A randomised controlled trial to assess the effectiveness of a single session of nurse administered massage for short term relief of chronic non-malignant pain

Background: Massage is increasingly used to manage chronic pain but its benefit has not been clearly established. The aim of the study is to determine the effectiveness of a single session of nurse-administered massage for the short term relief of chronic non-malignant pain and anxiety. Methods: A randomised controlled trial design was used, in which the patients were assigned to a massage or control group. The massage group received a 15 minute manual massage and the control group a 15 minute visit to talk about their pain. Adult patients attending a pain relief unit with a diagnosis of chronic pain whose pain was described as moderate or severe were eligible for the study. An observer blind to the patients' treatment group carried out assessments immediately before (baseline), after treatment and 1, 2, 3 and 4 hours later. Pain was assessed using 100 mm visual analogue scale and the McGill Pain Questionnaire. Pain Relief was assessed using a five point verbal rating scale. Anxiety was assessed with the Spielberger short form State-Trait Anxiety Inventory. Results: 101 patients were randomised and evaluated, 50 in the massage and 51 in the control group. There were no statistically significant differences between the groups at baseline interview. Patients in the massage but not the control group had significantly less pain compared to baseline immediately after and one hour post treatment. 95% confidence interval for the difference in mean pain reduction at one hour post treatment between the massage and control groups is 5.47 mm to 24.70 mm. Patients in the massage but not the control group had a statistically significant reduction in anxiety compared to baseline immediately after and at 1 hour post treatment. Conclusion: Massage is effective in the short term for chronic pain of moderate to severe intensity

Characterization of Shewanella oneidensis MtrC: a cell-surface decaheme cytochrome involved in respiratory electron transport to extracellular electron acceptors

MtrC is a decaheme c-type cytochrome associated with the outer cell membrane of Fe(III)-respiring species of the Shewanella genus. It is proposed to play a role in anaerobic respiration by mediating electron transfer to extracellular mineral oxides that can serve as terminal electron acceptors. The present work presents the first spectropotentiometric and voltammetric characterization of MtrC, using protein purified from Shewanella oneidensis MR-1. Potentiometric titrations, monitored by UV–vis absorption and electron paramagnetic resonance (EPR) spectroscopy, reveal that the hemes within MtrC titrate over a broad potential range spanning between approximately +100 and approximately -500 mV (vs. the standard hydrogen electrode). Across this potential window the UV–vis absorption spectra are characteristic of low-spin c-type hemes and the EPR spectra reveal broad, complex features that suggest the presence of magnetically spin-coupled low-spin c-hemes. Non-catalytic protein film voltammetry of MtrC demonstrates reversible electrochemistry over a potential window similar to that disclosed spectroscopically. The voltammetry also allows definition of kinetic properties of MtrC in direct electron exchange with a solid electrode surface and during reduction of a model Fe(III) substrate. Taken together, the data provide quantitative information on the potential domain in which MtrC can operate

An off-board quantum point contact as a sensitive detector of cantilever motion

Recent advances in the fabrication of microelectromechanical systems (MEMS) and their evolution into nanoelectromechanical systems (NEMS) have allowed researchers to measure extremely small forces, masses, and displacements. In particular, researchers have developed position transducers with resolution approaching the uncertainty limit set by quantum mechanics. The achievement of such resolution has implications not only for the detection of quantum behavior in mechanical systems, but also for a variety of other precision experiments including the bounding of deviations from Newtonian gravity at short distances and the measurement of single spins. Here we demonstrate the use of a quantum point contact (QPC) as a sensitive displacement detector capable of sensing the low-temperature thermal motion of a nearby micromechanical cantilever. Advantages of this approach include versatility due to its off-board design, compatibility with nanoscale oscillators, and, with further development, the potential to achieve quantum limited displacement detection.Comment: 5 pages, 5 figure

Multiplexed SNP typing of ancient DNA clarifies the origin of Andaman mtDNA haplogroups amongst South Asian tribal populations

© 2006 Endicott et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The issue of errors in genetic data sets is of growing concern, particularly in population genetics where whole genome mtDNA sequence data is coming under increased scrutiny. Multiplexed PCR reactions, combined with SNP typing, are currently under-exploited in this context, but have the potential to genotype whole populations rapidly and accurately, significantly reducing the amount of errors appearing in published data sets. To show the sensitivity of this technique for screening mtDNA genomic sequence data, 20 historic samples of the enigmatic Andaman Islanders and 12 modern samples from three Indian tribal populations (Chenchu, Lambadi and Lodha) were genotyped for 20 coding region sites after provisional haplogroup assignment with control region sequences. The genotype data from the historic samples significantly revise the topologies for the Andaman M31 and M32 mtDNA lineages by rectifying conflicts in published data sets. The new Indian data extend the distribution of the M31a lineage to South Asia, challenging previous interpretations of mtDNA phylogeography. This genetic connection between the ancestors of the Andamanese and South Asian tribal groups ~30 kya has important implications for the debate concerning migration routes and settlement patterns of humans leaving Africa during the late Pleistocene, and indicates the need for more detailed genotyping strategies. The methodology serves as a low-cost, high-throughput model for the production and authentication of data from modern or ancient DNA, and demonstrates the value of museum collections as important records of human genetic diversity.Phillip Endicott, Mait Metspalu, Chris Stringer, Vincent Macaulay, Alan Cooper, Juan J. Sanche

Research on Artificial Intelligence Ethics Based on the Evolution of Population Knowledge Base

The unclear development direction of human society is a deep reason for that it is difficult to form a uniform ethical standard for human society and artificial intelligence. Since the 21st century, the latest advances in the Internet, brain science and artificial intelligence have brought new inspiration to the research on the development direction of human society. Through the study of the Internet brain model, AI IQ evaluation, and the evolution of the brain, this paper proposes that the evolution of population knowledge base is the key for judging the development direction of human society, thereby discussing the standards and norms for the construction of artificial intelligence ethics.Comment: 12 pages, 6 figures,1 tabl

Search for Charged Higgs Bosons in e+e- Collisions at \sqrt{s} = 189 GeV

A search for pair-produced charged Higgs bosons is performed with the L3 detector at LEP using data collected at a centre-of-mass energy of 188.6 GeV, corresponding to an integrated luminosity of 176.4 pb^-1. Higgs decays into a charm and a strange quark or into a tau lepton and its associated neutrino are considered. The observed events are consistent with the expectations from Standard Model background processes. A lower limit of 65.5 GeV on the charged Higgs mass is derived at 95 % confidence level, independent of the decay branching ratio Br(H^{+/-} -> tau nu)

Membranes by the Numbers

Many of the most important processes in cells take place on and across membranes. With the rise of an impressive array of powerful quantitative methods for characterizing these membranes, it is an opportune time to reflect on the structure and function of membranes from the point of view of biological numeracy. To that end, in this article, I review the quantitative parameters that characterize the mechanical, electrical and transport properties of membranes and carry out a number of corresponding order of magnitude estimates that help us understand the values of those parameters.Comment: 27 pages, 12 figure

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

The Utilization of Data Analysis Techniques in Predicting Student Performance in Massive Open Online Courses (MOOCs)

The growth of the Internet has enabled the popularity of open online learning platforms to increase over the years. This has led to the inception of Massive Open Online Courses (MOOCs) that enrol, millions of people, from all over the world. Such courses operate under the concept of open learning, where content does not have to be delivered via standard mechanisms that institutions employ, such as physically attending lectures. Instead learning occurs online via recorded lecture material and online tasks. This shift has allowed more people to gain access to education, regardless of their learning background. However, despite these advancements in delivering education, completion rates for MOOCs are low. In order to investigate this issue, the paper explores the impact that technology has on open learning and identifies how data about student performance can be captured to predict trend so that at risk students can be identified before they drop-out. In achieving this, subjects surrounding student engagement and performance in MOOCs and data analysis techniques are explored to investigate how technology can be used to address this issue. The paper is then concluded with our approach of predicting behaviour and a case study of the eRegister system, which has been developed to capture and analyse data. Keywords: Open Learning; Prediction; Data Mining; Educational Systems; Massive Open Online Course; Data Analysi