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Fulltext Controlled temperature-mediated curcumin release from magneto-thermal nanocarriers to kill bone tumors

Khodaei A, Jahanmard F, Madaah Hosseini HR, Bagheri R, Dabbagh A, Weinans H, et al.

Bioact Mater, 2022 May;11:107-117.
PMID: 34938916 DOI: 10.1016/j.bioactmat.2021.09.028

Systemic chemotherapy has lost its position to treat cancer over the past years mainly due to drug resistance, side effects, and limited survival ratio. Among a plethora of local drug delivery systems to solve this issue, the combinatorial strategy of chemo-hyperthermia has recently received attention. Herein we developed a magneto-thermal nanocarrier consisted of superparamagnetic iron oxide nanoparticles (SPIONs) coated by a blend formulation of a three-block copolymer Pluronic F127 and F68 on the oleic acid (OA) in which Curcumin as a natural and chemical anti-cancer agent was loaded. The subsequent nanocarrier SPION@OA-F127/F68-Cur was designed with a controlled gelation temperature of the shell, which could consequently control the release of curcumin. The release was systematically studied as a function of temperature and pH, via response surface methodology (RSM). The bone tumor killing efficacy of the released curcumin from the carrier in combination with the hyperthermia was studied on MG-63 osteosarcoma cells through Alamar blue assay, live-dead staining and apoptosis caspase 3/7 activation kit. It was found that the shrinkage of the F127/F68 layer stimulated by elevated temperature in an alternative magnetic field caused the curcumin release. Although the maximum release concentration and cell death took place at 45 °C, treatment at 41 °C was chosen as the optimum condition due to considerable cell apoptosis and lower side effects of mild hyperthermia. The cell metabolic activity results confirmed the synergistic effects of curcumin and hyperthermia in killing MG-63 osteosarcoma cells.
Fulltext Exploring the role of artificial intelligence in chemotherapy development, cancer diagnosis, and treatment: present achievements and future outlook

Abdul Rasool Hassan B, Mohammed AH, Hallit S, Malaeb D, Hosseini H

Front Oncol, 2025;15:1475893.
PMID: 39990683 DOI: 10.3389/fonc.2025.1475893

BACKGROUND: Artificial intelligence (AI) has emerged as a transformative tool in oncology, offering promising applications in chemotherapy development, cancer diagnosis, and predicting chemotherapy response. Despite its potential, debates persist regarding the predictive accuracy of AI technologies, particularly machine learning (ML) and deep learning (DL).
OBJECTIVE: This review aims to explore the role of AI in forecasting outcomes related to chemotherapy development, cancer diagnosis, and treatment response, synthesizing current advancements and identifying critical gaps in the field.
METHODS: A comprehensive literature search was conducted across PubMed, Embase, Web of Science, and Cochrane databases up to 2023. Keywords included "Artificial Intelligence (AI)," "Machine Learning (ML)," and "Deep Learning (DL)" combined with "chemotherapy development," "cancer diagnosis," and "cancer treatment." Articles published within the last four years and written in English were included. The Prediction Model Risk of Bias Assessment tool was utilized to assess the risk of bias in the selected studies.
CONCLUSION: This review underscores the substantial impact of AI, including ML and DL, on cancer diagnosis, chemotherapy innovation, and treatment response for both solid and hematological tumors. Evidence from recent studies highlights AI's potential to reduce cancer-related mortality by optimizing diagnostic accuracy, personalizing treatment plans, and improving therapeutic outcomes. Future research should focus on addressing challenges in clinical implementation, ethical considerations, and scalability to enhance AI's integration into oncology care.

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