Predicting best treatment in rheumatoid arthritis

BACKGROUND: Although targeted biological treatments have transformed the outlook for patients with rheumatoid arthritis (RA), 40% of patients show poor clinical response, and there is an imperative to unravel the molecular pathways and mechanisms underlying non-response and disease progression. 5-20% of RA individuals do not respond to all current medications including biologic and targeted therapies, which suggests that distinct pathogenic processes underlie multi-drug refractoriness. OBJECTIVES: In this brief review we discuss advances from recent studies in precision medicine in rheumatoid arthritis. METHODS: Bulk RNA-Sequencing of synovial biopsies from RA individuals combined with histology and deep clinical phenotyping has revealed substantial insights into divergent pathogenic pathways which lead to disease progression and illuminated mechanisms underlying failure to response to specific treatments. Biopsy-driven randomised controlled trials, such as R4RA and the forthcoming STRAP trial, have enabled the development of machine learning predictive models for predicting response to different therapies. RESULTS: In the Pathobiology of Early Arthritis Cohort (PEAC), gene expression analysis showed that individuals could be classified into three gene expression subgroups which correlated with histopathotypes defined by histological markers: pauci-immune fibroid pathotype characterised by fibroblasts and an absence of immune inflammatory cells; diffuse-myeloid pathotype characterised by macrophage influx; and the lympho-myeloid pathotype delineated by the presence of B cells, but typically containing a complex inflammatory infiltrate with ectopic lymphoid structure formation. In the R4RA biopsy-driven randomised controlled trial, patients were randomised to either rituximab or tocilizumab. Comprehensive analysis of synovial biopsies pre/post-treatment identified gene signatures of response associated with pathogenic pathways which could be tracked over time. A group of true refractory patients were identified who had failed anti-TNF prior to the study (it was an entry criterion) and then subsequently failed both trial biologics during the trial. RNA-Seq analysis and digital spatial profiling identified specific cell types including DKK3+ fibroblasts as being associated with the refractory state. We identified machine learning predictive models based on specific gene signatures which were able to predict future response to therapy as well as the refractory state. CONCLUSIONS: RNA-sequencing of synovial biopsies has enabled substantial progress in understanding disease endotypes in RA and identifying synovial gene signatures which predict prognosis and future response to treatment

Consent for the use of human biological samples for biomedical research: a mixed methods study exploring the UK public’s preferences

OBJECTIVE: A mixed-methods study exploring the UK general public's views towards consent for the use of biosamples for biomedical research.<p></p> SETTING: Cross-sectional population-based focus groups followed by an online survey.<p></p> PARTICIPANTS: 12 focus groups (81 participants) selectively sampled to reflect a range of demographic groups; 1110 survey responders recruited through a stratified sampling method with quotas set on sex, age, geographical location, socioeconomic group and ethnicity.<p></p> MAIN OUTCOME MEASURES: (1) Views on the importance of consent when donating residual biosamples for medical research; (2) preferences for opt-in or opt-out consent approaches and (3) preferences for different consent models.<p></p> RESULTS: Participants believed obtaining consent for use of residual biosamples was important as it was 'morally correct' to ask, and enabled people to make an active choice and retain control over their biosamples. Survey responders preferred opt-in consent (55%); the strongest predictor was being from a low socioeconomic group (OR 2.22, 95% CI 1.41 to 3.57, p=0.001) and having a religious affiliation (OR 1.36, 95% CI 1.01 to 1.81, p=0.04). Focus group participants had a slight preference for opt-out consent because by using this approach more biosamples would be available and facilitate research. Concerning preferred models of consent for research use of biosamples, survey responders preferred specific consent with recontact for each study for which their biosamples are eligible. Focus group participants preferred generic consent as it provided 'flexibility for researchers' and reduced the likelihood that biosamples would be wasted. The strongest predictor for preferring specific consent was preferring opt-in consent (OR 4.58, 95% CI 3.30 to 6.35, p=0.015) followed by non-'White' ethnicity (OR 2.94, 95% CI 1.23 to 7.14, p<0.001).<p></p> CONCLUSIONS: There is a preference among the UK public for ongoing choice and control over donated biosamples; however, increased knowledge and opportunity for discussion is associated with acceptance of less restrictive consent models for some people.<p></p&gt

The role of the environment in eliciting phantom-like sensations in non-amputees

Following the amputation of a limb, many amputees report that they can still vividly perceive its presence despite conscious knowledge that it is not physically there. However, our ability to probe the mental representation of this experience is limited by the intractable and often distressing pain associated with amputation. Here, we present a method for eliciting phantom-like experiences in non-amputees using a variation of the rubber hand illusion in which a finger has been removed from the rubber hand. An interpretative phenomenological analysis revealed that the structure of this experience shares a wide range of sensory attributes with subjective reports of phantom limb experience. For example, when the space where the ring finger should have been on the rubber hand was stroked, 93% of participants (i.e., 28/30) reported the vivid presence of a finger that they could not see and a total of 57% (16/28) of participants who felt that the finger was present reported one or more additional sensory qualities such as tingling or numbness (25%; 7/28) and alteration in the perceived size of the finger (50%; 14/28). These experiences indicate the adaptability of body experience and share some characteristics of the way that phantom limbs are described. Participants attributed changes to the shape and size of their “missing” finger to the way in which the experimenter mimed stroking in the area occupied by the missing finger. This alteration of body perception is similar to the phenomenon of telescoping experienced by people with phantom limbs and suggests that our sense of embodiment not only depends on internal body representations but on perceptual information coming from peripersonal space

The Potential of Conductivity, Redox Potential and Dissolved Oxygen in Raw Milk Quality Prediction

Changes in milk quality are associated with changes in dissolved oxygen (DO), redox potential (Eh) and conductivity (Co) reflecting the potential of these parameters in quality prediction. However, limited interpretation of those changes/results limits the application of the same in raw milk quality prediction. The aim of this study was therefore to explore the potential of DO, Eh and Co in milk quality assessment. Raw milk, lactoperoxidase system (LP-s) activated raw milk and LP-s activated Ultra High Temperature (UHT) milk inoculated singly with pure strains were used in this study. The performances of DO, Eh and Co in quality prediction were assessed against the objective methods: pH, titratable acidity (TA), alcohol stability test (AST), clot on boiling (COB), dye reduction tests and total viable counts (TVC). The results showed that any negative Eh value, a Co value greater than the initial Co value and DO around zero or below detection limit all indicated spoilage. These corresponded well with increases in microbial numbers indicative of spoilage recorded at about 7 log cycles of bacterial counts.  Co and Eh were in consistent agreement in quality estimate with AST and TA but more sensitive than COB and pH. On the other hand, DO showed similar sensitivity as COB and pH but was more lenient than AST and TA. The results generally confirmed the suitability of DO and Eh for routine analysis in both normal and LP-s activated milk; however, the use of Co requires a prior knowledge of the initial Co value of milk under test which complicates its use in routine analysis.Key words: Quality prediction, conductivity, redox potential, dissolved oxyge

Small vessel vasculitis and dry gangrene secondary to combined CTLA-4 and PD-1 blockade in malignant mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive tumour with an overall poor prognosis. In October 2020, first line treatment with the PD-1 antagonist nivolumab and the CTLA-4 antagonist ipilimumab for unresectable disease was FDA approved-the first approved treatment regime since 2004. Interim analyses from the phase 3 CHECKMATE-743 study shows improvements in overall survival. Skin-related toxicities are the most commonly reported any-grade treatment-related adverse event from combined nivolumab and ipilimumab therapy. CASE PRESENTATION: Here we report a case of a 35-year-old white male who developed digital ischaemia secondary to small vessel vasculitis after receiving PD-1 and CTLA-4 blockade therapy for MPM. His progressive ischaemia became gangrenous, and he required multi-speciality input and treatment with prednisolone, prostacyclin, mycophenolate mofetil and hydroxychloroquine. CONCLUSIONS: Our case highlights the importance of early detection, intervention, and a multispecialty approach to managing such complications in order to minimise the associated morbidity and mortality

The contribution of nature to people: applying concepts of values and properties to rate the management importance of natural elements

An important, and yet unresolved question in natural resource management is how best to manage natural elements and their associated values to ensure human wellbeing. Specifically, there is a lack of measurement tools to assess the contribution of nature to people. We present one approach to overcome this global issue and show that the preferred state of any system element, in terms of realising human values, is a function of element properties. Consequently, natural resource managers need to understand the nature of the relationships between element properties and values if they are to successfully manage for human wellbeing. In two case studies of applied planning, we demonstrate how to identify key element properties, quantify their relationships to priority human values, and combine this information to model the contribution of elements to human wellbeing. In one of the two case studies we also compared the modelling outputs with directly elicited stakeholder opinions regarding the importance of the elements for realising the given priority values. The two, largely congruent outputs provide additional support for the approach. The study shows that rating sets of elements on their relative overall value for human wellbeing, or utility, provides critical information for subsequent management decisions and a basis for productive new research. We consider that the described approach is broadly applicable within the domain of natural resource management

Establishing consensus of position-specific predictors for elite youth soccer in England

Purpose: To construct a valid and reliable methodology for the development of position- specific predictors deemed appropriate for talent identification purposes within elite youth soccer in England. Method: N = 10 experts participated in a three-step modified e-Delphi poll to generate consensus on a series of generic youth player attributes. A follow up electronic survey completed by coaches, scouts and recruitment staff (n = 99) ranked these attributes to specific player- positions. Results: A final list of 44 player attributes found consensus using the three-step modified e-Delphi poll and the findings indicated that player-positional attributes considered most important at the youth phase are more psychological and technical than physiological or anthropometric. Despite ‘hidden’ attributes (e.g. coachability, flair, versatility, vision etc) finding consensus on the e-Delphi poll, there was no evidence to support these traits when associated with a specific playing position. Conclusion: For those practitioners responsible for talent recruitment, our findings may provide greater understanding of the multiple attributes required for some playing positions. However, new ecological research is required to assess the veracity of our claims

Can Appreciative Inquiry give primary school children voice and influence over their writing lessons? An exploratory multiple case study of three classes of primary children and their teachers using Appreciative Inquiry (AI) to: facilitate pupil participation; create new learning experiences in writing lessons; and help to evaluate the AI process in schools

This multiple case study explored the potential for Appreciative Inquiry (AI) to give three classes of primary children voice and influence over decisions that affect their learning, and facilitated their involvement in evaluating AI. Using mixed methods, it examined changes in: children and teachers’ beliefs about the value of pupil participation; curriculum activities for writing; and children’s attitudes, progress and attainment. The children and teachers suggested improvements to the AI process so that it can be as inclusive as possible. The results indicated that AI has the potential to shift the culture of pupil participation in the class, but needs time (and good timing) to be effective. Children devised innovative curriculum activities, often for real purposes, which were highly motivating and engaging. However, standardised measures of pupil attitudes and attainment provided no evidence of positive change. An important finding from the children was how challenging group work can be within AI, especially for children with Special Educational Needs and Disability (SEND). This study makes an original contribution to the literature on pupil participation and AI, with the expectation that the AI process may now be developed further within schools

Comparison between Suitable Priors for Additive Bayesian Networks

Additive Bayesian networks are types of graphical models that extend the usual Bayesian generalized linear model to multiple dependent variables through the factorisation of the joint probability distribution of the underlying variables. When fitting an ABN model, the choice of the prior of the parameters is of crucial importance. If an inadequate prior - like a too weakly informative one - is used, data separation and data sparsity lead to issues in the model selection process. In this work a simulation study between two weakly and a strongly informative priors is presented. As weakly informative prior we use a zero mean Gaussian prior with a large variance, currently implemented in the R-package abn. The second prior belongs to the Student's t-distribution, specifically designed for logistic regressions and, finally, the strongly informative prior is again Gaussian with mean equal to true parameter value and a small variance. We compare the impact of these priors on the accuracy of the learned additive Bayesian network in function of different parameters. We create a simulation study to illustrate Lindley's paradox based on the prior choice. We then conclude by highlighting the good performance of the informative Student's t-prior and the limited impact of the Lindley's paradox. Finally, suggestions for further developments are provided.Comment: 8 pages, 4 figure