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Immersive learning practices (ILPs) in higher education are multidisciplinary in nature and varied in levels of integration into the student learning process. They appear in a variety of higher education programs such as teacher education, social work, law, and health sciences, and in practices such as service-learning, study away, internships, and foreign-language instruction. Based on observations of teaching and data from an open-ended survey and semi-structured interviews with post-secondary educators from three different countries, this study theorizes that immersive learning practices are composed of six distinct underlying theoretical components that work in combination. These six components can be used to describe, define, compare, and design different types of structured ILPs. This study suggests that ILPs are pedagogically distinct from other forms of engaged and experiential learning.

Abstract Embedding precision medicine in paediatric oncology shows promise to have a positive impact on how children with cancer will be treated in the future. While there are a number of studies of precision medicine in childhood cancer, there is limited evidence available on the cost of implementing the related testing. This is the first Australian study that systematically measures the cost of using precision medicine in the care of high-risk childhood cancers, through the Zero Childhood Cancer Precision Medicine Programme. In 2021 Australian dollars, the estimated costs inclusive of genomic and preclinical testing were: (A) $12,743 per patient for access; (B) $14,262 per identification of molecular cause; and (C) $21,769 per MTB recommendation. The information gained supports the understanding of the cost of reporting clinically significant outcomes relevant to the biology of the tumour, diagnosis, prognosis and potentially improving clinical management for a child.

Abstract In this community effort, we compare measurements between 34 laboratories from 19 countries, utilizing mixtures of labelled authentic synthetic standards, to quantify by mass spectrometry four clinically used ceramide species in the NIST (National Institute of Standards and Technology) human blood plasma Standard Reference Material (SRM) 1950, as well as a set of candidate plasma reference materials (RM 8231). Participants either utilized a provided validated method and/or their method of choice. Mean concentration values, and intra- and inter-laboratory coefficients of variation (CV) were calculated using single-point and multi-point calibrations, respectively. These results are the most precise (intra-laboratory CVs ≤ 4.2%) and concordant (inter-laboratory CVs < 14%) community-derived absolute concentration values reported to date for four clinically used ceramides in the commonly analyzed SRM 1950. We demonstrate that calibration using authentic labelled standards dramatically reduces data variability. Furthermore, we show how the use of shared RM can correct systematic quantitative biases and help in harmonizing lipidomics. Collectively, the results from the present study provide a significant knowledge base for translation of lipidomic technologies to future clinical applications that might require the determination of reference intervals (RIs) in various human populations or might need to estimate reference change values (RCV), when analytical variability is a key factor for recall during multiple testing of individuals.

Background: Machine learning models can provide quick and reliable assessments in place of medical practitioners. With over 50 million adults in the United States suffering from osteoarthritis, there is a need for models capable of interpreting musculoskeletal ultrasound images. However, machine learning requires lots of data, which poses significant challenges in medical imaging. Therefore, we explore two strategies for enriching a musculoskeletal ultrasound dataset independent of these limitations: traditional augmentation and diffusion-based image synthesis. Methods: First, we generate augmented and synthetic images to enrich our dataset. Then, we compare the images qualitatively and quantitatively, and evaluate their effectiveness in training a deep learning model for detecting thickened synovium and knee joint recess distension. Results: Our results suggest that synthetic images exhibit some anatomical fidelity, diversity, and help a model learn representations consistent with human opinion. In contrast, augmented images may impede model generalizability. Finally, a model trained on synthetically enriched data outperforms models trained on un-enriched and augmented datasets. Conclusions: We demonstrate that diffusion-based image synthesis is preferable to traditional augmentation. Our study underscores the importance of leveraging dataset enrichment strategies to address data scarcity in medical imaging and paves the way for the development of more advanced diagnostic tools.

Abstract The ability to image early treatment response to radiotherapy in head and neck squamous cell carcinoma (HNSCC) will enable the identification of radioresistant tumor volumes suitable for treatment intensification. Here, we propose the system xc − radiotracer (4S)-4-(3-[18F]fluoropropyl)-L-glutamate ([18F]FSPG) as a non-invasive method to monitor radiation response in HNSCC. We assessed temporal changes in cell death, antioxidant status, and [18F]FSPG retention following a single dose of 10 Gy irradiation in FaDU HNSCC cells. Next, using a fractionated course of radiotherapy, we assessed tumor volume changes and performed [18F]FSPG-PET imaging in FaDU-bearing mouse xenografts, followed by ex vivo response assessment. In cells, 10 Gy irradiation reduced [18F]FSPG retention, coinciding with the induction of apoptosis and the production of reactive oxygen species. In vivo, [18F]FSPG tumor retention was halved seven days after the start of treatment, which preceded radiotherapy-induced tumor shrinkage, thereby confirming [18F]FSPG-PET as an early and sensitive marker of radiation response.

Abstract Background The majority of persons with dementia (PWD) are mainly cared for by their family members in the home. Evidence is however scarce on family caregivers’ psychosocial burden and quality of life in Asian countries including Malaysia. This study describes the baseline data of a telephone-delivered psychoeducational intervention study and examines the determinants of outcome measures (caregiver burden, depressive and anxiety symptoms, quality of life and caregiving self-efficacy) among Malaysian family caregivers to PWD. Methods This was a cross-sectional study originated from the baseline survey of a randomized control trial of 121 family caregivers recruited from lists of PWD who were registered at memory and psychiatry clinics in three tertiary care hospitals in Malaysia. The participants were assessed for caregiver burden by the Zarit Burden Interview, depressive and anxiety symptoms by the Hospital Anxiety and Depression Scale, quality of life by the Control, Autonomy, Self-Realization, and Pleasure Scale, and caregiving self-efficacy by the Revised Scale for Caregiving Self-Efficacy. Results Prevalence of caregiver burden was 69.4%, depressive symptoms 32.2% and anxiety symptoms 32.2%. Family caregivers to PWD having perceived peer support e.g., social/family/friend/significant other supports were less likely to report caregiver burden, depressive and anxiety symptoms, and more likely to report higher levels of quality of life and caregiving self-efficacy. Being married and PWD’s ability to self-care were associated with lesser likelihood of experiencing caregiver burden, depressive and anxiety symptoms. The other determinants of greater probability of reporting better quality of life were caregivers’ employment and having Islamic faith. Marital status (married), PWD’s ability to self-care, spousal relationship with PWD and shared caregiving process were associated with higher likelihood of reporting caregiving self-efficacy. Conclusion Caregiver burden, depressive and anxiety symptoms are prevalent in family caregivers to PWD in Malaysia. Social support and caregiving related factors influence family caregivers’ quality of life and caregiving self-efficacy. Implementing psychoeducational intervention and support in the psychiatry and memory clinics may help improve the psychosocial burden, quality of life and caregiving self-efficacy in family caregivers of PWD. Trial registration ISRCTN14565552 (retrospectively registered).

In recent years, Artificial Intelligence has been used to assist healthcare professionals in detecting and diagnosing neurodegenerative diseases. In this study, we propose a methodology to analyze functional Magnetic Resonance Imaging signals and perform classification between Parkinson’s disease patients and healthy participants using Machine Learning algorithms. In addition, the proposed approach provides insights into the brain regions affected by the disease. The functional Magnetic Resonance Imaging from the PPMI and 1000-FCP datasets were pre-processed to extract time series from 200 brain regions per participant, resulting in 11,600 features. Causal Forest and Wrapper Feature Subset Selection algorithms were used for dimensionality reduction, resulting in a subset of features based on their heterogeneity and association with the disease. We utilized Logistic Regression and XGBoost algorithms to perform PD detection, achieving 97.6% accuracy, 97.5% F1 score, 97.9% precision, and 97.7%recall by analyzing sets with fewer than 300 features in a population including men and women. Finally, Multiple Correspondence Analysis was employed to visualize the relationships between brain regions and each group (women with Parkinson, female controls, men with Parkinson, male controls). Associations between the Unified Parkinson’s Disease Rating Scale questionnaire results and affected brain regions in different groups were also obtained to show another use case of the methodology. This work proposes a methodology to (1) classify patients and controls with Machine Learning and Causal Forest algorithm and (2) visualize associations between brain regions and groups, providing high-accuracy classification and enhanced interpretability of the correlation between specific brain regions and the disease across different groups.

Abstract Tree-thinking is a fundamental skill set for understanding evolutionary theory and, thus, part of biological and scientific literacy. Research on this topic is mostly directed towards tree-reading—the umbrella-term for all skills enabling a person to gather and infer information from a given tree. Tree-building or phylogenetic inference as the second complementary sub-skill-set, encompassing all skills which enable a person to build a phylogenetic tree from given data, is not understood as well. To understand this topic we conducted think-aloud-tasks with tree-building experts and conducted supplementary guided interviews with them. We used school-like character tables, as they are common in high schools for the experts to build trees and audio-recorded their speech while building the trees. Analyzing the transcripts of the tasks we could find a basic methodology for building trees and define a set of backbone-skills of tree-building. Those are based on an iterative cycle going through phases of organizing information, searching and setting taxa/characters, organizing and checking oneself. All experts used simple guidelines, either deploying maximum parsimony to arrive at a solution or relying heavily on their previous knowledge. From that, we were able to utilize our result to formulate a guideline and helpful suggestions especially for beginners and novices in the field of tree-building to develop a better understanding of this topic.

Abstract Background The majority of persons with dementia in Sweden reside in their own homes with support from family members. Approximately, 12% of persons with dementia have immigrant background. Within the next 20 years, the number of persons with dementia who are non-ethnic Swedes is said to double. Family caregivers with immigrant backgrounds are noted to receive less support in the community than ethnic Swedes and rate their health status lower than ethnic Swedish peers. The Swedish National Board of Health and Welfare have highlighted the importance of follow-up support for family caregivers with immigrant backgrounds as there is a recognized gap in research and available information tailored to meet the needs of this group. Purpose of the study The purpose of the study is to test effectiveness of an mHealth based intervention through which community social workers can improve caregiving competence of non-European immigrant family caregivers of people with dementia living at home in Sweden. The overarching aim is to reduce caregiver burden and depressive symptoms, and improve quality of life. Methods A randomized controlled trial (RCT) including wait list control group will be performed consisting of an intervention group (A, n = 44) and a wait list control group (B, n = 44), totaling a sample size of 88. On completion of the 10-weeks long intervention in the intervention group, the intervention will be delivered to group B. Effect of the intervention will be analyzed between and within groups over time. The content of the educational component of the intervention is inspired by the iSupport manual developed by the World Health Organization. The contents, in the form of a booklet, aims to equip the family caregivers with structured information on understanding dementia as a condition and its management at home, including self-care guidance designed specifically for family caregivers themselves. Discussion Similar telephone-delivered intervention studies targeted for family caregivers to persons with dementia are ongoing in Malaysia and will start in India using the same booklet adapted to the local context. These studies will provide evidence on the effectiveness of using digital technologies to deliver support to those who may not be reached or adequately served by the traditional healthcare system. Trial registration ISRCTN registry, Registration number ISRCTN64235563.

Abstract Background This study evaluates longitudinal associations between glycaemic control, measured by mean and within-patient variability of glycated haemaglobin (HbA1c) levels, and major depressive disorder (MDD) in individuals with type 2 diabetes (T2D), focusing on the timings of these diagnoses. Methods In UK Biobank, T2D was defined using self-report and linked health outcome data, then validated using polygenic scores. Repeated HbA1c measurements (mmol/mol) over the 10 years following T2D diagnosis were outcomes in mixed effects models, with disease duration included using restricted cubic splines. Four MDD exposures were considered: MDD diagnosis prior to T2D diagnosis (pre-T2D MDD), time between pre-T2D MDD diagnosis and T2D, new MDD diagnosis during follow-up (post-T2D MDD) and time since post-T2D MDD diagnosis. Models with and without covariate adjustment were considered. Results T2D diagnostic criteria were robustly associated with T2D polygenic scores. In 11,837 T2D cases (6.9 years median follow-up), pre-T2D MDD was associated with a 0.92 increase in HbA1c (95% CI: [0.00, 1.84]), but earlier pre-T2D MDD diagnosis correlated with lower HbA1c. These pre-T2D MDD effects became non-significant after covariate adjustment. Post-T2D MDD individuals demonstrated increasing HbA1c with years since MDD diagnosis ( $$\beta =0.51$$ β = 0.51 , 95% CI: [0.17, 0.86]). Retrospectively, across study follow-up, within-patient variability in HbA1c was 1.16 (95% CI: 1.13–1.19) times higher in post-T2D MDD individuals. Conclusions The timing of MDD diagnosis is important for understanding glycaemic control in T2D. Poorer control was observed in MDD diagnosed post-T2D, highlighting the importance of depression screening in T2D, and closer monitoring for individuals who develop MDD after T2D.

Abstract Background Apparently healthy dogs of various breeds eating nontraditional, high‐pulse diets can have larger left ventricular diameter, lower systolic function, and more ventricular premature complexes (VPCs) compared with dogs eating traditional, low‐pulse diets. It is unknown whether Irish Wolfhounds eating high‐pulse diets have similar cardiac abnormalities. Hypothesis/Objectives To compare electrocardiographic and echocardiographic findings between Irish Wolfhounds eating high‐ or low‐pulse diets. Animals Ninety‐seven Irish Wolfhounds. Methods Retrospective study of Irish Wolfhounds that had echocardiography performed at dog shows between October 2018 and May 2021. Demographic information, echocardiographic measurements, cardiac rhythm (1‐minute lead II rhythm strip), and main diet were recorded retrospectively. Diets were classified as high‐pulse or low‐pulse based on the presence and location of pulses (peas, lentils, chickpeas, or dry beans) on the ingredient list. Results Thirty‐five of 97 Irish Wolfhounds (36%) were eating high‐pulse diets and 62 of 97 (64%) were eating low‐pulse diets. There were no significant differences between diet groups in echocardiographic measurements. A significantly higher percentage of dogs in the high‐pulse diet group (6/35 [17%]) had VPCs compared with those in the low‐pulse diet group (1/62 [2%]; effect size = 0.15 [95% confidence interval: 0.004‐0.31]; P = .005). Conclusions and Clinical Importance In this retrospective study of apparently healthy Irish Wolfhounds, high‐pulse diets were associated with a higher prevalence of VPCs which could represent early cardiac abnormalities.

Objective: The aim of research is to provide greater understanding of ADHD in adult females by exploring first-hand experiences of female university students with ADHD in the UK, and the impact of such experiences on social, academic, and psychological functioning. Methods: Semi-structured interviews were conducted with eight adult women attending university in the UK--all clinically diagnosed with ADHD during adulthood. Results: Participants experiences were rich and insightful, identifying that many women with ADHD experience stigmatization and social discrimination, amongst other social, academic, and psychological difficulties. Conclusion: Overall, the research identifies the pressing need for greater understanding and appreciation of ADHD in females, particularly amongst health professionals.

Wildfire events are becoming more frequent and severe on a global scale. Rising temperatures, prolonged drought, and the presence of pyrophytic invasive grasses are contributing to the degradation of native vegetation communities. Within the Great Basin region of the western U.S., increasing wildfire frequency is transforming the ecosystem toward a higher degree of homogeneity, one dominated by invasive annual grasses and declining landscape productivity. Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are a species of conservation concern that rely on large tracts of structurally and functionally diverse sagebrush (Artemisia spp.) communities. Using a 12-year (2008-2019) telemetry dataset, we documented immediate impacts of wildfire on demographic rates of a population of sage-grouse that were exposed to two large wildfire events (Virginia Mountains Fire Complex-2016; Long Valley Fire-2017) near the border of California and Nevada. Spatiotemporal heterogeneity in demographic rates were accounted for using a Before-After Control-Impact Paired Series (BACIPS) study design. Results revealed a 40% reduction in adult survival and a 79% reduction in nest survival within areas impacted by wildfires. Our results indicate that wildfire has strong and immediate impacts to two key life stages of a sagebrush indicator species and underscores the importance of fire suppression and immediate restoration following wildfire events.