AIMC Topic: Osteosarcoma

Clear Filters Showing 31 to 40 of 46 articles

A support vector machine classifier for the prediction of osteosarcoma metastasis with high accuracy.

International journal of molecular medicine
In this study, gene expression profiles of osteosarcoma (OS) were analyzed to identify critical genes associated with metastasis. Five gene expression datasets were screened and downloaded from Gene Expression Omnibus (GEO). Following assessment by M...

Effect of Short-Term Stimulation with Interleukin-1β and Differentiation Medium on Human Mesenchymal Stromal Cell Paracrine Activity in Coculture with Osteoblasts.

BioMed research international
INTRODUCTION: Human mesenchymal stromal cells (hMSCs) exhibit the potential to accelerate bone healing by enhanced osteogenic differentiation. Interleukin-1β is highly expressed during fracture healing and has been demonstrated to exert a significant...

Microfluidics-based label-free SERS profiling of exosomes with machine learning for osteosarcoma diagnosis.

Talanta
Osteosarcoma (OS) calls for early diagnosis to significantly improve patient survival rates. Exosomes hold significant potential as noninvasive biomarkers for the early diagnosis of cancer. Here, we design a microfluidic device to purify and analyze ...

Impact of environmental pollution on human health: Investigating the role of Polycyclic Aromatic Hydrocarbons in pediatric osteosarcoma.

Ecotoxicology and environmental safety
BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs), widely emitted through industrial processes and vehicular exhaust, are recognized environmental carcinogens. Although PAH exposure has been linked to various malignancies, the specific molecular me...

Exosomal Gene Biomarkers in Osteosarcoma: Mifepristone as a Targeted Therapeutic Revealed by Multi-Omics Analysis.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Osteosarcoma (OS) is an aggressive bone cancer that mainly occurs in children and adolescents. OS patients are mainly treated with neoadjuvant chemotherapy and surgical resection. This treatment is effective for early osteosarcoma. However, the effec...

Radiomics-based machine learning in prediction of response to neoadjuvant chemotherapy in osteosarcoma: A systematic review and meta-analysis.

Clinical imaging
BACKGROUND AND AIMS: Osteosarcoma (OS) is the most common primary bone malignancy, and neoadjuvant chemotherapy (NAC) improves survival rates. However, OS heterogeneity results in variable treatment responses, highlighting the need for reliable, non-...

Multimodal Diagnostic Approach for Osteosarcoma and Bone Callus Using Hyperspectral Imaging and Deep Learning.

Journal of biophotonics
Distinguishing osteosarcoma from bone callus remains a clinical challenge due to their morphological similarities. This study proposes J-CAN, a multimodal deep learning framework integrating hyperspectral imaging (HSI) and H&E-stained pathology for r...

Feasibility of machine learning-based modeling and prediction to assess osteosarcoma outcomes.

Scientific reports
Osteosarcoma, an aggressive bone malignancy predominantly affecting children and adolescents, is characterized by a poor prognosis and high mortality rates. The development of reliable prognostic tools is critical for advancing personalized treatment...

Development of a prognostic model for osteosarcoma based on macrophage polarization-related genes using machine learning: implications for personalized therapy.

Clinical and experimental medicine
While neoadjuvant chemotherapy combined with surgical resection has improved the prognosis for patients with osteosarcoma, its impact on metastatic and recurrent cases remains limited. Immunotherapy is emerging as a promising alternative. However, th...

Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing's sarcoma: nomogram and webpage.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
OBJECTIVE: The objective of this study was to analyze the incidence and overall survival (OS) of osteosarcoma (OSC) and Ewing's sarcoma (EWS) in a pediatric and adolescent population, employing machine learning (ML) and deep learning (DL) models to p...