AIMC Topic: Cell Line, Tumor
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Multi-omics analysis and experiments uncover the function of cancer stemness in ovarian cancer and establish a machine learning-based model for predicting immunotherapy responses.
Frontiers in immunology
Dec 11, 2024
BACKGROUND: The heterogeneity of cancer makes it challenging to predict its response to immunotherapy, highlighting the need to find reliable biomarkers for assessment. The sophisticated role of cancer stemness in mediating resistance to immune check...
Integrating necroptosis into pan-cancer immunotherapy: a new era of personalized treatment.
Frontiers in immunology
Dec 9, 2024
INTRODUCTION: Necroptosis has emerged as a promising biomarker for predicting immunotherapy responses across various cancer types. Its role in modulating immune activation and therapeutic outcomes offers potential for precision oncology.
Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth.
Cell communication and signaling : CCS
Dec 5, 2024
BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long durational erlotinib treatment of non-small cell lung cancer (NSCLC) patients, leading to drug resistance and disease progression. Identification of new selec...
Harnessing machine learning and multi-omics to explore tumor evolutionary characteristics and the role of AMOTL1 in prostate cancer.
International journal of biological macromolecules
Dec 4, 2024
Although recent advancements have shed light on the crucial role of coordinated evolution among cell subpopulations in influencing disease progression, the full potential of these insights has not yet been fully harnessed in the clinical application ...
MIRD Pamphlet No. 31: MIRDcell V4-Artificial Intelligence Tools to Formulate Optimized Radiopharmaceutical Cocktails for Therapy.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Dec 3, 2024
Radiopharmaceutical cocktails have been developed over the years to treat cancer. Cocktails of agents are attractive because 1 radiopharmaceutical is unlikely to have the desired therapeutic effect because of nonuniform uptake by the targeted cells. ...
Extending visual range of bacteria with upconversion nanoparticles and constructing NIR-responsive bio-microrobots.
Journal of colloid and interface science
Dec 1, 2024
The motility of bacteria is crucial for navigating competitive environments and is closely linked to physiological activities essential for their survival, such as biofilm development. Precise regulation of bacterial motility enhances our understandi...
Ultradense Electrochemical Chip and Machine Learning for High-Throughput, Accurate Anticancer Drug Screening.
ACS sensors
Nov 29, 2024
Despite the potentialities of electrochemical sensors, these devices still encounter challenges in devising high-throughput and accurate drug susceptibility testing. The lack of platforms for providing these analyses over the preclinical trials of dr...
Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning.
Nature communications
Nov 29, 2024
Integrating diverse types of biological data is essential for a holistic understanding of cancer biology, yet it remains challenging due to data heterogeneity, complexity, and sparsity. Addressing this, our study introduces an unsupervised deep learn...
A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds.
SAR and QSAR in environmental research
Nov 28, 2024
Identifying new compounds with minimal side effects to enhance patients' quality of life is the ultimate goal of drug discovery. Due to the expensive and time-consuming nature of experimental investigations and the scarcity of data in traditional QSA...
Measuring Metabolic Changes in Cancer Cells Using Two-Photon Fluorescence Lifetime Imaging Microscopy and Machine-Learning Analysis.
Journal of biophotonics
Nov 25, 2024
Two-photon (2P) fluorescence lifetime imaging microscopy (FLIM) was used to track cellular metabolism with drug treatment of auto-fluorescent coenzymes NAD(P)H and FAD in living cancer cells. Simultaneous excitation at 800 nm of both coenzymes was co...
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