Philadelphia-Negative Classical Myeloproliferative Neoplasms: Critical Concepts and Management Recommendations From European LeukemiaNet

We present a review of critical concepts and produce recommendations on the management of Philadelphia-negative classical myeloproliferative neoplasms, including monitoring, response definition, first-and second-line therapy, and therapy for special issues. Key questions were selected according the criterion of clinical relevance. Statements were produced using a Delphi process, and two consensus conferences involving a panel of 21 experts appointed by the European LeukemiaNet (ELN) were convened. Patients with polycythemia vera (PV) and essential thrombocythemia (ET) should be defined as high risk if age is greater than 60 years or there is a history of previous thrombosis. Risk stratification in primary myelofibrosis (PMF) should start with the International Prognostic Scoring System (IPSS) for newly diagnosed patients and dynamic IPSS for patients being seen during their disease course, with the addition of cytogenetics evaluation and transfusion status. High-risk patients with PV should be managed with phlebotomy, low-dose aspirin, and cytoreduction, with either hydroxyurea or interferon at any age. High-risk patients with ET should be managed with cytoreduction, using hydroxyurea at any age. Monitoring response in PV and ET should use the ELN clinicohematologic criteria. Corticosteroids, androgens, erythropoiesis-stimulating agents, and immunomodulators are recommended to treat anemia of PMF, whereas hydroxyurea is the first-line treatment of PMF-associated splenomegaly. Indications for splenectomy include symptomatic portal hypertension, drug-refractory painful splenomegaly, and frequent RBC transfusions. The risk of allogeneic stem-cell transplantation-related complications is justified in transplantation-eligible patients whose median survival time is expected to be less than 5 years.

The Paediatric Rheumatology International Trials Organisation provisional criteria for the evaluation of response to therapy in juvenile dermatomyositis.

Objective To develop a provisional definition for the evaluation of response to therapy in juvenile dermatomyositis (DM) based on the Paediatric Rheumatology International Trials Organisation juvenile DM core set of variables. Methods Thirty-seven experienced pediatric rheumatologists from 27 countries achieved consensus on 128 difficult patient profiles as clinically improved or not improved using a stepwise approach (patient's rating, statistical analysis, definition selection). Using the physicians' consensus ratings as the “gold standard measure,” chi-square, sensitivity, specificity, false-positive and-negative rates, area under the receiver operating characteristic curve, and kappa agreement for candidate definitions of improvement were calculated. Definitions with kappa values >0.8 were multiplied by the face validity score to select the top definitions. Results The top definition of improvement was at least 20% improvement from baseline in 3 of 6 core set variables with no more than 1 of the remaining worsening by more than 30%, which cannot be muscle strength. The second-highest scoring definition was at least 20% improvement from baseline in 3 of 6 core set variables with no more than 2 of the remaining worsening by more than 25%, which cannot be muscle strength (definition P1 selected by the International Myositis Assessment and Clinical Studies group). The third is similar to the second with the maximum amount of worsening set to 30%. This indicates convergent validity of the process. Conclusion We propose a provisional data-driven definition of improvement that reflects well the consensus rating of experienced clinicians, which incorporates clinically meaningful change in core set variables in a composite end point for the evaluation of global response to therapy in juvenile DM.

Measuring inconsistency in network intrusion rules

In this preliminary case study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. Finally, we measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. We conclude that such measures are useful for the network intrusion domain assuming that incorporating domain knowledge for correlation of rules is feasible.

Factor structure and validity of the Alcohol Use Disorders Identification Test (AUDIT) in a sample of mentally disordered offenders

Investigations of the factor structure of the Alcohol Use Disorders Identification Test (AUDIT) have produced conflicting results. The current study assessed the factor structure of the AUDIT for a group of Mentally Disordered Offenders (MDOs) and examined the pattern of scoring in specific subgroups. The sample comprised 2005 MDOs who completed a battery of tests including the AUDIT. Confirmatory factor analyses revealed that a two-factor solution – alcohol consumption and alcohol-related consequences – provided the best data fit for AUDIT scores. A three-factor solution provided an equally good fit, but the second and third factors were highly correlated and a measure of parsimony also favoured the two-factor solution. This study provides useful information on the factor structure of the AUDIT amongst a large MDO population, while also highlighting the difficulties associated with the presence of people with mental health problems in the criminal justice system.

Measuring Inconsistency in a Network Intrusion Detection Rule Set Based on Snort

In this preliminary study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which are based on Snort and incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. We measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. Finally, we propose a new measure of inconsistency for prioritized knowledge which incorporates the normalized number of atoms in a language involved in inconsistency to provide a deeper inspection of inconsistent formulae. We conclude that such measures are useful for the network intrusion domain assuming that introducing expert knowledge for correlation of rules is feasible.

Development of a risk model for adverse drug events in the elderly

The aim of this study was to develop a predictive model for adverse drug events (ADEs) in elderly patients. Socio-demographic and medical data were collected from chart reviews, computerised information and a patient interview, for a population of 929 elderly patients (aged greater than or equal to 65 years) whose admission to the Waveney/B raid Valley Hospital in Northern Ireland was not scheduled. A further 204 patients formed a validation group. An ADE score was assigned to each patient using a modified Naranjo algorithm scoring system. The ADE scores ranged from 0 to 8. For the purposes of developing a risk model, scores of 4 or more were considered to constitute a high risk of an ADE.

An Examination of Volunteer Motivation in Credit Unions: Informing Volunteer Resource Management

Volunteer recruitment and retention is a problem that most credit unions experience. Research suggests that knowledge of volunteer motivation can inform volunteer management strategies. This paper uses a survey approach to determine whether current volunteers in credit unions in Northern Ireland are more motivated by the actual act of volunteering, by the output from the volunteering activity (including altruism) or because the volunteering activity increases their human capital value. Altruistic reasons are found to be the most influential, with the act of volunteering also scoring highly. This knowledge should inform volunteer recruitment programmes and internal appraisal processes as management can reinforce messages that provide positive feedback to volunteers on the social benefits being achieved by the credit union. This will further motivate current volunteers, ensuring retention. When motivation was analyzed by volunteer characteristics we found that older volunteers, retired volunteers and volunteers who are less educated are more motivated in their role. There was little evidence that individuals volunteer to improve their human capital worth.

Dense pixel matching between unrectified and distorted images using dynamic programming

In this paper, a novel framework for dense pixel matching based on dynamic programming is introduced. Unlike most techniques proposed in the literature, our approach assumes neither known camera geometry nor the availability of rectified images. Under such conditions, the matching task cannot be reduced to finding correspondences between a pair of scanlines. We propose to extend existing dynamic programming methodologies to a larger dimensional space by using a 3D scoring matrix so that correspondences between a line and a whole image can be calculated. After assessing our framework on a standard evaluation dataset of rectified stereo images, experiments are conducted on unrectified and non-linearly distorted images. Results validate our new approach and reveal the versatility of our algorithm.

Computational identification of self-inhibitory peptides from envelope proteins

Fusion process is known to be the initial step of viral infection and hence targeting the entry process is a promising strategy to design antiviral therapy. The self-inhibitory peptides derived from the enveloped (E) proteins function to inhibit the proteinprotein interactions in the membrane fusion step mediated by the viral E protein. Thus, they have the potential to be developed into effective antiviral therapy. Herein, we have developed a Monte Carlo-based computational method with the aim to identify and optimize potential peptide hits from the E proteins. The stability of the peptides, which indicates their potential to bind in situ to the E proteins, was evaluated by two different scoring functions, dipolar distance-scaled, finite, ideal-gas reference state and residue-specific all-atom probability discriminatory function. The method was applied to a-helical Class I HIV-1 gp41, beta-sheet Class II Dengue virus (DENV) type 2 E proteins, as well as Class III Herpes Simplex virus-1 (HSV-1) glycoprotein, a E protein with a mixture of a-helix and beta-sheet structural fold. The peptide hits identified are in line with the druggable regions where the self-inhibitory peptide inhibitors for the three classes of viral fusion proteins were derived. Several novel peptides were identified from either the hydrophobic regions or the functionally important regions on Class II DENV-2 E protein and Class III HSV-1 gB. They have potential to disrupt the proteinprotein interaction in the fusion process and may serve as starting points for the development of novel inhibitors for viral E proteins. 

Cellular senescence induced by aberrant MAD2 levels impacts on paclitaxel responsiveness in vitro

BACKGROUND: The mitotic arrest deficiency protein 2 (MAD2) is a key component of the mitotic spindle assembly checkpoint, monitoring accurate chromosomal alignment at the metaphase plate before mitosis. MAD2 also has a function in cellular senescence and in a cell’s response to microtubule inhibitory (MI) chemotherapy exemplified by paclitaxel.
METHODS: Using an siRNA approach, the impact of MAD2 down-regulation on cellular senescence and paclitaxel responsiveness was investigated. The endpoints of senescence, cell viability, migration, cytokine expression, cell cycle analysis and anaphase bridge scoring were carried out using standard approaches.
RESULTS: We show that MAD2 down-regulation induces premature senescence in the MCF7 breast epithelial cancer cell line. These MAD2-depleted (MAD2k) cells are also significantly replicative incompetent but retain viability. Moreover, they show significantly higher levels of anaphase bridges and polyploidy compared to controls. In addition, these cells secrete higher levels of IL-6 and IL-8
representing key components of the senescence-associated secretory phenotype (SASP) with the ability to impact on neighbouring cells. In support of this, MAD2kcells show enhanced migratory ability. At 72 h after paclitaxel, MAD2kcells show a significant further induction of senescence compared with paclitaxel naive controls. In addition, there are significantly more viable cells in the MAD2k MCF7 cell line after paclitaxel reflecting the observed increase in senescence.
CONCLUSION: Considering that paclitaxel targets actively dividing cells, these senescent cells will evade cytotoxic kill. In conclusion, compromised MAD2 levels induce a population of senescent cells resistant to paclitaxel.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

Bending It Like Beckham: How to Visually Fool the Goalkeeper

Background: As bending free-kicks becomes the norm in modern day soccer, implications for goalkeepers have largely been ignored. Although it has been reported that poor sensitivity to visual acceleration makes it harder for expert goalkeepers to perceptually judge where the curved free-kicks will cross the goal line, it is unknown how this affects the goalkeeper's actual movements.

Methodology/Principal Findings: Here, an in-depth analysis of goalkeepers' hand movements in immersive, interactive virtual reality shows that they do not fully account for spin-induced lateral ball acceleration. Hand movements were found to be biased in the direction of initial ball heading, and for curved free-kicks this resulted in biases in a direction opposite to those necessary to save the free-kick. These movement errors result in less time to cover a now greater distance to stop the ball entering the goal. These and other details of the interceptive behaviour are explained using a simple mathematical model which shows how the goalkeeper controls his movements online with respect to the ball's current heading direction. Furthermore our results and model suggest how visual landmarks, such as the goalposts in this instance, may constrain the extent of the movement biases.

Conclusions: While it has previously been shown that humans can internalize the effects of gravitational acceleration, these results show that it is much more difficult for goalkeepers to account for spin-induced visual acceleration, which varies from situation to situation. The limited sensitivity of the human visual system for detecting acceleration, suggests that curved free-kicks are an important goal-scoring opportunity in the game of soccer.

Awarding global grades in OSCEs: Evaluation of a novel eLearning resource for OSCE examiners

BACKGROUND:
A novel online resource has been developed to aid OSCE examiner training comprising a series of videos of OSCE performances that allow inter-examiner comparison of global grade decisions.

AIMS:
To evaluate this training resource in terms of usefulness and ability to improve examiner confidence in awarding global grades in OSCEs.

METHOD:
Data collected from the first 200 users included global grades awarded, willingness to change grades following peer comparison and confidence in awarding grades before and after training.

RESULTS:
Most (86.5%) agreed that the resource was useful in developing global grade scoring ability in OSCEs, with a significant improvement in confidence in awarding grades after using the training package (p<0.001).

CONCLUSIONS:
This is a useful and effective online training package. As an adjunct to traditional training it offers a practical solution to the problem of availability of examiners.

Predicting IQ of biologically "at risk" children from age 3 to school entry:sensitivity and specificity of the Stanford-Binet Intelligence Scale IV

Predictive validity of the Stanford-Binet Intelligence Scale Fourth Edition (S-B IV) from age 3 years to ages 4-5 years was evaluated with biologically "at risk" children without major sensory or motor impairments (n = 236). Using the standard scoring, children with full scale IQ <or = 84 on the Wechsler Preschool and Primary Scale of Intelligence at age 4-5 years were poorly identified (sensitivity 54%) from the composite S-B IV score at age 3. However, sensitivity improved greatly to 78% by including as a predictor the number of subtests the child was actually able to perform at age 3 years. Measures from the Home Screening Questionnaire and ratings of mother-child interaction further improved sensitivity to 83%. The standard method for calculating the composite score on the S-B IV excludes subtests with a raw score of 0, which overestimates cognitive functioning in young biologically high risk children. Accuracy of early identification was improved significantly by considering the number of subtests the child did not perform at age 3 years.

Behavior problems in children requiring inpatient rehabilitation treatment for asthma

Forty-eight asthmatic children (age 6-16 years), inpatients at the Hugh McMillan Medical Centre, were rated by their parents on their behavior using Achenbach's Child Behaviour Checklist. Completed checklists were used to determine normalized T scores for behavior syndromes, and these were compared against norms for clinically referred and nonreferred children. Behavior problems were elevated compared with nonreferred children for both boys and girls, with boys scoring at a clinical level. While many behavior problems were recognized, somatic complaints was a prominent syndrome, particularly for those in the 6-11-year age group.