Bridging the Gap

Bridging the Gap: Events

First Call - Funds Awarded

Results of the First Call

The Bridging the Gap board granted four travel awards in the first round of calls. We were impressed with the variety and quality of the proposals. See below for an overview of the projects funded.

Computational analysis of live-cell imaging data - Joshua Rappoport, School of Biosciences

Clathrin-mediated endocytosis (CME) is a process through which numerous biologically relevant cargoes specifically enter the cell through coated vesicles (Figure 1). Cargo for CME includes ion channels, cell adhesion molecules, activated receptors, as well as human pathogens. The hetero-tetrameric adaptor complex AP-2 connects cargo molecules to the forming clathrin coat. Recent observations support the hypothesis that not all AP-2 components function identically as a single unit all the time. Thus, we have are tracking fluorescent-protein tagged markers for each AP-2 sub-unit in live cells by total internal reflection fluorescence (TIRF) microscopy. TIRF permits the selective imaging of events at and near the plasma membrane of living cells.

The goal of this project will be to quantitatively compare TIRF data acquired from experiments imaging each AP-2 marker along with clathrin during CME in live cells (Figure 4). The fluorescence profiles of individual AP-2/clathrin puncta will be evaluated over time. In each case clathrin fluorescence will be used as a primary marker allowing direct comparison with AP-2. Thus, each of the four individual AP-2 markers will be compared, relative to the internal clathrin control. This will require development of automated particle identification and tracking applications, as well as means by which digitised images can be quantitatively and statistically compared. Analysis with these previously unavailable applications will allow new insight into the regulation of CME and the role of adaptor molecules beyond our current understanding

Collaborative investigation of the impact of ambient air pollution on birth outcome - Ian Litchfield, Institute of Occupational and Environmental Medicine

Recent research has begun to explore the effects of prenatal exposure to air pollution on adverse pregnancy outcomes. Studies exploring the link with still birth were inconclusive whilst those investigating reduced birth weight and birth defects were suggestive of a causal relationship and further research was called for.

A number of underlying mechanisms are potentially responsible; these include foetal hypoxia, oxidative stress, and toxicity from urban air pollution to certain cell populations during development. This investigation will provide precise estimates of the relationship between exposure to traffic-related and other air pollutants and the risk of low birth weight, stillbirth and ventricular septal defect. These estimates will be specific to the time of pregnancy and will be based on multi-pollutant models. We will also assess joint effects of pollutants and whether season modifies the effects of air pollution. We intend to focus our interest on two large populations in two different climates, namely Western Europe and Far East Asia. We will also conduct pooled analyses of the two data sets which will allow us to assess potential heterogeneity of results and, in the case of homogeneity, will increase the overall power of the study

Our partners in Taiwan

The Taipei group has experience of large scale studies of this nature and has investigated the impact of environmental exposure in terms of water quality and air quality on a variety of health outcomes. Their expertise in handling these large data sets and particularly in correlating air quality with health outcome is internationally renowned and will be invaluable to the group based here at Birmingham as we look to expand our expertise, knowledge and influence in the field.

Decoding the 3D world - Andrew Welchman, School of Psychology

Perceiving the three-dimensional (3D) structure of the world is a fundamental visual ability, supporting interaction with people and objects in our environment. To estimate depth, the brain relies on information that is ambiguous: the inverse mapping from retina to world is ill-posed and different cues (e.g. binocular disparity, perspective, texture) may be conflicting. Well-known ambiguous figures, such as the Necker cube, illustrate the brain's dilemma: different depth configurations are compatible with the same sensory input, resulting in alternating interpretations. Understanding the processing involved in translating ambiguous depth signals into a perceptual estimate of 3D structure remains a considerable open challenge.

In this project we combine brain imaging techniques (fMRI) and advanced computational analysis methods based on machine learning (Multi-voxel Pattern Analysis) to gain new insight into the neural mechanisms that underlie our perception of the depth structure of the world around us. In particular, we are combining measures of neural activity in healthy human adult, with concurrent measures of perception to develop computational models that quantify the way in which different brain areas and circuits represent sensory data from the environment.

In collaboration with Dr Bosco Tjan (University of Southern California), we aim to develop novel paradigms to assess the information processing hierarchy of the human visual cortex, detailing the ways in which the brain hierarchically refines information to derive a robust and stable interpretation of the structure of the world around us. Through this we aim to get closer to understanding how the brain solves the puzzle of 3D perception.

Data mining and knowledge discovery by convex optimization - Yu Xia, Shool of Mathematics

Data mining and knowledge discovery is an important tool in both nature and social sciences, including biology, finance, business. Many problems arising from data mining and knowledge discovery can actually be modeled as an optimization problem. However, due to the division of disciplines, few efforts have been made to apply optimization techniques to data mining and knowledge discovery.

Professor Nesterov is the author of 4 monographs and more than 70 refereed papers in the leading optimization journals. Winner of the triennial Dantzig Prize 2000 awarded by SIAM and Mathematical Programming Society for a research having a major impact on the field of mathematical programming. We would like to visit Prof. Nesterov and invite Prof. Nesterov to visit Birmingham so that we can discuss how to design new optimization techniques and adapt existing optimization methods to efficiently solve some most important data mining and knowledge problems. Our visits will lead to a joint grand application and identify future research directions.