From research to practice: Enabling healthcare professionals to promote a physically activity lifestyle to people with spinal cord injury.

Objective: It is vital that people with spinal cord injury (SCI) maintain a physically active lifestyle for lifelong health and well-being. Yet within hospital rehabilitation and upon discharge from this context into the community, people with SCI are largely inactive. Physiotherapists are well placed to promote a physically active lifestyle and have been identified by people with SCI as valued and trusted messengers of physical activity (PA). The purpose of this study was to explore what physiotherapists in SCI rehabilitation perceive about PA for people with SCI and what they do in relation to promoting PA. Design: The design of this interpretive qualitative study was underpinned by ontological relativism (i.e., reality is multiple and created) and epistemological constructionism (i.e., knowledge is constructed and subjective). Method: Semi-structured interviews were completed with eighteen neurological physiotherapists (2-22 years’ experience) from SCI centres (United Kingdom and Ireland). An inductive thematic analysis was conducted. Results: Three themes were identified: 1) perceived importance of physical activity; 2) inconsistent physical activity promotion efforts; and 3) unease with activity-based rehabilitation. Together these themes reveal that although physiotherapists do value PA, active promotion of PA remains largely absent from what they do. Conclusions: This study contributes to the exercise psychology literature by identifying the need for PA promotion to be a structured and integral component of physiotherapy practice. SCI specific PA guidelines must be developed and communicated via appropriate knowledge translation strategies to enable physiotherapists to effectively promote a physically active lifestyle

Stories of hope or hopeful stories? Reflections on ethical dilemmas in spinal cord injury rehabilitation and physical activity

Ethical considerations in ethnographic research are not something to be ticked off once clearance is granted by the ethics committee. Rather, ethical considerations should remain at the forefront of the researcher’s mind as they face numerous ethical dilemmas throughout the course of a study. Ethics in practice should therefore be considered as a process of on-going maintenance and reflexivity. This paper draws upon the importance of reflexive ethics to highlight how broad procedural ethics considered at the beginning of a research project continue to inform ethical dilemmas as they arise during data collection and analysis. Ethical dilemmas encountered in a physical activity rehabilitation centre for people with spinal cord injury will be reflected upon to offer insights into negotiating the researcher’s desire to gain rich descriptions, whilst caring for the participants’ well-being. These dilemmas will include managing the expectations of the research project and negotiating delicate issues in spinal cord injury rehabilitation such as recovery and hope

A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer

A common characteristic of environmental epidemiology is the multi-dimensional aspect of exposure patterns, frequently reduced to a cumulative exposure for simplicity of analysis. By adopting a flexible Bayesian clustering approach, we explore the risk function linking exposure history to disease. This approach is applied here to study the relationship between different smoking characteristics and lung cancer in the framework of a population based case control study

Narrative constructions of anorexia and abuse: An athlete's search for meaning in trauma

Interpretive approaches to the study of eating disorders are scarce. Narrative analysis provides an attractive means to address this shortfall and is applied to the life story of Beth, a former elite athlete with experience of anorexia nervosa and, as she revealed, sexual abuse. Six unstructured life history interviews took place yielding more than 9 hours of interview data. Throughout our conversations, Beth constructed multiple, fragile, and sometimes contrasting narrative coherences indicative of a fragmented and uncertain understanding of her life. It is argued that how Beth makes sense of her trauma is consequential for her future experiences

SDHA related tumorigenesis: a new case series and literature review for variant interpretation and pathogenicity

Purpose To evaluate the role of germline SDHA mutation analysis by (1) comprehensive literature review, (2) description of novel germline SDHA mutations and (3) in silico structural prediction analysis of missense substitutions in SDHA. Patients and methods A systematic literature review and a retrospective review of the molecular and clinical features of patients identified with putative germline variants in UK molecular genetic laboratories was performed. To evaluate the molecular consequences of SDHA missense variants, a novel model of the SDHA/B/C/D complex was generated and the structural effects of missense substitutions identified in the literature, our UK novel cohort and a further 32 “control missense variants” were predicted by the mCSM computational platform. These structural predictions were correlated with the results of tumor studies and other bioinformatic predictions. Results Literature review revealed reports of 17 different germline SDHA variants in 47 affected individuals from 45 kindreds. A further 10 different variants in 15 previously unreported cases (seven novel variants in eight patients) were added from our UK series. In silico structural prediction studies of 11 candidate missense germline mutations suggested that most (63.7%) would destabilize the SDHA protomer, and that most (78.1%) rare SDHA missense variants present in a control data set (ESP6500) were also associated with impaired protein stability. Conclusion The clinical spectrum of SDHA-associated neoplasia differs from that of germline mutations in other SDH-subunits. The interpretation of the significance of novel SDHA missense substitutions is challenging. We recommend that multiple investigations (e.g. tumor studies, metabolomic profiling) should be performed to aid classification of rare missense variants before genetic testing results are used to influence clinical management.We thank the following funding agencies NIHR (RC, ER, GC and ERM), European Research Council Advanced Researcher Award (ERM), the Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) (DBA and DEVP), Fundaçao de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) (MR/M026302/1) (DEVP), NHMRC CJ Martin Fellowship (APP1072476) (DBA), Boehringer Ingelheim Fonds PhD Fellowship (RS) and the British Heart Foundation (GC, ERM), Sanofi Endocrinology Research Bursary Award (RC). GIST Support UK. (RG86004) (RC

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland

Metabolomics, machine learning and immunohistochemistry to predict succinate dehydrogenase mutational status in phaeochromocytomas and paragangliomas

Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours with a hereditary background inover one-third of patients. Mutations in succinate dehydrogenase (SDH) genes increase the risk for PPGLs and severalother tumours. Mutations in subunit B (SDHB) in particular are a risk factor for metastatic disease, further highlight-ing the importance of identifying SDHx mutations for patient management. Genetic variants of unknown signi-cance, where implications for the patient and family members are unclear, are a problem for interpretation. Forsuch cases, reliable methods for evaluating protein functionality are required. Immunohistochemistry for SDHB(SDHB-IHC) is the method of choice but does not assess functionality at the enzymatic level. Liquid chromatogra-phy–mass spectrometry-based measurements of metabolite precursors and products of enzymatic reactions providean alternative method. Here, we compare SDHB-IHC with metabolite proling in 189 tumours from 187 PPGLpatients. Besides evaluating succinate:fumarate ratios (SFRs), machine learning algorithms were developed to estab-lish predictive models for interpreting metabolite data. Metabolite proling showed higher diagnostic specicitycompared to SDHB-IHC (99.2% versus 92.5%, p = 0.021), whereas sensitivity was comparable. Application of machine learning algorithms to metabolite proles improved predictive ability over that of the SFR, in particular forhard-to-interpret cases of head and neck paragangliomas (AUC 0.9821 versus 0.9613, p = 0.044). Importantly, thecombination of metabolite proling with SDHB-IHC has complementary utility, as SDHB-IHC correctly classied allbut one of the false negatives from metabolite proling strategies, while metabolite proling correctly classied allbut one of the false negatives/positives from SDHB-IHC. From 186 tumours with conrmed status of SDHx variantpathogenicity, the combination of the two methods resulted in 185 correct predictions, highlighting the benets ofboth strategies for patient management