Drivers for renewal and reform of contemporary nursing curricula: A blueprint for change

The creation of a curriculum blueprint appropriate to the development of a professional nurse who is practice-ready for the current and future context of health service delivery must take account of the extant context as well as an unpredictable and sometimes ambiguous future. The curriculum renewal process itself ought to challenge existing long held ideals, practices, and sacred cows within the health and higher education sectors. There is much to consider and importantly curriculum developers need to be mindful of reform within the health sector and health workforce education, as well as the concomitant vision and requirements of the nursing profession. Curriculum must develop more than discipline knowledge and skills: it must provide an infrastructure for generic abilities both social and intellectual in order to better prepare students for the registered nurse role. This paper discusses a number of forces that are essential to consider in curriculum development in undergraduate nursing education. © eContent Management Pty Ltd

Ordering folate assays is no longer justified for investigation of anemias, in folic acid fortified countries

<p>Abstract</p> <p>Background</p> <p>Since 1998, in the countries where there is mandatory fortification of grain products with folic acid, folate deficiency has become very rare. Consequently, we decided to find out whether there is any justification for ordering folate assays for investigation of anemias.</p> <p>Methods</p> <p>We reviewed serum folate (SF) and red cell folate (RF) data at two teaching hospitals in Canada. At the Health Sciences Centre (HSC) the folate data for the year 2001 were analyzed and the medical records of those with low SF or low RF were reviewed. At St. Boniface General Hospital(SBGH)all folate data between January 1996 and Dec 31,2004 were analyzed and the medical records of all who had low RF between January 1,1999 and December 31,2004 were reviewed.</p> <p>Results</p> <p>In 2001, at HSC, 11 out of 2154(0.5%)SF were low(<7.0 nmol/L) and 4 out of 560 (0.7%) RF were low (<417 nmol/L). In no subject with low SF or RF could the anemia be attributed to folate deficiency. At SBGH during the 3-year-period of 1999-2001, 19 out of 991(1.9%) had low RF (<225 nmol/L) but in only 2 patients (0.2%) the low RF was in folate deficiency anemia range; but neither of them had anemia.</p> <p>Conclusion</p> <p>In countries where there is mandatory fortification of grain products with folic acid, folate deficiency to the degree that could cause anemia is extremely rare. Ordering folate assays for investigation of anemias, in these countries, is waste of time and money. The result of these tests is more likely to mislead the physicians than to provide any useful information.</p

Identification and validation of oncologic miRNA biomarkers for Luminal A-like breast cancer

Introduction: Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting. Methods: Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n=54) and controls (n=56). RNA was extracted, reverse transcribed and subjected to microarray analysis (n=10 Luminal A-like; n=10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n=44 Luminal A; n=46 Control) and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated. Results: Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis ( miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652 ). The biomarker potential of 4 miRNAs ( miR-29a, miR-181a , miR-223 and miR-652 ) was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p=0.001, 0.004, 0.009 and 0.004 respectively). Binary logistic regression confirmed that combination of 3 of these miRNAs ( miR-29a, miR-181a and miR-652 ) could reliably differentiate between cancers and controls with an AUC of 0.80. Conclusion: This study provides insight into the underlying molecular portrait of Luminal A-like breast cancer subtype. From an initial 76 miRNAs, 4 were validated with altered expression in the blood of women with Luminal A-like breast cancer. The expression profiles of these 3 miRNAs, in combination with mammography, has potential to facilitate accurate subtype- specific breast tumor detection

Improving the prediction of disease-related variants using protein three-dimensional structure

Background: Single Nucleotide Polymorphisms (SNPs) are an important source of human genome variability. Non-synonymous SNPs occurring in coding regions result in single amino acid polymorphisms (SAPs) that may affect protein function and lead to pathology. Several methods attempt to estimate the impact of SAPs using different sources of information. Although sequence-based predictors have shown good performance, the quality of these predictions can be further improved by introducing new features derived from three-dimensional protein structures.Results: In this paper, we present a structure-based machine learning approach for predicting disease-related SAPs. We have trained a Support Vector Machine (SVM) on a set of 3,342 disease-related mutations and 1,644 neutral polymorphisms from 784 protein chains. We use SVM input features derived from the protein's sequence, structure, and function. After dataset balancing, the structure-based method (SVM-3D) reaches an overall accuracy of 85%, a correlation coefficient of 0.70, and an area under the receiving operating characteristic curve (AUC) of 0.92. When compared with a similar sequence-based predictor, SVM-3D results in an increase of the overall accuracy and AUC by 3%, and correlation coefficient by 0.06. The robustness of this improvement has been tested on different datasets and in all the cases SVM-3D performs better than previously developed methods even when compared with PolyPhen2, which explicitly considers in input protein structure information.Conclusion: This work demonstrates that structural information can increase the accuracy of disease-related SAPs identification. Our results also quantify the magnitude of improvement on a large dataset. This improvement is in agreement with previously observed results, where structure information enhanced the prediction of protein stability changes upon mutation. Although the structural information contained in the Protein Data Bank is limiting the application and the performance of our structure-based method, we expect that SVM-3D will result in higher accuracy when more structural date become available. \ua9 2011 Capriotti; licensee BioMed Central Ltd

Prime movers : mechanochemistry of mitotic kinesins

Mitotic spindles are self-organizing protein machines that harness teams of multiple force generators to drive chromosome segregation. Kinesins are key members of these force-generating teams. Different kinesins walk directionally along dynamic microtubules, anchor, crosslink, align and sort microtubules into polarized bundles, and influence microtubule dynamics by interacting with microtubule tips. The mechanochemical mechanisms of these kinesins are specialized to enable each type to make a specific contribution to spindle self-organization and chromosome segregation

Stress-Induced Reinstatement of Drug Seeking: 20 Years of Progress

In human addicts, drug relapse and craving are often provoked by stress. Since 1995, this clinical scenario has been studied using a rat model of stress-induced reinstatement of drug seeking. Here, we first discuss the generality of stress-induced reinstatement to different drugs of abuse, different stressors, and different behavioral procedures. We also discuss neuropharmacological mechanisms, and brain areas and circuits controlling stress-induced reinstatement of drug seeking. We conclude by discussing results from translational human laboratory studies and clinical trials that were inspired by results from rat studies on stress-induced reinstatement. Our main conclusions are (1) The phenomenon of stress-induced reinstatement, first shown with an intermittent footshock stressor in rats trained to self-administer heroin, generalizes to other abused drugs, including cocaine, methamphetamine, nicotine, and alcohol, and is also observed in the conditioned place preference model in rats and mice. This phenomenon, however, is stressor specific and not all stressors induce reinstatement of drug seeking. (2) Neuropharmacological studies indicate the involvement of corticotropin-releasing factor (CRF), noradrenaline, dopamine, glutamate, kappa/dynorphin, and several other peptide and neurotransmitter systems in stress-induced reinstatement. Neuropharmacology and circuitry studies indicate the involvement of CRF and noradrenaline transmission in bed nucleus of stria terminalis and central amygdala, and dopamine, CRF, kappa/dynorphin, and glutamate transmission in other components of the mesocorticolimbic dopamine system (ventral tegmental area, medial prefrontal cortex, orbitofrontal cortex, and nucleus accumbens). (3) Translational human laboratory studies and a recent clinical trial study show the efficacy of alpha-2 adrenoceptor agonists in decreasing stress-induced drug craving and stress-induced initial heroin lapse

Efficient Attribute-Based Signatures for Unbounded Arithmetic Branching Programs

This paper presents the first attribute-based signature (ABS) scheme in which the correspondence between signers and signatures is captured in an arithmetic model of computation. Specifically, we design a fully secure, i.e., adaptively unforgeable and perfectly signer-private ABS scheme for signing policies realizable by arithmetic branching programs (ABP), which are a quite expressive model of arithmetic computations. On a more positive note, the proposed scheme places no bound on the size and input length of the supported signing policy ABP’s, and at the same time, supports the use of an input attribute for an arbitrary number of times inside a signing policy ABP, i.e., the so called unbounded multi-use of attributes. The size of our public parameters is constant with respect to the sizes of the signing attribute vectors and signing policies available in the system. The construction is built in (asymmetric) bilinear groups of prime order, and its unforgeability is derived in the standard model under (asymmetric version of) the well-studied decisional linear (DLIN) assumption coupled with the existence of standard collision resistant hash functions. Due to the use of the arithmetic model as opposed to the boolean one, our ABS scheme not only excels significantly over the existing state-of-the-art constructions in terms of concrete efficiency, but also achieves improved applicability in various practical scenarios. Our principal technical contributions are (a) extending the techniques of Okamoto and Takashima [PKC 2011, PKC 2013], which were originally developed in the context of boolean span programs, to the arithmetic setting; and (b) innovating new ideas to allow unbounded multi-use of attributes inside ABP’s, which themselves are of unbounded size and input length

Quantifying the Evolution of Vascular Barrier Disruption in Advanced Atherosclerosis with Semipermeant Nanoparticle Contrast Agents

Acute atherothrombotic occlusion in heart attack and stroke implies disruption of the vascular endothelial barrier that exposes a highly procoagulant intimal milieu. However, the evolution, severity, and pathophysiological consequences of vascular barrier damage in atherosclerotic plaque remain unknown, in part because quantifiable methods and experimental models are lacking for its in vivo assessment.To develop quantitative nondestructive methodologies and models for detecting vascular barrier disruption in advanced plaques.Sustained hypercholesterolemia in New Zealand White (NZW) rabbits for >7-14 months engendered endothelial barrier disruption that was evident from massive and rapid passive penetration and intimal trapping of perfluorocarbon-core nanoparticles (PFC-NP: ∼250 nm diameter) after in vivo circulation for as little as 1 hour. Only older plaques (>7 mo), but not younger plaques (<3 mo) demonstrated the marked enhancement of endothelial permeability to these particles. Electron microscopy revealed a complex of subintimal spongiform channels associated with endothelial apoptosis, superficial erosions, and surface-penetrating cholesterol crystals. Fluorine ((19)F) magnetic resonance imaging and spectroscopy (MRI/MRS) enabled absolute quantification (in nanoMolar) of the passive permeation of PFC-NP into the disrupted vascular lesions by sensing the unique spectral signatures from the fluorine core of plaque-bound PFC-NP.The application of semipermeant nanoparticles reveals the presence of profound barrier disruption in later stage plaques and focuses attention on the disrupted endothelium as a potential contributor to plaque vulnerability. The response to sustained high cholesterol levels yields a progressive deterioration of the vascular barrier that can be quantified with fluorine MRI/MRS of passively permeable nanostructures. The possibility of plaque classification based on the metric of endothelial permeability to nanoparticles is suggested