Search Results (925)

Background: Amino acid tracer positron emission tomography–magnetic resonance imaging (PET-MRI) was shown to be superior to MRI alone for evaluating central nervous system (CNS) tumours in adults. This study aimed to investigate the utility of amino acid PET-MRI in children with CNS tumours. Methods: We reviewed the amino acid PET-MRI findings of children with suspected or confirmed CNS neoplasms managed in a territory-wide referral centre in Hong Kong from 2022 to 2025. Maximal standardized uptake values (SUVmax) were captured, and tumour-to-background SUVmax ratios (TBRmax) were measured with reference to adjacent or contralateral normal brain structures. Comparisons were made among patients with clinical high-grade and low-grade/non-neoplastic lesions. Results: Thirty-seven patients were included, with 63 PET-MRIs performed. PET-MRI was performed as part of initial diagnostics in 41% of the cases, for response assessment in 48%, and evaluation of residual/relapsed disease in 11%. High-grade lesions had a significantly higher SUVmax and TBRmax compared to low-grade/non-malignant lesions (median SUVmax 3.7 vs. 1.6, p = 0.00006; median TBRmax 2.06 vs. 0.91, p = 0.00002). Optimal SUVmax and TBRmax cut-offs by ROC analysis were 2.38 and 1.62, respectively. Similar performance was reproduced by focusing on the subset of patients with suspected CNS germ cell tumours (CNS-GCT). The impact of amino acid PET availability is considerable, as clinical management was modified in 65% of patients. Conclusions: Our study demonstrates the performance and clinical utility of amino acid PET-MRI in the management of children with CNS pathologies. Amino acid PET-MRI contributes to the diagnosis, monitoring, and treatment guidance of these patients, providing crucial information for decision-making. Full article

Background: Cryopreservation of hematopoietic stem cells (HSCs) at −80 °C using uncontrolled-rate freezing is frequently employed in resource-constrained settings, yet concerns remain regarding long-term viability and clinical efficacy. Reliable post-thaw assessment is essential to ensure graft quality and engraftment success. Methods: This single-center, retrospective study evaluated 72 cryopreserved stem cell products from 25 patients stored at −80 °C for a median of 868 days. Viability was assessed using both acridine orange (AO) staining and 7-AAD (7-aminoactinomycin D) flow cytometry at three time points: collection (T0), pre-infusion (T1), and delayed post-thaw evaluation (T2). Associations between viability loss, storage duration, and clinical engraftment outcomes were analyzed. Results: Median post-thaw viability remained high (94.8%) despite a moderate time-dependent decline (~1.02% per 100 days; R² = 0.283, p < 0.001). Mean viability loss at T2 was 9.2% (AO) and 6.6% (flow cytometry). AO demonstrated greater sensitivity to delayed degradation, with a significant difference between methods (p < 0.001). Engraftment kinetics were preserved in most patients, with neutrophil and platelet recovery primarily influenced by disease type rather than product integrity. Notably, storage duration and donor age were not significantly associated with engraftment outcomes or CD34⁺ cell dose. Conclusion: Long-term cryopreservation at −80 °C maintains HSC viability sufficient for durable engraftment, despite gradual decline. While transplant outcomes are primarily dictated by disease biology and remission status, AO staining provides enhanced sensitivity for detecting delayed cellular damage. Notably, our viability-loss model offers a practical framework for predicting product quality, potentially supporting graft selection and clinical decision-making in real-world, resource-constrained transplant settings. Full article

Introduction: Prostate cancer is one of the most common neoplasia in men, and its clinical evolution is highly influenced by psycho-emotional factors, especially in elderly patients. Comorbidities, the perception of one’s identity and its impact on life quality become relevant variables in the therapeutic decision. Sexual dysfunction after treatment along with decreased libido, erectile dysfunction and ejaculatory dysfunction are significant problems in patients with prostate cancer. Case presentation: The present study presents the oncological evolution of an elderly patient with a dual diagnosis, prostate adenocarcinoma and lung squamous cell carcinoma, who faced a significant amount of medical and psychological challenges. Reluctance to hormone therapy was closely linked to the fear of sexual dysfunction, a very common reaction in elderly men concerned with maintaining autonomy and intimacy. The peculiarity of the case consists in the interaction between the evolution of the disease, the therapeutic decisions and the psychological impact on the patient. Discussion: Androgen deprivation therapy negatively influences multiple aspects of sexual function, significantly impairing the life quality of patients diagnosed with prostate cancer. In this context, therapy through acceptance and commitment is the appropriate one, its main purpose being to change the patient’s relationship with suffering—from struggle and rejection to active acceptance and value of the present. The intervention of the psychologist or the psychotherapist is essential in decision-making counseling, using coping techniques, the clarification of personal values and the involvement of the family in the decision-making process. Oncological psychology helps the patient redefine their life goals and priorities, not just to choose a treatment. Conclusions: Sexuality and psychological health are deeply affected by prostate cancer. Psychological flexibility and emotional support can mitigate this negative impact. The integration of therapy through acceptance and commitment in the rehabilitation after treatment increases effectiveness and patient satisfaction. Full article

Soft tissue sarcomas (STSs) are a rare and highly heterogeneous group of tumours originating from mesenchymal cells, characterized by significant clinical and biological diversity. Due to this complexity, STSs present considerable challenges in both diagnosis and treatment, requiring an expert, multidisciplinary, and coordinated approach. To address these challenges, a multidisciplinary team of experts from the Spanish Group for Research in Sarcomas (GEIS) has developed a comprehensive, evidence-based consensus guideline that incorporates the latest advancements in biology, imaging techniques, and treatment options. The primary objective of this guideline is to provide clear and practical, up-to-date recommendations addressing the key questions that arise in the management of STSs. This approach aims to support therapeutic decision-making, enhance overall patient management, and ultimately improve clinical outcomes for patients affected by STSs. Key recommendations include the use of MRI as the preferred imaging modality prior to biopsy and ensuring that all patients are referred to specialised sarcoma centres with a multidisciplinary team for diagnosis and treatment. Full article

Artificial intelligence (AI) and augmented intelligence have significant potential in oculoplastics, offering tools for diagnosis, treatment recommendations, and administrative efficiency. This article discusses current and potential applications of AI in ptosis, eyelid and conjunctival cancer, thyroid-associated orbitopathy (TAO), giant cell arteritis (GCA), and orbital fractures. AI-based programs can assist in screening, predicting surgical outcomes, and improving patient care through data-driven decisions. Privacy concerns, particularly with the use of facial and ocular photographs, require robust solutions, including blockchain, federated learning and steganography. Large generalizable datasets with adequate validation are crucial for future AI development. While AI can assist in clinical decision-making and administrative tasks, physician oversight remains critical to prevent potential errors. Large language models like ChatGPT also have the potential to counsel patients, although further validation is needed to ensure accuracy and patient safety. Ultimately, AI should be regarded as an augmentative tool that supports, rather than replaces, physician expertise in oculoplastic care. Full article

Background/Objectives: Small renal masses (SRMs) are being detected more often due to the increasing use of imaging techniques. Many of these lesions are benign or grow slowly, but a small proportion can exhibit aggressive behavior. Several reports have shown that synchronous metastases may occur even in small renal cell carcinomas (RCCs). Our aim is to assess the malignant potential and the metastatic risk of very small RCCs (≤2 cm). Methods: We reviewed consecutive patients who underwent partial nephrectomy for SRMs at our tertiary referral center between 2005 and 2024, focusing on those with a maximum pathologic diameter ≤ 2 cm. Clinical and pathological data were collected, and cases with aggressive features were described. In addition, a literature search on the Medline/PubMed database was performed to identify previously published cases of RCC ≤ 2 cm and to assess their risk of synchronous metastases (SM). Results: Among 578 patients who underwent partial nephrectomy, 116 patients (20%) had tumors ≤ 2 cm, 90 (77.5%) of which were malignant, whereas 22.5% were benign (oncocytoma = 13%; angiomyolipoma = 5%). Median age and tumor size were 51 yrs and 1.7 cm, respectively. Histology showed clear cell (72.2%), papillary (20%), chromophobe (6.6%), and mixed (0.9%). Two patients (2.2%) experienced aggressive disease: one with synchronous metastases and one with recurrence and later progression. From the literature, we identified 16 additional cases of RCC ≤ 2 cm with synchronous metastases and found an important heterogeneity of results regarding the metastatic potential of SRMs. Conclusions: Although uncommon, synchronous metastases can occur in RCCs even smaller than 1–2 cm. Reported rates for SM of SRMs across the literature range between 1% and 13%, with higher risk observed in tumors larger than 3 cm, but without an absolute safe cutoff. Tumor size alone is therefore insufficient to exclude aggressive potential. Clinical decision-making should consider histology, grade, patient age, radiologic features, and emerging molecular markers to guide surveillance and treatment in this growing patient population. Full article

Background/Objectives: Oral cavity squamous cell carcinoma (OCSCC) is an aggressive malignancy, often diagnosed at an advanced stage and with stagnant survival outcomes despite advances in surgical and oncologic management. Tumor-infiltrating lymphocytes (TILs) have been explored as potential prognostic markers in many solid tumors; however, their role in OCSCC remains under researched. This study aimed to assess the prognostic value of TILs in a cohort of patients with regionally advanced, p16-negative squamous cell carcinoma of all oral cavity subsites and to evaluate for any correlation of TILs and extranodal extension (ENE). Methods: A retrospective study was conducted on 103 consecutive patients treated with comprehensive surgical resection. TILs were quantified using the standardized method proposed by the International Immuno-Oncology Biomarkers Working Group. Statistical analyses evaluated associations with a comprehensive set of independent variables and survival endpoints. Results: High stromal infiltration at the invasive margin (>25%) was independently associated with significantly improved overall survival (HR 4.53, p = 0.005), disease-specific survival (HR 4.49, p = 0.008), and disease-free survival (HR 3.42, p = 0.025). Patients with ENE demonstrated lower TILs compared with ENE-negative patients (median 40% vs. 57.5%), a difference that reached statistical significance in both parametric and nonparametric testing (Welch’s t-test p = 0.032; Mann–Whitney U p = 0.030). Conclusions: TILs quantified by this standardized method are a reliable, independent prognostic biomarker in regionally advanced OCSCC of all subsites and are also associated with extranodal extension of regional metases. This study gives rationale for consideration of inclusion of TILS into future immunotherapeutic decision-making and further investigations of TIL-ENE association. Full article

Liquid biopsy, which analyzes tumor secretomes in biological fluids, allows us to not only diagnose cancer, but also evaluate the effectiveness of antitumor therapy, predict the prognosis of the disease, and select targeted therapy. One of the promising sources for identifying tumor markers using liquid biopsy is exosomes—small extracellular vesicles (sEVs) (30–150 nm in size) that are secreted by all types of cells, including tumor cells, to exchange information. It is known that during the maturation process, mainly biologically active proteins and non-coding RNA are packaged into exosomes, and tumor cells secrete significantly more exosomes than normal cells. Taking into account the involvement of microRNAs in the mechanisms of carcinogenesis, their high stability in EVs, and ease of detection, exosomal microRNAs are the most promising tumor markers for creating panels that can serve as a guide both for clarifying diagnostics and for making therapeutic decisions on effective cancer treatment, including breast cancer (BC). The purpose of this review is to summarize information on the shortcomings of modern methods for diagnosing early BC, the involvement of exosomal microRNAs in BC dissemination (impact on the immune system, epithelial–mesenchymal transition, proliferation, invasion, migration, angiogenesis, and metastasis), and the high diagnostic potential of exosomal microRNAs for detecting early BC. Full article

Background/Objectives: Diffuse large B cell lymphoma (DLBCL) is a highly heterogeneous and aggressive lymphoma with a high incidence rate. Although modern therapeutic approaches have significantly improved patient survival rates, treatment relapse and drug resistance remain major clinical challenges. Programmed cell death (PCD) promotes tumorigenesis and regulates the tumor microenvironment (TME) and drug sensitivity. Exploring the application potential of PCD in DLBCL could pave the way for new treatment strategies for this malignancy. Methods: We systematically analyzed 13 types of PCD pathways and integrated transcriptomic and clinical data from 832 DLBCL patients (GSE10846, GSE11318, and GSE87371). A PCD-based prognostic signature, termed the Programmed Cell Death Score (PCDS), was constructed using 20 key PCD-related genes. Its clinical relevance was evaluated through survival analysis, drug response profiling, and tumor immune infiltration assessment using CIBERSORT, ESTIMATE, and ssGSEA algorithms. Results: The PCDS robustly stratified patients by survival and outperformed conventional clinical indicators such as age, stage, Eastern Cooperative Oncology Group (ECOG), and lactate dehydrogenase (LDH) in prognostic prediction. High-PCDS tumors were associated with immune suppression, characterized by reduced CD8⁺ T cell infiltration, elevated M2 macrophages, and increased programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) expression. Drug sensitivity analysis revealed that high-PCDS patients may benefit more from agents like sorafenib and fulvestrant, while low-PCDS patients responded better to NU7441. Functional validation using DLBCL cell lines and xenografts confirmed the oncogenic role of a representative gene (CTH) within the model. Conclusions: This study presents a novel prognostic scoring system derived from multiple PCD pathways that effectively stratifies DLBCL patients by risk and therapeutic responsiveness. Notably, the PCDS is closely associated with key immunological characteristics of the TME. These findings advance personalized treatment strategies and support clinically relevant decision-making in DLBCL. Full article

Objective: To develop and validate a radiomics-based MRI model for prediction of diffuse-type tenosynovial giant cell tumor (D-TGCT), which has higher postoperative recurrence and more aggressive behavior than localized-type (L-TGCT). The study was conducted under the hypothesis that MRI-based radiomics models can predict D-TGCT with diagnostic performance significantly greater than chance level, as measured by the area under the receiver operating characteristic (ROC) curve (AUC) (null hypothesis: AUC ≤ 0.5; alternative hypothesis: AUC > 0.5). Materials and Methods: This retrospective study included 84 patients with histologically confirmed TGCT (54 L-TGCT, 30 D-TGCT) who underwent preoperative MRI between January 2005 and December 2024. Tumor segmentation was manually performed on T2-weighted (T2WI) and contrast-enhanced T1-weighted images. After standardized preprocessing, 1691 radiomic features were extracted, and feature selection was performed using minimum redundancy maximum relevance. Multivariate logistic regression (MLR) and random forest (RF) classifiers were developed using a training cohort (n = 52) and tested in an independent test cohort (n = 32). Model performance was assessed AUC, sensitivity, specificity, and accuracy. Results: In the training set, D-TGCT prevalence was 32.6%; in the test set, it was 40.6%. The MLR model used three T2WI features: wavelet-LHL_glszm_GrayLevelNonUniformity, wavelet-HLL_gldm_LowGrayLevelEmphasis, and square_firstorder_Median. Training performance was high (AUC 0.94; sensitivity 75.0%; specificity 90.9%; accuracy 85.7%) but dropped in testing (AUC 0.60; sensitivity 62.5%; specificity 60.6%; accuracy 61.2%). The RF classifier demonstrated more stable performance [(training) AUC 0.85; sensitivity 43.8%; specificity 87.9%; accuracy 73.5% and (test) AUC 0.73; sensitivity 56.2%; specificity 72.7%; accuracy 67.3%]. Conclusions: Radiomics-based MRI models may help predict D-TGCT. While the MLR model overfitted, the RF classifier demonstrated relatively greater robustness and generalizability, suggesting that it may support clinical decision-making for D-TGCT in the future. Full article

Background: Multiple sclerosis is a multifactorial neurodegenerative disease characterized by autoimmune and inflammatory processes. Despite advancements in disease-modifying therapies, multiple sclerosis remains challenging due to its complex pathophysiology and variable clinical presentation. Current therapies focus on managing inflammation and promoting immunosuppression but do not achieve complete symptom regression or enhance remyelination. Emerging therapies, such as Peroxisome Proliferator-Activated Receptor gamma (PPARγ) agonists and Bruton tyrosine kinase (BTK) inhibitors, show promise in modulating inflammation and targeting immune cells. Innovative approaches like human fetal neural precursor cells (hfPNCs) and mesenchymal stem cell transplantation are being explored to reduce neural inflammation and improve neuroprotection. Early diagnosis and intervention are crucial for managing multiple sclerosis effectively and preventing progression to severe forms and permanent disability. Therapeutic education for individuals with multiple sclerosis and their caregivers is essential, emphasizing the need for clear, reliable information to support disease management and improve quality of life. Objectives: This review provides an up-to-date overview of multiple sclerosis pathophysiology, current treatments, and emerging therapies, aiming to enhance the knowledge base of healthcare professionals and researchers, facilitating informed decision-making and contributing to ongoing research efforts. Full article

Genetically encoded fluorescent protein (FP)-based biosensors have revolutionized cell biology research by enabling real-time monitoring of molecular activities in live cells with exceptional spatial and temporal resolution. Multiplexed biosensing advances this capability by allowing the simultaneous tracking of multiple signaling pathways to uncover network interactions and dynamic coordination. However, challenges in spectral overlap limit broader implementation. Innovative strategies have been devised to address these challenges, including spectral separation through FP palette expansion and novel biosensor designs, temporal differentiation using photochromic or reversibly switching FPs, and spatial segregation of biosensors to specific subcellular regions or through cell barcoding techniques. Combining multiplexed biosensors with artificial intelligence-driven analysis holds great potential for uncovering cellular decision-making processes. Continued innovation in this field will deepen our understanding of molecular networks in cells, with implications for both fundamental biology and therapeutic development. Full article

Antibody function is an important topic for the understanding of disease, but it would be quite challenging to make an accurate prediction of a paratope position from very limited information such as a B cell receptor’s (BCR’s) amino acid sequence alone. In this context, this study presents a knowledge-based Bidirectional Encoder Representation from Transformers (K-BERT) to deliver a precise prediction of a paratope position from a B cell receptor’s amino acid sequence alone. Here, the knowledge context of an amino acid consisted of its predecessor amino acids. These knowledge contexts were either common among all amino acids within each BCR chain or different for different amino acids within each BCR chain. Also, oversampling was employed given that the original data of 20,679 cases (900 BCR chains) were characterized by class imbalance, i.e., 18,724:1955 for labels 0:1. The performance measures in terms of sensitivity and F1 registered great improvements as different knowledge contexts and oversampling were introduced. The accuracy, sensitivity, specificity and F1 of a baseline model (with common knowledge and no oversampling) were 90.3, 0.0, 100.0 and 50.0, respectively. On the other hand, the corresponding accuracy, sensitivity, specificity and F1 of the final model (with different knowledge and strong oversampling) were 83.2, 90.1, 78.1 and 84.1. The final model demonstrated better sensitivity and F1 outcomes compared to the baseline model, i.e., 90.1 vs. 0.0 for sensitivity, 84.1 vs. 50.0 for F1. In conclusion, the K-BERT is an effective decision support system to predict a paratope position from a B cell receptor’s amino acid sequence alone. It has great potential for antibody therapeutics. Full article

The characterization and mapping of urban landscape spatial form are critical for advancing sustainable planning and informed environmental management. From a morphometric perspective, this study introduces a novel, data-driven framework for typo-morphological analysis. First, morphological cells (MCs) are defined as objectively and universally applicable spatial units for morphometric investigation. Second, by integrating a multi-dimensional cognition of full-scale morphological and associated landscape elements, we construct a set of 48 spatial form indicators and attach them to morphological cells, enabling a precise description of each unit. Third, a Gaussian mixture model (GMM) is employed to cluster the metrical information within the spatially lagged context derived from the topological structure of the morphological cells, resulting in the delineation of distinct typo-morphological zones (TMZs). We then adopt Ward’s algorithm to establish a hierarchical relationship among identified urban landscape types. Using Wuxi City, China, as a case study, our results demonstrate the effectiveness of the proposed framework in capturing the heterogeneity and underlying connotation of urban landscape spatial characteristics. Building upon the unsupervised clustering results, we further apply the classification and regression tree (CART) to provide a supervised interpretation of the key spatial form conditions driving typological decisions. It facilitates the systematic identification of the components and formative mechanisms of spatial form. The findings contribute a scalable, reproducible, and interpretable typo-morphometric approach for analyzing urban landscape spatial characteristics, thereby providing a robust quantitative foundation for integrated decision-making in landscape planning, socio-ecological assessment, and urban design practices. More broadly, the study carries both applied and theoretical significance for advancing refined urban governance and fostering interdisciplinary research related to urban sustainable development. Full article

Background: Generalized myasthenia gravis (gMG) is a heterogeneous autoimmune disorder marked by antibody-mediated disruption of neuromuscular transmission. Despite advancements in immunosuppressive therapies and biologics, a subset of patients remains refractory, necessitating more targeted and personalized treatment strategies. Objective: This review aims to synthesize current knowledge of the immunopathological mechanisms across gMG subtypes and to explore emerging therapeutic targets tailored to these diverse disease phenotypes. Methods: A narrative review was conducted, integrating recent findings from clinical trials, immunogenetic studies, and preclinical research to describe subtype-specific immune mechanisms and corresponding therapeutic innovations. Results: gMG subtypes—characterized by autoantibody profiles (AChR, MuSK, LRP4, or seronegative), thymic histopathology, and age of onset—demonstrate distinct immunological pathways. Early-onset MG is associated with thymic hyperplasia and Th17-driven inflammation; thymoma-associated MG involves central tolerance breakdown; late-onset MG shows immune senescence and altered T-cell regulation. MuSK- and LRP4-positive MG exhibit unique cytokine and antibody signatures. Novel therapeutic strategies include B cell- and T cell-targeted therapies (e.g., anti-CD19, anti-CD38, JAK inhibitors), cytokine inhibitors (IL-6, IL-17, IL-23), FcRn antagonists, complement inhibitors, and gene- or cell-based therapies such as CAR-T and CAAR-T cells. Conclusion: The evolving landscape of gMG treatment reflects a shift toward immunopathology-based precision medicine. Better characterization of subtype-specific molecular signatures and immune dysfunctions is essential to guide clinical decision-making and improve outcomes for treatment-refractory patients. Full article