Purpose: The purpose of this study was to quantify the microscopic dose distribution surrounding gold nanoparticles (GNPs) irradiated at therapeutic energies and to measure the changes in cell survival in vitro caused by this dose enhancement.
Methods: The dose distributions from secondary electrons surrounding a single gold nanosphere and single gold nanocube of equal volume were both simulated using MCNP6. Dose enhancement factors (DEFs) in the 1 μm volume surrounding a GNP were calculated and compared between a nanosphere and nanocube and between 6 and 18 MV energies. This microscopic effect was explored further by experimentally measuring the cell survival of C-33a cervical cancer cells irradiated at 18 MV with varying doses of energy and concentrations of GNPs. Survival of cells receiving no irradiation, a 3 Gy dose, and a 6 Gy dose of 18 MV energy were determined for each concentration of GNPs.
Results: It was observed that the dose from electrons surrounding the gold nanocube surpasses that of a gold nanosphere up to a distance of 1.1 μm by 18.5% for the 18 MV energy spectrum and by 23.1% for the 6 MV spectrum. DEFs ranging from ∼2 to 8 were found, with the maximum DEF resulting from the case of the gold nanocube irradiated at 6 MV energy. Experimentally, for irradiation at 18 MV, incubating cells with 6 nM (0.10% gold by mass) GNPs produces an average 6.7% decrease in cell survival, and incubating cells with 9 nM (0.15% gold by mass) GNPs produces an average 14.6% decrease in cell survival, as compared to cells incubated and irradiated without GNPs.
Conclusion: We have successfully demonstrated the potential radiation dose enhancing effects in vitro and microdosimetrically from gold nanoparticles.
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http://dx.doi.org/10.1080/09553002.2022.2087931 | DOI Listing |
Arch Pathol Lab Med
January 2025
the Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles (Petersen, Stuart, He, Ju, Ghezavati, Siddiqi, Wang).
Context.—: The co-occurrence of plasma cell neoplasm (PCN) and lymphoplasmacytic lymphoma (LPL) is rare, and their clonal relationship remains unclear.
Objective.
Pediatr Dermatol
January 2025
Department of Dermatology of Hospital, Universitario Virgen de Valme, Sevilla, Spain.
Background/objectives: Anaplastic large cell lymphomas (ALCLs) present unique challenges due to their clinical and genetic heterogeneity. This study investigated the clinical characteristics of children diagnosed with systemic ALCL.
Methods: Retrospective data from 14 pediatric patients diagnosed with systemic ALCL at Valme University Hospital were studied.
Mol Biol Rep
January 2025
Goat Genetics and Breeding Division, ICAR-Central Institute for Research On Goats, Makhdoom, Farah, Mathura, 281 122, Uttar Pradesh, India.
Background: Extracellular matrix (ECM) proteins play a crucial role in regulating the biological properties of adherent cells. For cryopreserved fibroblasts, a favourable ECM environment can help restore their natural morphology and function more rapidly, minimizing post-thaw stress responses.
Methods And Results: This study explored the functional responses of cryopreserved enriched caprine adult dermal fibroblast (cadFibroblast) cells to structural [collagen-IV and rat tail collagen (RTC)] and adhesion ECM proteins (laminin, fibronectin, and vitronectin) under in vitro culture conditions.
Discov Oncol
January 2025
Department of Neurosurgery, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, 415003, Hunan, China.
Purpose: Glioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive biomarkers for glioma.
View Article and Find Full Text PDFNat Commun
January 2025
Bioinformatics and computational systems biology of cancer, Institut Curie, Inserm U900, PSL Research University, Paris, France.
Immunotherapy is improving the survival of patients with metastatic non-small cell lung cancer (NSCLC), yet reliable biomarkers are needed to identify responders prospectively and optimize patient care. In this study, we explore the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We analyze baseline multimodal data from a cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, including positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!