AIMC Topic: Mutation

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Divergent Clonal Evolution and Early Dissemination Promote Genetic Heterogeneity of Metastases in Castration-Resistant Prostate Cancer.

Cancer research
UNLABELLED: Lethal prostate cancer has passed through at least two evolutionary bottlenecks: acquisition of metastatic potential and development of castration resistance. A better understanding of how this affects genetic heterogeneity across metasta...

Machine Learning Classifier Using Blood Count Parameters and Erythropoietin to Predict JAK2 Mutations in Patients With Erythrocytosis.

Archives of pathology & laboratory medicine
CONTEXT.—: Differentiating polycythemia vera from other causes of erythrocytosis is a diagnostic challenge. Although most patients with polycythemia vera have Janus kinase 2 (JAK2) mutations, extensive testing is impractical because this is an uncomm...

Digital pathology and image analysis of p53 biomarker in lymphomas using two algorithms: correlation with genotype and visual inspection.

Journal of clinical pathology
p53 immunohistochemistry (IHC) is widely used as a rapid surrogate for detecting mutations, with mutations being a key biomarker for poor outcomes in lymphomas. We developed two algorithms using digital quantification tools to assess p53 expression...

Understanding the stability landscape of LbCas12a by deep analysis of stabilizing mutations and mutation combinations.

Protein science : a publication of the Protein Society
Cas12a is one of the most widely used Cas nucleases for genome editing and in vitro diagnosis. A number of engineered Cas12a mutants have been identified with improved activity and stability. However, it remains largely unaddressed how these mutation...

Generating realistic artificial human genomes using adversarial autoencoders.

NAR genomics and bioinformatics
A publicly available human genome is both valuable to researchers and a risk for its donor. Many actors could exploit it to extract information about the donor's health or that of their relatives. Recent efforts have employed artificial intelligence ...

Deep Learning-Based Multimodal Feature Interaction-Guided Fusion: Enhancing the Evaluation of EGFR in Advanced Lung Adenocarcinoma.

Academic radiology
RATIONALE AND OBJECTIVES: The aim of this study is to develop a deep learning-based multimodal feature interaction-guided fusion (DL-MFIF) framework that integrates macroscopic information from computed tomography (CT) images with microscopic informa...

External Validation of a CT-Based Radiogenomics Model for the Detection of EGFR Mutation in NSCLC and the Impact of Prevalence in Model Building by Using Synthetic Minority Over Sampling (SMOTE): Lessons Learned.

Academic radiology
RATIONALE AND OBJECTIVES: Radiogenomics holds promise in identifying molecular alterations in nonsmall cell lung cancer (NSCLC) using imaging features. Previously, we developed a radiogenomics model to predict epidermal growth factor receptor (EGFR) ...

Genomic and machine learning approaches to predict antimicrobial resistance in .

Microbiology spectrum
UNLABELLED: is a multidrug-resistant pathogen, which poses a major challenge to clinical management due to its increasing resistance to common antibiotics, such as levofloxacin (LEV) and trimethoprim-sulfamethoxazole (SXT), and poor clinical respons...

Predicting p53 Status in IDH-Mutant Gliomas Using MRI-Based Radiomic Model.

Cancer medicine
OBJECTIVES: Accurate and noninvasive detection of p53 status in isocitrate dehydrogenase mutant (IDH-mt) glioma is clinically meaningful for molecular stratification of glioma, yet it remains challenging. We aimed to investigate the diagnostic effica...