Distribution of terminal nerve entry points to the flexor and extensor groups of forearm muscles:An anatomical study

The motor points of the skeletal muscles, mainly of interest to anatomists and physiologists, have recently attracted much attention from researchers in the field of functional electrical stimulation. The muscle motor point has been defined as the entry point of the motor nerve branch into the epimysium of the muscle belly. Anatomists have pointed out that many muscles in the limbs have multiple motor points. Knowledge of the location of nerve branches and terminal nerve entry points facilitates the exact insertion and the suitable selection of the number of electrodes required for each muscle for functional electrical stimulation. The present work therefore aimed to describe the number, location, and distribution of motor points in the human forearm muscles to obtain optimal hand function in many clinical situations. Twenty three adult human cadaveric forearms were dissected. The numbers of primary nerves and motor points for each muscle were tabulated. The mean numbers and the standard deviation were calculated and grouped in tables. Data analyses were performed with the use of a statistical analysis package (SPSS 13.0). The proximal third of the muscle was the usual part of the muscle that received the motor points. Most of the forearm muscles were innervated from the lateral side and deep surface of the muscle. The information in this study may also be usefully applied in selective denervation procedures to balance muscles in spastic upper limbs. Copyright © 2007 Via Medica.

An evaluation of a critical care course for undergraduate nursing students

AIM:
The aim of this paper was to evaluate a 2-day critical care course (CCC) delivered to a cohort of adult branch nursing students.

BACKGROUND:
In today's health care system there is an increase in the number of critically ill patients being cared for in a ward environment. As a result, nurses require the knowledge and skills to effectively manage this patient group. Skills such as prompt recognition of the sick patient, effective communication and performing basic management care skills are necessary.

METHODS:
The CCC was provided to final year adult branch nursing students (n = 182) within a university in the UK. On completion of the course, participants were invited to undertake a Likert scale questionnaire. The questionnaire also contained a free response section to elicit qualitative information. Quantitative data were analysed using SPSS version 17.0 and descriptive statistics produced. Qualitative responses were analysed thematically.

RESULTS:
There was a 73.7% (n = 135) response rate. Overall, there was a positive evaluation of the course. Students (89.6%; n = 121) reported a perceived increase in confidence when caring for critically ill patients following the course and 88.2% (n = 119) felt that their knowledge and skills had improved at the end of the 2-day course.

CONCLUSION:
This study supports the implementation of critical care training for undergraduate nursing students. There are implications for the development of specific modules, aiming to improve undergraduate nursing students' recognition, assessment and management of the critically ill patient.

Herschel key program HERITAGE:A far-infrared source catalog for the Magellanic Clouds

Observations from the HERschel Inventory of the Agents of Galaxy Evolution (HERITAGE ) have been used to identify dusty populations of sources in the Large and Small Magellanic Clouds (LMC and SMC). We conducted the study using the HERITAGE catalogs of point sources available from the Herschel Science Center from both the Photodetector Array Camera and Spectrometer (PACS; 100 and 160 μm) and Spectral and Photometric Imaging Receiver (SPIRE; 250, 350, and 500 μm) cameras. These catalogs are matched to each other to create a Herschel band-merged catalog and then further matched to archival Spitzer IRAC and MIPS catalogs from the Spitzer Surveying the Agents of Galaxy Evolution (SAGE) and SAGE-SMC surveys to create single mid- to far-infrared (far-IR) point source catalogs that span the wavelength range from 3.6 to 500 μm. There are 35,322 unique sources in the LMC and 7503 in the SMC. To be bright in the FIR, a source must be very dusty, and so the sources in the HERITAGE catalogs represent the dustiest populations of sources. The brightest HERITAGE sources are dominated by young stellar objects (YSOs), and the dimmest by background galaxies. We identify the sources most likely to be background galaxies by first considering their morphology (distant galaxies are point-like at the resolution of Herschel) and then comparing the flux distribution to that of the Herschel Astrophysical Terahertz Large Area Survey (ATLAS ) survey of galaxies. We find a total of 9745 background galaxy candidates in the LMC HERITAGE images and 5111 in the SMC images, in agreement with the number predicted by extrapolating from the ATLAS flux distribution. The majority of the Magellanic Cloud-residing sources are either very young, embedded forming stars or dusty clumps of the interstellar medium. Using the presence of 24 μm emission as a tracer of star formation, we identify 3518 YSO candidates in the LMC and 663 in the SMC. There are far fewer far-IR bright YSOs in the SMC than the LMC due to both the SMC's smaller size and its lower dust content. The YSO candidate lists may be contaminated at low flux levels by background galaxies, and so we differentiate between sources with a high ("probable") and moderate ("possible ") likelihood of being a YSO. There are 2493/425 probable YSO candidates in the LMC/SMC. Approximately 73% of the Herschel YSO candidates are newly identified in the LMC, and 35% in the SMC. We further identify a small population of dusty objects in the late stages of stellar evolution including extreme and post-asymptotic giant branch, planetary nebulae, and supernova remnants. These populations are identified by matching the HERITAGE catalogs to lists of previously identified objects in the literature. Approximately half of the LMC sources and one quarter of the SMC sources are too faint to obtain accurate ample FIR photometry and are unclassified.

Discovering subgroups of patients from DNA copy number data using NMF on compacted matrices

In the study of complex genetic diseases, the identification of subgroups of patients sharing similar genetic characteristics represents a challenging task, for example, to improve treatment decision. One type of genetic lesion, frequently investigated in such disorders, is the change of the DNA copy number (CN) at specific genomic traits. Non-negative Matrix Factorization (NMF) is a standard technique to reduce the dimensionality of a data set and to cluster data samples, while keeping its most relevant information in meaningful components. Thus, it can be used to discover subgroups of patients from CN profiles. It is however computationally impractical for very high dimensional data, such as CN microarray data. Deciding the most suitable number of subgroups is also a challenging problem. The aim of this work is to derive a procedure to compact high dimensional data, in order to improve NMF applicability without compromising the quality of the clustering. This is particularly important for analyzing high-resolution microarray data. Many commonly used quality measures, as well as our own measures, are employed to decide the number of subgroups and to assess the quality of the results. Our measures are based on the idea of identifying robust subgroups, inspired by biologically/clinically relevance instead of simply aiming at well-separated clusters. We evaluate our procedure using four real independent data sets. In these data sets, our method was able to find accurate subgroups with individual molecular and clinical features and outperformed the standard NMF in terms of accuracy in the factorization fitness function. Hence, it can be useful for the discovery of subgroups of patients with similar CN profiles in the study of heterogeneous diseases.

Power and Energy Implications of the Number of Threads Used on the Intel Xeon Phi

Energy consumption has become an important area of research of late. With the advent of new manycore processors, situations have arisen where not all the processors need to be active to reach an optimal relation between performance and energy usage. In this paper a study of the power and energy usage of a series of benchmarks, the PARSEC and the SPLASH- 2X Benchmark Suites, on the Intel Xeon Phi for different threads configurations, is presented. To carry out this study, a tool was designed to monitor and record the power usage in real time during execution time and afterwards to compare the r

Mapping neutral, ion and electron number densities within laser ablated plasma plumes

Spatially and temporally varying neutral, ion and electron number densities have been mapped out within laser ablated plasma plumes expanding into vacuum. Ablation of a magnesium target was performed using a KrF laser, 30 ns pulse duration and 248 nm wavelength. During the initial stage of plasma expansion (t <EQ 100 ns) interferometry has been used to obtain line averaged electron number densities, for laser power densities on target in the range 1.3 - 3.0 X 108 W/cm2. Later in the plasma expansion (t equals 1 microsecond(s) ) simultaneous absorption and laser induced fluorescence spectroscopy has been used to determine 3D neutral and ion number densities, for a power density equal to 6.7 X 107 W/cm2. Two distinct regions within the plume were identified. One is a fast component (approximately 106 cm-1) consisting of ions and neutrals with maximum number densities observed to be approximately 30 and 4 X 1012 cm-3 respectively, and the second consists of slow moving neutral material at a number density of up to 1015 cm-3. Additionally a Langmuir probe has been used to obtain ion and electron number densities at very late times in the plasma expansion (1 microsecond(s) <EQ t <EQ 15 microsecond(s) ). A copper target was ablated using a Nd:YAG laser, 7.5 ns duration and 532 nm (2 (omega) ) wavelength, with a power density on target equal to 6 X 108 W/cm2. Two regions within the plume with different velocities were observed. Within a fast component (approximately 3 X 106 cms-1) electron and ion number densities of the order 5 X 1012 cm-3 were observed and within the second slower component (approximately 106 cms-1) electron and ion number densities of the order 1 - 2 X 1013 cm-3 were determined.

Distributed Massive MIMO in Cellular Networks: Impact of Imperfect Hardware and Number of Oscillators

Distributed massive multiple-input multiple-output (MIMO) combines the array gain of coherent MIMO processing with the proximity gains of distributed antenna setups. In this paper, we analyze how transceiver hardware impairments affect the downlink with maximum ratio transmission. We derive closed-form spectral efficiencies expressions and study their asymptotic behavior as the number of the antennas increases. We prove a scaling law on the hardware quality, which reveals that massive MIMO is resilient to additive distortions, while multiplicative phase noise is a limiting factor. It is also better to have separate oscillators at each antenna than one per BS.

The paradox of invasion: Reeves’ muntjac deer invade the British Isles from a limited number of founding females

High levels of genetic diversity and high propagule pressure are favoured by conservation biologists as the basis for successful reintroductions and ensuring the persistence of populations. However, invasion ecologists recognize the ‘paradox of invasion’, as successful species introductions may often be characterized by limited numbers of individuals and associated genetic bottlenecks. In the present study, we used a combination of high-resolution nuclear and mitochondrial genetic markers to investigate the invasion history of Reeves' muntjac deer in the British Isles. This invasion has caused severe economic and ecological damage, with secondary spread currently a concern throughout Europe and potentially globally. Microsatellite analysis based on eight loci grouped all 176 introduced individuals studied from across the species' range in the UK into one genetic cluster, and seven mitochondrial D-loop haplotypes were recovered, two of which were present at very low frequency and were related to more common haplotypes. Our results indicate that the entire invasion can be traced to a single founding event involving a low number of females. These findings highlight the fact that even small releases of species may, if ignored, result in irreversible and costly invasion, regardless of initial genetic diversity or continual genetic influx.

Magnetic Characteristics of a High-layer-number NiFe/FeMn Multilayer

We report the static & dynamic magnetic characteristics of a high-layer-number NiFe/FeMn multilayer test structure with potential applications in broadband absorber and filter devices. To allow fine control over the absorption linewidths and to understand the mechanisms governing the resonances in a tailored structure similar to that expected to be used in real world applications, the multilayer was intentionally designed to have layer thickness and interface roughness variations. Magnetometry measurements show the sample has complex hysteresis loops with features consistent with single ferromagnetic film reversals. Structural characterisation by transmission electron microscopy allows us to correlate the magnetic properties with structural features. Analysis of resonance frequencies from broadband ferromagnetic resonance measurements as a function of field magnitude and orientation provide values of the local exchange bias, rotatable anisotropy, and uniaxial anisotropy fields for specific layers in the stack and explain the observed mode softening. The linewidths of the multilayer are adjustable around the bias field, approaching twice that seen at larger fields, allowing control over the bandwidth of devices formed from the structure.

Low alanine aminotransferase levels and higher number of cardiovascular events in people with Type 2 diabetes: analysis of the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study.

AIMS: To determine whether alanine aminotransferase or gamma-glutamyltransferase levels, as markers of liver health and non-alcoholic fatty liver disease, might predict cardiovascular events in people with Type 2 diabetes.

METHODS: Data from the Fenofibrate Intervention and Event Lowering in Diabetes study were analysed to examine the relationship between liver enzymes and incident cardiovascular events (non-fatal myocardial infarction, stroke, coronary and other cardiovascular death, coronary or carotid revascularization) over 5 years.

RESULTS: Alanine aminotransferase level had a linear inverse relationship with the first cardiovascular event occurring in participants during the study period. After adjustment, for every 1 sd higher baseline alanine aminotransferase value (13.2 U/l), the risk of a cardiovascular event was 7% lower (95% CI 4-13; P=0.02). Participants with alanine aminotransferase levels below and above the reference range 8-41 U/l for women and 9-59 U/l for men, had hazard ratios for a cardiovascular event of 1.86 (95% CI 1.12-3.09) and 0.65 (95% CI 0.49-0.87), respectively (P=0.001). No relationship was found for gamma-glutamyltransferase.

CONCLUSIONS: The data may indicate that in people with Type 2 diabetes, which is associated with higher alanine aminotransferase levels because of prevalent non-alcoholic fatty liver disease, a low alanine aminotransferase level is a marker of hepatic or systemic frailty rather than health. This article is protected by copyright. All rights reserved.

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.