Resistance training and reduction of treatment side effects in prostate cancer patients

Purpose: To examine the effect of progressive resistance training on muscle function, functional performance, balance, body composition, and muscle thickness in men receiving androgen deprivation for prostate cancer. Methods: Ten men aged 59-82 yr on androgen deprivation for localized prostate cancer undertook progressive resistance training for 20 wk at 6- to 12-repetition maximum (RM) for 12 upper- and lower-body exercises in a university exercise rehabilitation clinic. Outcome measures included muscle strength and muscle endurance for the upper and lower body, functional performance (repeated chair rise, usual and fast 6-m walk, 6-m backwards walk, stair climb, and 400-m walk time), and balance by sensory organization test. Body composition was measured by dual-energy x-ray absorptiometry and muscle thickness at four anatomical sites by B-mode ultrasound. Blood samples were assessed for prostate specific antigen (PSA), testosterone, growth hormone (GH), cortisol, and hemoglobin. Results: Muscle strength (chest press, 40.5%; seated row, 41.9%; leg press, 96.3%; P < 0.001) and muscle endurance (chest press, 114.9%; leg press, 167.1%; P < 0.001) increased significantly after training. Significant improvement (P < 0.05) occurred in the 6-m usual walk (14.1%), 6-m backwards walk (22.3%), chair rise (26.8%), stair climbing (10.4%), 400-m walk (7.4%), and balance (7.8%). Muscle thickness increased (P < 0.05) by 15.7% at the quadriceps site. Whole-body lean mass was preserved with no change in fat mass. There were no significant changes in PSA, testosterone, GH, cortisol, or hemoglobin. Conclusions: Progressive resistance exercise has beneficial effects on muscle strength, functional performance and balance in older men receiving androgen deprivation for prostate cancer and should be considered to preserve body composition and reduce treatment side effects.

Effects of anitoxidant supplementation and exercise training on erythrocyte antioxidant enzymes

Erythrocytes transport oxygen to tissues and exercise-induced oxidative stress increases erythrocyte damage and turnover. Increased use of antioxidant supplements may alter protective erythrocyte antioxidant mechanisms during training. Aim of study: To examine the effects of antioxidant supplementation, (alpha-lipoic acid and a-tocopherol) and/or endurance training on the antioxidant defenses of erythrocytes. Methods: Young male Wistar rats were. assigned to (1) sedentary; (2) sedentary and antioxidant-supplemented; (3) endurance-trained; or (4) endurance-trained and antioxidant-supplemented groups for 14 weeks. Erythrocyte superoxide dismutase (SOD), glutathione peroxidase (GPX), and catalase (CAT) activities, and plasma malondialdehyde (MDA) were then measured. Results: Antioxidant supplementation had no significant effect (p > 0.05) on activities of antioxidant enzymes in sedentary animals. Similarly, endurance training alone also bad no effect (p > 0.05). GPX (125.9 2.8 vs. 121.5 3.0 U.gHb(-1), p < 0.05) and CAT (6.1 0.2 vs. 5.6 0.2 U.mgHb-1, p < 0.05) activities were increased in supplemented trained animals compared to non-supplemented sedentary animals whereas SOD (61.8 4.3 vs. 52.0 5.2 U.mgHb(-1), p < 0.05) activity was decreased. Plasma MDA was not different among groups (p > 0.05). Conclusions: In a rat model, the combination of exercise training and antioxidant supplementation increased antioxidant enzyme activities (GPX, CAT) compared with each individual intervention.

Training emotional intelligence: Presenting the results of an experimental study

This presentation outlines the results of an eighteen month study examining the effect of an emotions focused training intervention on the emotional intelligence of employees from a large public sector organisation. Utilising an experimental methodology, 280 staff attended a two-day program focused on training emotional intelligence skills and abilities. These interventions were created around Mayer and Salovey’s four-branch model of emotional intelligence (awareness, understanding, facilitation and management of emotions). The experimental group’s emotional intelligence was tested pre and post training using the Workgroup Emotional Intelligence Profile (WEIP). In addition, a control group from the same organisation also completed the same measure at three points during the same eighteen month period. Analysis of the control and experimental group data were conducted, and whilst no changes were found in the control group, the experimental group’s overall emotional intelligence significantly improved post training. To further strengthen these findings, a measure of effect size using Cohen’s d was also conducted to assess the magnitude of the training intervention’s overall effect. Full results will be presented during the presentation, with feedback on the study and methods utilised encouraged from participants.

High- and low-volume resistance training similarly enhances functional performance in older adults

It is well known that resistance training improves muscle strength in older adults and may enhance or preserve functional performance. However, it is unclear if the volume of work undertaken in the elderly alters the response in functional performance. PURPOSE: To investigate the effect of a high- versus low-volume resistance training program on functional performance in older adults. METHODS: Thirty-two healthy men and women aged 65-78 years were randomly assigned to either a single-set (SS, n = 16) or 3-set (MS, n = 16) progressive resistance training program for 20 weeks. Groups trained 2 days per week using machine weights at 8 repetitions maximum (8-RM) for 7 upper and lower body exercises. Muscle strength was assessed by the 1-RM and functional performance by a battery of tests (repeated chair rise, usual and fast 6-m walk, 6-m backwards walk, floor rise to standing, stair climb, and 400-m walk time). RESULTS: Twenty-eight subjects completed the study. There was no difference between groups at baseline in muscle strength or functional performance. Whole body muscle strength significantly increased in both groups with greater gains in the 3-set group (MS 32.9 ± 3.1%; SS 18.6 ± 2.7%, mean ± SE; P < 0.01). Significant improvement (time effect, P < 0.01) occurred for both groups in the chair rise (MS 13.6 ± 3.2%; SS 10.2 ± 3.0%), 6-m backwards walk (MS 14.9 ± 3.3%; SS 14.3 ± 4.2%), stair climb (MS 6.4 ± 2.8%; SS 7.7 ± 3.1%) and 400-m walk (MS 7.4 ± 1.4%; SS 3.9 ± 1.2%). There were no interaction (group × time) effects for functional performance and no differences by sex. CONCLUSION: Resistance training that utilizes either a singleset or 3-set regimen may significantly and similarly improve functional performance in community-dwelling older adults. Enhancement of functional performance may prolong independence and improve quality of life. ©2004The American College of Sports Medicine

Evaluation and comparison of mammalian subcellular localization prediction methods

Background: Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function of hypothetical or novel proteins. These data are difficult to obtain experimentally but have become especially important since many whole genome sequencing projects have been finished and many resulting protein sequences are still lacking detailed functional information. In order to address this paucity of data, many computational prediction methods have been developed. However, these methods have varying levels of accuracy and perform differently based on the sequences that are presented to the underlying algorithm. It is therefore useful to compare these methods and monitor their performance. Results: In order to perform a comprehensive survey of prediction methods, we selected only methods that accepted large batches of protein sequences, were publicly available, and were able to predict localization to at least nine of the major subcellular locations (nucleus, cytosol, mitochondrion, extracellular region, plasma membrane, Golgi apparatus, endoplasmic reticulum (ER), peroxisome, and lysosome). The selected methods were CELLO, MultiLoc, Proteome Analyst, pTarget and WoLF PSORT. These methods were evaluated using 3763 mouse proteins from SwissProt that represent the source of the training sets used in development of the individual methods. In addition, an independent evaluation set of 2145 mouse proteins from LOCATE with a bias towards the subcellular localization underrepresented in SwissProt was used. The sensitivity and specificity were calculated for each method and compared to a theoretical value based on what might be observed by random chance. Conclusion: No individual method had a sufficient level of sensitivity across both evaluation sets that would enable reliable application to hypothetical proteins. All methods showed lower performance on the LOCATE dataset and variable performance on individual subcellular localizations was observed. Proteins localized to the secretory pathway were the most difficult to predict, while nuclear and extracellular proteins were predicted with the highest sensitivity.

Bayesian training of mixture density networks

Mixture Density Networks (MDNs) are a well-established method for modelling the conditional probability density which is useful for complex multi-valued functions where regression methods (such as MLPs) fail. In this paper we extend earlier research of a regularisation method for a special case of MDNs to the general case using evidence based regularisation and we show how the Hessian of the MDN error function can be evaluated using R-propagation. The method is tested on two data sets and compared with early stopping.

Training Bayesian networks for image segmentation

We are concerned with the problem of image segmentation in which each pixel is assigned to one of a predefined finite number of classes. In Bayesian image analysis, this requires fusing together local predictions for the class labels with a prior model of segmentations. Markov Random Fields (MRFs) have been used to incorporate some of this prior knowledge, but this not entirely satisfactory as inference in MRFs is NP-hard. The multiscale quadtree model of Bouman and Shapiro (1994) is an attractive alternative, as this is a tree-structured belief network in which inference can be carried out in linear time (Pearl 1988). It is an hierarchical model where the bottom-level nodes are pixels, and higher levels correspond to downsampled versions of the image. The conditional-probability tables (CPTs) in the belief network encode the knowledge of how the levels interact. In this paper we discuss two methods of learning the CPTs given training data, using (a) maximum likelihood and the EM algorithm and (b) emphconditional maximum likelihood (CML). Segmentations obtained using networks trained by CML show a statistically-significant improvement in performance on synthetic images. We also demonstrate the methods on a real-world outdoor-scene segmentation task.

The training experience of primary care pharmacists

Objectives — To map the tasks, activities and training provision for primary care pharmacists (PCPs) and to identify perceived future training needs. Methods — Survey undertaken in 1998/1999 using a pre-piloted, postal, self-completion questionnaire to two samples of PCPs. Setting — PCPs in (a) the West Midlands and (b) England (outside West Midlands). Key findings — The response rate was 66 per cent. A majority (68 per cent) had worked in the role for less than two years. Eighty per cent had some form of continuing education or training for the role although only 50 per cent had a formal qualification. Over two-thirds had contributed to the funding of their training, with one-third providing all funding. Seventy-four per cent of PCPs agreed that pharmacists should go through a procedure to ensure competence (accreditation) before being allowed to work for a general medical practice or primary care group. Views on the need for formal education/training prior to work differed: 82 per cent of those with formal qualifications, but only 46 per cent of those without, considered that this should be a requirement. There was general agreement that training/education had met training needs. Views on future training closely reflected previous training experiences, with a focus upon pharmaceutical roles rather than upon generic skill development and the acquisition of management skills. Conclusions — The study provides a snapshot in time of the experience of pioneer PCPs and the training available to them. PCPs will need further training or updating if they are to provide the wider roles required by the developing needs of the National Health Service. Consideration should be given to formal recognition of the training of PCPs in order to assure competence. The expectation that pharmacists should fund their own training is likely to be a barrier to uptake of training and uncertainties over funding will militate against consistency of training.

Delivering phonological and phonics training within whole-class teaching

Background: Early, intensive phonological awareness and phonics training is widely held to be beneficial for children with poor phonological awareness. However, most studies have delivered this training separately from children's normal whole-class reading lessons. Aims: We examined whether integrating this training into whole class, mixed-ability reading lessons could impact on children with poor phonological awareness, whilst also benefiting normally developing readers. Sample: Teachers delivered the training within a broad reading programme to whole classes of children from Reception to the end of Year 1 (N=251). A comparison group of children received standard teaching methods (N=213). Method: Children's literacy was assessed at the beginning of Reception, and then at the end of each year until 1 year post-intervention. Results: The strategy significantly impacted on reading performance for normally developing readers and those with poor phonological awareness, vastly reducing the incidence of reading difficulties from 20% in comparison schools to 5% in intervention schools. Conclusions: Phonological and phonics training is highly effective for children with poor phonological awareness, even when incorporated into whole-class teaching.

Probabilistic methods for drug discovery

This thesis introduces a flexible visual data exploration framework which combines advanced projection algorithms from the machine learning domain with visual representation techniques developed in the information visualisation domain to help a user to explore and understand effectively large multi-dimensional datasets. The advantage of such a framework to other techniques currently available to the domain experts is that the user is directly involved in the data mining process and advanced machine learning algorithms are employed for better projection. A hierarchical visualisation model guided by a domain expert allows them to obtain an informed segmentation of the input space. Two other components of this thesis exploit properties of these principled probabilistic projection algorithms to develop a guided mixture of local experts algorithm which provides robust prediction and a model to estimate feature saliency simultaneously with the training of a projection algorithm.Local models are useful since a single global model cannot capture the full variability of a heterogeneous data space such as the chemical space. Probabilistic hierarchical visualisation techniques provide an effective soft segmentation of an input space by a visualisation hierarchy whose leaf nodes represent different regions of the input space. We use this soft segmentation to develop a guided mixture of local experts (GME) algorithm which is appropriate for the heterogeneous datasets found in chemoinformatics problems. Moreover, in this approach the domain experts are more involved in the model development process which is suitable for an intuition and domain knowledge driven task such as drug discovery. We also derive a generative topographic mapping (GTM) based data visualisation approach which estimates feature saliency simultaneously with the training of a visualisation model.

An evaluation of pharmacy education and pre-registration training

This thesis covers two major aspects of pharmacy education; undergraduate education and pre-registration training. A cohort of pharmacy graduates were surveyed over a period of four years, on issues related to undergraduate education, pre-registration training and continuing education. These graduates were the first-ever to sit the pre-registration examination. In addition, the opinions of pre-registration tutors were obtained on pre-registration training, during the year that competence-based assessment was introduced. It was concluded that although the undergraduate course provided a broad base of knowledge suitable for graduates in all branches of pharmacy, several issues were identified which would require attention in future developments of the course. These were: 1. the strong support for the expansion of clinical, social and practice-based teaching. 2. the strong support to retain the scientific content to the same extent as in the three-year course. 3. a greater use of problem-based learning methods. The graduates supported the provision of a pre-registration continuing education course to help prepare for the examination and in areas inadequately covered in the undergraduate course. There was also support for the introduction of some form of split branch training. There was no strong evidence to suggest that the training had been an application of undergraduate education. In general, competence-based training was well regarded by tutors as an appropriate and effective method of skill assessment. However, community tutors felt it was difficult to carry out effectively due to day-to-day time constraints. The assistant tutors in hospital pharmacy were found to have a very important role in provision of training, and should be adequately trained and supported. The study recommends the introduction of uniform training and a quality assurance mechanism for all tutors and assistants undertaking this role.

Self-training from labeled features for sentiment analysis

Sentiment analysis concerns about automatically identifying sentiment or opinion expressed in a given piece of text. Most prior work either use prior lexical knowledge defined as sentiment polarity of words or view the task as a text classification problem and rely on labeled corpora to train a sentiment classifier. While lexicon-based approaches do not adapt well to different domains, corpus-based approaches require expensive manual annotation effort. In this paper, we propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon with preferences on expectations of sentiment labels of those lexicon words being expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie-review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than existing weakly-supervised sentiment classification methods despite using no labeled documents.

Practical methods of tracking of nonstationary time series applied to real-world data

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.

Developing critical understanding in HRM students:using innovative teaching methods to encourage deep approaches to study

Purpose – This paper aims to focus on developing critical understanding in human resource management (HRM) students in Aston Business School, UK. The paper reveals that innovative teaching methods encourage deep approaches to study, an indicator of students reaching their own understanding of material and ideas. This improves student employability and satisfies employer need. Design/methodology/approach – Student response to two second year business modules, matched for high student approval rating, was collected through focus group discussion. One module was taught using EBL and the story method, whilst the other used traditional teaching methods. Transcripts were analysed and compared using the structure of the ASSIST measure. Findings – Critical understanding and transformative learning can be developed through the innovative teaching methods of enquiry-based learning (EBL) and the story method. Research limitations/implications – The limitation is that this is a single case study comparing and contrasting two business modules. The implication is that the study should be replicated and developed in different learning settings, so that there are multiple data sets to confirm the research finding. Practical implications – Future curriculum development, especially in terms of HE, still needs to encourage students and lecturers to understand more about the nature of knowledge and how to learn. The application of EBL and the story method is described in a module case study – “Strategy for Future Leaders”. Originality/value – This is a systematic and comparative study to improve understanding of how students and lecturers learn and of the context in which the learning takes place.

Foundations of an intervention package to improve communication in residential care settings:a mixed methods study

Background: The prevalence of hearing loss is considerably higher in individuals in residential care than in people within the community-dwelling population, and yet hearing aids and hearing services are relatively underused. Care staff have a key role in supporting access to services. Objectives: This study identifies staff perspectives on hearing loss and their views about potential hearing service improvements. Study design: A four-stage mixed methods study was used, made up of qualitative interviews, observation, a survey and a stakeholder involvement meeting. Results: The qualitative stages indicated that staff were concerned about their levels of interaction with residents. Staff considered maximizing communication as part of their professional role. The quantitative survey indicated that these views were widely held by staff, and the stakeholder stage identified the need for social support and dedicated staff training opportunities. Conclusion: Care home staff regard communication as a shared issue. Future interventions could enhance access to hearing services and provide care home staff with training in hearing loss and hearing aid management. © 2013 Informa Healthcare.