopene is a phytochemical that belongs to a group of pigments known as carotenoids. It is red, lipophilic and naturally occurring in many fruits and vegetables, with tomatoes and tomato-based products containing the highest concentrations of bioavailable lycopene. Several epidemiological studies have linked increased lycopene consumption with decreased prostate cancer risk. These findings are supported by in vitro and in vivo experiments showing that lycopene not only enhances the antioxidant response of prostate cells, but that it is even able to inhibit proliferation, induce apoptosis and decrease the metastatic capacity of prostate cancer cells. However, there is still no clearly proven clinical evidence supporting the use of lycopene in the prevention or treatment of prostate cancer, due to the only limited number of published randomized clinical trials and the varying quality of existing studies. The scope of this article is to discuss the potential impact of lycopene on prostate cancer by giving an overview about its molecular mechanisms and clinical effects. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

Mechanical stimulation of the pro-angiogenic capacity of human fracture haematoma: Involvement of VEGF mechano-regulation

Compromised angiogenesis appears to be a major limitation in various suboptimal bone healing situations. Appropriate mechanical stimuli support blood vessel formation in vivo and improve healing outcomes. However, the mechanisms responsible for this association are unclear. To address this question, the paracrine angiogenic potential of early human fracture haematoma and its responsiveness to mechanical loading, as well as angiogenic growth factors involved, were investigated in vitro. Human haematomas were collected from healthy patients undergoing surgery within 72. h after bone fracture. The haematomas were embedded in a fibrin matrix, and cultured in a bioreactor resembling the in vivo conditions of the early phase of bone healing (20 compression, 1. Hz) over 3. days. Conditioned medium (CM) from the bioreactor was then analyzed. The matrices were also incubated in fresh medium for a further 24. h to evaluate the persistence of the effects. Growth factor (GF) concentrations were measured in the CM by ELISAs. In vitro tube formation assays were conducted on Matrigel with the HMEC-1 cell line, with or without inhibition of vascular endothelial growth factor receptor 2 (VEGFR2). Cell numbers were quantified using an MTS test. In vitro endothelial tube formation was enhanced by CM from haematomas, compared to fibrin controls. The angiogenesis regulators, vascular endothelial growth factor (VEGF) and transforming growth factor β1 (TGF-β1), were released into the haematoma CM, but not angiopoietins 1 or 2 (Ang1, 2), basic fibroblast growth factor (bFGF) or platelet-derived growth factor (PDGF). Mechanical stimulation of haematomas, but not fibrin controls, further increased the induction of tube formation by their CM. The mechanically stimulated haematoma matrices retained their elevated pro-angiogenic capacity for 24. h. The pro-angiogenic effect was cancelled by inhibition of VEGFR2 signalling. VEGF concentrations in CM tended to be elevated by mechanical stimulation; this was significant in haematomas from younger, but not from older patients. Other GFs were not mechanically regulated. In conclusion, the paracrine pro-angiogenic capacity of early human haematomas is enhanced by mechanical stimulation. This effect lasts even after removing the mechanical stimulus and appears to be VEGFR2-dependent.

Bike share's impact on car use : evidence from the United States, Great Britain, and Australia

There are currently more than 400 cities operating bike share programs. Purported benefits of bike share programs include flexible mobility, physical activity, reduced congestion, emissions and fuel use. Implicit or explicit in the calculation of program benefits are assumptions regarding the modes of travel replaced by bike share journeys. This paper examines the degree to which car trips are replaced by bike share, through an examination of survey and trip data from bike share programs in Melbourne, Brisbane, Washing, D.C., London, and Minneapolis/St. Paul. A secondary and unique component of this analysis examines motor vehicle support services required for bike share fleet rebalancing and maintenance. These two components are then combined to estimate bike share’s overall contribution to changes in vehicle kilometres traveled. The results indicate that the estimated mean reduction in car use due to bike share is at least twice the distance covered by operator support vehicles, with the exception of London, in which the relationship is reversed, largely due to a low car mode substitution rate. As bike share programs mature, evaluation of their effectiveness in reducing car use may become increasingly important. This paper reveals that by increasing the convenience of bike share relative to car use and by improving perceptions of safety, the capacity of bike share programs to reduce vehicle trips and yield overall net benefits will be enhanced. Researchers can adapt the analytical approach proposed in this paper to assist in the evaluation of current and future bike share programs.

Applying the ecological model of behavior change to a physical activity trial in retirement communities : description of the study protocol

Objectives To describe the intervention protocol for the first multilevel ecological intervention for physical activity in retirement communities that addresses individual, interpersonal and community influences on behavior change. Design A cluster randomized controlled trial design was employed with two study arms: a physical activity intervention and an attention control successful aging condition. Setting Sixteen continuing care retirement communities in San Diego County. Participants Three hundred twenty older adults, aged 65 years and older, are being recruited to participate in the trial. In addition, peer leaders are being recruited to lead some study activities, especially to sustain the intervention after study activities ceased. Intervention Participants in the physical activity trial receive individual, interpersonal and community intervention components. The individual level components include pedometers, goal setting and individual phone counseling. The interpersonal level components include group education sessions and peer-led activities. The community level components include resource audits and enumeration, tailored walking maps, and community improvement projects. The successful aging group receives individual and group attention about successful aging topics. Measurements The main outcome is light to moderate physical activity, measured objectively by accelerometry. Other objective outcomes included physical functioning, blood pressure, physical fitness, and cognitive functioning. Self report measures include depressive symptoms and health related quality of life. Results The intervention is being delivered successfully in the communities and compliance rates are high. Conclusion Ecological Models call for interventions that address multiple levels of the model. Previous studies have not included components at each level and retirement communities provide a model environment to demonstrate how to implement such an intervention.

Management of over-the-counter insomnia complaints in Australian community pharmacies: A standardized patient study

Objective To evaluate the current management of over-the-counter (OTC) insomnia complaints in Australian community pharmacies using standardized patient methodology. Methods Trained standardized patients visited a sample of 100 randomly selected South East Queensland community pharmacies in June 2011. The standardized patients enacted two OTC insomnia scenarios: a direct product request (DPR) (n = 50) and a symptom-based request (SBR) (n = 50). Results of the interactions were documented immediately after each visit and evaluated using the Pharmaceutical Society of Australia's WHAT STOP GO protocol as a standard comparison. Key findings Of all DPRs, 30% were handled entirely by the pharmacist, 70% of staff enquired about specific symptoms and 28% investigated the cause of insomnia. No staff investigated the frequency of product use. The DPR scenario resulted in a 92% supply of the requested doxylamine product (Restavit). In the SBR scenario, 18% of requests were handled entirely by the pharmacist, 58% of staff enquired about specific symptoms and 44% investigated the cause of insomnia. Staff recommended medicated products (38%), or herbal (78%) or non-drug techniques (18%). Investigation into smoking and alcohol intake was not undertaken in DPR or SBR interactions, while questioning on caffeine intake was undertaken in 2 and 14% of cases respectively. There were no significant differences found in the handling of sleep requests by pharmacists compared to pharmacy assistants. Conclusion The standardized patient methodology was a successful way to assess the community pharmacy counselling provided with OTC sleep requests and suboptimal staff responses were found when compared with recommended practice standards.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.