The Perceived Effectiveness of Medical Social Work Faculty

Within the health care field, medical social work has expanded rapidly over the past few years (Bracht, 1974). Medical social workers comprise approximately 1.5 percent of the total medical schools\u27 faculty in the United States (Grinnell, Kyte & Hunter, 1976). There is additional evidence that medical social work faculty will increase over the years to come (Grinnell, Kyte, Hunter & Larson, 1976; Crinnell, Kyte & Hunter, 1976; Grinnell & Kyte, 1978b; & Grinnell & Kyte, 1979). Additionally, empirical studies have been conducted that analyzed the functions of social work faculty in medical schools (Grinnell & Kyte, 1978c; Grinnell & Kyte, 1980). However, the above literature has left two important questions unanswered. First, how do social work faculty in medical settings perceive their effectiveness, and second, what educational factors are associated with their perceived effectiveness? Thus, the purpose of this article is to present the results of an empirically based research project that examines these two areas. This information will serve as a valuable bench mark in contributing to the data we now have on the general effectiveness of social workers

Osteosarcoma outcomes at a South African tertiary hospital

Background. Osteosarcoma is the most common primary malignant bone tumour. There is a high incidence of late presentation in the developing world, posing additional challenges in the treatment of this aggressive disease.Objective. To evaluate clinical outcomes of patients with osteosarcoma at Charlotte Maxeke Johannesburg Academic Hospital (CMJAH), a tertiary hospital in South Africa, and compare these with similar studies in the developing world.Methods. This was a retrospective study of 61 patients treated at CMJAH between 2007 and 2011, with a minimum follow-up of 1.3 years (range 1.3 - 6.3).Results. An average of 4.5 months elapsed before patients were first seen at the CMJAH tumour unit. Fifty-eight patients (95.1%) initially sought conventional medical care. Three patients (4.9%) presented with pathological fractures. All the patients underwent biopsy, performed an average of 3 weeks after arrival at the tumour unit. In most cases the delay was due to limited access to magnetic resonance imaging. Most patients (n=41, 67.2%) were at Enneking stage 2B, 4 (6.6%) were at stage 2A and 16 (26.2%) were at stage 3. Of the patients, 13 (21.3%) underwent limb salvage procedures, 33 (54.1%) had amputations, 4 (6.6%) refused further treatment and 11 (18.0%) received palliative care only; 55 patients (90.2%) received chemotherapy. Two patients developed local recurrence, one of whom had an amputation and the other further wide excision. Two patients received palliative radiotherapy. Of the patients, 82.0% were HIV-negative, 4.9% HIVpositive and the rest of unknown status. At the time of the study, all but two patients, who came from other countries, were traceable or known to have died. Our overall 1-year and 5-year survival rates were 62.7% (95% confidence interval (CI) 49.1 - 73.9) and 38.1% (95% CI 24.6 - 51.4), respectively. Male patients and those with a higher Enneking stage had a poorer prognosis.Conclusion. Although most patients sought conventional medical care, unacceptable delays worsened survival. However, our survival rates are better than those in other developing countries. We advocate that professional, public and political awareness of osteosarcoma be improved as a matter of urgency, to facilitate rapid tertiary referral and expedite management

Interpol: An R package for preprocessing of protein sequences

<p>Abstract</p> <p>Background</p> <p>Most machine learning techniques currently applied in the literature need a fixed dimensionality of input data. However, this requirement is frequently violated by real input data, such as DNA and protein sequences, that often differ in length due to insertions and deletions. It is also notable that performance in classification and regression is often improved by numerical encoding of amino acids, compared to the commonly used sparse encoding.</p> <p>Results</p> <p>The software "Interpol" encodes amino acid sequences as numerical descriptor vectors using a database of currently 532 descriptors (mainly from AAindex), and normalizes sequences to uniform length with one of five linear or non-linear interpolation algorithms. Interpol is distributed with open source as platform independent R-package. It is typically used for preprocessing of amino acid sequences for classification or regression.</p> <p>Conclusions</p> <p>The functionality of Interpol widens the spectrum of machine learning methods that can be applied to biological sequences, and it will in many cases improve their performance in classification and regression.</p

Role of electrostatic interactions in amyloid beta-protein (Abeta) oligomer formation: A discrete molecular dynamics study

Pathological folding and oligomer formation of the amyloid beta-protein (Abeta) are widely perceived as central to Alzheimer's disease (AD). Experimental approaches to study Abeta self-assembly are problematic, because most relevant aggregates are quasi-stable and inhomogeneous. We apply a discrete molecular dynamics (DMD) approach combined with a four-bead protein model to study oligomer formation of the amyloid beta-protein (Abeta). We address the differences between the two most common Abeta alloforms, Abeta40 and Abeta42, which oligomerize differently in vitro. We study how the presence of electrostatic interactions (EIs) between pairs of charged amino acids affects Abeta40 and Abeta42 oligomer formation. Our results indicate that EIs promote formation of larger oligomers in both Abeta40 and Abeta42. The Abeta40 size distribution remains unimodal, whereas the Abeta42 distribution is trimodal, as observed experimentally. Abeta42 folded structure is characterized by a turn in the C-terminus that is not present in Abeta40. We show that the same C-terminal region is also responsible for the strongest intermolecular contacts in Abeta42 pentamers and larger oligomers. Our results suggest that this C-terminal region plays a key role in the formation of Abeta42 oligomers and the relative importance of this region increases in the presence of EIs. These results suggest that inhibitors targeting the C-terminal region of Abeta42 oligomers may be able to prevent oligomer formation or structurally modify the assemblies to reduce their toxicity.Comment: Accepted for publication at Biophysical Journa

A Small Conductance Calcium-Activated K⁺ Channel in C. elegans, KCNL-2, Plays a Role in the Regulation of the Rate of Egg-Laying

In the nervous system of mice, small conductance calcium-activated potassium (SK) channels function to regulate neuronal excitability through the generation of a component of the medium afterhyperpolarization that follows action potentials. In humans, irregular action potential firing frequency underlies diseases such as ataxia, epilepsy, schizophrenia and Parkinson's disease. Due to the complexity of studying protein function in the mammalian nervous system, we sought to characterize an SK channel homologue, KCNL-2, in C. elegans, a genetically tractable system in which the lineage of individual neurons was mapped from their early developmental stages. Sequence analysis of the KCNL-2 protein reveals that the six transmembrane domains, the potassium-selective pore and the calmodulin binding domain are highly conserved with the mammalian homologues. We used widefield and confocal fluorescent imaging to show that a fusion construct of KCNL-2 with GFP in transgenic lines is expressed in the nervous system of C. elegans. We also show that a KCNL-2 null strain, kcnl-2(tm1885), demonstrates a mild egg-laying defective phenotype, a phenotype that is rescued in a KCNL-2-dependent manner. Conversely, we show that transgenic lines that overexpress KCNL-2 demonstrate a hyperactive egg-laying phenotype. In this study, we show that the vulva of transgenic hermaphrodites is highly innervated by neuronal processes and by the VC4 and VC5 neurons that express GFP-tagged KCNL-2. We propose that KCNL-2 functions in the nervous system of C. elegans to regulate the rate of egg-laying. © 2013 Chotoo et al

Systematic evaluation of patient-reported outcome (PRO) protocol content and reporting in UK cancer clinical trials: the EPiC study protocol.

Emerging evidence suggests that patient-reported outcome (PRO)-specific information may be omitted in trial protocols and that PRO results are poorly reported, limiting the use of PRO data to inform cancer care. This study aims to evaluate the standards of PRO-specific content in UK cancer trial protocols and their arising publications and to highlight examples of best-practice PRO protocol content and reporting where they occur. The objective of this study is to determine if these early findings are generalisable to UK cancer trials, and if so, how best we can bring about future improvements in clinical trials methodology to enhance the way PROs are assessed, managed and reported.Trials in which the primary end point is based on a PRO will have more complete PRO protocol and publication components than trials in which PROs are secondary end points.Completed National Institute for Health Research (NIHR) Portfolio Cancer clinical trials (all cancer specialities/age-groups) will be included if they contain a primary/secondary PRO end point. The NIHR portfolio includes cancer trials, supported by a range of funders, adjudged as high-quality clinical research studies. The sample will be drawn from studies completed between 31 December 2000 and 1 March 2014 (n=1141) to allow sufficient time for completion of the final trial report and publication. Two reviewers will then review the protocols and arising publications of included trials to: (1) determine the completeness of their PRO-specific protocol content; (2) determine the proportion and completeness of PRO reporting in UK Cancer trials and (3) model factors associated with PRO protocol and reporting completeness and with PRO reporting proportion.The study was approved by the ethics committee at University of Birmingham (ERN_15-0311). Trial findings will be disseminated via presentations at local, national and international conferences, peer-reviewed journals and social media including the CPROR twitter account and UOB departmental website (http://www.birmingham.ac.uk/cpro0r)

Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution