Digital Commons Network^™

Smart Medical System Integrating Clinical Workflows For Robust Skin Cancer Detection Across Heterogeneous Pathologies, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

All Works

Skin cancer is among the most prevalent and life-threatening dermatological diseases worldwide, with melanoma responsible for a substantial proportion of skin cancer–related deaths due to delayed and unreliable diagnosis. Conventional clinical screening based on visual inspection and expert interpretation is inherently subjective and often affected by inter-observer variability, lesion heterogeneity, and imaging artifacts, highlighting the need for accurate and generalizable automated diagnostic systems. This study proposes a novel hybrid deep learning architecture for skin cancer classification that integrates an attention-guided autoencoder with a transformer-inspired global context modeling module, forming a unified and robust representation learning framework. The encoder–decoder structure is …

Temporally Rigorous And Traceable Predictive Maintenance Via Joint Labeler-Model Optimization, Maytha Al-Ali, Ahmad Alharbi

All Works

Predictive maintenance (PdM) is a critical enabler of intelligent asset management in Industry 4.0, yet many existing frameworks remain difficult to operationalize due to methodological fragmentation. Common limitations include sacrificing temporal realism and class granularity for computational expediency, decoupling labeling strategy design from model hyperparameter optimization, and insufficient support for reproducibility and deployment traceability; particularly in rare-failure regimes. To address these challenges, we propose a unified, end-to-end, and fully traceable PdM framework that jointly optimizes labeling and model parameters while enforcing strict temporal fidelity. The proposed pipeline co-optimizes the failure lookahead window () and LightGBM hyperparameters within a single Bayesian …

Kindergarten Teachers’ Perceptions Of Instructional Approaches For Teaching Sequencing Concepts: Worksheet, Hands-On, And Beebot-Integrated Lessons, Savannah P. Partin

Electronic Theses and Dissertations

The purpose of this qualitative multiple-case study was to explore kindergarten teachers’ perceptions of three instructional approaches for teaching sequencing concepts: worksheet-based instruction, hands-on manipulative instruction, and BeeBot-integrated instruction. Sequencing is a foundational early literacy skill that supports reading comprehension, story retelling, and understanding the order of events. Although sequencing is commonly taught through traditional instructional methods, limited research has examined how kindergarten teachers perceive the use of educational robotics as a tool for literacy instruction. The study was guided by constructivist theory, sociocultural theory, and developmental systems theory. Participants included six kindergarten teachers from a public elementary school in …

Understanding The Out-Of-Distribution Generalization Of Chain-Of-Thought Reasoning In Llms, Nuojing Liang, Xiaotong Yuan, Pan Zhou

Research Collection School Of Computing and Information Systems

Chain-of-Thought (CoT) reasoning substantially improves Large Language Models (LLMs), yet its out-of-distribution (OOD) generalization mechanism remains theoretically underexplored. We study CoT as compositional OOD generalization: the target task lacks complete reasoning trajectories or direct input-output pairs, while training provides only in-distribution (ID) atomic step data. We show that CoT generalizes by repeatedly applying a shared single-step predictor to compose reusable ID transitions. Theoretically, the OOD task risk is controlled by the sum of ID subtask risks, scaled by a depth-independent hard-decoding coefficient Bℓ b = O(k) that is independent of the reasoning depth T. A Rademachercomplexity analysis further gives an …

A Deep Learning Ensemble Framework For Multi-Subtype Renal Tumor Classification Using Contrast-Enhanced Ct, Hisham Abdeltawab, Ahmed Alksas, Mohamed Ghazal, Ashraf Khalil, Norah Saleh Alghamdi, Rasha T. Abouelkheir, Ahmed Elmahdy, Mohamed Abou El-Ghar, Sohail Contractor, Ayman El–Baz

All Works

Renal cell carcinoma (RCC) is considered the most aggressive and common form of renal cancer. Therefore, early detection is crucial to ensure appropriate and effective treatment planning. In our study, we propose a novel computer-aided diagnostic (CAD) approach which incorporates a deep learning ensemble to differentiate between five renal tumor subtypes, utilising the modality of contrast-enhanced computed tomography (CE-CT). The addressed renal lesions are malignant tumors (chromophobe RCC (chRCC), papillary RCC (pRCC), and clear cell RCC (ccRCC)) and benign tumors (renal oncocytoma (RO) and angiomyolipoma (AML)). Our study includes 280 patients who underwent renal biopsy, 112 patients were diagnosed with …

Integrating Machine Learning And Explainable Ai For Employee Attrition Prediction In Hr Analytics, Maytha Al-Ali, Majed Alwateer, Shatha Abed Alsaedi, Hossam Magdy Balaha, Mahmoud Badawy, Mostafa A. Elhosseini

All Works

Employee attrition poses significant challenges to organizations, impacting productivity, morale, and financial stability. Predicting attrition and understanding its underlying drivers are critical for implementing effective retention strategies. In this study, we propose a comprehensive framework that utilizes advanced machine learning techniques to predict employee attrition and job change likelihood. The framework integrates robust preprocessing pipelines, state-of-the-art predictive models, and explainability tools such as SHAP (SHapley Additive exPlanations) to ensure transparency and fairness in HR analytics. By addressing key challenges such as class imbalance, feature selection, and model interpretability, our approach provides actionable insights for proactive talent management. We evaluate the …

A Robust Approach For Olive Leaf Disease Detection In Uncontrolled Environments, Rima Grati, Khouloud Boukadi, Emna Ben Abdallah, Ahmed Seffah

All Works

Detecting diseases in olive leaves is crucial for maintaining tree health and ensuring stable olive production. Early signs of infection often appear on the leaves, making them a key indicator for timely disease detection and intervention. Traditionally, farmers rely on visual inspection or laboratory tests to diagnose plant diseases. However, recent advancements in deep learning (DL) have significantly improved the accuracy and efficiency of olive leaf disease diagnosis. Numerous studies in the literature have explored this task using CNN-based architectures and, more recently, Vision Transformers. While these models have shown promising performance on benchmark datasets, they are often trained and …

Ai-Driven Collision Risk Prediction And Debris Optimization In Low Earth Orbit, Emad Alkhazraji, Mohamed E. Yahia, R. E. Tolba, N. S. Alharthi

All Works

Debris congestion and collision in low Earth orbit have become a major point of concern due to the rapid expansion of activities in that region. In this work, an AI-driven framework is developed and deployed to predict, analyze, and optimize collision risk across the altitude inclination space. Local debris object population, mass density distribution, and conjunction derived risk are computed. Then, an AI surrogate model, viz., gradient-boosted decision trees, was trained to predict collision conjunction relative probabilities and risk. Thereafter, data analysis and explain ability techniques are utilized to uncover underlying risk drivers and reveal how altitude, inclination, mass loading, …

Utilizing The Invasive Fruitwood Pyrus Calleryana As Substrate For Mushroom Cultivation, An Experimental Study In Practical Sustainability, Matthew D. Helton

Masters Theses and Doctoral Dissertations

This study evaluated the feasibility of using woodchips from the invasive Pyrus calleryana (Callery pear) as substrate for mushroom cultivation. Pleurotus ostreatus, Hericium erinaceus, and Ganoderma lucidum were grown on a pear wood substrate and on a conventional oak substrate to compare, yield, sensory attributes, and metabolite production. P. ostreatus showed no significant differences in yield or biological efficiency (p > 0.05), only sweetness (p = 0.022) differed significantly. H. erinaceus yield and efficiency were similar (p > 0.05), with greater second-flush yields in oak controls (p = 0.034) but no sensory differences (p > 0.05). G. lucidum performance was comparable across treatments …

Historical Piccolo Concerti And Works By Women Composers, Repertoire Catalogue, And A New Concerto For Piccolo And Orchestra, Mikaela Storm

Doctoral Scholarly Projects & Capstones

The following document is an overview of historical piccolo concerti with an emphasis on works by women, a repertoire catalogue of the piccolo concerti, and an analysis/performance guide for my own Concerto for Piccolo and Orchestra: The Dreamer. The primary goal of this document and subsequent score is to provide a resource for future composers, music theorists, conductors, and performers. The piccolo has limited repertoire in comparison to many of the standard instruments in our modern Western musical canon, and the number of piccolo concertos (particularly by women) is even smaller. The concerto that I have written, subtitled “The Dreamer,” …

The Hidden Heatwave: Thermal Hazards In The New York City Subway System, Abdou Rachid Bah, Maimuna Muntaha, Lenny L. Metlitsky, Cesar Pascal Vasquez, Tyler Ayala, Isaac Morel Lopez, Shaquan A. Larose, Kingston Ditsch, Kip Nielsen, Shaunak Sharma, Reginald U. Avila-Ortega Blake, Hamidreza I. Norouzi

Publications and Research

Underground transit systems (Subway) are susceptible to frequent heat waves, which pose serious health and safety risks to commuters and transit workers. Yet, the patterns and extent of temperature changes within the subway system remain insufficiently understood. To address this gap, we conducted a study of thermal variability across 112 subway stations in New York City. Temperature and relative humidity were measured at both platform and street levels. Results show that during the summer, 70% of subway stations had platform heat index higher than street level heat index. We also developed a machine learning forecasting model to predict platform-level temperatures. …

The Impact Of Testing-Parameter Variability On Force Production In The Isometric Single-Leg Long-Lever Bridge: Implications For Training And Testing Rigor In Sporting Environments, Adam E. Sundh, Nicholas J. Ripley, A. J. Lamb, Conor J. Cantwell, Paul Comfort

Research outputs 2022 to 2026

Background: The aim of this study was to determine the impact of knee angle variability on force production outcomes during the single-leg isometric long-lever bridge, thus providing monitoring guidelines for testing rigor with direct implications for feasibility across a variety of high-performance sporting environments. Methods: Thirty men (age: 19.4 ± 1.3 years; height: 179.8 ± 6.3 cm; body mass: 80.4 ± 10.3 kg) and 14 women (age: 20.0 ± 1.3 years; height: 166.9 ± 7.2 cm; body mass: 64.4 ± 7.4 kg) all of whom were Division 3 athletes with no recent injury history volunteered to participate in the study. …

A Genomic Approach For Accurate Identification Of Closely Related Species With Next-Generation Sequencing Samples, Nour Al Dain Marzouka, Amira Al-Aamri, Fatima Alshamsi, Mariam Khalili, Sarah El Hajj Chehadeh, Meera S. Mohamed, Yassir Mohammed Eltahir, Rafeek Koliyan, Mohamed Moustafa Abdelhalim, Assem Attia, Mira Mousa, Guan Tay, Habiba Alsafar

Research outputs 2022 to 2026

Accurate species identification from Whole Genome Sequencing (WGS) data remains challenging, particularly for closely related species such as sheep (Ovis aries) and goats (Capra hircus). Through analysis of mapping quality metrics and Kraken2 taxonomic classification of 40 WGS sheep and goat samples, we demonstrate that conventional approaches yield ambiguous results, with overlapping alignment rates and inconclusive taxonomic assignments. We present a robust comparative genomic approach that uses species-specific genomic regions to distinguish these species in WGS samples. We define species-specific regions as those exhibiting distinctive coverage patterns: average coverage when samples are aligned to their matching reference genome but absent/low …

A Global Image-Based Data Repository Of Killer Whale Interactions With Elasmobranchs, Emma Luck, Isabella L. Reeves, Maeva Terrapon, Rebecca Wellard, Stephanie K. Venables, Alison V. Towner, Alison A. Kock, Charlotte Hussain, Molly Altschwager, Rosie Ballard, Evans Baudin, Nancy Black, Evan Brodsky, Jade Cantrall, Julio Cardoso, Matt I.D. Carter, Oliver Clarke, Santiago Diaz-Pazmino, David Donnelly, Georgina Cabayol Ferraz, Arlaine Francisco, Laura González García, Mark Jackman, Aimee Jan, Eric Martin, Dane Mcdermott, James Moskito, Blair Ranford, Jesús Erick Higuera Rivas, Jasmin O’Brien, Anton Oleynik, Hernán Orellana-Vásquez, Daniela Alarcón Ruales, Gemma Sharp, Jade Sharp, Alisa Schulman-Janiger, Colleen M. Talty, Paul Tixier, John A. Totterdell, Steve Truluck, Jennah Tucker, Tara Weberg, M. Fernanda Urrutia-Osorio, Machi Yoshida, Jochen R. Zaeschmar, Lauren Meyer

Research outputs 2022 to 2026

Killer whales (Orcinus orca) are cosmopolitan apex predators that interact with numerous species, including sharks, skates, and rays (subclass Elasmobranchii). Interactions between killer whales and elasmobranchs have garnered attention from the scientific community, but the dynamics of these events are poorly understood, as interactions are often challenging to observe. In this study, we collated imagery of interactions between killer whales and elasmobranchs to create the first image-based repository of interspecific interactions between marine predators. A total of 320 photos and videos from 82 unique interactions were collected from 12 countries. A minimum of 18 elasmobranch species across 16 genera were …

The Impact Of The Basel And Bamako Conventions On Hazardous Waste Trafficking And Environmental Governance In West Africa, Prince Nii Koi Kotei, Kwadwo Adusei-Asante, Shajimon Peter

Research outputs 2022 to 2026

This study examines the dynamics of hazardous waste trafficking and environmental governance in West Africa. It evaluates the Basel and Bamako conventions through the lens of environmental justice, environmental governance, and the global Race to the Bottom concept. It assesses the environmental governance models adopted by these conventions in West Africa and beyond and evaluates their effectiveness towards achieving environmental justice. This study uses a critical appraisal framework to assess the relevance, sustainability, enforcement, ethical consideration, equity and practicability of the Basel and Bamako Conventions. A total of 28 articles were rigorously selected from multiple databases. It was found that …

The Service Variety Paradox In Crypto-Exchanges: A Stimulus-Organism-Response (Sor) Perspective, Cheuk Hang Au, Po Hsu Shieh, Vladimir Nurbaev, Kris M.Y. Law, Kevin K.W. Ho

Research outputs 2022 to 2026

Digital platforms face a fundamental paradox: while expanding service variety is a dominant competitive strategy, it risks inducing a “paradox of choice” that confuses and deters users. This tension manifests with extreme clarity in the nascent, high-complexity market of cryptocurrency exchanges, creating a pressing empirical puzzle. To resolve this, we adopt the Stimulus-Organism-Response (SOR) perspective in a three-stage mixed-method study to investigate how platforms can strategically manage this trade-off. Our qualitative exploration (Study 1) established a capital flow schema called “inflow, roll, and go” and identified key complexity-reduction mechanisms. A subsequent survey (n = 190, Study 2) validated that perceived …

A Deep Learning Based Three-Stage Fusion Neural Network With Composite Adaptive Momentum Optimizer For Bangla Cyberbully Identification, Mahin Montasir Afif, Abdullah Al Noman, Kazi Abdullah Jarif, Md Emamul Arefin Islam, Sathya Narayana Sharma K, Mahfujur Rahman, Dipta Gomes, Kazi Tanvir, Md Obaidur Rahaman, Syed Mohammed Shamsul Islam

Research outputs 2022 to 2026

Cyberbullying in Bangla social media is an increasingly critical issue, posing severe risks to mental health and online safety. Despite the growing need for automated detection systems, challenges such as limited linguistic resources and the nuanced characteristics of the Bangla language hinder model performance. In this study, we propose TriB-FNN, a novel and explainable three-stage fusion neural network, designed to effectively capture cyberbully in Bangla social media texts. The model integrates Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory (Bi-LSTM), and Gated Recurrent Units (GRUs) in a hierarchical pipeline. To optimize training, we employ a Composite Adaptive Momentum (CAM) Optimizer, …

A Dynamic Framework Of Professional Identity Formation In Trainees For Low-Resource Settings: A Qualitative Study, Yilin Chen, Peixin Lin, Hengshun Du, Jiaxin Wu, Xuanhua Zheng, Mi Yao, Kai Lin

Research outputs 2022 to 2026

Background: Professional Identity Formation (PIF) is a dynamic and context-dependent socialisation process; while existing research identifies various influencing factors, there is a paucity of cohesive frameworks that capture the stage-related internalisation of identity elements within practice. This gap is particularly salient in low-resource settings, such as China’s Rural-Streamed Medical Education Programme (RMEP), where substantial turnover and tenuous professional identity among trainees present significant challenges. Drawing upon the Ring Theory of Personhood (RToP) as a theoretical lens, this study aims to construct a dynamic framework for understanding PIF among RMEP trainees, thereby offering insights to enhance PIF for healthcare professionals in …

Abcb5⁺ Mesenchymal Stem Cells Enable High-Ratio Cellular Augmentation Of Bone Grafts Without Loss Of Osteogenic Function, Jakob Hofmann, Tim Niklas Bewersdorf, Ulrike Sommer, Kai Borcherding, Karsten Thiel, Christoph Ganss, Matthias Gerstner, Markus H. Frank, Gerhard Schmidmaier, Mark Andreas Kluth, Tobias Grossner

Research outputs 2022 to 2026

Autologous bone grafting remains the standard for reconstruction of bone defects but is constrained by limited graft volume and loss of osteogenic capacity when expanded with acellular materials. We hypothesized that allogeneic ABCB5⁺ mesenchymal stem cells (MSCs) can serve as a biologic cell source to augment bone marrow-derived MSC (BM-MSC) populations without impairing osteogenesis. Primary human BM-MSCs from five donors were combined with GMP-manufactured ABCB5⁺ MSCs at graded replacement ratios (0–95%) and cultured under osteogenic conditions for 21 days. Osteogenic potential was evaluated using complementary assays of mineralization, biochemical activity, and matrix composition. Robust osteogenesis was maintained across all groups, …

From Proteome To Palate: Proteomics-Led Insights Into Sensory Quality In Oats (Avena Sativa L.), Clare E. O'Lone, Angéla Juhász, Utpal Bose, Haelee Fenton, Dini Ganesalingam, Allan Rattey, Michelle L. Colgrave

Research outputs 2022 to 2026

Background: Oats (Avena sativa L.) are a rapidly expanding ingredient in plant-based beverages, snacks and fermented products, where texture, flavour, aroma and colour shape consumer acceptance. A comparatively high lipid content (2–10% w/w) reduces milling efficiency and predisposes products to oxidative rancidity, while textural variation, bitterness and colour instability further constrain product development. The molecular basis for these processing and sensory challenges lies in the globulin-dominant grain proteome.

Scope and approach: This review synthesises advances in liquid chromatography–tandem mass spectrometry (LC-MS/MS) proteomics to quantitatively profile the four protein groups shaping oat sensory quality: storage, grain softness-related, lipid-associated, and metabolic and …

Paternal Age And Offspring Bone Health And Body Composition At 20 Years: Findings From The Raine Study, Mia A. Percival, Kun Zhu, John P. Walsh, Marc Sim, Kara B. Anderson, Julie A. Pasco, Natalie K. Hyde

Research outputs 2022 to 2026

Aims: There is growing evidence supporting paternal contributions to child health. Previous findings from the Vitamin D In Pregnancy study suggest that advanced paternal age is associated with a range of poorer bone measures for offspring at age 11 years. Whether these associations are evident when peak bone mass is attained remains unknown. This study aimed to investigate associations between paternal age and offspring bone health and body composition at age 20 years.

Methods: Data from the Raine study, a multigenerational cohort, were used. Among 1183 offspring with total body DXA data (Norland XR-36 densitometer) at the 20-year follow up, …

Translation, Cross-Cultural Adaptation, And Psychometric Validation Of The Team Emergency Assessment Measure (Team) Into European Spanish: A Multi-Perspective Study Including Peer-Assessment, Esther Leon-Castelao, Jose Luis Medina-Moya, Alejandro Durante-Lopez, Pedro Castro-Rebollo, Simon Cooper, Antoni Ruiz-Bueno, Jordi Bañeras

Research outputs 2022 to 2026

Background: The Team Emergency Assessment Measure (TEAM) is the most widely used tool for evaluating emergency team performance, with robust psychometric evidence across multiple languages and settings. However, no European Spanish version has been validated, and no previous TEAM study has simultaneously assessed teamwork from four complementary rater perspectives: instructors from the learners’ own specialty, instructors from other specialties, self-assessment by the performing participants, and peer-assessment by observing peers. This study aimed to translate, culturally adapt, and psychometrically validate a European Spanish version of the TEAM (s-TEAM) and to evaluate its reliability and validity across these four perspectives in emergency …

Trace Pfoa Synergistically Intensifies Nanoplastic-Humic Acid Fouling In Forward Osmosis: Mitigation Using A Mxene-Tio2 Substrate And A Ta/Fe3+ Interlayer, Roham Ghanbari, Javad Farahbakhsh, Mohadeseh Najafi Arani, Ratish Permala, Stefan Iglauer, Masoumeh Zargar

Research outputs 2022 to 2026

Multicomponent fouling arising from the coexistence of per- and polyfluoroalkyl substances (PFAS), nanoplastics (NPs), and natural organic matter (NOM) remains poorly understood and limits membrane-based water treatment. Here, these interactions and their mitigation are examined through coordinated substrate-interlayer engineering in forward osmosis membranes. A hydrogen-bonded MXene-TiO2 (HMT) composite is incorporated into the polysulfone substrate to improve pore structure, hydrophilicity, and mass transfer, while a tannic acid/Fe3+ interlayer regulates interfacial polymerization and surface chemistry. Control membranes are employed to decouple the individual and combined effects of these modifications. Fouling experiments under single, binary, and ternary conditions reveal that trace PFAS cause …

Using Scoping Reviews As Precursors To Systematic Reviews: A Typology And Practical Guidance Derived From Eight Worked Examples, Hanan Khalil, Zachary Munn, Christina Godfrey, Micah D.J. Peters, Ellen Davies, Fiona Campbell, Danielle Pollock, Andrea C. Tricco, Dawid Pieper

Research outputs 2022 to 2026

Objectives: Scoping reviews are often conducted as a precursor to a systematic review (SR), yet guidance on how this relationship should be planned, executed, and reported is limited. We aimed to illustrate, through worked examples, the ways in which scoping reviews can function as precursors to SRs and to derive practical guidance for teams planning linked or sequential syntheses.

Study Design and Setting: We undertook a methodological analysis of eight contemporary evidence synthesis papers and protocols spanning veterinary medicine, animal welfare, public health, mental health, occupational health, and patient and public involvement, identified through the authors’ knowledge of the evidence …

Bone, Muscle, And Physical Function Measures In Older Adults According To Levels Of Social Disadvantage: A Cross-Sectional Study, Jason Talevski, Sharon Brennan-Olsen, Stefanie Bird, Sara Vogrin, Alison Beauchamp, Mizhgan Fatima, Cassandra Smith, Gustavo Duque

Research outputs 2022 to 2026

Summary: This cross-sectional study of 300 older adults (aged ≥ 50 years) found that less education, lower income, and health care card ownership are associated with reduced bone, muscle, and physical function measures. This underscores the need for targeted preventive strategies for osteoporosis and sarcopenia that address socioeconomic-related disparities. Purpose: The prevalence of chronic diseases follows a social gradient, although this is unclear in musculoskeletal conditions. This study aims to examine the association between social disadvantage and diagnostic measures of osteoporosis and sarcopenia in community-dwelling older adults. Methods: A single-centre, cross-sectional study was conducted in adults (≥ 50 years) residing …

Depression, Psychological Distress, And Coping Strategies Among African Migrants In Australia: A Cross-Sectional Web-Based Study, Uchechukwu Levi Osuagwu, Lillian Mwanri, Edith N. Botchway-Commey, David Chisanga, Agness Tembo, Nnaemeka Meribe, Kathomi Gatwiri, Obed Adonteng-Kissi, Kerrie P. Doyle, Frank Darkwa Baffour, Ahmed A. Moustafa

Research outputs 2022 to 2026

Background: African migrants constitute a significant proportion of the Australian population. While migration and resettlement offer opportunities, the associated stressors may adversely affect the mental health and well-being of African migrants. This study explored, for the first time, the prevalence of depression and psychological distress among African migrants in Australia and the relationship between coping mechanisms and mental health outcomes. Methods: A web-based cross-sectional survey of adult African migrants in Australia was conducted between February and May 2022. Participants (N = 167) who did not have a refugee status who resided in Australia for at least 12 months were recruited …

Do Flywheel Exercises Provide Eccentric-Overload Training?, Darjan Spudić, Kazunori Nosaka

Research outputs 2022 to 2026

Interests in eccentric resistance exercises have been increasing in both research and practice. However, implementing eccentric resistance exercise training is often challenging due to the mechanical limitations of traditional training equipment. To address this, flywheel (FW) devices emerged as a practical alternative. FW devices are commonly considered to provide eccentric-overload training, in which the load is greater in eccentric than concentric phase. However, this is not always the case. In this article, we summarize the mechanical and physiological factors influencing the effectiveness of FW devices in achieving eccentric overload. Then, we discuss a significant limitation of FW resistance exercise in …

Methylated Cfdna May Distinguish Between High- And Intermediate-Risk Uveal Melanoma: A Pilot Study, Mike Wu, Daniël P. De Bruyn, Ruben G. Boers, Aaron B. Beasley, Daan M. Hazelaar, Stavros Makrodimitris, Joachim B. Boers, Jolanda Vaarwater, Ronald O.B. De Keizer, Robert M. Verdijk, Nicole C. Naus, Dion Paridaens, Saskia M. Wilting, Elin S. Gray, Wilfred F.J. Van Ijcken, Joost Gribnau, Annelies De Klein, Erwin Brosens, Emine Kiliç

Research outputs 2022 to 2026

Background: Uveal melanoma (UM) is a highly aggressive malignancy with a metastatic risk that depends on the molecular subclass. This subclass can be determined through molecular characterization of tumor-derived tissue. With eye-sparing treatments, tumor tissue is rarely available for molecular testing. We hypothesized that minimal invasive biomarkers such as methylated cell-free DNA (cfDNA) or circulating tumor DNA (ctDNA) can be used for prognosis and monitoring of patients. Methods: Plasma cfDNA was isolated from healthy blood donors (HBDs, N = 19) and UM patients (N = 22). Plasma was collected at baseline (localized disease, N = 13) and during follow-up (metastatic …

Perspective: Improving Social Connection And Inclusion Through Equitable Digital Health Solutions, Dominika Kwasnicka, Jaimon Kelly, Eleanor Quested, Loretta Baldassar, Suzanne Robinson, Richard Sinnott, Paul O’Halloran, Anne Tiedemann, Paul Flatau, Rajna Ogrin, Jane Farmer, Abby C. King

Research outputs 2022 to 2026

In this Perspective, we address the critical intersection of digital health, social connection, and health equity. Taking an interdisciplinary and complex adaptive systems perspective, we highlight evidence-based digital solutions to improve social connection and inclusion and, consequently, health outcomes. We describe actionable strategies for ensuring that digital health innovations benefit all, highlighting how user-centered design can address diverse needs, particularly for structurally disadvantaged populations.

Sarcomerogenesis: Evidence, Context And Key Stimuli—Response To The Commentary By Power Et Al., Anthony J. Blazevich, Walter Herzog, João Pedro Nunes

Research outputs 2022 to 2026

No abstract provided.