Mechanistic details of the membrane perforation and passive translocation of TAT peptides

The trans-activator of transcription (TAT) peptide is regarded as the “gold standard��� for cell-penetrating peptides, capable of traversing a mammalian membrane passively into the cytosolic space. This characteristic has been exploited through conjugation of TAT for applications such as drug delivery. However, the process by which TAT achieves membrane penetration remains ambiguous and unresolved. Mechanistic details of TAT peptide action are revealed herein by using three complementary methods: quartz crystal microbalance with dissipation (QCM-D), scanning electrochemical microscopy (SECM) and atomic force microscopy (AFM). When combined, these three scales of measurement define that the membrane uptake of the TAT peptide is by trans-membrane insertion using a “worm-hole” pore that leads to ion permeability across the membrane layer. AFM data provided nanometre-scale visualisation of TAT punctuation using a mammalian-mimetic membrane bilayer. The TAT peptide does not show the same specificity towards a bacterial mimetic membrane and QCM-D and SECM showed that the TAT peptide demonstrates a disruptive action towards these membranes. This investigation supports the energy-independent uptake of the cationic TAT peptide and provides empirical data that clarify the mechanism by which the TAT peptide achieves its membrane activity. The novel use of these three biophysical techniques provides valuable insight into the mechanism for TAT peptide translocation, which is essential for improvements in the cellular delivery of TAT-conjugated cargoes including therapeutic agents required to target specific intracellular locations.

Machine learning approaches to analysing textual injury surveillance data: A systematic review

Objective To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Design Systematic review. Data sources The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. Selection criteria For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. Methods The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Results Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. Conclusions The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field.

MITIE C-Arm - Advanced innovation in education

Aim: In 2013 QUT introduced the Medical Imaging Training Immersive Environment (MITIE) as a virtual reality (VR) platform that allowed students to practice general radiography. The system software has been expanded to now include C-Arm. The aim of this project was to investigate the use of this technology in the pedagogy of undergraduate medical imaging students who have limited to no experience in the use of the C-Arm clinically. Method: The Medical Imaging Training Immersive Environment (MITIE) application provides students with realistic and fully interactive 3D models of C-Arm equipment. As with VR initiatives in other health disciplines (1–2) the software mimics clinical practice as much as possible and uses 3D technology to enhance 3D spatial awareness and realism. The application allows students to set up and expose a virtual patient in a 3D environment as well as creating the resultant “image” for comparison with a gold standard. Automated feedback highlights ways for the student to improve their patient positioning, equipment setup or exposure factors. The students' equipment knowledge was tested using an on line assessment quiz and surveys provided information on the students' pre-clinical confidence scale, with post-clinical data comparisons. Ethical approval for the project was provided by the university ethics panel. Results: This study is currently under way and this paper will present analysis of initial student feedback relating to the perceived value of the application for confidence in a high risk environment (i.e. operating theatre) and related clinical skills development. Further in-depth evaluation is ongoing with full results to be presented. Conclusion: MITIE C-Arm has a development role to play in the pre-clinical skills training for Medical Radiation Science students. It will augment their theoretical understanding prior to their clinical experience. References 1. Bridge P, Appleyard R, Ward J, Phillips R, Beavis A. The development and evaluation of a virtual radiotherapy treatment machine using an immersive visualisation environment. Computers and Education 2007; 49(2): 481–494. 2. Gunn T, Berry C, Bridge P et al. 3D Virtual Radiography: Development and Initial Feedback. Paper presented at the 10th Annual Scientific Meeting of Medical Imaging and Radiation Therapy, March 2013 Hobart, Tasmania.

Modified MLVA for genotyping Queensland invasive Streptococcus pneumoniae

Background Globally, over 800 000 children under five die each year from infectious diseases caused by Streptococcus pneumoniae. To understand genetic relatedness between isolates, study transmission routes, assess the impact of human interventions e.g. vaccines, and determine infection sources, genotyping methods are required. The ‘gold standard��� genotyping method, Multi-Locus Sequence Typing (MLST), is useful for long-term and global studies. Another genotyping method, Multi-Locus Variable Number of Tandem Repeat Analysis (MLVA), has emerged as a more discriminatory, inexpensive and faster technique; however there is no universally accepted method and it is currently suitable for short-term and localised epidemiology studies. Currently Australia has no national MLST database, nor has it adopted any MLVA method for short-term or localised studies. This study aims to improve S. pneumoniae genotyping methods by modifying the existing MLVA techniques to be more discriminatory, faster, cheaper and technically less demanding than previously published MLVA methods and MLST. Methods Four different MLVA protocols, including a modified method, were applied to 317 isolates of serotyped invasive S. pneumoniae isolated from sterile body sites of Queensland children under 15 years from 2007–2012. MLST was applied to 202 isolates for comparison. Results The modified MLVA4 is significantly more discriminatory than the ‘gold standard��� MLST method. MLVA4 has similar discrimination compared to other MLVA techniques in this study). The failure to amplify particular loci in previous MLVA methods were minimised in MLVA4. Failure to amplify BOX-13 and Spneu19 were found to be serotype specific. Conclusion We have modified a highly discriminatory MLVA technique for genotyping Queensland invasive S. pneumoniae. MLVA4 has the ability to enhance our understanding of the pneumococcal epidemiology and the changing genetics of the pneumococcus in localised and short-term studies.

Somewhere between haste and delay... Investigating the interactions of road users and pedestrians in a dynamic rail level crossing environment

There are currently 23,500 level crossings in Australia, broadly divided into one of two categories: active level crossings which are fully automatic and have boom barriers, alarm bells, flashing lights, and pedestrian gates; and passive level crossings, which are not automatic and aim to control road and pedestrianised walkways solely with stop and give way signs. Active level crossings are considered to be the gold standard for transport ergonomics when grade separation (i.e. constructing an over- or underpass) is not viable. In Australia, the current strategy is to annually upgrade passive level crossings with active controls but active crossings are also associated with traffic congestion, largely as a result of extended closure times. The percentage of time level crossings are closed to road vehicles during peak periods increases with the rise in the frequency of train services. The popular perception appears to be that once a level crossing is upgraded, one is free to wipe their hands and consider the job done. However, there may also be environments where active protection is not enough, but where the setting may not justify the capital costs of grade separation. Indeed, the associated congestion and traffic delay could compromise safety by contributing to the risk taking behaviour by motorists and pedestrians. In these environments it is important to understand what human factor issues are present and ask the question of whether a one size fits all solution is indeed the most ergonomically sound solution for today’s transport needs.

Development of a method to assess the quality of ankle joint reduction in 3D

This project developed a quantitative method for determining the quality of the surgical alignment of the bone fragments after an ankle fracture. The research examined the feasibility of utilising MRI-based bone models versus the gold standard CT-based bone models in order to reduce the amount of ionising radiation the patient is exposed to. In doing so, the thesis reports that there is potential for MRI to be used instead of CT depending on the scanning parameters used to obtain the medical images, the distance of the implant relative to the joint surface, and the implant material.

Supine to standing cobb angle change in idiopathic scoliosis: The effect of endplate preselection

INTRODUCTION Standing radiographs are the ‘gold standard��� for clinical assessment of adolescent idiopathic scoliosis (AIS), with the Cobb Angle used to measure the severity and progression of the scoliotic curve. Supine imaging modalities can provide valuable 3D information on scoliotic anatomy, however, due to changes in gravitational loading direction, the geometry of the spine alters between the supine and standing position which in turn affects the Cobb Angle measurement. Previous studies have consistently reported a 7-10° [1-3] Cobb Angle increase from supine to standing, however, none have reported the effect of endplate pre-selection and which (if any) curve parameters affect the supine to standing Cobb Angle difference. CONCLUSION There is a statistically significant relationship between supine to standing Cobb Angle change and fulcrum flexibility. Therefore, this difference can be considered a measure of spinal flexibility. Pre-selecting vertebral endplates causes only minor changes.

Five years of GWAS discovery

The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section. © 2012 The American Society of Human Genetics.

Are we waiting too long for the cardiovascular outcome trials with the glucagon-like peptide-1 receptor agonists?

Several new medicines are in development for the treatment of type 2 diabetes, and cardiovascular outcome trials are the gold standard for these medicines. This editorial demonstrates that despite being available for over 10 years, there are no cardiovascular outcome studies for any of the glucagon-like peptide-1 (GLP-1) receptor agonists, which demonstrate cardiovascular safety or benefit in subjects with high cardiovascular risk. The author argues that the FDA should be ensuring that clinical outcome studies for subjects with type 2 diabetes and high cardiovascular risk be undertaken in a timelier manner.

Spanish version of the screening Orebro Musculoskeletal Pain Questionnaire: A cross-cultural adaptation and validation

Background Spanish is one of the five most spoken languages in the world. There is currently no published Spanish version of the Örebro Musculoskeletal Pain Questionnaire (OMPQ). The aim of the present study is to describe the process of translating the OMPQ into Spanish and to perform an analysis of reliability, internal structure, internal consistency and concurrent criterion-related validity. Methods Design: Translation and psychometric testing. Procedure: Two independent translators translated the OMPQ into Spanish. From both translations a consensus version was achieved. A backward translation was made to verify and resolve any semantic or conceptual problems. A total of 104 patients (67 men/37 women) with a mean age of 53.48 (±11.63), suffering from chronic musculoskeletal disorders, twice completed a Spanish version of the OMPQ. Statistical analysis was performed to evaluate the reliability, the internal structure, internal consistency and concurrent criterion-related validity with reference to the gold standard questionnaire SF-12v2. Results All variables except “Coping” showed a rate above 0.85 on reliability. The internal structure calculation through exploratory factor analysis indicated that 75.2% of the variance can be explained with six components with an eigenvalue higher than 1 and 52.1% with only three components higher than 10% of variance explained. In the concurrent criterion-related validity, several significant correlations were seen close to 0.6, exceeding that value in the correlation between general health and total value of the OMPQ. Conclusions The Spanish version of the screening questionnaire OMPQ can be used to identify Spanish patients with musculoskeletal pain at risk of developing a chronic disability.

The dependence of computed tomography number to relative electron density conversion on phantom geometry and its impact on planned dose

A computed tomography number to relative electron density (CT-RED) calibration is performed when commissioning a radiotherapy CT scanner by imaging a calibration phantom with inserts of specified RED and recording the CT number displayed. In this work, CT-RED calibrations were generated using several commercially available phantoms to observe the effect of phantom geometry on conversion to electron density and, ultimately, the dose calculation in a treatment planning system. Using an anthropomorphic phantom as a gold standard, the CT number of a material was found to depend strongly on the amount and type of scattering material surrounding the volume of interest, with the largest variation observed for the highest density material tested, cortical bone. Cortical bone gave a maximum CT number difference of 1,110 when a cylindrical insert of diameter 28 mm scanned free in air was compared to that in the form of a 30 × 30 cm2 slab. The effect of using each CT-RED calibration on planned dose to a patient was quantified using a commercially available treatment planning system. When all calibrations were compared to the anthropomorphic calibration, the largest percentage dose difference was 4.2 % which occurred when the CT-RED calibration curve was acquired with heterogeneity inserts removed from the phantom and scanned free in air. The maximum dose difference observed between two dedicated CT-RED phantoms was ±2.1 %. A phantom that is to be used for CT-RED calibrations must have sufficient water equivalent scattering material surrounding the heterogeneous objects that are to be used for calibration.

Long-term effect of childhood liver transplantation on body cell mass

Malnutrition is common in end-stage liver disease, but a correction after transplantation is expected. Body cell mass (BCM) assessment using total body potassium (TBK) measurements is considered the gold standard for assessing nutritional status. The aim of this study was to examine the BCM and, therefore, nutritional status of long-term survivors after childhood liver transplantation. © 2014 American Association for the Study of Liver Diseases.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Cognitive deficits and the Paced Auditory Serial Addition Test performance among patients with multiple sclerosis

Multiple sclerosis (MS) is a chronic, inflammatory disease of the central nervous system, characterized especially by myelin and axon damage. Cognitive impairment in MS is common but difficult to detect without a neuropsychological examination. Valid and reliable methods are needed in clinical practice and research to detect deficits, follow their natural evolution, and verify treatment effects. The Paced Auditory Serial Addition Test (PASAT) is a measure of sustained and divided attention, working memory, and information processing speed, and it is widely used in MS patients neuropsychological evaluation. Additionally, the PASAT is the sole cognitive measure in an assessment tool primarly designed for MS clinical trials, the Multiple Sclerosis Functional Composite (MSFC). The aims of the present study were to determine a) the frequency, characteristics, and evolution of cognitive impairment among relapsing-remitting MS patients, and b) the validity and reliability of the PASAT in measuring cognitive performance in MS patients. The subjects were 45 relapsing-remitting MS patients from Seinäjoki Central Hospital, Department of Neurology and 48 healthy controls. Both groups underwent comprehensive neuropsychological assessments, including the PASAT, twice in a one-year follow-up, and additionally a sample of 10 patients and controls were evaluated with the PASAT in serial assessments five times in one month. The frequency of cognitive dysfunction among relapsing-remitting MS patients in the present study was 42%. Impairments were characterized especially by slowed information processing speed and memory deficits. During the one-year follow-up, the cognitive performance was relatively stable among MS patients on a group level. However, the practice effects in cognitive tests were less pronounced among MS patients than healthy controls. At an individual level the spectrum of MS patients cognitive deficits was wide in regards to their characteristics, severity, and evolution. The PASAT was moderately accurate in detecting MS-associated cognitive impairment, and 69% of patients were correctly classified as cognitively impaired or unimpaired when comprehensive neuropsychological assessment was used as a "gold standard". Self-reported nervousness and poor arithmetical skills seemed to explain misclassifications. MS-related fatigue was objectively demonstrated as fading performance towards the end of the test. Despite the observed practice effect, the reliability of the PASAT was excellent, and it was sensitive to the cognitive decline taking place during the follow-up in a subgroup of patients. The PASAT can be recommended for use in the neuropsychological assessment of MS patients. The test is fairly sensitive, but less specific; consequently, the reasons for low scores have to be carefully identified before interpreting them as clinically significant.

Small nerve fiber quantification in the diagnosis of diabetic sensorimotor polyneuropathy: Comparing corneal confocal microscopy with intraepidermal nerve fiber density

OBJECTIVE Quantitative assessment of small fiber damage is key to the early diagnosis and assessment of progression or regression of diabetic sensorimotor polyneuropathy (DSPN). Intraepidermal nerve fiber density (IENFD) is the current gold standard, but corneal confocal microscopy (CCM), an in vivo ophthalmic imaging modality, has the potential to be a noninvasive and objective image biomarker for identifying small fiber damage. The purpose of this study was to determine the diagnostic performance of CCM and IENFD by using the current guidelines as the reference standard. RESEARCH DESIGN AND METHODS Eighty-nine subjects (26 control subjects and 63 patients with type 1 diabetes), with and without DSPN, underwent a detailed assessment of neuropathy, including CCM and skin biopsy. RESULTS Manual and automated corneal nerve fiber density (CNFD) (P < 0.0001), branch density (CNBD) (P < 0.0001) and length (CNFL) (P < 0.0001), and IENFD (P < 0.001) were significantly reduced in patients with diabetes with DSPN compared with control subjects. The area under the receiver operating characteristic curve for identifying DSPN was 0.82 for manual CNFD, 0.80 for automated CNFD, and 0.66 for IENFD, which did not differ significantly (P = 0.14). CONCLUSIONS This study shows comparable diagnostic efficiency between CCM and IENFD, providing further support for the clinical utility of CCM as a surrogate end point for DSPN.