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Predictive models for immune checkpoint inhibitor response in cancer: A review of current approaches and future directions
Get PDFCheckpoint inhibitors have revolutionised cancer treatment, yet only 20–30 % of patients achieve durable responses, highlighting the critical need for predictive models. This review focuses on PD-1/PD-L1 pathway inhibitors as monotherapy, examining current prediction frameworks spanning biomarker-based approaches, multi-omics integration, mathematical modelling, and artificial intelligence applications. Recent advances include SCORPIO and LORIS machine learning systems demonstrating superior statistical performance compared to traditional biomarkers, with area under curve values of 0.763. However, critical analysis reveals significant limitations in external validation across diverse healthcare settings, with many promising models failing to maintain performance outside their development institutions. Traditional pathological assessment by expert pathologists, including standardised PD-L1 scoring and tumour-infiltrating lymphocyte quantification, continues to form the foundation of clinical decision-making and provides essential validation for emerging AI approaches. Despite extensive research, established biomarkers show limited predictive accuracy, with PD-L1 demonstrating predictive value in only 28.9 % of FDA approvals. Multi-feature models incorporating genomic and clinical data show improved accuracy but face substantial validation challenges. Integration of spatial biomarkers and digital pathology has enhanced capabilities, achieving area under curve values of 0.84 in select studies. The most critical challenge is the “validation gap”, many models show excellent single-institution performance but fail external validation, limiting clinical translation. Current obstacles include inadequate standardisation, interpretability concerns, and healthcare system integration difficulties. Future directions must prioritise rigorous multi-institutional validation studies, development of clinically implementable frameworks, and addressing practical deployment challenges to realise precision immunotherapy's potential
The Impact of Artificial Intelligence and Machine Learning in Organ Retrieval and Transplantation: A Comprehensive Review
Get PDFThis narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks. Predictive analytics further enable personalized treatment plans by forecasting organ rejection, infection risks, and patient recovery trajectories, thereby supporting early intervention strategies and long-term patient management. AI also optimizes operational efficiency within transplant centers by predicting organ demand, scheduling surgeries efficiently, and managing inventory to minimize wastage, thus streamlining workflows and enhancing resource allocation. Despite these advancements, several challenges hinder the widespread adoption of AI and ML in organ transplantation. These include data privacy concerns, regulatory compliance issues, interoperability across healthcare systems, and the need for rigorous clinical validation of AI models. Addressing these challenges is essential to ensuring the reliable, safe, and ethical use of AI in clinical settings. Future directions for AI and ML in transplantation medicine include integrating genomic data for precision immunosuppression, advancing robotic surgery for minimally invasive procedures, and developing AI-driven remote monitoring systems for continuous post-transplantation care. Collaborative efforts among clinicians, researchers, and policymakers are crucial to harnessing the full potential of AI and ML, ultimately transforming transplantation medicine and improving patient outcomes while enhancing healthcare delivery efficiency
Exploring ableism and occupational therapy: Occupational therapy students’ perspectives
Get PDFAim:
To explore occupational therapy students’ perspectives on ableism and its implications for occupational therapy practice. This formed part of a wider study that also explored occupational therapy educators’ perspectives.
Method:
An online survey was used to collect students’ perspectives, using a mixture of Likert scales and open-ended questions.
Findings:
The sample comprised 56 occupational therapy students from the United Kingdom ( n = 36), United States of America ( n = 16) and Canada ( n = 4) enrolled in a mixture of undergraduate ( n = 13) and postgraduate ( n = 43) pre-registration degree programmes. Thirty-four percent of respondents perceived occupational therapy as inherently ableist. This rose to 50% after respondents were presented with a comprehensive definition of ableism. Students reported witnessing and/or experiencing ableism within education (63%) and practice placements (55%). Eighty-six percent of students recognised they may hold unconscious ableist views, and 96% agreed they would like more support to engage in disability studies.
Conclusion/Impact:
Findings indicated a potential link between understanding of ableism and students’ views that occupational therapy is ableist. Most students were aware of the potential they hold unconscious biases and welcomed support to engage further with disability studies. Further qualitative research is needed. Following this, systemic changes to address the harm of ableism can begin to be addressed
Artificial Intelligence in in-vitro fertilization (IVF): A New Era of Precision and Personalization in Fertility Treatments
Get PDFIn-vitro fertilization (IVF) has been a transformative advancement in assisted reproductive technology. However, success rates remain suboptimal, with only about one-third of cycles resulting in pregnancy and fewer leading to live births. This narrative review explores the potential of artificial intelligence (AI), machine learning (ML), and deep learning (DL) to enhance various stages of the IVF process. Personalization of ovarian stimulation protocols, gamete selection, and embryo annotation and selection are critical areas where AI may benefit significantly. AI-driven tools can analyze vast datasets to predict optimal stimulation protocols, potentially improving oocyte quality and fertilization rates. In sperm and oocyte quality assessment, AI can offer precise, objective analyses, reducing subjectivity and standardizing evaluations. In embryo selection, AI can analyze time-lapse imaging and morphological data to support the prediction of embryo viability, potentially aiding implantation outcomes. However, the role of AI in improving clinical outcomes remains to be confirmed by large-scale, well-designed clinical trials. Additionally, AI has the potential to enhance quality control and workflow optimization within IVF laboratories by continuously monitoring key performance indicators (KPIs) and facilitating efficient resource utilization. Ethical considerations, including data privacy, algorithmic bias, and fairness, are paramount for the responsible implementation of AI in IVF. Future research should prioritize validating AI tools in diverse clinical settings, ensuring their applicability and reliability. Collaboration among AI experts, clinicians, and embryologists is essential to drive innovation and improve outcomes in assisted reproduction. AI's integration into IVF holds promise for advancing patient care, but its clinical potential requires careful evaluation and ongoing refinement
Neurobiological and neuropsychological disturbance in EDS
Get PDFEhlers-Danlos Syndrome (EDS) is a collection of connective tissue disorders, defined by genetic defects in collagen and extracellular matrix proteins that lead to joint hypermobility, skin fragility, and vascular complications. However, recent studies point to a broader impact, revealing how EDS has both neurological and psychological effects. This review explores these neurological and neuropsychological dimensions of EDS across its 13 subtypes, drawing together evidence on brain structure changes such as Chiari malformations and craniocervical instability, alongside small fibre neuropathy, blood–brain barrier vulnerabilities, and cerebrovascular risks, particularly prevalent in the vascular EDS subtype. The review will also explore how these physical disruptions may act upon mental health, fueling anxiety, mood instability, and cognitive challenges. Mechanisms such as neuroinflammation, altered interoception, and chronic pain may contribute to these effects and drive emotional dysregulation. By reviewing clinical observations, neuroimaging findings, and emerging theories, this paper highlights the importance of understanding the involvement of the brain in EDS. The review highlights the need for a shift in approach to EDS, and an integrated effort across neurology, psychiatry, and genetics to better support those living EDS
User-Centered Assessment of MRI Equipment Flexibility, Workspace Adequacy, User Interface Usability, and Technical Proficiency
No full textThe effective operation of magnetic resonance imaging (MRI) systems relies on physical interactions with complex imaging environments, equipment, and user interfaces (UIs). However, there is limited empirical data evaluating how physical interactions with MRI equipment and accessories, workspace configuration, MRI UI design, and technical proficiency influence clinical workflow. In this study, a cross-sectional survey was conducted among MRI end-users, across public and private health facilities (n = 13), using a structured questionnaire to assess demographics, patient positioning and equipment handling, MRI workspace adequacy, interface usability (guided by Nielsen's heuristics), and self-reported MRI skill proficiency. The predominant field strength of scanners in current use was 1.5T. General Electric was the most frequently used MRI scanner brand. Most respondents received their MRI training from nonvendor sources—such as academic institutions or peer-based instruction—rather than directly from equipment manufacturers. High ease-of-use ratings were reported for patient positioning and equipment handling tasks. Workspace adequacy was mostly rated as very adequate to highly adequate. Computed Tomography-experienced users showed moderate-to-high proficiency in MRI pulse sequencing and image optimization. However, lower proficiency was noted in quality assurance and physiologic monitoring. Help documentation within the MRI interface received the lowest usability scores. No significant differences in usability or proficiency were found between those trained by vendors versus nonvendors (U = 8.5–15.0; p = 0.376–0.921). Opportunities exist to enhance clinical workflow and patient throughput by refining error-handling features, improving support documentation, reinforcing ongoing professional development, and re-evaluating training delivery by incorporating iterative, multimedia-based learning modules and regular postinstallation refresher sessions. End-user input in UI design and user feedback analysis should be prioritized to improve system usability and clinical efficiency
The Spectral West: Supenature and the Gothic in the Western Film
No full textThis book considers the presence of the supernatural and Gothic elements of the Western on screen. These dark and sinister undertones often exist in Western narratives to draw attention to the ever-present issue of death and its haunting resonance which characters encounter. This book examines this through key historic moments in Western film and its contemporary incarnations. The book detects imposing correlations in themes and currents between the Gothic and the Western relating to existential crisis and a loss of faith in ideologies and institutions. These themes represent the tensions between the old and the new, the deranged insistence on civility and order in a chaotic landscape, disillusionment and the shattering of faith in the natural order, and even nature and order themselves. The Western, just like the Gothic tale, reminds us that new frontiers are mired in the past, and optimism and survival are hunted down and haunted by guilt-ridden past and passed anxieties and traumas
Walking through the North York Moors National Park – a place of adventure, conservation and healing
No full textSpace Junk
No full textThis entry discusses the jettisoned materials produced in the course of human exploration and commercialisation of space, in earth orbit and beyond. Often described as space ‘junk’ or debris, such objects are produced in various ways and are rapidly increasing in number. The implications of such accumulation are discussed as well as proposals for mitigation and the prospects for international agreements. Speculative ventures in pursuit of the commercial realisation of space tourism and planetary colonisation are increasing and likely to lead to further orbital pollution