A primary breast cancer with distinct foci of estrogen receptor-alpha positive and negative cells derived from the same clonal origin as revealed by whole exome sequencing

© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Background/purpose: Tumor heterogeneity is a now well-recognized phenomenon that can affect the classification, prognosis and treatment of human cancers. Heterogeneity is often described in primary breast cancers based upon histologic subtypes, hormone- and HER2-receptor status, and immunolabeling for various markers, which can be seen within a single tumor as mixed cellular populations, or as separate discrete foci. Experimental design/methods: Here, we present a case report of a patient’s primary breast cancer that had two separate but adjacent histologic components, one that was estrogen receptor (ER) positive, and the other ER negative. Each component was subjected to whole exome sequencing and compared for gene identity to determine clonal origin. Results: Using prior bioinformatic tools, we demonstrated that both the ER positive and negative components shared many variants, including passenger and driver alterations. Copy number variations also supported the two components were derived from a single common clone. Conclusions: These analyses strongly suggest that the two ER components of this patient’s breast cancer were derived from the same clonal origin. Our results have implications for the evolution of breast cancers with mixed histologies, and how they might be best managed for optimal therapy

Team level identification predicts perceived and actual team performance: longitudinal multilevel analyses with sports teams

Social identification and team performance literatures typically focus on the relationship between individual differences in identification and individual-level performance. By using a longitudinal multilevel approach, involving 369 members of 45 sports teams across England and Italy, we compared how team-level and individual-level variance in social identification together predicted team and individual performance outcomes. As hypothesised, team-level variance in identification significantly predicted subsequent levels of both perceived and actual team performance in cross-lagged analyses. Conversely, individual-level variance in identification did not significantly predict subsequent levels of perceived individual performance. These findings support recent calls for social identity to be considered a multilevel construct and highlight the influence of group-level social identification on group-level processes and outcomes, over and above its individual-level effects

A quasi classical approach to electron impact ionization

A quasi classical approximation to quantum mechanical scattering in the Moeller formalism is developed. While keeping the numerical advantage of a standard Classical--Trajectory--Monte--Carlo calculation, our approach is no longer restricted to use stationary initial distributions. This allows one to improve the results by using better suited initial phase space distributions than the microcanonical one and to gain insight into the collision mechanism by studying the influence of different initial distributions on the cross section. A comprehensive account of results for single, double and triple differential cross sections for atomic hydrogen will be given, in comparison with experiment and other theories.Comment: 21 pages, 10 figures, submitted to J Phys

Establishing the baseline level of repetitive element expression in the human cortex

Background: Although nearly half of the human genome is comprised of repetitive sequences, the expression profile of these elements remains largely uncharacterized. Recently developed high throughput sequencing technologies provide us with a powerful new set of tools to study repeat elements. Hence, we performed whole transcriptome sequencing to investigate the expression of repetitive elements in human frontal cortex using postmortem tissue obtained from the Stanley Medical Research Institute. Results: We found a significant amount of reads from the human frontal cortex originate from repeat elements. We also noticed that Alu elements were expressed at levels higher than expected by random or background transcription. In contrast, L1 elements were expressed at lower than expected amounts. Conclusions: Repetitive elements are expressed abundantly in the human brain. This expression pattern appears to be element specific and can not be explained by random or background transcription. These results demonstrate that our knowledge about repetitive elements is far from complete. Further characterization is required to determine the mechanism, the control, and the effects of repeat element expression

Towards Intelligent Crowd Behavior Understanding through the STFD Descriptor Exploration

Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of input video signals. This integrated solution defines an image descriptor (named spatio-temporal feature descriptor - STFD) that reflects the global motion information of crowds over time. A CNN has then been adopted to classify dominant or large-scale crowd abnormal behaviors. The work reported has focused on: 1) detecting moving objects in online (or near real-time) manner through spatio-temporal segmentations of crowds that is defined by the similarity of group trajectory structures in temporal space and the foreground blocks based on Gaussian Mixture Model (GMM) in spatial space; 2) dividing multiple clustered groups based on the spectral clustering method by considering image pixels from spatio-temporal segmentation regions as dynamic particles; 3) generating the STFD descriptor instances by calculating the attributes (i.e., collectiveness, stability, conflict and crowd density) of particles in the corresponding groups; 4) inputting generated STFD descriptor instances into the devised convolutional neural network (CNN) to detect suspicious crowd behaviors. The test and evaluation of the devised models and techniques have selected the PETS database as the primary experimental data sets. Results against benchmarking models and systems have shown promising advancements of this novel approach in terms of accuracy and efficiency for detecting crowd anomalies

Towards Intelligent Crowd Behavior Understanding through the STFD Descriptor Exploration

Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of input video signals. This integrated solution defines an image descriptor (named spatio-temporal feature descriptor - STFD) that reflects the global motion information of crowds over time. A CNN has then been adopted to classify dominant or large-scale crowd abnormal behaviors. The work reported has focused on: 1) detecting moving objects in online (or near real-time) manner through spatio-temporal segmentations of crowds that is defined by the similarity of group trajectory structures in temporal space and the foreground blocks based on Gaussian Mixture Model (GMM) in spatial space; 2) dividing multiple clustered groups based on the spectral clustering method by considering image pixels from spatio-temporal segmentation regions as dynamic particles; 3) generating the STFD descriptor instances by calculating the attributes (i.e., collectiveness, stability, conflict and crowd density) of particles in the corresponding groups; 4) inputting generated STFD descriptor instances into the devised convolutional neural network (CNN) to detect suspicious crowd behaviors. The test and evaluation of the devised models and techniques have selected the PETS database as the primary experimental data sets. Results against benchmarking models and systems have shown promising advancements of this novel approach in terms of accuracy and efficiency for detecting crowd anomalies

Understanding Work Practices of Autonomous Agile Teams: A Social-psychological Review

The purpose of this paper is to suggest additional aspects of social psychology that could help when making sense of autonomous agile teams. To make use of well-tested theories in social psychology and instead see how they replicated and differ in the autonomous agile team context would avoid reinventing the wheel. This was done, as an initial step, through looking at some very common agile practices and relate them to existing findings in social-psychological research. The two theories found that I argue could be more applied to the software engineering context are social identity theory and group socialization theory. The results show that literature provides social-psychological reasons for the popularity of some agile practices, but that scientific studies are needed to gather empirical evidence on these under-researched topics. Understanding deeper psychological theories could provide a better understanding of the psychological processes when building autonomous agile team, which could then lead to better predictability and intervention in relation to human factors

A Systematic Survey of Mini-Proteins in Bacteria and Archaea

BACKGROUND: Mini-proteins, defined as polypeptides containing no more than 100 amino acids, are ubiquitous in prokaryotes and eukaryotes. They play significant roles in various biological processes, and their regulatory functions gradually attract the attentions of scientists. However, the functions of the majority of mini-proteins are still largely unknown due to the constraints of experimental methods and bioinformatic analysis. METHODOLOGY/PRINCIPAL FINDINGS: In this article, we extracted a total of 180,879 mini-proteins from the annotations of 532 sequenced genomes, including 491 strains of Bacteria and 41 strains of Archaea. The average proportion of mini-proteins among all genomic proteins is approximately 10.99%, but different strains exhibit remarkable fluctuations. These mini-proteins display two notable characteristics. First, the majority are species-specific proteins with an average proportion of 58.79% among six representative phyla. Second, an even larger proportion (70.03% among all strains) is hypothetical proteins. However, a fraction of highly conserved hypothetical proteins potentially play crucial roles in organisms. Among mini-proteins with known functions, it seems that regulatory and metabolic proteins are more abundant than essential structural proteins. Furthermore, domains in mini-proteins seem to have greater distributions in Bacteria than Eukarya. Analysis of the evolutionary progression of these domains reveals that they have diverged to new patterns from a single ancestor. CONCLUSIONS/SIGNIFICANCE: Mini-proteins are ubiquitous in bacterial and archaeal species and play significant roles in various functions. The number of mini-proteins in each genome displays remarkable fluctuation, likely resulting from the differential selective pressures that reflect the respective life-styles of the organisms. The answers to many questions surrounding mini-proteins remain elusive and need to be resolved experimentally

Validity and usefulness of members reports of implementation progress in a quality improvement initiative: findings from the Team Check-up Tool (TCT)

<p>Abstract</p> <p>Background</p> <p>Team-based interventions are effective for improving safety and quality of healthcare. However, contextual factors, such as team functioning, leadership, and organizational support, can vary significantly across teams and affect the level of implementation success. Yet, the science for measuring context is immature. The goal of this study is to validate measures from a short instrument tailored to track dynamic context and progress for a team-based quality improvement (QI) intervention.</p> <p>Methods</p> <p>Design: Secondary cross-sectional and longitudinal analysis of data from a clustered randomized controlled trial (RCT) of a team-based quality improvement intervention to reduce central line-associated bloodstream infection (CLABSI) rates in intensive care units (ICUs).</p> <p>Setting: Forty-six ICUs located within 35 faith-based, not-for-profit community hospitals across 12 states in the U.S.</p> <p>Population: Team members participating in an ICU-based QI intervention.</p> <p>Measures: The primary measure is the Team Check-up Tool (TCT), an original instrument that assesses context and progress of a team-based QI intervention. The TCT is administered monthly. Validation measures include CLABSI rate, Team Functioning Survey (TFS) and Practice Environment Scale (PES) from the Nursing Work Index.</p> <p>Analysis: Temporal stability, responsiveness and validity of the TCT.</p> <p>Results</p> <p>We found evidence supporting the temporal stability, construct validity, and responsiveness of TCT measures of intervention activities, perceived group-level behaviors, and barriers to team progress.</p> <p>Conclusions</p> <p>The TCT demonstrates good measurement reliability, validity, and responsiveness. By having more validated measures on implementation context, researchers can more readily conduct rigorous studies to identify contextual variables linked to key intervention and patient outcomes and strengthen the evidence base on successful spread of efficacious team-based interventions. QI teams participating in an intervention should also find data from a validated tool useful for identifying opportunities to improve their own implementation.</p