Search

The 100,000 Genomes Project (the ‘Project’), announced in December 2012, was established to: • develop new capability and capacity in genomic medicine in order to transform the provision of health services in England; • create new capability for clinical genomics research and • establish an infrastructure for the protection and analysis of clinical and genomic data. The primary mechanism to achieve these aims was through sequencing 100,000 genomes from patients with cancers, rare disorders and infectious diseases, linking the resultant sequence data to a standardised, extensible account of diagnosis, treatment and outcomes. The Project achieved its goal of sequencing 100,000 genomes in December 2018. The Policy Innovation and Evaluation Research Unit (PIRU) at London School of Hygiene and Tropical Medicine (LSHTM) was asked by the then Department of Health to conduct a qualitative study exploring the experiences of those people who donated their DNA to the Project (‘participants’) and the experiences of health care staff involved in the Project, as well as the public’s perceptions of genomic research more generally. Data collection for the current study took place between late 2015 and late 2017. The aims of this study were to: • Understand the motivation of people who agreed to take part in the 100,000 Genomes Project; their experiences of receiving information, giving consent and taking part; their attitudes to data sharing, governance and confidentiality and their views about feedback and use of their Project data for research and clinical care. • Learn about the experiences of clinicians who asked people to take part in the Project. • Explore the understanding and perceptions of members of the public of genomic research in general. • Explore the understanding and perceptions of the non-specialist NHS workforce of genomic research in general, and of the 100,000 Genomes Project in particular, and to identify potential training needs related to any roll-out of genomic medicine services in the NHS. • Draw on the above, in order to make suggestions for improvement, thereby improving the likelihood of the Project achieving its goals. This summary report complements the full report of the study which sets out the methods and findings in greater detail (Ryan et al., 2020). There is also a related section on the healthtalk website (healthtalk.org/experiences-participating-100000genomes-project) which draws on this study’s interviews with participants. It includes eight educational films covering differing aspects of the experience of taking part in the 100,000 Genomes Project: • being invited to take part; • concerns about taking part; • reasons for wanting to take part; • deciding to take part; • sample storage; • data protection and sharing; • thoughts on medical research and genomic medicine; • messages for health professionals and Genomics England. This resource will be of interest and of use to healthcare professionals, policy makers and the general public.

This paper describes a technique that generates speech acoustics from articulator movements. Our motivation is to help people who can no longer speak following laryngectomy, a procedure that is carried out tens of thousands of times per year in the Western world. Our method for sensing articulator movement, permanent magnetic articulography, relies on small, unobtrusive magnets attached to the lips and tongue. Changes in magnetic field caused by magnet movements are sensed and form the input to a process that is trained to estimate speech acoustics. In the experiments reported here this “Direct Synthesis” technique is developed for normal speakers, with glued-on magnets, allowing us to train with parallel sensor and acoustic data. We describe three machine learning techniques for this task, based on Gaussian mixture models, deep neural networks, and recurrent neural networks (RNNs). We evaluate our techniques with objective acoustic distortion measures and subjective listening tests over spoken sentences read from novels (the CMU Arctic corpus). Our results show that the best performing technique is a bidirectional RNN (BiRNN), which employs both past and future contexts to predict the acoustics from the sensor data. BiRNNs are not suitable for synthesis in real time but fixed-lag RNNs give similar results and, because they only look a little way into the future, overcome this problem. Listening tests show that the speech produced by this method has a natural quality that preserves the identity of the speaker. Furthermore, we obtain up to 92% intelligibility on the challenging CMU Arctic material. To our knowledge, these are the best results obtained for a silent-speech system without a restricted vocabulary and with an unobtrusive device that delivers audio in close to real time. This work promises to lead to a technology that truly will give people whose larynx has been removed their voices back.

To compare administrative coverage data with results from household coverage surveys for vitamin A supplementation (VAS) and deworming campaigns conducted during 2010-2015 in 12 African countries.Paired t-tests examined differences between administrative and survey coverage for 52 VAS and 34 deworming dyads. Independent t-tests measured VAS and deworming coverage differences between data sources for door-to-door and fixed-site delivery strategies and VAS coverage differences between 6- to 11-month and 12- to 59-month age group.For VAS, administrative coverage was higher than survey estimates in 47 of 52 (90%) campaign rounds, with a mean difference of 16.1% (95% CI: 9.5-22.7; P 0.001). For deworming, administrative coverage exceeded survey estimates in 31 of 34 (91%) comparisons, with a mean difference of 29.8% (95% CI: 16.9-42.6; P 0.001). Mean ± SD differences in coverage between administrative and survey data were 12.2% ± 22.5% for the door-to-door delivery strategy and 25.9% ± 24.7% for the fixed-site model (P = 0.06). For deworming, mean ± SD differences in coverage between data sources were 28.1% ± 43.5% and 33.1% ± 17.9% for door-to-door and fixed-site distribution, respectively (P = 0.64). VAS administrative coverage was higher than survey estimates in 37 of 49 (76%) comparisons for the 6- to 11-month age group and 45 of 48 (94%) comparisons for the 12- to 59-month age group.Reliance on health facility data alone for calculating VAS and deworming coverage may mask low coverage and prevent measures to improve programmes. Countries should periodically validate administrative coverage estimates with population-based methods.

Total removal of the larynx may be required to treat laryn- geal cancer: speech is lost. This article shows that it may be possible to restore speech by sensing movement of the remaining speech articula- tors and use machine learning algorithms to derive a transformation to convert this sensor data into an acoustic signal. The resulting “silent speech,” which may be delivered in real time, is intelligible and sounds natural. The identity of the speaker is recognisable. The sensing tech- nique involves attaching small, unobtrusive magnets to the lips and tongue and monitoring changes in the magnetic field induced by their movement.

By speech articulator movement and training a transformation to audio we can restore the power of speech to someone who has lost their larynx. We sense changes in magnetic field caused by movements of small magnets attached to the lips and tongue. The sensor transformation uses recurrent neural networks.