Common Medical Comorbidities, Demographic Factors and Levels of Plasma Biomarkers of Alzheimer’s Disease and Neurodegeneration in Black/African American Older Adults
Emerging evidence suggests that systemic physiological factors may influence plasma biomarker concentrations of Alzheimer’s disease (AD) and related neurodegenerative processes, potentially affecting their specificity for central nervous system pathology. This study examined the relationship of demographic factors and medical comorbidities with plasma biomarkers of AD and neurodegeneration in a community-dwelling cohort of Black/African American (B/AA) older adults (N = 141). Participants underwent plasma assessment of phosphorylated tau at threonine 217 (p-Tau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). Results showed associations between plasma p-Tau217 and amyloid PET positivity, and significant intercorrelations among p-Tau217, GFAP, and NfL. Stepwise regression models incorporated demographics, amyloid PET status, and laboratory measures of renal, metabolic, and lipid function as predictors for each biomarker. p-Tau217 was primarily predicted by amyloid PET and renal function; GFAP by age and sex; and NfL by renal function, age, and sex. Findings indicate plasma biomarker concentrations in B/AA older adults reflect both central AD-related pathology and systemic physiological factors, particularly renal function, and demographic influences. Results underscore the importance of accounting for comorbid medical conditions and demographic characteristics when interpreting blood-based biomarkers and highlight the need for comprehensive medical phenotyping to improve diagnostic specificity and clinical utility.
Current state of knowledge on the epidemiology, aetiology, diagnosis, and management of heart involvement in eosinophilia. A Clinical Consensus Statement of the ESC Working Group on Myocardial & Pericardial Diseases
Abstract Heart involvement in eosinophilia represents a rare entity with substantial cardiac morbidity and mortality. This disorder is often overlooked and diagnosed in its advanced stages. In a subgroup of patients with eosinophilic heart disease, peripheral blood eosinophilia may not be present, and the biopsy of the affected organ or tissue is essential to establish the correct diagnosis. In this clinical consensus statement, an expert consensus group reviews the epidemiology, aetiology, diagnosis, and management of eosinophilic heart disease. The aim of the document is to increase awareness about the cardiac involvement associated with eosinophilia in order to diagnose the disease in early phases and prevent deleterious heart damage and adverse outcomes of affected individuals. The spectrum of physiological and immunological derangements requires a multidisciplinary approach for optimal management of affected individuals.
Fluoroscopy-Guided Motion Management in Particle Therapy: Evolution, Challenges, and AI-Enabled Opportunities
The sharp dose gradients that underpin the dosimetric advantage of particle therapy over photon therapy can be undermined by the interplay effects due to intra-fraction motion in modern pencil beam scanning systems. Fluoroscopy-Guided Particle Therapy (FGPT) offers a promising path to improved motion management through real-time tracking of tumors or surrogate signals. The advent of flat-panel detector (FPD)-based technology has enabled tighter integration of fluoroscopy/fluorography into treatment units and accelerated clinical adoption and research, with commercial systems such as Hitachi’s Real-time Gated Particle Therapy (RGPT) now available. However, the need for implanted fiducial markers, with the associated invasiveness and risk of complications, limits the utility of RGPT to a few anatomic sites in selected patients. The full potential of FGPT, therefore, depends on reliable marker-less tumor tracking, which remains challenging because soft-tissue targets are obscured by overlapping anatomy along the X-ray path, leading to reduced reliability of traditional image-registration algorithms in the projection domain. Recent advances in deep learning and AI-driven image registration have renewed hope for overcoming these barriers, enabling real-time marker-less tracking for particle therapy. This review outlines the evolution of fluoroscopy technology from image intensifier (II) to FPD-based systems, summarizes historical and recent vendor-supported FGPT strategies, and surveys emerging AI-based algorithms in the literature. A general review of machine learning-based image registration is provided, challenges in generalizability and interpretability are highlighted, and potential paths toward reliable, clinically deployable FGPT are discussed.
Novel Compounds as TREM2 Modulators for Treating Alzheimer’s Disease, Parkinson’s Disease, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, and Nasu-Hakola Disease
This guideline has been updated. This ASCO Living Guideline is reviewed on an eight-week cycle. Please see the online dynamic version for the latest updates. Living guidelines are developed for selected topic areas with rapidly evolving evidence that drives frequent change in recommended clinical practice. Living guidelines are updated on a regular schedule by a standing expert panel that systematically reviews the health literature on a continuous basis, as described in the ASCO Guidelines Methodology Manual . ASCO Living Guidelines follow the ASCO Conflict of Interest Policy Implementation for Clinical Practice Guidelines . Living Guidelines and updates are not intended to substitute for independent professional judgment of the treating clinician and do not account for individual variation among patients. See appendix for disclaimers and other important information ( Appendix 1 and Appendix 2 ). Updates are published regularly and can be found on the ASCO Publications website .
Pathology Foundation Models: Evolution, Current Landscape, Challenges and Opportunities from a Technical and Clinical Perspective
Foundation models are reshaping computational pathology by enabling scalable task-agnostic representations of histopathological whole-slide images (WSIs). Unlike earlier task-specific deep learning systems, pathology foundation models (PFMs) leverage massive whole-slide image repositories and self-supervised Vision Transformer architectures to achieve broad generalization and few-shot adaptability. Their evolution reflects a shift from weakly supervised approaches such as Clustering-Constrained Attention Multiple Instance Learning (CLAM) and hierarchical architectures such as Hierarchical Image Pyramid Transformer (HIPT) to large-scale efforts including foundation models, UNI, Virchow, Phikon, CONtrastive learning from Captions for Histopathology (CONCH), GigaPath, H-Optimus, Transformer-Based Pathology Image and Text Alignment Network (TITAN), and the Mayo Clinic Atlas. These models demonstrate impressive performance across diagnostic and prognostic benchmarks while also opening pathways for multimodal integration with genomics and clinical data. Yet significant barriers remain including inconsistent generalization across institutions, interpretability lagging behind clinical needs, and slow integration into routine laboratory workflows. Certain domains of anatomic pathology such as cytopathology, transplant pathology, frozen sections, and rare tumor subtypes remain particularly resistant to current models. Here, we review the development of PFMs, critically evaluate their strengths and limitations, and outline priorities for their safe and effective clinical translation. We argue that the next phase of PFM development will depend on rigorous benchmarking, pathologist-in-the-loop deployment, and multimodal fusion ensuring these models evolve from research tools into clinically robust systems.
Is There a Unified Etiology of Hypoplastic Left Heart Syndrome? Evaluating Genetic, Structural, and Hemodynamic Models of Disease Initiation
Background: Hypoplastic left heart syndrome (HLHS) is defined as “a spectrum of congenital cardiovascular malformations with normally aligned great arteries without a common atrioventricular junction, characterized by underdevelopment of the left heart with significant hypoplasia of the left ventricle including atresia, stenosis, or hypoplasia of the aortic or mitral valve, or both valves, and hypoplasia of the ascending aorta and aortic arch”. Without treatment, HLHS is usually lethal in the neonate. Many hypotheses have been advanced to explain the etiology of HLHS; however, no single theory appears to fully explain the phenotypic variability seen in HLHS. Furthermore, many of these theories offer no explanations regarding the precipitating events which lead to the development of HLHS. Objective: This review considers and critically evaluates the strengths and weaknesses of the leading theories proposed to explain the pathogenesis of HLHS—including hemodynamic disturbances, primary myocardial structural defects, valvar malformations, and genetic or epigenetic alterations that may provoke developmental and anatomic abnormalities. After presenting each model, we propose a novel, comprehensive, and data-driven framework which may assist researchers in developing models for the pathogenesis of the various subtypes of HLHS. Methods: Key findings from human fetal imaging, histopathology, genetic studies, and animal models were considered, as well as the hypothetical contribution of each in observed HLHS phenotypes. The rationales for these findings as causal factors initiating individual HLHS patterns, as well as how they might contribute to HLHS in general, were critically analyzed. Results: The flow theory is strongly supported by animal models and in utero interventions that demonstrate the impact of altered hemodynamics on cardiac morphogenesis. However, the flow theory fails to identify initial causes of disturbed flow or related histological features of HLHS like endocardial fibroelastosis. The myocardial and valve-first models suggest an important role in developmental defects, but do not necessarily have a strong experimental basis that provides explanations for how they mediate HLHS. Genetic studies in patients with HLHS have identified several candidate causal mutations. However, such genetic causes of HLHS exhibit incomplete phenotypic penetrance and clinical impact. A multifactorial framework attempts to integrate these diverse mechanisms and may provide the most coherent explanation that can accommodate the heterogeneity and variable presentation of HLHS. Such a framework may identify multiple forces that drive disease but does not provide useful pathways for future research about HLHS. Conclusions: No single hypothesis has fully explained how HLHS is initiated, progresses, and presents with the clinical conditions that are encountered by cardiac surgeons and cardiologists. The most current models suggest that the spectrum of HLHS reflects acomplex interaction between genetic susceptibility, flow-dependent cardiac remodeling, and environmental factors in utero. A multifactorial model integrates these diverse mechanisms and may provide the most coherent explanation for the various phenotypic variations in HLHS. Based on our analysis of the most current data and the strengths and weaknesses of the current theoretical frameworks, we propose a novel research strategy aimed at identifying specific cardiac progenitor cell populations whose dysregulation may represent a unifying explanation for the etiology of the various phenotypes of HLHS. Based on the arguments made throughout this manuscript that evaluate the various genetic, structural, and hemodynamic models of initiation of disease, we believe that the significant phenotypic variability across the spectrum of HLHS (i.e., the different anatomic subtypes for “classic” HLHS) most likely reflects different underlying etiologies and mechanisms. At the very least, it is very likely that the timing of the insult is critical in determining anatomic subtype. Based on the published data and the arguments within this manuscript, it seems naive to think that there is a single unifying mechanism explain all forms of HLHLS.
The landscape of antibody production systems: recombinant expression for research, diagnostics and therapy
Over the past three decades, the emergence of recombinant antibodies has positioned them as the fastest-growing class of therapeutic proteins and as well as crucial reagents for both diagnostics and specific research applications. The industrial production of most therapeutic antibodies currently relies on mammalian cell lines, primarily Chinese Hamster Ovary (CHO) cells, which remain the gold standard in biopharmaceutical manufacturing due to their exceptionally high production yields, robustness, regulatory acceptance, and consistent product quality. Nevertheless, new approaches using specifically adapted expression systems are emerging. These new host organisms enable the production of antibodies with posttranslational modifications that closely resemble those found in the human system, without the need for animal-derived source materials. For diagnostic and research purposes, a broad range of production systems has been developed. These include Gram-negative and Gram-positive bacteria, yeasts, filamentous fungi, insect cell lines, and transgenic plants. Additionally, smaller single domain antibodies and bispecific fragments that do not require glycosylation can be successfully produced in bacteria for therapeutic applications. Some of these molecules have already been approved by regulatory authorities in the European Union and the United States, and several more are currently in clinical trials. This review therefore focuses on the broad and evolving landscape of recombinant antibody production systems and their applicability across various fields.
Optimizing Radiography Utilization: Multidisciplinary Expert Consensus Recommendations Endorsed by the Society of Academic Bone Radiologists, Society of Skeletal Radiology, American Society of Emergency Radiology,
Expert consensus recommendations from 21 academic centers were established for appropriate radiography utilization at 12 potentially low-yield anatomic sites through a multidisciplinary process endorsed by six major American medical societies.
Long-Term Survey to Assess Recurrence and Complications of Surgically Treated Pleomorphic Adenoma
Objective(s): To (1) report on the long-term recurrence rate of surgically managed pleomorphic adenoma (PA) and (2) assess long-term surgical outcomes after parotidectomy Methods: Cross-sectional survey of all patients with a pathologic diagnosis of PA who underwent surgical management in a tertiary care center from 01/1997 to 12/2023 and had access to an electronic patient portal. Surveys were delivered via electronic patient portal or phone call with 6 questions to assess recurrence and long-term surgical outcomes. Time to first recurrence and recurrence free survival were analyzed using a Kaplan-Meier curve. Results: Seven hundred-forty-five patients met inclusion criteria and received the survey, with a 56% response rate (n = 420). The clinical median follow-up length was 51 days, which extended to a median length of 6.2 years following the survey. The median change in follow-up length was 5.37 years ( P < .001). The recurrence rate was 1% at 5 years, with a median time to first recurrence of 7.54 years. 13% and 9% of responders reported facial asymmetry and incisional cosmetic concerns, respectively. 33% of patients reported experiencing Frey syndrome, which increased from 5.2% of survey responders with documented Frey syndrome at their original post-operative assessment. Conclusion: Long-term assessment of PA outcomes confirms low recurrence rates, suggesting regular surveillance of recurrence is likely unnecessary. Complaints of Frey syndrome increased in frequency with longer term follow-up, which should be considered during patient counseling. Level of Evidence: 3