A management architecture for active networks

In this paper we present an architecture for network and applications management, which is based on the Active Networks paradigm and shows the advantages of network programmability. The stimulus to develop this architecture arises from an actual need to manage a cluster of active nodes, where it is often required to redeploy network assets and modify nodes connectivity. In our architecture, a remote front-end of the managing entity allows the operator to design new network topologies, to check the status of the nodes and to configure them. Moreover, the proposed framework allows to explore an active network, to monitor the active applications, to query each node and to install programmable traps. In order to take advantage of the Active Networks technology, we introduce active SNMP-like MIBs and agents, which are dynamic and programmable. The programmable management agents make tracing distributed applications a feasible task. We propose a general framework that can inter-operate with any active execution environment. In this framework, both the manager and the monitor front-ends communicate with an active node (the Active Network Access Point) through the XML language. A gateway service performs the translation of the queries from XML to an active packet language and injects the code in the network. We demonstrate the implementation of an active network gateway for PLAN (Packet Language for Active Networks) in a forty active nodes testbed. Finally, we discuss an application of the active management architecture to detect the causes of network failures by tracing network events in time

Bananas as an Energy Source during Exercise: A Metabolomics Approach

This study compared the acute effect of ingesting bananas (BAN) versus a 6% carbohydrate drink (CHO) on 75-km cycling performance and post-exercise inflammation, oxidative stress, and innate immune function using traditional and metabolomics-based profiling. Trained cyclists (N = 14) completed two 75-km cycling time trials (randomized, crossover) while ingesting BAN or CHO (0.2 g/kg carbohydrate every 15 min). Pre-, post-, and 1-h-post-exercise blood samples were analyzed for glucose, granulocyte (GR) and monocyte (MO) phagocytosis (PHAG) and oxidative burst activity, nine cytokines, F2-isoprostanes, ferric reducing ability of plasma (FRAP), and metabolic profiles using gas chromatography-mass spectrometry. Blood glucose levels and performance did not differ between BAN and CHO (2.41±0.22, 2.36±0.19 h, P = 0.258). F2-isoprostanes, FRAP, IL-10, IL-2, IL-6, IL-8, TNFα, GR-PHAG, and MO-PHAG increased with exercise, with no trial differences except for higher levels during BAN for IL-10, IL-8, and FRAP (interaction effects, P = 0.003, 0.004, and 0.012). Of 103 metabolites detected, 56 had exercise time effects, and only one (dopamine) had a pattern of change that differed between BAN and CHO. Plots from the PLS-DA model visualized a distinct separation in global metabolic scores between time points [R2Y(cum) = 0.869, Q2(cum) = 0.766]. Of the top 15 metabolites, five were related to liver glutathione production, eight to carbohydrate, lipid, and amino acid metabolism, and two were tricarboxylic acid cycle intermediates. BAN and CHO ingestion during 75-km cycling resulted in similar performance, blood glucose, inflammation, oxidative stress, and innate immune levels. Aside from higher dopamine in BAN, shifts in metabolites following BAN and CHO 75-km cycling time trials indicated a similar pattern of heightened production of glutathione and utilization of fuel substrates in several pathways

Issues potentially affecting quality of life arising from long-term medicines use: a qualitative study

Background Polypharmacy is increasing and managing large number of medicines may create a burden for patients. Many patients have negative views of medicines and their use can adversely affect quality of life. No studies have specifically explored the impact of general long-term medicines use on quality of life. Objective To determine the issues which patients taking long-term medicines consider affect their day-to-day lives, including quality of life. Setting Four primary care general practices in North West England Methods Face-to-face interviews with adults living at home, prescribed four or more regular medicines for at least 1 year. Interviewees were identified from primary care medical records and purposively selected to ensure different types of medicines use. Interviews were recorded, transcribed and analysed thematically. Results Twenty-one interviews were conducted and analysed. Patients used an average of 7.8 medicines, 51 % were preventive, 40 % for symptom relief and 9 % treatment. Eight themes emerged: relationships with health professionals, practicalities, information, efficacy, side effects, attitudes, impact and control. Ability to discuss medicines with health professionals varied and many views were coloured by negative experiences, mainly with doctors. All interviewees had developed routines for using multiple medicines, some requiring considerable effort. Few felt able to exert control over medicines routines specified by health professionals. Over half sought additional information about medicines whereas others avoided this, trusting in doctors to guide their medicines use. Patients recognised their inability to assess efficacy for many medicines, notably those used for prophylaxis. All were concerned about possible side effects and some had poor experiences of discussing concerns with doctors. Medicines led to restrictions on social activities and personal life to the extent that, for some, life can revolve around medicines. Conclusion There is a multiplicity and complexity of issues surrounding medicines use, which impact on day-to-day lives for patients with long-term conditions. While most patients adapt to long-term medicines use, others did so at some cost to their quality of life

Simplified Luminal Water Imaging for the Detection of Prostate Cancer From Multiecho T2 MR Images

BACKGROUND: Luminal water imaging (LWI) suffers less from imaging artifacts than the diffusion-weighted imaging used in multiparametric MRI of the prostate. LWI obtains multicompartment tissue information from a multiecho T2 dataset. PURPOSE: To compare a simplified LWI technique with apparent diffusion coefficient (ADC) in classifying lesions based on groupings of PI-RADS v2 scores. Secondary aims were to investigate whether LWI differentiates between histologically confirmed tumor and normal tissue as effectively as ADC, and whether LWI is correlated with the multicompartment parameters of the vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) diffusion model. STUDY TYPE: A subset of a larger prospective study. POPULATION: In all, 65 male patients aged 49-79 were scanned. FIELD STRENGTH/SEQUENCE: A 32-echo T2 and a six b-value diffusion sequence (0, 90, 500, 1500, 2000, 3000 s/mm2 ) at 3T. ASSESSMENT: Regions of interest were placed by a board-certified radiologist in areas of lesion and benign tissue and given PI-RADS v2 scores. STATISTICAL TESTS: Receiver operating characteristic and logistic regression analyses were performed. RESULTS: LWI classifies tissue as PI-RADS 1,2 or PI-RADS 3,4,5 with an area under curve (AUC) value of 0.779, compared with 0.764 for ADC. LWI differentiated histologically confirmed malignant from nonmalignant tissue with AUC, sensitivity, and specificity values of 0.81, 75%, and 87%, compared with 0.75, 83%, and 67% for ADC. The microstructural basis of the LWI technique is further suggested by the correspondence with the VERDICT diffusion-based microstructural imaging technique, with α, A1 , A2 , and LWF showing significant correlations. DATA CONCLUSION: LWI alone can predict PI-RADS v2 score groupings and detect histologically confirmed tumors with an ability similar to ADC alone without the limitations of diffusion-weighted MRI. This is important, given that ADC has an advantage in these tests as it already informs PI-RADS v2 scoring. LWI also provides multicompartment information that has an explicit biophysical interpretation, unlike ADC. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018

PRESENT 2020: Text Expanding on the Checklist for Proper Reporting of Evidence in Sport and Exercise Nutrition Trials.

Some readers may not have access to the full paper, so a properly formatted and well-written abstract is imperative. Authors should give priority to information about the current study rather than using the abstract for an extensive background or rationale. 2a Methods: Key information regarding the study design, methods, and population should be summarized to enable broad understanding of the study from the abstract. 2b Results: Readers are interested in extracting key data that reflect the main findings of the study. The abstract should present data (e.g., the absolute magnitude of values and the size/precision of effects—specifying which measures of central tendency and variability are stated) rather than simply stating the presence, absence, or direction of effects. The presentation of p values or similar inferential statistics is no substitute for reporting actual data (Maughan, 2004). 2c Conclusion: Priority should be given to the reporting of results as per the previous section, with only a brief concluding statement thereafter. A concise conclusion based on what was actually measured in the study is preferred to speculative interpretations, with cautious use of language to avoid hyperbole or improper inference of causality (Brown et al., 2013). It is not appropriate or necessary to identify further research priorities here

Noninvasive diffusion magnetic resonance imaging of brain tumour cell size for the early detection of therapeutic response

Cancer cells differ in size from those of their host tissue and are known to change in size during the processes of cell death. A noninvasive method for monitoring cell size would be highly advantageous as a potential biomarker of malignancy and early therapeutic response. This need is particularly acute in brain tumours where biopsy is a highly invasive procedure. Here, diffusion MRI data were acquired in a GL261 glioma mouse model before and during treatment with Temozolomide. The biophysical model VERDICT (Vascular Extracellular and Restricted Diffusion for Cytometry in Tumours) was applied to the MRI data to quantify multi-compartmental parameters connected to the underlying tissue microstructure, which could potentially be useful clinical biomarkers. These parameters were compared to ADC and kurtosis diffusion models, and, measures from histology and optical projection tomography. MRI data was also acquired in patients to assess the feasibility of applying VERDICT in a range of different glioma subtypes. In the GL261 gliomas, cellular changes were detected according to the VERDICT model in advance of gross tumour volume changes as well as ADC and kurtosis models. VERDICT parameters in glioblastoma patients were most consistent with the GL261 mouse model, whilst displaying additional regions of localised tissue heterogeneity. The present VERDICT model was less appropriate for modelling more diffuse astrocytomas and oligodendrogliomas, but could be tuned to improve the representation of these tumour types. Biophysical modelling of the diffusion MRI signal permits monitoring of brain tumours without invasive intervention. VERDICT responds to microstructural changes induced by chemotherapy, is feasible within clinical scan times and could provide useful biomarkers of treatment response