AIMC Topic: Cell Line, Tumor

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Machine learning-assisted pattern recognition and imaging of multiplexed cancer cells a porphyrin-embedded dendrimer array.

Journal of materials chemistry. B
Early cancer detection plays a vital role in improving the survival rate of cancer patients, underscoring the importance of developing cancer detection methods. However, it is a great challenge to achieve simple, rapid, and accurate methods for simul...

Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning.

Frontiers in immunology
BACKGROUND: Several studies indicate that smoking is one of the major risk factors for bladder cancer. Nicotine and its metabolites, the main components of tobacco, have been found to be strongly linked to the occurrence and progression of bladder ca...

Machine Learning-Engineered Nanozyme System for Synergistic Anti-Tumor Ferroptosis/Apoptosis Therapy.

Small (Weinheim an der Bergstrasse, Germany)
Nanozymes with multienzyme-like activity have sparked significant interest in anti-tumor therapy via responding to the tumor microenvironment (TME). However, the consequent induction of protective autophagy substantially compromises the therapeutic e...

Machine learning and multi-omics characterization of SLC2A1 as a prognostic factor in hepatocellular carcinoma: SLC2A1 is a prognostic factor in HCC.

Gene
Hepatocellular carcinoma (HCC) is characterized by high incidence, significant mortality, and marked heterogeneity, making accurate molecular subtyping essential for effective treatment. Using multi-omics data from HCC patients, we applied diverse cl...

Freeze-Thaw-Induced Patterning of Extracellular Vesicles with Artificial Intelligence for Breast Cancers Identifications.

Small (Weinheim an der Bergstrasse, Germany)
Extracellular vesicles (EVs) play a crucial role in the occurrence and progression of cancer. The efficient isolation and analysis of EVs for early cancer diagnosis and prognosis have gained significant attention. In this study, for the first time, a...

Novel machine learning model for predicting cancer drugs' susceptibilities and discovering novel treatments.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVE: Timely treatment is crucial for cancer patients, so it's important to administer the appropriate treatment as soon as possible. Because individuals can respond differently to a given drug due to their unique genomic profiles...

3D electron microscopy for analyzing nanoparticles in the tumor endothelium.

Proceedings of the National Academy of Sciences of the United States of America
Delivering medical agents to diseased tissues has been challenging, leading researchers to study the in vivo transport process in the body for improving delivery. Many imaging techniques exist for mapping the distribution of medical agent-carrying na...

Cross-disease transcriptomic analysis reveals DOK3 and PAPOLA as therapeutic targets for neuroinflammatory and tumorigenic processes.

Frontiers in immunology
OBJECTIVE: Subarachnoid hemorrhage (SAH) and tumorigenesis share numerous biological complexities; nevertheless, the specific gene expression profiles and underlying mechanisms remain poorly understood. This study aims to identify differentially expr...