2,946 research outputs found
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If you donāt gel with prisoners, then it affects how they use the servicesā: a preliminary investigation of the importance of relationships in promoting engagement with prison-based resettlement interventions
The Potential for Student Performance Prediction in Small Cohorts with Minimal Available Attributes
The measurement of student performance during their progress through university study provides academic leadership with critical information on each studentās likelihood of success. Academics have traditionally used their interactions with individual students through class activities and interim assessments to identify those āat riskā of failure/withdrawal. However, modern university environments, offering easy on-line availability of course material, may see reduced lecture/tutorial attendance, making such identification more challenging. Modern data mining and machine learning techniques provide increasingly accurate predictions of student examination assessment marks, although these approaches have focussed upon large student populations and wide ranges of data attributes per student. However, many university modules comprise relatively small student cohorts, with institutional protocols limiting the student attributes available for analysis. It appears that very little research attention has been devoted to this area of analysis and prediction. We describe an experiment conducted on a final-year university module student cohort of 23, where individual student data are limited to lecture/tutorial attendance, virtual learning environment accesses and intermediate assessments. We found potential for predicting individual student interim and final assessment marks in small student cohorts with very limited attributes and that these predictions could be useful to support module leaders in identifying students potentially āat risk.ā.Peer reviewe
Ketogenic diet improves behaviors in a maternal immune activation model of autism spectrum disorder
Prenatal factors influence autism spectrum disorder (ASD) incidence in children and can increase ASD symptoms in offspring of animal models. These may include maternal immune activation (MIA) due to viral or bacterial infection during the first trimesters. Unfortunately, regardless of ASD etiology, existing drugs are poorly effective against core symptoms. For nearly a century a ketogenic diet (KD) has been used to treat seizures, and recent insights into mechanisms of ASD and a growing recognition that immune/inflammatory conditions exacerbate ASD risk has increased interest in KD as a treatment for ASD. Here we studied the effects of KD on core ASD symptoms in offspring exposed to MIA. To produce MIA, pregnant C57Bl/6 mice were injected with the viral mimic polyinosinic-polycytidylic acid; after weaning offspring were fed KD or control diet for three weeks. Consistent with an ASD phenotype of a higher incidence in males, control diet-fed MIA male offspring were not social and exhibited high levels of repetitive self-directed behaviors; female offspring were unaffected. However, KD feeding partially or completely reversed all MIA-induced behavioral abnormalities in males; it had no effect on behavior in females. KD-induced metabolic changes of reduced blood glucose and elevated blood ketones were quantified in offspring of both sexes. Prior work from our laboratory and others demonstrate KDs improve relevant behaviors in several ASD models, and here we demonstrate clear benefits of KD in the MIA model of ASD. Together these studies suggest a broad utility for metabolic therapy in improving core ASD symptoms, and support further research to develop and apply ketogenic and/or metabolic strategies in patients with ASD
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Correction: The Relationship between Therapeutic Alliance and Service User Satisfaction in Mental Health Inpatient Wards and Crisis House Alternatives: A Cross-Sectional Study
Site specific genetic incorporation of azidophenylalanine in Schizosaccharomyces pombe
The diversity of protein functions is impacted in significant part by the chemical properties of the twenty amino acids, which are used as building blocks for nearly all proteins. The ability to incorporate unnatural amino acids (UAA) into proteins in a site specific manner can vastly expand the repertoire of protein functions and also allows detailed analysis of protein function. In recent years UAAs have been incorporated in a site-specific manner into proteins in a number of organisms. In nearly all cases, the amber codon is used as a sense codon, and an orthogonal tRNA/aminoacyl-tRNA synthetase (RS) pair is used to generate amber suppressing tRNAs charged with the UAA. In this work, we have developed tools to incorporate the cross-linking amino acid azido-phenylalanine (AzF) through the use of bacterial tRNATyr and a modified version of TyrRS, AzFRS, in Schizosaccharomyces pombe, which is an attractive model organism for the study of cell behavior and function. We have incorporated AzF into three different proteins. We show that the majority of AzF is modified to amino-phenyl alanine, but protein cross-linking was still observed. These studies set the stage for exploitation of this new technology for the analysis of S. pombe proteins
Neutral Evolution as Diffusion in phenotype space: reproduction with mutation but without selection
The process of `Evolutionary Diffusion', i.e. reproduction with local
mutation but without selection in a biological population, resembles standard
Diffusion in many ways. However, Evolutionary Diffusion allows the formation of
local peaks with a characteristic width that undergo drift, even in the
infinite population limit. We analytically calculate the mean peak width and
the effective random walk step size, and obtain the distribution of the peak
width which has a power law tail. We find that independent local mutations act
as a diffusion of interacting particles with increased stepsize.Comment: 4 pages, 2 figures. Paper now representative of published articl
Mental Health and Psychosocial Functioning in Recently Separated U.S. Women Veterans: Trajectories and Bi-Directional Relationships
Prior research on the relationship between veteransā mental health and psychosocial functioning has primarily relied on male samples. Here, we investigated prospective longitudinal relationships between mental health and psychosocial functioning in 554 female Iraq and Afghanistan War veterans who were surveyed three times between two- and seven-years following separation from service. Mixed effects modeling revealed that increasing depression and posttraumatic stress disorder (PTSD) severity predicted declines in work functioning. Increasing PTSD severity predicted declining parental functioning and worsening depression predicted a decline in relationship functioning. In turn, decreased work and intimate relationship functioning predicted increased PTSD and depression symptom severity suggesting bi-directional effects between mental health and psychosocial functioning. An examination of the effect of deployment stressors on psychosocial functioning revealed that deployment sexual harassment was the strongest predictor of decreased psychosocial functioning across all domains. Evidence for the reciprocal nature of relationships between mental health and psychosocial functioning underscore the need for treatment targeted at PTSD and depression, as well as work and relationship functioning to improve outcomes for women veterans
Kinetic growth walks on complex networks
Kinetically grown self-avoiding walks on various types of generalized random
networks have been studied. Networks with short- and long-tailed degree
distributions were considered (, degree or connectivity), including
scale-free networks with . The long-range behaviour of
self-avoiding walks on random networks is found to be determined by finite-size
effects. The mean self-intersection length of non-reversal random walks, ,
scales as a power of the system size $N$: $ \sim N^{\beta}$, with an
exponent $\beta = 0.5$ for short-tailed degree distributions and $\beta < 0.5$
for scale-free networks with $\gamma < 3$. The mean attrition length of kinetic
growth walks, , scales as , with an exponent
which depends on the lowest degree in the network. Results of
approximate probabilistic calculations are supported by those derived from
simulations of various kinds of networks. The efficiency of kinetic growth
walks to explore networks is largely reduced by inhomogeneity in the degree
distribution, as happens for scale-free networks.Comment: 10 pages, 8 figure
Detection of gene amplification in matched tumour and plasma DNA from breast cancer patients by quantitative PCR
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