2,818 research outputs found
Test-enhanced learning of clinical reasoning: a crossover randomised trial
CONTEXT: Clinical reasoning is an essential skill, the foundations of which should be acquired during undergraduate medical education. Student performance in clinical reasoning can be assessed using key feature examinations. However, within a paradigm of test-enhanced learning, such examinations may also be used to enhance long-term retention of procedural knowledge relevant to clinical reasoning. OBJECTIVES: This study tested the hypothesis that repeated testing with key feature questions is more effective than repeated case-based learning in fostering clinical reasoning. METHODS: In this randomised crossover trial, Year 4 medical students attended 10 weekly computer-based seminars during which patient case histories covering general medical conditions were displayed. The presentation format was switched between groups every week. In the control condition, students studied long case narratives. The intervention condition used the same content but augmented case presentation with a sequence of key feature questions. Using a within-subjects design, student performance on intervention and control items was assessed at 13 weeks (exit examination) and 9 months (retention test) after the first day of term. RESULTS: A total of 87 of 124 eligible students provided complete data for the longitudinal analysis (response rate: 70.2%). In the retention test, mean ± standard deviation student scores on intervention items were significantly higher than those on control items (56.0 ± 25.8% versus 48.8 ± 24.7%; p < 0.001). The results remained unchanged after accounting for exposure time in a linear regression analysis that also adjusted for sex and general student performance levels. CONCLUSIONS: This is the first study to demonstrate an effect of test-enhanced learning on clinical reasoning as assessed with key feature questions. In this randomised trial, repeated testing was more effective than repeated case-based learning alone. Curricular implementation of longitudinal key feature testing may considerably enhance student learning outcomes in relevant aspects of clinical medicine
Things change: Women’s and men’s marital disruption dynamics in Italy during a time of social transformations, 1970-2003
We study women’s and men’s marital disruption in Italy between 1970 and 2003. By applying an event-history analysis to the 2003 Italian variant of the Generations and Gender Survey we found that the spread of marital disruption started among middle-highly educated women. Then in recent years it appears that less educated women have also been able to dissolve their unhappy unions. Overall we can see the beginning of a reversed educational gradient from positive to negative. In contrast the trend in men’s marital disruption risk appears as a change over time common to all educational groups, although with persisting educational differentials.determinants, educational differences, event history analysis, gender difference, Italy, marital disruption
Differential expression analysis for sequence count data
*Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.

*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. 

*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from "http://www-huber.embl.de/users/anders/DESeq":http://www-huber.embl.de/users/anders/DESeq
Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens.
BackgroundTo determine differentially expressed and spliced RNA transcripts in chronic lymphocytic leukemia specimens a high throughput RNA-sequencing (HTS RNA-seq) analysis was performed.MethodsTen CLL specimens and five normal peripheral blood CD19+ B cells were analyzed by HTS RNA-seq. The library preparation was performed with Illumina TrueSeq RNA kit and analyzed by Illumina HiSeq 2000 sequencing system.ResultsAn average of 48.5 million reads for B cells, and 50.6 million reads for CLL specimens were obtained with 10396 and 10448 assembled transcripts for normal B cells and primary CLL specimens respectively. With the Cuffdiff analysis, 2091 differentially expressed genes (DEG) between B cells and CLL specimens based on FPKM (fragments per kilobase of transcript per million reads and false discovery rate, FDR q < 0.05, fold change >2) were identified. Expression of selected DEGs (n = 32) with up regulated and down regulated expression in CLL from RNA-seq data were also analyzed by qRT-PCR in a test cohort of CLL specimens. Even though there was a variation in fold expression of DEG genes between RNA-seq and qRT-PCR; more than 90 % of analyzed genes were validated by qRT-PCR analysis. Analysis of RNA-seq data for splicing alterations in CLL and B cells was performed by Multivariate Analysis of Transcript Splicing (MATS analysis). Skipped exon was the most frequent splicing alteration in CLL specimens with 128 significant events (P-value <0.05, minimum inclusion level difference >0.1).ConclusionThe RNA-seq analysis of CLL specimens identifies novel DEG and alternatively spliced genes that are potential prognostic markers and therapeutic targets. High level of validation by qRT-PCR for a number of DEG genes supports the accuracy of this analysis. Global comparison of transcriptomes of B cells, IGVH non-mutated CLL (U-CLL) and mutated CLL specimens (M-CLL) with multidimensional scaling analysis was able to segregate CLL and B cell transcriptomes but the M-CLL and U-CLL transcriptomes were indistinguishable. The analysis of HTS RNA-seq data to identify alternative splicing events and other genetic abnormalities specific to CLL is an added advantage of RNA-seq that is not feasible with other genome wide analysis
Profiling allele-specific gene expression in brains from individuals with autism spectrum disorder reveals preferential minor allele usage.
One fundamental but understudied mechanism of gene regulation in disease is allele-specific expression (ASE), the preferential expression of one allele. We leveraged RNA-sequencing data from human brain to assess ASE in autism spectrum disorder (ASD). When ASE is observed in ASD, the allele with lower population frequency (minor allele) is preferentially more highly expressed than the major allele, opposite to the canonical pattern. Importantly, genes showing ASE in ASD are enriched in those downregulated in ASD postmortem brains and in genes harboring de novo mutations in ASD. Two regions, 14q32 and 15q11, containing all known orphan C/D box small nucleolar RNAs (snoRNAs), are particularly enriched in shifts to higher minor allele expression. We demonstrate that this allele shifting enhances snoRNA-targeted splicing changes in ASD-related target genes in idiopathic ASD and 15q11-q13 duplication syndrome. Together, these results implicate allelic imbalance and dysregulation of orphan C/D box snoRNAs in ASD pathogenesis
Integrated genomics and proteomics define huntingtin CAG length-dependent networks in mice.
To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington's disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock-in mice with increasing CAG repeat lengths. We found repeat length-dependent transcriptional signatures to be prominent in the striatum, less so in cortex, and minimal in the liver. Coexpression network analyses revealed 13 striatal and 5 cortical modules that correlated highly with CAG length and age, and that were preserved in HD models and sometimes in patients. Top striatal modules implicated mHtt CAG length and age in graded impairment in the expression of identity genes for striatal medium spiny neurons and in dysregulation of cyclic AMP signaling, cell death and protocadherin genes. We used proteomics to confirm 790 genes and 5 striatal modules with CAG length-dependent dysregulation at the protein level, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo
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Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.
Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10-6, 1.7 × 10-9, 3.5 × 10-12 and 1.0 × 10-4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes
Cooperation, Norms, and Revolutions: A Unified Game-Theoretical Approach
Cooperation is of utmost importance to society as a whole, but is often
challenged by individual self-interests. While game theory has studied this
problem extensively, there is little work on interactions within and across
groups with different preferences or beliefs. Yet, people from different social
or cultural backgrounds often meet and interact. This can yield conflict, since
behavior that is considered cooperative by one population might be perceived as
non-cooperative from the viewpoint of another.
To understand the dynamics and outcome of the competitive interactions within
and between groups, we study game-dynamical replicator equations for multiple
populations with incompatible interests and different power (be this due to
different population sizes, material resources, social capital, or other
factors). These equations allow us to address various important questions: For
example, can cooperation in the prisoner's dilemma be promoted, when two
interacting groups have different preferences? Under what conditions can costly
punishment, or other mechanisms, foster the evolution of norms? When does
cooperation fail, leading to antagonistic behavior, conflict, or even
revolutions? And what incentives are needed to reach peaceful agreements
between groups with conflicting interests?
Our detailed quantitative analysis reveals a large variety of interesting
results, which are relevant for society, law and economics, and have
implications for the evolution of language and culture as well
Potential climatic transitions with profound impact on Europe
We discuss potential transitions of six climatic subsystems with large-scale impact on Europe, sometimes denoted as tipping elements. These are the ice sheets on Greenland and West Antarctica, the Atlantic thermohaline circulation, Arctic sea ice, Alpine glaciers and northern hemisphere stratospheric ozone. Each system is represented by co-authors actively publishing in the corresponding field. For each subsystem we summarize the mechanism of a potential transition in a warmer climate along with its impact on Europe and assess the likelihood for such a transition based on published scientific literature. As a summary, the ‘tipping’ potential for each system is provided as a function of global mean temperature increase which required some subjective interpretation of scientific facts by the authors and should be considered as a snapshot of our current understanding. <br/
Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses
The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined
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