Evaluation of the current knowledge limitations in breast cancer research: a gap analysis

BACKGROUND A gap analysis was conducted to determine which areas of breast cancer research, if targeted by researchers and funding bodies, could produce the greatest impact on patients. METHODS Fifty-six Breast Cancer Campaign grant holders and prominent UK breast cancer researchers participated in a gap analysis of current breast cancer research. Before, during and following the meeting, groups in seven key research areas participated in cycles of presentation, literature review and discussion. Summary papers were prepared by each group and collated into this position paper highlighting the research gaps, with recommendations for action. RESULTS Gaps were identified in all seven themes. General barriers to progress were lack of financial and practical resources, and poor collaboration between disciplines. Critical gaps in each theme included: (1) genetics (knowledge of genetic changes, their effects and interactions); (2) initiation of breast cancer (how developmental signalling pathways cause ductal elongation and branching at the cellular level and influence stem cell dynamics, and how their disruption initiates tumour formation); (3) progression of breast cancer (deciphering the intracellular and extracellular regulators of early progression, tumour growth, angiogenesis and metastasis); (4) therapies and targets (understanding who develops advanced disease); (5) disease markers (incorporating intelligent trial design into all studies to ensure new treatments are tested in patient groups stratified using biomarkers); (6) prevention (strategies to prevent oestrogen-receptor negative tumours and the long-term effects of chemoprevention for oestrogen-receptor positive tumours); (7) psychosocial aspects of cancer (the use of appropriate psychosocial interventions, and the personal impact of all stages of the disease among patients from a range of ethnic and demographic backgrounds). CONCLUSION Through recommendations to address these gaps with future research, the long-term benefits to patients will include: better estimation of risk in families with breast cancer and strategies to reduce risk; better prediction of drug response and patient prognosis; improved tailoring of treatments to patient subgroups and development of new therapeutic approaches; earlier initiation of treatment; more effective use of resources for screening populations; and an enhanced experience for people with or at risk of breast cancer and their families. The challenge to funding bodies and researchers in all disciplines is to focus on these gaps and to drive advances in knowledge into improvements in patient care

Self-calibrating smooth pursuit through active efficient coding

International audienceThis paper presents a model for the autonomous learning of smooth pursuit eye movements based on an efficient coding criterion for active perception. This model accounts for the joint development of visual encoding and eye control. Sparse coding models encode the incoming data at two different spatial resolu-tions and capture the statistics of the input in spatio-temporal basis functions. A reinforcement learner controls eye velocity so as to maximize a reward signal based on the efficiency of the encoding. We consider the embodiment of the approach in the iCub simulator and real robot.Motion perception and smooth pursuit control are not explicitly expressed as tasks for the robot to achieve but emerge as the result of the system's active attempt to efficiently encode its sensory inputs. Experiments demonstrate that the proposed approach is self-calibrating and robust to strong perturbations of the perception-action link

β-Catenin-Dependent and -Independent Effects of ΔN-Plakoglobin on Epidermal Growth and Differentiation

Both β-catenin and plakoglobin can stimulate the expression of Lef/Tcf target genes in vitro. β-Catenin is known to associate with Lef/Tcf factors and to participate directly in transactivation in vivo, whereas the role of plakoglobin in transcriptional regulation has been less studied. To analyze the functions of plakoglobin in vivo, we generated transgenic mice expressing in the epidermis N-terminally truncated plakoglobin (ΔN122-PG) lacking the glycogen synthase kinase 3β phosphorylation sites and therefore protected against degradation (transgenic line K5-ΔN122-PG). The expression of ΔN122-PG led to the formation of additional hair germs, hyperplastic hair follicles, and noninvasive hair follicle tumors, a phenotype reminiscent of that induced by expression of N-terminally truncated β-catenin. However, if expressed in β-catenin-null epidermis, ΔN122-PG did not induce new hair follicle germs and follicular tumors. Thus, ΔN122-PG cannot substitute for β-catenin in its signaling functions in vivo and the phenotype observed in K5-ΔN122-PG mouse skin must be due to the aberrant activation of β-catenin signaling. On the other hand, the expression of ΔN122-PG in β-catenin-null skin significantly increased the survival rate of mutant mice, rescued differentiation, and limited excessive proliferation in the interfollicular epidermis, suggesting that plakoglobin may be involved in the intracellular signaling events essential for epidermal differentiation

A Joint Learning Framework of Visual Sensory Representation, Eye Movements, and Depth Representation for Developmental Robotic Agents

In this paper, we propose a novel visual learning framework for developmental robotics agents which mimics the developmental learning concept from human infants. It can be applied to an agent to autonomously perceive depths by simultaneously developing its visual sensory representation, eye movement control, and depth representation knowledge through integrating multiple visual depth cues during self-induced lateral body movement. Based on the active efficient coding theory (AEC), a sparse coding and a reinforcement learning are tightly coupled with each other by sharing a unify cost function to update the performance of the sensory coding model and eye motor control. The generated multiple eye motor control signals for different visual depth cues are used together as inputs for the multi-layer neural networks for representing the given depth from simple human-robot interaction. We have shown that the proposed learning framework, which is implemented on the Hoap-3 humanoid robot simulator, can effectively learn to autonomously develop the sensory visual representation, eye motor control, and depth perception with self-calibrating ability at the same time

Visual Servoing

International audienceVisual servoing refers to the use of visual data as input of real-time closed-loop control schemes for controlling the motion of a dynamic system, a robot typically. It can be defined as sensor-based control from a vision sensor and relies on techniques from image processing, computer vision, and control theory

Robot Visual Control

International audienc