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Delphi Process In preparation for the first Delphi exercise, a list of questions was produced from the academic literature, webbased sources and interviews with experts. These questions were structured into broad dimensions and a draft questionnaire piloted. A final list of 73 questions formed the basis of the first Delphi survey. Participants were asked to grade the perceived importance of each question for inclusion in HTA reports on new prenatal genetic tests (4 = Essential; 3 = Desirable, but not essential; 2 = Useful but should not be required; 1 = Of little/ no importance; 0 = I have no basis for judgement). Secondly, they were asked to indicate whether a question should be addressed during test development or whether the question could be addressed later once the technology is ready for implementation. Finally, Panel members were encouraged to identify any other questions which appeared to be missing from the initial list. For copy of questionnaire, see Annex 1: Delphi Round 1 Questionnaire. Respondents were also asked to provide personal details to give some indication of their HTA experience and specialist expertise. Analysis of responses demonstrated that SAFE Delphi panel members represent a highly experienced, multidisciplinary international group of experts with the knowledge required to define which key questions should be addressed in HTA reports on new prenatal genetic tests. Delphi Responses Responses were received from 77/90 (86%) of Panel members. These were analysed with a cut-off of 75% (±3%) applied as an indicator of Panel consensus for all questions. Thus, any question which three out of four respondents rated as essential or desirable was retained, whilst those not achieving this level of agreement were provisionally excluded. In addition, mean scores were also calculated (excluding 0 = I have no basis for judgement) for each question. A mean score >3.25 ± 0.05 was taken as an indication that the Panel had identified a particular question as being of the highest priority to address in HTA.Final version (published as open access)

In order to understand and analyse {\it genetic regulatory networks}, the complex control structures which regulate cellular systems, well supported qualitative formal modelling techniques are required. In this paper we make a case that biological systems with deterministic behaviour can be modelled by speed-independent circuits. We apply techniques from asynchronous circuit design, based on {\it Signal Transition Graphs (STGs)}, to modelling, visualising and analysing genetic regulatory networks. STGs are an interpreted Petri net model that have been extensively used in asynchronous circuit design. We investigate how the sufficient conditions ensuring that an STG can be implemented by a speed-independent circuit can be interpreted in the context of genetic regulatory networks.We observe that these properties provide important insights into a model and highlight areas which need to be refined. Thus, STGs provide a well supported formal framework for genetic regulatory networks that allows realistic models to be incrementally developed and analysed. We demonstrate the proposed STG approach with a case study of constructing and analysing a speed-independent circuit specification for lysis-lysogeny switch in phage lambda.

To understand the function of genetic regulatory networks in the development of cellular systems, we must not only realise the individual network entities, but also the manner by which they interact. Multi-valued networks are a promising qualitative approach for modelling such genetic regulatory networks, providing an interesting compromise between the simplicity of Boolean models and more detailed quantitative models. However, at present multi-valued networks lack the formal analysis techniques and tools required to comprehensively investigate a genetic regulatory model. This is compounded by the fact that little appears to be known about the relationship between multi-valued models and their more abstract Boolean counterparts. We present a flexible formal framework for modelling and analysing multi-valued genetic regulatory networks using high-level Petri nets. We propose an approach for translating a multi-valued model in to a corresponding compact high-level Petri net model using logic minimization techniques and consider coping with the problem of incomplete data that often occurs in practice. We demonstrate our approach with a detailed case study in which part of the genetic regulatory network responsible for the carbon starvation stress response in Escherichia coli is modelled and analysed. We then compare and contrast this multi-valued model to a corresponding Boolean model and present an initial investigation into the formal relationship between these two modelling approaches.

In order to understand complex genetic regulatory networks researchers require automated formal modelling techniques that provide appropriate analysis tools. In this paper we propose a new qualitative model for genetic regulatory networks based on Petri nets and detail a process for automatically constructing these models using logic minimization. We take as our starting point the Boolean network approach in which regulatory entities are viewed abstractly as binary switches. The idea is to extract terms representing a Boolean network using logic minimization and to then directly translate these terms into appropriate Petri net control structures. The resulting compact Petri net model addresses a number of shortcomings associated with Boolean networks and is particularly suited to analysis using the wide range of Petri net tools. We demonstrate our approach by presenting a detailed case study in which the genetic regulatory network underlying the nutritional stress response in Escherichia coli is modelled and analysed.

This research presents a comprehensive, multiphase investigation of a heterozygous microdeletion on chromosome 17p13.3, spanning chr17:1,411,408–1,841,103 (GRCh37/hg19), with a nominal length of 429,696 base pairs. The affected interval encompasses 17 annotated loci, including 13 protein-coding genes and four noncoding loci. The investigation examines the genomic architecture, molecular functions, tissue-specific expression, dosage sensitivity, and potential physiological consequences of this deletion, with particular emphasis on visual-system biology, neurodevelopment, and candidate mechanisms relevant to epileptic photosensitivity. The research integrates genomic annotation, published experimental findings, molecular pathway analysis, human tissue-expression resources, retinal single-cell transcriptomic evidence, and comparative evaluations of genetic perturbation models. Particular attention is given to phosphoinositide signaling, phospholipid metabolism, intracellular trafficking, retinal maintenance, cellular stress responses, DNA-damage protection, neuronal development, and network organization.

This report concentrates on three main areas. First and foremost, we set the background context for RhD NIPD in prenatal care. While the methodology chapter describes how the literature review was carried out and how additional information was collected, the second chapter provides an overview of the key issues associated with pregnancy of RhD negative women. We present background information based on publications from 1997 to 2006 which describe the genetic condition and its prevalence (RhD negativity) in populations, as well as the frequency of cases of sensitisation and HDN (haemolytic disease of the newborn). We also discuss current service provision for RhD negative women in a number of European countries and look at how the NIPD test might be set within current service contexts.Final version (published as open access)

The increasing relevance of electric and hybrid propulsion systems in aviation demands innovative approaches to reduce emissions, noise, and structural loads. Within the research project NERO (Neuartige Emissionsreduktion durch Optimierung), a multidisciplinary methodology for the analysis and optimization of highly loaded lifting propellers has been developed and applied. The study combines aerodynamic, aeroelastic, and aeroacoustic simulations with experimental investigations to address the challenges of dynamically induced loads under off-design operating conditions, particularly during transition flight. A novel propeller geometry was derived using a combination of genetic optimization algorithms and geometric modifications such as sweep and cone angle variations. Results indicate significant improvements in propeller efficiency and reductions in tonal noise emissions and dynamic load amplitudes. In addition, a propeller-integrated Vibration Reduction System (VRS) was developed to actively mitigate dynamic structural loads. Numerical investigations demonstrate the potential of the VRS to reduce load amplitudes substantially while also contributing to noise reduction. However, trade-offs regarding the mechanical load path, system weight and integration complexity were identified. The presented approach demonstrates a viable pathway toward more efficient, quieter, and structurally robust propeller systems, contributing to the advancement of sustainable aviation technologies.

Endometriosis is a chronic, oestrogen-dependent inflammatory disease affecting an estimated 10% of women of reproductive age. The mean diagnostic delay is 6–7 years.Current evidence supports viewing endometriosis beyond a purely gynaecological condition: it combines peripheral inflammation, central sensitisation, genetic susceptibility and associations with other chronic conditions.Objective. To provide a structured protocol integrating the contributions of the gynaecological (endometriosis) surgeon, reproductive medicine specialist, radiologist, pain specialist, colorectal surgeon, urologist, psychologist, pelvic-floor physiotherapist, dietitian and other team members.Methods. The protocol synthesises the ESHRE 2022 guideline, NICE NG73, ACOG guidance, the IDEA ultrasound and WES classification consensus statements, Cochrane reviews and key randomised trials (Section 4). Primary sources and GRADE-based guidelines were prioritised.Results. A six-step patient pathway is proposed: (1) clinical suspicion and early recognition; (2) non-invasive imaging; (3) empirical therapy and a personalised plan; (4) surgery in a centre of expertise where indicated; (5) recovery, rehabilitation and long-term suppression; (6) outcome monitoring (PROMs) and comorbidity screening.Conclusions. Managing endometriosis as a chronic, multisystem condition through a coordinated team may improve pain control, quality of life and reproductive outcomes. The protocol requires local adaptation and independent expert verification before clinical use

Modelling and computational simulation are crucial for the large-scale engineering of biological circuits since they allow the system under design to be simulated prior to implementation in vivo. To support automated, model-driven design it is desirable that in silico models are modular, composable and use standard formats. The synthetic biology design process typically involves the composition of genetic circuits from individual parts. At the most basic level these parts are representations of genetic features such as promoters, ribosome binding sites (RBSs), and coding sequences (CDSs). However, it is also desirable to model the biological molecules and behaviour that arise when these parts are combined in vivo. Modular models of parts can be composed and their associated systems simulated, facilitating the process of model centred design. The availability of databases of modular models is essential to support software tools used in the model-driven design process. In this paper we present an approach to support the development of composable, modular models for synthetic biology, termed Standard Virtual Parts. We then describe a programmatically accessible and publicly available database of these models to allow their use by computational design tools.

To exploit the vast data obtained from high throughput molecular biology, a variety of modelling and analysis techniques must be fully utilised. In this thesis, Petri nets are investigated within the context of computational systems biology, with the specific focus of facilitating the creation and analysis of models of biological pathways. The analysis of qualitative models of genetic networks using safe Petri net techniques was investigated with particular reference to model checking. To exploit existing model repositories a mapping was presented for the automatic translation of models encoded in the Systems Biology Markup Language (SBML) into the Petri Net framework. The mapping is demonstrated via the conversion and invariant analysis of two published models of the glycolysis pathway. Dynamic stochastic simulations of biological systems suffer from two problems: computational cost; and lack of kinetic parameters. A new stochastic Petri net simulation tool, NASTY was developed which addresses the prohibitive real-time computational costs of simulations by using distributed job scheduling. In order to manage and maximise the usefulness of simulation results a new data standard, TSML was presented. The computational power of NASTY provided the basis for the development of a genetic algorithm for the automatic parameterisation of stochastic models. This parameter estimation technique was evaluated on a published model of the general stress response of E. coli. An attempt to enhance the parameter estimation process using sensitivity analysis was then investigated. To explore the scope and limits of applying the Petri net techniques presented, a realistic case study investigated how the Pho and sB regulons interact to mitigate phosphate stress in Bacillus subtilis. This study made use of a combination of qualitative and quantitative Petri net techniques and was able to confirm an existing experimental hypothesis.

To exploit the vast data obtained from high throughput molecular biology, a variety of modelling and analysis techniques must be fully utilised. In this thesis, Petri nets are investigated within the context of computational systems biology, with the specific focus of facilitating the creation and analysis of models of biological pathways. The analysis of qualitative models of genetic networks using safe Petri net techniques was investigated with particular reference to model checking. To exploit existing model repositories a mapping was presented for the automatic translation of models encoded in the Systems Biology Markup Language (SBML) into the Petri Net framework. The mapping is demonstrated via the conversion and invariant analysis of two published models of the glycolysis pathway. Dynamic stochastic simulations of biological systems suffer from two problems: computational cost; and lack of kinetic parameters. A new stochastic Petri net simulation tool, NASTY was developed which addresses the prohibitive real-time computational costs of simulations by using distributed job scheduling. In order to manage and maximise the usefulness of simulation results a new data standard, TSML was presented. The computational power of NASTY provided the basis for the development of a genetic algorithm for the automatic parameterisation of stochastic models. This parameter estimation technique was evaluated on a published model of the general stress response of E. coli. An attempt to enhance the parameter estimation process using sensitivity analysis was then investigated. To explore the scope and limits of applying the Petri net techniques presented, a realistic case study investigated how the Pho and sB regulons interact to mitigate phosphate stress in Bacillus subtilis. This study made use of a combination of qualitative and quantitative Petri net techniques and was able to confirm an existing experimental hypothesis. This work was supervised by Anil Wipat and Jason Steggles.

With growing maturity Internet services are proving integral to the provision of computer services. To provide consistent end-user experiences these services are increasingly augmented with some notion of ‘Quality-of-Service’ (QoS), which typically requires the management of computing resources to maintain a predictable level of service performance. It is difficult to guarantee consistent service provision in dynamic and open environments such as the Internet. However service monitoring can be used to inform compensatory actions by collecting meaningful service performance data from strategic points in an active service environment. Due to the unpredictable nature of the Internet distributed monitoring mechanisms face challenges with respect to the various communication protocols, application languages, and monitoring requirements associated with a service environment. With the growing popularity of Internet services creation of monitoring solutions on a per-service basis becomes time-consuming and misses opportunities to re-use existing logic. Ideally monitoring solutions would be domain-agnostic, automatically generated and automatically deployed. This thesis progresses these ambitions by providing a generic, distributed monitoring and evaluation framework based on Metric Collector (MeCo) components. These components can transparently gather measurement data across a range of service technologies as used within E-Commerce service environments. MeCo components form part of a framework which can interpret Service Level Agreements (SLAs) to automatically provide tailored service monitoring. The evaluation paradigms of the MeCo Framework are re-appropriated for use in Distributed Virtual Environments (DVEs). Quantifiable QoS requirements are established for Interest Management mechanisms (which limit message production based on object localities within a DVE). These are then incorporated into a DVE Simulator application. This application allows DVE application developers to evaluate Interest Management configurations for their suitability. Extensions to the DVE Simulator are exhibited in the Evolutionary Optimisation Simulator (EOS), which provides automated optimisation capabilities for DVE configurations through utilisation of genetic algorithm techniques.