Radiation-induced skin injury in the animal model of scleroderma: implications for post-radiotherapy fibrosis

<p>Abstract</p> <p>Background</p> <p>Radiation therapy is generally contraindicated for cancer patients with collagen vascular diseases (CVD) such as scleroderma due to an increased risk of fibrosis. The tight skin (TSK) mouse has skin which, in some respects, mimics that of patients with scleroderma. The skin radiation response of TSK mice has not been previously reported. If TSK mice are shown to have radiation sensitive skin, they may prove to be a useful model to examine the mechanisms underlying skin radiation injury, protection, mitigation and treatment.</p> <p>Methods</p> <p>The hind limbs of TSK and parental control C57BL/6 mice received a radiation exposure sufficient to cause approximately the same level of acute injury. Endpoints included skin damage scored using a non-linear, semi-quantitative scale and tissue fibrosis assessed by measuring passive leg extension. In addition, TGF-β1 cytokine levels were measured monthly in skin tissue.</p> <p>Results</p> <p>Contrary to our expectations, TSK mice were more resistant (i.e. 20%) to radiation than parental control mice. Although acute skin reactions were similar in both mouse strains, radiation injury in TSK mice continued to decrease with time such that several months after radiation there was significantly less skin damage and leg contraction compared to C57BL/6 mice (p < 0.05). Consistent with the expected association of transforming growth factor beta-1 (TGF-β1) with late tissue injury, levels of the cytokine were significantly higher in the skin of the C57BL/6 mouse compared to TSK mouse at all time points (p < 0.05).</p> <p>Conclusion</p> <p>TSK mice are not recommended as a model of scleroderma involving radiation injury. The genetic and molecular basis for reduced radiation injury observed in TSK mice warrants further investigation particularly to identify mechanisms capable of reducing tissue fibrosis after radiation injury.</p

PEDIA: prioritization of exome data by image analysis

Purpose Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. Methods Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. Results The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20–89% and the top 10 accuracy rate by more than 5–99% for the disease-causing gene. Conclusion Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

Bladder Sparing Approaches for Muscle-Invasive Bladder Cancers.

OPINION STATEMENT: Organ preservation has been increasingly utilised in the management of muscle-invasive bladder cancer. Multiple bladder preservation options exist, although the approach of maximal TURBT performed along with chemoradiation is the most favoured. Phase III trials have shown superiority of chemoradiotherapy compared to radiotherapy alone. Concurrent chemoradiotherapy gives local control outcomes comparable to those of radical surgery, but seemingly more superior when considering quality of life. Bladder-preserving techniques represent an alternative for patients who are unfit for cystectomy or decline major surgical intervention; however, these patients will need lifelong rigorous surveillance. It is important to emphasise to the patients opting for organ preservation the need for lifelong bladder surveillance as risk of recurrence remains even years after radical chemoradiotherapy treatment. No randomised control trials have yet directly compared radical cystectomy with bladder-preserving chemoradiation, leaving the age-old question of superiority of one modality over another unanswered. Radical cystectomy and chemoradiation, however, must be seen as complimentary treatments rather than competing treatments. Meticulous patient selection is vital in treatment modality selection with the success of recent trials within the field of bladder preservation only being possible through this application of meticulous selection criteria compared to previous decades. A multidisciplinary approach with radiation oncologists, medical oncologists, and urologists is needed to closely monitor patients who undergo bladder preservation in order to optimise outcomes

Preferences of the public for sharing health data: discrete choice experiment

Background: Digital technological development in the last 20 years has led to significant growth in digital collection, use, and sharing of health data. To maintain public trust in the digital society and to enable acceptable policy-making in the future, it is important to investigate people’s preferences for sharing digital health data. Objective: The aim of this study is to elicit the preferences of the public in different Northern European countries (the United Kingdom, Norway, Iceland, and Sweden) for sharing health information in different contexts. Methods: Respondents in this discrete choice experiment completed several choice tasks, in which they were asked if data sharing in the described hypothetical situation was acceptable to them. Latent class logistic regression models were used to determine attribute-level estimates and heterogeneity in preferences. We calculated the relative importance of the attributes and the predicted acceptability for different contexts in which the data were shared from the estimates. Results: In the final analysis, we used 37.83% (1967/5199) questionnaires. All attributes influenced the respondents’ willingness to share health information (P<.001). The most important attribute was whether the respondents were informed about their data being shared. The possibility of opting out from sharing data was preferred over the opportunity to consent (opt-in). Four classes were identified in the latent class model, and the average probabilities of belonging were 27% for class 1, 32% for class 2, 23% for class 3, and 18% for class 4. The uptake probability varied between 14% and 85%, depending on the least to most preferred combination of levels. Conclusions: Respondents from different countries have different preferences for sharing their health data regarding the value of a review process and the reason for their new use. Offering respondents information about the use of their data and the possibility to opt out is the most preferred governance mechanism

Dynamic Consent: a potential solution to some of the challenges of modern biomedical research

BACKGROUND: Innovations in technology have contributed to rapid changes in the way that modern biomedical research is carried out. Researchers are increasingly required to endorse adaptive and flexible approaches to accommodate these innovations and comply with ethical, legal and regulatory requirements. This paper explores how Dynamic Consent may provide solutions to address challenges encountered when researchers invite individuals to participate in research and follow them up over time in a continuously changing environment. METHODS: An interdisciplinary workshop jointly organised by the University of Oxford and the COST Action CHIP ME gathered clinicians, researchers, ethicists, lawyers, research participants and patient representatives to discuss experiences of using Dynamic Consent, and how such use may facilitate the conduct of specific research tasks. The data collected during the workshop were analysed using a content analysis approach. RESULTS: Dynamic Consent can provide practical, sustainable and future-proof solutions to challenges related to participant recruitment, the attainment of informed consent, participant retention and consent management, and may bring economic efficiencies. CONCLUSIONS: Dynamic Consent offers opportunities for ongoing communication between researchers and research participants that can positively impact research. Dynamic Consent supports inter-sector, cross-border approaches and large scale data-sharing. Whilst it is relatively easy to set up and maintain, its implementation will require that researchers re-consider their relationship with research participants and adopt new procedures