Covariant un-reduction for curve matching

The process of un-reduction, a sort of reversal of reduction by the Lie group symmetries of a variational problem, is explored in the setting of field theories. This process is applied to the problem of curve matching in the plane, when the curves depend on more than one independent variable. This situation occurs in a variety of instances such as matching of surfaces or comparison of evolution between species. A discussion of the appropriate Lagrangian involved in the variational principle is given, as well as some initial numerical investigations.Comment: Conference paper for MFCA201

The LKB1 Tumor Suppressor as a Biomarker in Mouse and Human Tissues

Germline mutations in the LKB1 gene (also known as STK11) cause the Peutz-Jeghers Syndrome, and somatic loss of LKB1 has emerged as causal event in a wide range of human malignancies, including melanoma, lung cancer, and cervical cancer. The LKB1 protein is a serine-threonine kinase that phosphorylates AMP-activated protein kinase (AMPK) and other downstream targets. Conditional knockout studies in mouse models have consistently shown that LKB1 loss promotes a highly-metastatic phenotype in diverse tissues, and human studies have demonstrated a strong association between LKB1 inactivation and tumor recurrence. Furthermore, LKB1 deficiency confers sensitivity to distinct classes of anticancer drugs. The ability to reliably identify LKB1-deficient tumors is thus likely to have important prognostic and predictive implications. Previous research studies have employed polyclonal antibodies with limited success, and there is no widely-employed immunohistochemical assay for LKB1. Here we report an assay based on a rabbit monoclonal antibody that can reliably detect endogenous LKB1 protein (and its absence) in mouse and human formalin-fixed, paraffin-embedded tissues. LKB1 protein levels determined through this assay correlated strongly with AMPK phosphorylation both in mouse and human tumors, and with mRNA levels in human tumors. Our studies fully validate this immunohistochemical assay for LKB1 in paraffin-embedded formalin tissue sections. This assay should be broadly useful for research studies employing mouse models and also for the development of human tissue-based assays for LKB1 in diverse clinical settings

Inflated 3D ConvNet context analysis for violence detection

According to the Wall Street Journal, one billion surveillance cameras will be deployed around the world by 2021. This amount of information can be hardly managed by humans. Using a Inflated 3D ConvNet as backbone, this paper introduces a novel automatic violence detection approach that outperforms state-of-the-art existing proposals. Most of those proposals consider a pre-processing step to only focus on some regions of interest in the scene, i.e., those actually containing a human subject. In this regard, this paper also reports the results of an extensive analysis on whether and how the context can affect or not the adopted classifier performance. The experiments show that context-free footage yields substantial deterioration of the classifier performance (2% to 5%) on publicly available datasets. However, they also demonstrate that performance stabilizes in context-free settings, no matter the level of context restriction applied. Finally, a cross-dataset experiment investigates the generalizability of results obtained in a single-collection experiment (same dataset used for training and testing) to cross-collection settings (different datasets used for training and testing)

Gait Analysis for Gender Classification in Forensics

Gender Classification (GC) is a natural ability that belongs to the human beings. Recent improvements in computer vision provide the possibility to extract information for different classification/recognition purposes. Gender is a soft biometrics useful in video surveillance, especially in uncontrolled contexts such as low-light environments, with arbitrary poses, facial expressions, occlusions and motion blur. In this work we present a methodology for the construction of a gait analyzer. The methodology is divided into three major steps: (1) data extraction, where body keypoints are extracted from video sequences; (2) feature creation, where body features are constructed using body keypoints; and (3) classifier selection when such data are used to train four different classifiers in order to determine the one that best performs. The results are analyzed on the dataset Gotcha, characterized by user and camera either in motion

Gotcha-I: A Multiview Human Videos Dataset

The growing need of security in large open spaces led to the need to use video capture of people in different context and illumination and with multiple biometric traits as head pose, body gait, eyes, nose, mouth, and further more. All these traits are useful for a multibiometric identification or a person re-identification in a video surveillance context. Body Worn Cameras (BWCs) are used by the police of different countries all around the word and their use is growing significantly. This raises the need to develop new recognition methods that consider multibiometric traits on person re-identification. The purpose of this work is to present a new video dataset called Gotcha-I. This dataset has been obtained using more mobile cameras to adhere to the data of BWCs. The dataset includes videos from 62 subjects in indoor and outdoor environments to address both security and surveillance problem. During these videos, subjects may have a different behavior in videos such as freely, path, upstairs, avoid the camera. The dataset is composed by 493 videos including a set of 180° videos for each face of the subjects in the dataset. Furthermore, there are already processed data, such as: the 3D model of the face of each subject with all the poses of the head in pitch, yaw and roll; and the body keypoint coordinates of the gait for each video frame. It’s also shown an application of gender recognition performed on Gotcha-I, confirming the usefulness and innovativeness of the proposed dataset

Translating Glutamate: From Pathophysiology to Treatment

The neurotransmitter glutamate is the primary excitatory neurotransmitter in mammalian brain and is responsible for most corticocortical and corticofugal neurotransmission. Disturbances in glutamatergic function have been implicated in the pathophysiology of several neuropsychiatric disorders—including schizophrenia, drug abuse and addiction, autism, and depression—that were until recently poorly understood. Nevertheless, improvements in basic information regarding these disorders have yet to translate into Food and Drug Administration–approved treatments. Barriers to translation include the need not only for improved compounds but also for improved biomarkers sensitive to both structural and functional target engagement and for improved translational models. Overcoming these barriers will require unique collaborative arrangements between pharma, government, and academia. Here, we review a recent Institute of Medicine–sponsored meeting, highlighting advances in glutamatergic theories of neuropsychiatric illness as well as remaining barriers to treatment development.National Institute of Mental Health (U.S.) (grant R37MH49334)National Institute of Mental Health (U.S.) (Intramural Research Program)National Institute of Mental Health (U.S.) (R01DA03383)National Institute of Mental Health (U.S.) (P50MH086385)National Institutes of Health (U.S.)FRAXA Research FoundationHoward Hughes Medical InstituteSimons Foundatio

Killer-cell immunoglobulin-like receptor diversity in an admixed South American population

Natural Killer (NK) cells are innate immune cells that mediate antiviral and antitumor responses. NK cell activation and induction of effector functions are tightly regulated by the integration of activating and inhibitory receptors such as killer immunoglobulin-like receptors (KIR)

DAAM is required for thin filament formation and Sarcomerogenesis during muscle development in Drosophila.

During muscle development, myosin and actin containing filaments assemble into the highly organized sarcomeric structure critical for muscle function. Although sarcomerogenesis clearly involves the de novo formation of actin filaments, this process remained poorly understood. Here we show that mouse and Drosophila members of the DAAM formin family are sarcomere-associated actin assembly factors enriched at the Z-disc and M-band. Analysis of dDAAM mutants revealed a pivotal role in myofibrillogenesis of larval somatic muscles, indirect flight muscles and the heart. We found that loss of dDAAM function results in multiple defects in sarcomere development including thin and thick filament disorganization, Z-disc and M-band formation, and a near complete absence of the myofibrillar lattice. Collectively, our data suggest that dDAAM is required for the initial assembly of thin filaments, and subsequently it promotes filament elongation by assembling short actin polymers that anneal to the pointed end of the growing filaments, and by antagonizing the capping protein Tropomodulin

Knowledge, attitudes and behaviours towards sun exposure in Chilean students

Artículo de publicación IS