A double-blind, randomized, controlled crossover trial of glutamine supplementation in home parenteral nutrition

Objective: Studies suggest clinical benefit of glutamine-supplemented parenteral nutrition. The aim was to determine if the inclusion of 10 g of glutamine as part of the nitrogen source of home parenteral nutrition (HPN) reduces infectious complications. Subjects/Methods: Thirty-five patients on HPN were recruited and 22 completed the study. Patients were randomized to receive either standard HPN or glutamine-supplemented HPN. Patients were assessed at randomization, 3 and 6 months later then they were crossed over to the alternative HPN and reassessed at 3 and 6 months. Assessments included plasma amino acid concentrations, intestinal permeability and absorption, nutritional status, oral and parenteral intake, quality of life, routine biochemistry and haematology. Results: No difference was seen between the groups at randomization. No difference was detected between the treatment phases for infective complications (55% in the standard treatment phase and 36% in the glutamine-supplemented phase P 0.67). There were no differences in nutritional status, intestinal permeability, plasma glutamine concentrations or quality of life. Conclusion: Although limited by the sample size, the study has shown that glutamine as part of the nitrogen source of parenteral nutrition can be given to patients on HPN for 6 months without any adverse effects.

Artichoke leaf extract (Cynara scolymus) reduces plasma cholesterol in otherwise healthy hypercholesterolemic adults: A randomized, double blind placebo controlled trial

Cardiovascular diseases are the chief causes of death in the UK, and are associated with high circulating levels of total cholesterol in the plasma. Artichoke leaf extracts (ALEs) have been reported to reduce plasma lipids levels, including total cholesterol, although high quality data is lacking. The objective of this trial was to assess the effect of ALE on plasma lipid levels and general well-being in otherwise healthy adults with mild to moderate hypercholesterolemia. 131 adults were screened for total plasma cholesterol in the range 6.0-8.0 mmol/l, with 75 suitable volunteers randomised onto the trial. Volunteers consumed 1280 mg of a standardised ALE, or matched placebo, daily for 12 weeks. Plasma total cholesterol decreased in the treatment group by an average of 4.2% (from 7.16 (SD 0.62) mmol/l to 6.86 (SD 0.68) mmol/l) and increased in the control group by an average of 1.9% (6.90 (SD 0.49) mmol/l to 7.03 (0.61) mmol/l), the difference between groups being statistically significant (p = 0.025). No significant differences between groups were observed for LDL cholesterol, HDL cholesterol or triglyceride levels. General well-being improved significantly in both the treatment (11%) and control groups (9%) with no significant differences between groups. In conclusion, ALE consumption resulted in a modest but favourable statistically significant difference in total cholesterol after 12 weeks. In comparison with a previous trial, it is suggested that the apparent positive health status of the study population may have contributed to the modesty of the observed response. (C) 2008 Elsevier GmbH. All rights reserved.

Bromelain as an adjunctive treatment for moderate-to-severe osteoarthritis of the knee: a randomized placebo-controlled pilot study

Background: Osteoarthritis (OA) of the knee is the most prevalent joint disorder. Previous studies suggest that bromelain, a pineapple extract, may be a safer alternative/adjunctive treatment for knee OA than current conventional treatment. Aim: To assess the efficacy of bromelain in treating OA of the knee. Design: Randomized, double-blind placebo-controlled trial. Methods: Subjects (n=47) with a confirmed diagnosis of moderate to severe knee OA were randomized to 12 weeks of bromelain 800 mg/day or placebo, with a 4-week follow-up. Knee (pain, stiffness and function) and quality-of-life symptoms were reported monthly in the WOMAC and SF36 questionnaires, respectively. Adverse events were also recorded. The primary outcome measure was the change in total WOMAC score from baseline to the end of treatment at week 12. Longitudinal models were used to evaluate outcome. Results: Thirty-one patients completed the trial (14 bromelain, 17 placebo). No statistically significant differences were observed between groups for the primary outcome (coefficient 11.16, p=0.27, 95%CI-8.86 to 31.18), nor the WOMAC subscales or SF36. Both treatment groups showed clinically relevant improvement in the WOMAC disability subscale only. Adverse events were generally mild in nature. Discussion: This study suggests that bromelain is not efficacious as an adjunctive treatment of moderate to severe OA, but its limitations support the need for a follow-up study.

Can a short period of micronutrient supplementation in older institutionalized people improve response to influenza vaccine? A randomized, controlled trial

OBJECTIVES: To test the hypothesis that a micronutrient supplement can improve seroconversion after influenza immunization in older institutionalized people. DESIGN: Randomized, double-blind, placebo-controlled study. SETTING: Nursing and residential homes in Liverpool, United Kingdom. PARTICIPANTS: One hundred sixty-four residents aged 60 and older from 31 homes were initially randomized; of these, 119 (72.6%) completed the study. INTERVENTION: Participants were randomized to receive a micronutrient supplement providing the reference nutrient intake for all vitamins and trace elements or identical placebo. Tablets were taken over an 8-week period during September and October 2000; influenza vaccine was administered 4 weeks after their commencement. MEASUREMENTS: The hemagglutination-inhibiting antibody response as defined by a fourfold or greater titer rise over 4 weeks and assessed separately for each of the three antigens contained in the 2000/2001 influenza vaccine (A/New Caledonia/20/99 (H1N1), A/Moscow/10/99 (H3N2), B/Beijing/184/93 (B)). RESULTS: Despite a significant increase in serum concentrations of vitamins A, C, D-3, E, folate, and selenium in the supplemented group, there was no significant difference between groups (supplemented vs placebo, respectively) in the proportion of participants seroconverting to H1N1 (41% vs 49%, P=.374), H3N2 (49% vs 58%, P=.343), or B (41% vs 40%, P=.944). CONCLUSION: A micronutrient supplement providing the reference nutrient intake administered over 8 weeks had no beneficial effect on antibody response to influenza vaccine in older people living in long-term care.

Advanced scalable algorithms for advanced architectures

With the latest advances in the area of advanced computer architectures we are seeing already large scale machines at petascale level and we are discussing exascale computing. All these require efficient scalable algorithms in order to bridge the performance gap. In this paper examples of various approaches of designing scalable algorithms for such advanced architectures will be given and the corresponding properties of these algorithms will be outlined and discussed. Examples will outline such scalable algorithms applied to large scale problems in the area Computational Biology, Environmental Modelling etc. The key properties of such advanced and scalable algorithms will be outlined.

Economic models and algorithms for distributed systems

Distributed computing paradigms for sharing resources such as Clouds, Grids, Peer-to-Peer systems, or voluntary computing are becoming increasingly popular. While there are some success stories such as PlanetLab, OneLab, BOINC, BitTorrent, and SETI@home, a widespread use of these technologies for business applications has not yet been achieved. In a business environment, mechanisms are needed to provide incentives to potential users for participating in such networks. These mechanisms may range from simple non-monetary access rights, monetary payments to specific policies for sharing. Although a few models for a framework have been discussed (in the general area of a "Grid Economy"), none of these models has yet been realised in practice. This book attempts to fill this gap by discussing the reasons for such limited take-up and exploring incentive mechanisms for resource sharing in distributed systems. The purpose of this book is to identify research challenges in successfully using and deploying resource sharing strategies in open-source and commercial distributed systems.

An analysis of real time implementation of Fourier transform-based frequency recognition algorithms

Frequency recognition is an important task in many engineering fields such as audio signal processing and telecommunications engineering, for example in applications like Dual-Tone Multi-Frequency (DTMF) detection or the recognition of the carrier frequency of a Global Positioning, System (GPS) signal. This paper will present results of investigations on several common Fourier Transform-based frequency recognition algorithms implemented in real time on a Texas Instruments (TI) TMS320C6713 Digital Signal Processor (DSP) core. In addition, suitable metrics are going to be evaluated in order to ascertain which of these selected algorithms is appropriate for audio signal processing(1).

Pulse shaping using state space algorithms

We discuss the use of pulse shaping for optimal excitation of samples in time-domain THz spectroscopy. Pulse shaping can be performed in a 4f optical system to specifications from state space models of the system's dynamics. Subspace algorithms may be used for the identification of the state space models.

Suboptimal system recovery from communication loss in a multi-robot localization scenario using EKF algorithms

This paper describes a multi-robot localization scenario where, for a period of time, the robot team loses communication with one of the robots due to system error. In this novel approach, extended Kalman filter (EKF) algorithms utilize relative measurements to localize the robots in space. These measurements are used to reliably compensate "dead-com" periods were no information can be exchanged between the members of the robot group.

Evolving features-algorithms knowledge map to support NIDS data intelligence and learning loop architecting – a generalised approach to NIDS pattern feature space knowledge processing

This paper describes a proposed new approach to the Computer Network Security Intrusion Detection Systems (NIDS) application domain knowledge processing focused on a topic map technology-enabled representation of features of the threat pattern space as well as the knowledge of situated efficacy of alternative candidate algorithms for pattern recognition within the NIDS domain. Thus an integrative knowledge representation framework for virtualisation, data intelligence and learning loop architecting in the NIDS domain is described together with specific aspects of its deployment.

Increasing detection rate of user-to-root attacks using genetic algorithms

An extensive set of machine learning and pattern classification techniques trained and tested on KDD dataset failed in detecting most of the user-to-root attacks. This paper aims to provide an approach for mitigating negative aspects of the mentioned dataset, which led to low detection rates. Genetic algorithm is employed to implement rules for detecting various types of attacks. Rules are formed of the features of the dataset identified as the most important ones for each attack type. In this way we introduce high level of generality and thus achieve high detection rates, but also gain high reduction of the system training time. Thenceforth we re-check the decision of the user-to- root rules with the rules that detect other types of attacks. In this way we decrease the false-positive rate. The model was verified on KDD 99, demonstrating higher detection rates than those reported by the state- of-the-art while maintaining low false-positive rate.

Optimization algorithms in FMRF model-based segmentation for LIDAR data and co-registered bands

In this paper, a fuzzy Markov random field (FMRF) model is used to segment land-objects into free, grass, building, and road regions by fusing remotely, sensed LIDAR data and co-registered color bands, i.e. scanned aerial color (RGB) photo and near infra-red (NIR) photo. An FMRF model is defined as a Markov random field (MRF) model in a fuzzy domain. Three optimization algorithms in the FMRF model, i.e. Lagrange multiplier (LM), iterated conditional mode (ICM), and simulated annealing (SA), are compared with respect to the computational cost and segmentation accuracy. The results have shown that the FMRF model-based ICM algorithm balances the computational cost and segmentation accuracy in land-cover segmentation from LIDAR data and co-registered bands.

Subspace and wavelet-packet algorithms for de-noising and classifying broadband THz transients

The results from a range of different signal processing schemes used for the further processing of THz transients are contrasted. The performance of different classifiers after adopting these schemes are also discussed.