'Kids sold, desperate moms need cash': Media representations of Zimbabwean women migrants

The article draws on 575 randomly selected articles from the South African Media database to explore the representation of Zimbabwean women migrants. Using critical discourse analysis (CDA), the article shows that some of the dominant construction types depict a picture of caricatured, stereotypical and stigmatised Zimbabwean migrant women without voice and individuality. In turn, the diversity of their actualities is not captured in the process of constructing the twin images of Zimbabwean women as victims and as purveyors of decadent and other negative social ills in society. We conclude that Zimbabwean women migrants appear in the SA media primarily in three negative images: suppliers of sexual services, as un-motherly, and as victims. We also conclude that there is need for media to capture the voices of migrant women recounting their everyday lived experiences in different political and socio-economic contexts in order to account for the migrant women's voices of resilience, defiance and victimhood and of agency, against the normalising and marginalising influences of political institutions and national border controls. This would also help capture the transformative nature of migration to the women, the 'home' in Zimbabwe and the 'home' in South Africa.IS

Prediction of grip and key pinch strength in 978 healthy subjects

<p>Abstract</p> <p>Background</p> <p>Hand strength is an important independent surrogate parameter to assess outcome and risk of morbidity and mortality. This study aimed to determine the predictive power of cofactors and to predict population-based normative grip and pinch strength.</p> <p>Methods</p> <p>A representative population survey was used as the basis for prediction analyses (n = 978). Bivariate relationships between grip/pinch strengths of the dominate hand were explored by means of all relevant mathematical functions to maximize prediction. The resulting best functions were combined into a multivariate regression.</p> <p>Results</p> <p>Polynoms (up to the third degree) were the best predictive functions. On the bivariate level, height was best correlated to grip (46.2% explained variance) and pinch strength (37.7% explained variance) in a linear relationship, followed by sex, age, weight, and occupational demand on the hand. Multivariate regression provided predicted values close to the empirical ones explaining 76.6% of the variance for grip strength and 67.7% for pinch strength.</p> <p>Conclusion</p> <p>The five easy-to-measure cofactors sex, age, body height, categorized occupational demand on the hand, and body weight provide a highly accurate prediction of normative grip and pinch strength.</p

The Spin Structure of the Nucleon

We present an overview of recent experimental and theoretical advances in our understanding of the spin structure of protons and neutrons.Comment: 84 pages, 29 figure

Feasibility of Prehospital Teleconsultation in Acute Stroke – A Pilot Study in Clinical Routine

BACKGROUND: Inter-hospital teleconsultation improves stroke care. To transfer this concept into the emergency medical service (EMS), the feasibility and effects of prehospital teleconsultation were investigated. METHODOLOGY/PRINCIPAL FINDINGS: Teleconsultation enabling audio communication, real-time video streaming, vital data and still picture transmission was conducted between an ambulance and a teleconsultation center. Pre-notification of the hospital was carried out with a 14-item stroke history checklist via e-mail-to-fax. Beside technical assessments possible influences on prehospital and initial in-hospital time intervals, prehospital diagnostic accuracy and the transfer of stroke specific data were investigated by comparing telemedically assisted prehospital care (telemedicine group) with local regular EMS care (control group). All prehospital stroke patients over a 5-month period were included during weekdays (7.30 a.m.-4.00 p.m.). In 3 of 18 missions partial dropouts of the system occurred; neurological co-evaluation via video transmission was conducted in 12 cases. The stroke checklist was transmitted in 14 cases (78%). Telemedicine group (n = 18) vs. control group (n = 47): Prehospital time intervals were comparable, but in both groups the door to brain imaging times were longer than recommended (median 59.5 vs. 57.5 min, p = 0.6447). The prehospital stroke diagnosis was confirmed in 61% vs. 67%, p = 0.8451. Medians of 14 (IQR 9) vs. 5 (IQR 2) stroke specific items were transferred in written form to the in-hospital setting, p<0.0001. In 3 of 10 vs. 5 of 27 patients with cerebral ischemia thrombolytics were administered, p = 0.655. CONCLUSIONS: Teleconsultation was feasible but technical performance and reliability have to be improved. The approach led to better stroke specific information; however, a superiority over regular EMS care was not found and in-hospital time intervals were unacceptably long in both groups. The feasibility of prehospital tele-stroke consultation has future potential to improve emergency care especially when no highly trained personnel are on-scene. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number Register (ISRCTN) ISRCTN83270177

Effective Stimuli for Constructing Reliable Neuron Models

The rich dynamical nature of neurons poses major conceptual and technical challenges for unraveling their nonlinear membrane properties. Traditionally, various current waveforms have been injected at the soma to probe neuron dynamics, but the rationale for selecting specific stimuli has never been rigorously justified. The present experimental and theoretical study proposes a novel framework, inspired by learning theory, for objectively selecting the stimuli that best unravel the neuron's dynamics. The efficacy of stimuli is assessed in terms of their ability to constrain the parameter space of biophysically detailed conductance-based models that faithfully replicate the neuron's dynamics as attested by their ability to generalize well to the neuron's response to novel experimental stimuli. We used this framework to evaluate a variety of stimuli in different types of cortical neurons, ages and animals. Despite their simplicity, a set of stimuli consisting of step and ramp current pulses outperforms synaptic-like noisy stimuli in revealing the dynamics of these neurons. The general framework that we propose paves a new way for defining, evaluating and standardizing effective electrical probing of neurons and will thus lay the foundation for a much deeper understanding of the electrical nature of these highly sophisticated and non-linear devices and of the neuronal networks that they compose

Chemokines cooperate with TNF to provide protective anti-viral immunity and to enhance inflammation

The role of cytokines and chemokines in anti-viral defense has been demonstrated, but their relative contribution to protective anti-viral responses in vivo is not fully understood. Cytokine response modifier D (CrmD) is a secreted receptor for TNF and lymphotoxin containing the smallpox virus-encoded chemokine receptor (SECRET) domain and is expressed by ectromelia virus, the causative agent of the smallpox-like disease mousepox. Here we show that CrmD is an essential virulence factor that controls natural killer cell activation and allows progression of fatal mousepox, and demonstrate that both SECRET and TNF binding domains are required for full CrmD activity. Vaccination with recombinant CrmD protects animals from lethal mousepox. These results indicate that a specific set of chemokines enhance the inflammatory and protective anti-viral responses mediated by TNF and lymphotoxin, and illustrate how viruses optimize anti-TNF strategies with the addition of a chemokine binding domain as soluble decoy receptors.We thank Javier Salguero for help with animal experimentation and immunohistochemistry, Rocío Martín and Carolina Sánchez for technical assistance and Daniel Rubio for discussions on the project. This work was funded by Grants from the Spanish Ministry of Economy and Competitiviness and European Union (European Regional Development’s Funds, FEDER) (grant SAF2015-67485-R), and the Wellcome Trust (grant 051087/Z97/Z). M.B.R.-A. and A. Alejo were recipients of a Ramón y Cajal Contract from the Spanish Ministry of Science and Innovation

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice