RNA interference (RNAi) has become a widely used reverse genetic tool to study gene function in eukaryotic organisms and is being developed as a technology for insect pest management. The efficiency of RNAi varies among organisms. Insects from different orders also display differential efficiency of RNAi, ranging from highly efficient (coleopterans) to very low efficient (lepidopterans). We investigated the reasons for varying RNAi efficiency between lepidopteran and coleopteran cell lines and also between the Colorado potato beetle, Leptinotarsa decemlineata and tobacco budworm, Heliothis virescens. The dsRNA either injected or fed was degraded faster in H. virescens than in L. decemlineata. Both lepidopteran and coleopteran cell lines and tissues efficiently took up the dsRNA. Interestingly, the dsRNA administered to coleopteran cell lines and tissues was taken up and processed to siRNA whereas the dsRNA was taken up by lepidopteran cell lines and tissues but no siRNA was detected in the total RNA isolated from these cell lines and tissues. The data included in this paper showed that the degradation and intracellular transport of dsRNA are the major factors responsible for reduced RNAi efficiency in lepidopteran insects.
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http://dx.doi.org/10.1080/15476286.2016.1191728 | DOI Listing |
Eur J Epidemiol
January 2025
Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Stockholm, Sweden.
The Stockholm Early Detection of Cancer Study (STEADY-CAN) cohort was established to investigate strategies for early cancer detection in a population-based context within Stockholm County, the capital region of Sweden. Utilising real-world data to explore cancer-related healthcare patterns and outcomes, the cohort links extensive clinical and laboratory data from both inpatient and outpatient care in the region. The dataset includes demographic information, detailed diagnostic codes, laboratory results, prescribed medications, and healthcare utilisation data.
View Article and Find Full Text PDFNPJ Precis Oncol
January 2025
Zentalis Pharmaceuticals, Inc., San Diego, CA, USA.
Upregulation of Cyclin E1 and subsequent activation of CDK2 accelerates cell cycle progression from G1 to S phase and is a common oncogenic driver in gynecological malignancies. WEE1 kinase counteracts the effects of Cyclin E1/CDK2 activation by regulating multiple cell cycle checkpoints. Here we characterized the relationship between Cyclin E1/CDK2 activation and sensitivity to the selective WEE1 inhibitor azenosertib.
View Article and Find Full Text PDFSci Rep
January 2025
School of Medicine, Nankai University, Tianjin, 300071, China.
Cholangiocarcinoma (CCA), a highly aggressive form of cancer, is known for its high mortality rate. A Disintegrin and Metalloprotease Domain-like Protein Decysin-1 (ADAMDEC1) can promote the development and metastasis in various tumors by degrading the extracellular matrix. However, its regulatory mechanism in CCA remains unclear.
View Article and Find Full Text PDFAnn Hematol
January 2025
Department of Hematology, Navy Medical Center of PLA, Naval Medical University, No. 338 West Huaihai Road, Changning District, Shanghai, 200052, China.
Multiple myeloma(MM) remains incurable with high relapse and chemoresistance rates. Differentially expressed genes(DEGs) between newly diagnosed myeloma and secondary plasma cell leukemia(sPCL) were subjected to a weighted gene co-expression network analysis(WGCNA). Drug resistant myeloma cell lines were established.
View Article and Find Full Text PDFSci Rep
January 2025
School of Physics, Engineering and Technology, University of York, Heslington, York, YO10 5DD, UK.
Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics remain challenged to risk-stratify such patients; hence, new methods of approach to biomolecularly sub-classify the disease are needed. Here we use an unsupervised self-organising map approach to analyse live-cell Raman spectroscopy data obtained from prostate cell-lines; our aim is to exemplify this method to sub-stratify, at the single-cell-level, the cancer disease state using high-dimensional datasets with minimal preprocessing.
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