In this study, different concentrations of five food dyes (amaranth, patent blue, carminic acid, indigotine and erythrosine) have been evaluated for genotoxicity in the Somatic Mutation and Recombination Test (SMART) of Drosophila melanogaster. Standard cross was used in the experiment. Larvae including two linked recessive wing hair mutations were chronically fed at different concentrations of the test compounds in standard Drosophila Instant Medium. Feeding ended with pupation of the surviving larvae. Wings of the emerging adult flies were scored for the presence of spots of mutant cells which can result from either somatic mutation or somatic recombination. For the evaluation of genotoxic effects, the frequencies of spots per wing in the treated series were compared to the control group, which was distilled water. The present study shows that carminic acid and indigotine demonstrated negative results while erythrosine demonstrated inconclusive results. In addition 25 mg mL(-1) concentration of patent blue and 12.5, 25 and 50 mg mL(-1) concentrations of amaranth demonstrated positive results in the SMART.
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http://dx.doi.org/10.1016/j.chemosphere.2012.03.032 | DOI Listing |
Int J Mol Sci
January 2025
Department of Neuropediatrics, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, 13353 Berlin, Germany.
Epilepsy affects 50 million people worldwide and is drug-resistant in approximately one-third of cases. Even when a structural lesion is identified as the epileptogenic focus, understanding the underlying genetic causes is crucial to guide both counseling and treatment decisions. Both somatic and germline DNA variants may contribute to the lesion itself and/or influence the severity of symptoms.
View Article and Find Full Text PDFBiology (Basel)
January 2025
Division of Thoracic Surgery, Cantonal Hospital Lucerne, 6000 Lucerne, Switzerland.
In 2001, two enzyme-encoding genes were recognized in the fruit fly . The genetic material, labeled and , encodes ribonuclease-type enzymes with slightly diverse target substrates. The human orthologue is .
View Article and Find Full Text PDFSci Rep
January 2025
Department of Respiratory Diseases, Qilu Hospital of Shandong University, No. 107, Culture West Road, Jinan, Shandong, China.
To integrate machine learning and multiomic data on lactylation-related genes (LRGs) for molecular typing and prognosis prediction in lung adenocarcinoma (LUAD). LRG mRNA and long non-coding RNA transcriptomes, epigenetic methylation data, and somatic mutation data from The Cancer Genome Atlas LUAD cohort were analyzed to identify lactylation cancer subtypes (CSs) using 10 multiomics ensemble clustering techniques. The findings were then validated using the GSE31210 and GSE13213 LUAD cohorts.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Computational Biology, Cornell University, Ithaca, 14853, NY, USA.
A major goal of cancer biology is to understand the mechanisms driven by somatically acquired mutations. Two distinct methodologies-one analyzing mutation clustering within protein sequences and 3D structures, the other leveraging protein-protein interaction network topology-offer complementary strengths. We present NetFlow3D, a unified, end-to-end 3D structurally-informed protein interaction network propagation framework that maps the multiscale mechanistic effects of mutations.
View Article and Find Full Text PDFMedicine (Baltimore)
January 2025
Department of Otolaryngology, Hangzhou Red Cross Hospital (Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine), Hangzhou, Zhejiang, China.
T-helper 17 (Th17) cells significantly influence the onset and advancement of malignancies. This study endeavor focused on delineating molecular classifications and developing a prognostic signature grounded in Th17 cell differentiation-related genes (TCDRGs) using machine learning algorithms in head and neck squamous cell carcinoma (HNSCC). A consensus clustering approach was applied to The Cancer Genome Atlas-HNSCC cohort based on TCDRGs, followed by an examination of differential gene expression using the limma package.
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