AIMC Topic: Cell Line, Tumor
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A machine learning-based immune response signature to facilitate prognosis prediction in patients with endometrial cancer.
Scientific reports
Dec 28, 2024
Endometrial cancer is the most prevalent form of gynecologic malignancy, with a significant surge in incidence among youngsters. Although the advent of the immunotherapy era has profoundly improved patient outcomes, not all patients benefit from immu...
BiGM-lncLoc: Bi-level Multi-Graph Meta-Learning for Predicting Cell-Specific Long Noncoding RNAs Subcellular Localization.
Interdisciplinary sciences, computational life sciences
Dec 26, 2024
The precise spatiotemporal expression of long noncoding RNAs (lncRNAs) plays a pivotal role in biological regulation, and aberrant expression of lncRNAs in different subcellular localizations has been intricately linked to the onset and progression o...
Detection of Human Bladder Epithelial Cancerous Cells with Atomic Force Microscopy and Machine Learning.
Cells
Dec 26, 2024
The development of noninvasive methods for bladder cancer identification remains a critical clinical need. Recent studies have shown that atomic force microscopy (AFM), combined with pattern recognition machine learning, can detect bladder cancer by ...
Integration of Graph Neural Networks and multi-omics analysis identify the predictive factor and key gene for immunotherapy response and prognosis of bladder cancer.
Journal of translational medicine
Dec 23, 2024
OBJECTIVE: The evaluation of the efficacy of immunotherapy is of great value for the clinical treatment of bladder cancer. Graph Neural Networks (GNNs), pathway analysis and multi-omics analysis have shown great potential in the field of cancer diagn...
Neural Networks, Computer
Prognosis
Reproducibility of Results
Single-Cell Analysis
Computational Biology
Cell Proliferation
Apoptosis
Humans
Tumor Microenvironment
Immunotherapy
Treatment Outcome
Proteasome Endopeptidase Complex
Urinary Bladder Neoplasms
Multiomics
Cell Line, Tumor
Gene Expression Regulation, Neoplastic
Cell Movement
CXCL12 impact on glioblastoma cells behaviors under dynamic culture conditions: Insights for developing new therapeutic approaches.
PloS one
Dec 23, 2024
Glioblastoma multiforme (GBM) is the most prevalent malignant brain tumor, with an average survival time of 14 to 20 months. Its capacity to invade brain parenchyma leads to the failure of conventional treatments and subsequent tumor recurrence. Rece...
Programmable ultrasound-mediated swarms manipulation of bacteria-red blood cell microrobots for tumor-specific thrombosis and robust photothermal therapy.
Trends in biotechnology
Dec 20, 2024
Despite the excellent advantages of biomicrorobots, such as autonomous navigation and targeting actuation, effective penetration and retention to deep lesion sites for effective therapy remains a longstanding challenge. Here, we present dual-engine c...
AI-based classification of anticancer drugs reveals nucleolar condensation as a predictor of immunogenicity.
Molecular cancer
Dec 20, 2024
BACKGROUND: Immunogenic cell death (ICD) inducers are often identified in phenotypic screening campaigns by the release or surface exposure of various danger-associated molecular patterns (DAMPs) from malignant cells. This study aimed to streamline t...
Use and Comparison of Machine Learning Techniques to Discern the Protein Patterns of Autoantibodies Present in Women with and without Breast Pathology.
Journal of proteome research
Dec 19, 2024
Breast cancer (BC) has become a global health problem, ranking first in incidence and fifth in mortality in women around the world. Although there are some diagnostic methods for the disease, these are not sufficiently effective and are invasive. In ...
Exploring tumor microenvironment interactions and apoptosis pathways in NSCLC through spatial transcriptomics and machine learning.
Cellular oncology (Dordrecht, Netherlands)
Dec 19, 2024
BACKGROUND: The most common type of lung cancer is non-small cell lung cancer (NSCLC), accounting for 85% of all cases. Programmed cell death (PCD), an important regulatory mechanism for cell survival and homeostasis, has become increasingly prominen...
Discovery of anticancer peptides from natural and generated sequences using deep learning.
International journal of biological macromolecules
Dec 18, 2024
Anticancer peptides (ACPs) demonstrate significant potential in clinical cancer treatment due to their ability to selectively target and kill cancer cells. In recent years, numerous artificial intelligence (AI) algorithms have been developed. However...
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