98 research outputs found

    Incipient Social Groups: An Analysis via In-Vivo Behavioral Tracking

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    Social psychology is fundamentally the study of individuals in groups, yet there remain basic unanswered questions about group formation, structure, and change. We argue that the problem is methodological. Until recently, there was no way to track who was interacting with whom with anything approximating valid resolution and scale. In the current study we describe a new method that applies recent advances in image-based tracking to study incipient group formation and evolution with experimental precision and control. In this method, which we term "in vivo behavioral tracking," we track individuals' movements with a high definition video camera mounted atop a large field laboratory. We report results of an initial study that quantifies the composition, structure, and size of the incipient groups. We also apply in-vivo spatial tracking to study participants' tendency to cooperate as a function of their embeddedness in those crowds. We find that participants form groups of seven on average, are more likely to approach others of similar attractiveness and (to a lesser extent) gender, and that participants' gender and attractiveness are both associated with their proximity to the spatial center of groups (such that women and attractive individuals are more likely than men and unattractive individuals to end up in the center of their groups). Furthermore, participants' proximity to others early in the study predicted the effort they exerted in a subsequent cooperative task, suggesting that submergence in a crowd may predict social loafing. We conclude that in vivo behavioral tracking is a uniquely powerful new tool for answering longstanding, fundamental questions about group dynamics

    Relationships between Gene Expression and Brain Wiring in the Adult Rodent Brain

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    We studied the global relationship between gene expression and neuroanatomical connectivity in the adult rodent brain. We utilized a large data set of the rat brain “connectome” from the Brain Architecture Management System (942 brain regions and over 5000 connections) and used statistical approaches to relate the data to the gene expression signatures of 17,530 genes in 142 anatomical regions from the Allen Brain Atlas. Our analysis shows that adult gene expression signatures have a statistically significant relationship to connectivity. In particular, brain regions that have similar expression profiles tend to have similar connectivity profiles, and this effect is not entirely attributable to spatial correlations. In addition, brain regions which are connected have more similar expression patterns. Using a simple optimization approach, we identified a set of genes most correlated with neuroanatomical connectivity, and find that this set is enriched for genes involved in neuronal development and axon guidance. A number of the genes have been implicated in neurodevelopmental disorders such as autistic spectrum disorder. Our results have the potential to shed light on the role of gene expression patterns in influencing neuronal activity and connectivity, with potential applications to our understanding of brain disorders. Supplementary data are available at http://www.chibi.ubc.ca/ABAMS

    SUMOylation of the Forkhead Transcription Factor FOXL2 Promotes Its Stabilization/Activation through Transient Recruitment to PML Bodies

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    International audienceBACKGROUND: FOXL2 is a transcription factor essential for ovarian development and maintenance. It is mutated in the genetic condition called Blepharophimosis Ptosis Epicantus inversus Syndrome (BPES) and in cases of isolated premature ovarian failure. We and others have previously shown that FOXL2 undergoes several post-translational modifications. METHODS AND PRINCIPAL FINDINGS: Here, using cells in culture, we show that interference with FOXL2 SUMOylation leads to a robust inhibition of its transactivation ability, which correlates with a decreased stability. Interestingly, FOXL2 SUMOylation promotes its transient recruitment to subnuclear structures that we demonstrate to be PML (Promyelocytic Leukemia) Nuclear Bodies. Since PML bodies are known to be sites where post-translational modifications of nuclear factors take place, we used tandem mass spectrometry to identify new post-translational modifications of FOXL2. Specifically, we detected four phosphorylated, one sulfated and three acetylated sites. CONCLUSIONS: By analogy with other transcription factors, we propose that PML Nuclear Bodies might transiently recruit FOXL2 to the vicinity of locally concentrated enzymes that could be involved in the post-translational maturation of FOXL2. FOXL2 acetylation, sulfation, phosphorylation as well as other modifications yet to be discovered might alter the transactivation capacity of FOXL2 and/or its stability, thus modulating its global intracellular activity

    Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

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    In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

    Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

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    Abstract: Machine learning methods offer great promise for fast and accurate detection and prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest radiographs (CXR) and chest computed tomography (CT) images. Many articles have been published in 2020 describing new machine learning-based models for both of these tasks, but it is unclear which are of potential clinical utility. In this systematic review, we consider all published papers and preprints, for the period from 1 January 2020 to 3 October 2020, which describe new machine learning models for the diagnosis or prognosis of COVID-19 from CXR or CT images. All manuscripts uploaded to bioRxiv, medRxiv and arXiv along with all entries in EMBASE and MEDLINE in this timeframe are considered. Our search identified 2,212 studies, of which 415 were included after initial screening and, after quality screening, 62 studies were included in this systematic review. Our review finds that none of the models identified are of potential clinical use due to methodological flaws and/or underlying biases. This is a major weakness, given the urgency with which validated COVID-19 models are needed. To address this, we give many recommendations which, if followed, will solve these issues and lead to higher-quality model development and well-documented manuscripts

    Angioedema Masqueraders

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    Angioedema is a common reason for referral to immunology and allergy specialists. Not all cases are in fact angioedema. There are many conditions that may mimic its appearance, resulting in misdiagnosis. This may happen when a clinician is unfamiliar with conditions resembling angioedema or when there is a low index of clinical suspicion. In this article, we explore a list of differential diagnoses based on body parts, including the lips, the limbs, periorbital tissues, the face, epiglottis and uvula, as well as the genitalia, that may pose as a masquerader even to an experienced eye

    Zebrafish tracking using convolutional neural networks

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