James Gopsill

A 3D in vitro model of the human breast duct: a method to unravel myoepithelial-luminal interactions in the progression of breast cancer

Background3D modelling fulfils a critical role in research, allowing for complex cell behaviour and interactions to be studied in physiomimetic conditions. With tissue banks becoming established for a number of cancers, researchers now have access to primary patient cells, providing the perfect building blocks to recreate and interrogate intricate cellular systems in the laboratory. The ducts of the human breast are composed of an inner layer of luminal cells supported by an outer layer of myoepithelial cells. In early-stage ductal carcinoma in situ, cancerous luminal cells are confined to the ductal space by an intact myoepithelial layer. Understanding the relationship between myoepithelial and luminal cells in the development of cancer is critical for the development of new therapies and prognostic markers. This requires the generation of new models that allows for the manipulation of these two cell types in a physiological setting.MethodsUsing access to the Breast Cancer Now Tissue Bank, we isolated pure populations of myoepithelial and luminal cells from human reduction mammoplasty specimens and placed them into 2D culture. These cells were infected with lentiviral particles encoding either fluorescent proteins, to facilitate cell tracking, or an inducible human epidermal growth factor receptor 2 (HER2) expression construct. Myoepithelial and luminal cells were then recombined in collagen gels, and the resulting cellular structures were analysed by confocal microscopy.Results Myoepithelial and luminal cells isolated from reduction mammoplasty specimens can be grown separately in 2D culture and retain their differentiated state. When recombined in collagen gels, these cells reform into physiologically reflective bilayer structures. Inducible expression of HER2 in the luminal compartment, once the bilayer has formed, leads to robust luminal filling, recapitulating ductal carcinoma in situ, and can be blocked with anti-HER2 therapies.ConclusionsThis model allows for the interaction between myoepithelial and luminal cells to be investigated in an in-vitro environment and paves the way to study early events in breast cancer development with the potential to act as a powerful drug discovery platform.

A Sequence-Based Approach to Analysing and Representing Engineering Project Normality

Engineering projects are often highly complex, unique and safety critical, which can lead to the complex engineering processes and activity. To ensure the success of engineering projects, the projects often have to comply with stringent regulations and company processes. In addition, the increasing in-service lifespan of products has led to an increase in the number of re-design and maintenance projects. These are often run concurrently in a highly time-constrained and high-pressured environment, which has led to the monitoring of the sequence of engineering activity becoming difficult. This is because, the sequence of engineering activity is typically achieved through the ability of the project managers to use their knowledge, experience and constant contact with the engineers. However, the viability of the current method to manually generate and evaluate the activity plan is becoming an issue due to the increasing number and distributed nature of these projects. As regulatory and/or company process demands, the data relating to the project is often archived and thus, provides a wealth of potentially useful information that could be utilised in the management of current projects. Therefore, this research investigates the potential value provided by the automatic construction of past project activity sequences, and proposes analytical methods to represent the normality of project activity based on the extracted patterns from their sequences. The evaluation applies industrial data, and shows that the results generated by the proposed approach can accurately reflect the similarity and normality of the projects.

An Exploratory Study into Automated Real-Time Categorisation of Engineering E-Mail

For large, spatially and temporally distributed engineering projects, e-mail is a central means for the discussion of engineering work and sharing of digital assets that define the product and its production process. The importance of communication and the value of its content for resolving issues post facto are universally accepted. More recently, the potential value of its content to predict events, issues and states a priori has been explored with some success. However, while in the former context (post facto) trends and patterns can be established through iteration and refinement over time, for prediction, heuristics need to be established in advance and closer to real-time analysis becomes necessary due to the critical and very often short timescales. It is this challenge of making predictions from the content of e-mail that is considered in this paper. In particular, the paper deals with engineering e-mail and the ability to automatically predict its purpose from its content rather than relying solely on the subject line. The work builds upon previous studies by the authors concerning the characterisation of the content of e-mail: what they are about, why they were sent and how the content is expressed. The paper summarises the previous work and looks at the potential of identifying the purpose of e-mail through the use of Naive Bayes and an adapted Latent Semantic Analysis approach. While the techniques have only been applied to an initial exploratory study of 98 e-mails, the results suggest the potential for automated real-time categorisation of engineering e-mails through achieving an accuracy of 66%. Such a capability would both support prioritisation of e-mail for engineers and macro level characterisation of project e-mail dynamics. The latter provides the opportunity for real-time analysis of an engineering projects status and correspondingly, modes of management intervention.

Modelling the Evolution of Computer Aided Design Models: Investigating the Potential for Supporting Engineering Project Management

The development of Computer Aided Design (CAD) models is a fundamental and distinct feature of Engineering Projects. CAD models can be considered to be the digital embodiment of the products’ design and are used to support a wide variety of tasks that span the embodiment, detail, manufacture and commissioning phases of a project. With this in mind, it is proposed that the monitoring and modelling of the edit trace behaviour of CAD files may provide additional understanding and evidence that supplements current approaches to monitor and manage engineering projects.

Deriving Infill Design of Fused Deposition Modelled Parts From Predicted Stress Profiles

The use of Fused Deposition Modelling (FDM) is increasing rapidly in both the commercial and industrial sectors as a means of rapidly prototyping geometrically complex parts. Particular affordances of FDM include the reduction of waste material during manufacture, the use of multiple materials within a single manufacturing process and the ability to manipulate the internal geometry of a part. The latter of which has seen the generation of many 2-dimensional repeating pattern structures such as square, rectilinear and hexagonal, as well as an emerging field of 3-dimensional structures. Although these patterns have provided stiffness and rigidity whilst reducing the production time of FDM prototypes, many do not consider the actual loading conditions of the part in-situ, where it is argued that further significant gains in the performance could be achieved. This includes further reduction in process time and increased part functionality. Thus, this paper presents initial work into the generation of an infill that is derived from the predicted stress profile for the part. This has been achieved through the post-processing of Finite Element (FE) models to identify the stress profile. Interpolation across these profiles leads to a set of aligned Bezier splines that enable the transmission of force and are also able to be manufactured using FDM. These splines are embedded within the typical slicing procedure of a part ahead of being manufactured on a FDM machine. Initial results from parts designed to support three-point bending loads show a 79% increase in the stiffness of the part alongside a consistent and repeatable mode of failure when compared to the commonly used honeycomb infill design.

Investigating the effect of scale and scheduling strategies on the productivity of 3D managed print services

Sales of extrusion 3D printers have seen a rapid growth and the market value is expected to triple over the next decade. This rapid growth can be attributed to a step change in capability and an increase in demand for 3D printed parts within mechanical, industrial and civil engineering processes. Correspondingly, a new technical prototyping platform – commonly referred to as Fabrication Laboratories – has emerged to provide a stimulus for local education, entrepreneurship, innovation and invention through the provision of on-demand 3D printing and prototyping services. Central to the effectiveness of the on-demand 3D printing and prototyping services – hereby referred to as 3D managed print services – is their ability to handle multiple users with varying knowledge and understanding of the manufacturing processes and scaling numbers of 3D printers in order to maximise productivity of the service. It is this challenge of productivity and more specifically the scalability and scheduling of prints that is considered in this article. The effect of scale and scheduling strategies on productivity is investigated through the modelling of four scheduling strategies for 3D managed print service of varying scales by altering the number of available printers and level of user demand. The two most common approaches (first-come first-serve and on-line continuous queue) and two alternatives based on bed space optimisation (first-fit decreasing height and first-fit decreasing height with a genetic algorithm) have been considered. Through Monte-Carlo simulation and comparison of the strategies, it is shown that increasing the scale of 3D managed print service improves the peak productivity and range of user demands at which the 3D managed print service remain productive. In addition, the alternative strategies are able to double the peak productivity of 3D managed print service as well as increase the user demand range where the 3D managed print service remains productive.

Data-Driven Modelling: Towards Interpreting and Understanding Process Evolution of In-Service Engineering Projects

Product service plays an essential role in day-to-day operations of nowadays manufacturing industries. However, the changing demands of the market/customers, the increasing complexity of product functionalities and the extended product lifecycles present challenges to related In-Service projects. In order to handle the increasing number of projects and to control the costs and resource consumptions, it is critical to improve the efficiency and automation of process management. Within this context, this paper introduces some data-driven approaches to interpret and represent changes of project process over time in an automatic manner. These approaches aim to help project actors improve their understanding of process structure and the efficiency of process management, and also enable them to investigate process changes from more dynamic perspectives. To evaluate the approaches, a dataset from an aerospace organisation is considered in this paper.