Citations

AbstractIn this review, we summarize the recent literature and use case examples to reach diagnostic criteria for the diagnosis of immunoglobulin G4 (IgG4)‐related diseases that may be of relevance to the practicing dermatologist.

Context Self‐regulated learning ( SRL ) requires an active learner who has developed a set of processes for managing the achievement of learning goals. Simulation‐based training is one context in which trainees can safely practise learning how to learn. Objectives The purpose of the present study was to evaluate, in the simulation‐based training context, the effectiveness of interventions designed to support trainees in SRL activities. We used the social‐cognitive model of SRL to guide a systematic review and meta‐analysis exploring the links between instructor supervision, supports or scaffolds for SRL , and educational outcomes. Methods We searched databases including MEDLINE and Scopus, and previous reviews, for material published until December 2011. Studies comparing simulation‐based SRL interventions with another intervention for teaching health professionals were included. Reviewers worked independently and in duplicate to extract information on learners, study quality and educational outcomes. We used random‐effects meta‐analysis to compare the effects of supervision (instructor present or absent) and SRL educational supports (e.g. goal‐setting study guides present or absent). Results From 11 064 articles, we included 32 studies enrolling 2482 trainees. Only eight of the 32 studies included educational supports for SRL . Compared with instructor‐supervised interventions, unsupervised interventions were associated with poorer immediate post‐test outcomes (pooled effect size: −0.34, p = 0.09; n = 19 studies) and negligible effects on delayed (i.e. > 1 week) retention tests (pooled effect size: 0.11, p = 0.63; n = 8 studies). Interventions including SRL supports were associated with small benefits compared with interventions without supports on both immediate post‐tests (pooled effect size: 0.23, p = 0.22; n = 5 studies) and delayed retention tests (pooled effect size: 0.44, p = 0.067; n = 3 studies). Conclusions Few studies in the simulation literature have designed SRL training to explicitly support trainees’ capacity to self‐regulate their learning. We recommend that educators and researchers shift from thinking about SRL as learning alone to thinking of SRL as comprising a shared responsibility between the trainee and the instructional designer (i.e. learning using designed supports that help prepare individuals for future learning).

Abstract Dendritic cells (DCs) play a pivotal role in the tumor microenvironment, which is known to affect disease progression in many human malignancies. Infiltration by mature, active DCs into the tumors confers an increase in immune activation and recruitment of disease-fighting immune effector cells and pathways. DCs are the preferential target of infiltrating T cells. However, tumor cells have means of suppressing DC function or of altering the tumor microenvironment in such a way that immune-suppressive DCs are recruited. Advances in understanding these changes have led to promising developments in cancer-therapeutic strategies targeting tumor-infiltrating DCs to subdue their immunosuppressive functions and enhance their immune-stimulatory capacity.

Abstract Motivation: Tag density plots are very important to intuitively reveal biological phenomena from capture-based sequencing data by visualizing the normalized read depth in a region. Results: We have developed iTagPlot to compute tag density across functional features in parallel using multicores and a grid engine and to interactively explore it in a graphical user interface. It allows us to stratify features by defining groups based on biological function and measurement, summary statistics and unsupervised clustering. Availability and implementation: http://sourceforge.net/projects/itagplot/. Contact: jechoi@gru.edu and jeochoi@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

Runx1 is a transcription factor essential for definitive hematopoiesis, and genetic abnormalities in Runx1 cause leukemia. Runx1 is functionally promiscuous and acts as either an oncogene or tumor suppressor gene in certain epithelial cancers. Recent evidence suggests that Runx1 is an important factor in breast cancer, however, its role remains ambiguous. Here, we addressed whether Runx1 has a specific pathological role during breast cancer progression and show that Runx1 has an oncogenic function. We observed elevated Runx1 expression in a subset of human breast cancers. Furthermore, throughout the course of disease progression in a classical mouse model of breast cancer (i.e., the MMTV‐PyMT transgenic model), Runx1 expression increases in the primary site (mammary gland) and is further upregulated in tumors and distal lung metastatic lesions. Ex vivo studies using tumor epithelial cells derived from these mice express significantly higher levels of Runx1 than normal mammary epithelial cells. The tumor cells exhibit increased rates of migration and invasion, indicative of an aggressive cancer phenotype. Inhibition of Runx1 expression using RNA interference significantly abrogates these cancer‐relevant phenotypic characteristics. Importantly, our data establish that Runx1 contributes to murine mammary tumor development and malignancy and potentially represents a key disease‐promoting and prognostic factor in human breast cancer progression and metastasis. J. Cell. Physiol. 230: 2522–2532, 2015. © 2015 Wiley Periodicals, Inc.