Real-time quantitative-PCR has been a priceless tool for gene expression analyses. The reaction, however, needs proper normalization with the use of housekeeping genes (HKGs), whose expression remains stable throughout the experimental conditions. Often, the combination of several genes is required for accurate normalization. Most importantly, there are no universal HKGs which can be used since their expression varies among different organisms, tissues or experimental conditions. In the present study, nine common HKGs (RPL19, tbp, ubx, GAPDH, α-TUB, β-TUB, 14-3-3zeta, RPE and actin3) are evaluated in thirteen different body parts, developmental stages and reproductive and olfactory tissues of two insects of agricultural importance, the medfly and the olive fly. Three software programs based on different algorithms were used (geNorm, NormFinder and BestKeeper) and gave different ranking of HKG stabilities. This confirms once again that the stability of common HKGs should not be taken for granted and demonstrates the caution that is needed in the choice of the appropriate HKGs. Finally, by estimating the average of a standard score of the stability values resulted by the three programs we were able to provide a useful consensus key for the choice of the best HKG combination in various tissues of the two insects.
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http://dx.doi.org/10.1038/srep45634 | DOI Listing |
PLoS One
January 2025
Heilongjiang University of Traditional Chinese Medicine, Harbin, Heilongjiang, China.
Hepatocellular carcinoma(HCC) has a high mortality and morbidity rate and seriously jeopardizes human life. Chemicals and chemotherapeutic agents have been experiencing problems such as side effects and drug resistance in the treatment of HCC, which cannot meet the needs of clinical treatment. Therefore, finding novel low-toxicity and high-efficiency anti-hepatocellular carcinoma drugs and exploring their mechanisms of action have become the current problems to be solved in the treatment of HCC.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America.
Background: Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data.
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January 2025
Department of Biochemistry, Institute of Health Science.
We aimed to explore the role of ikarugamycin (IKA) in breast cancer, its connection with hexokinase-2 (HK-2) repression, and tissue factor (TF). This study sought to extend the role of HK-2 as a TF activator in a comprehensive analysis of these interactions from the enzyme, gene, and protein levels. The investigation was performed with MDA-MB-231 and MCF-7 breast cancer lines.
View Article and Find Full Text PDFJ Vis Exp
January 2025
Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Harvard Medical School;
A method to quantitate the stabilization of Mitochondria-Associated endoplasmic reticulum Membranes (MAMs) in a 3-dimensional (3D) neural model of Alzheimer's disease (AD) is presented here. To begin, fresh human neuro progenitor ReN cells expressing β-amyloid precursor protein (APP) containing familial Alzheimer's disease (FAD) or naïve ReN cells are grown in thin (1:100) Matrigel-coated tissue culture plates. After the cells reach confluency, these are electroporated with expression plasmids encoding red fluorescence protein (RFP)-conjugated mitochondria-binding sequence of AKAP1(34-63) (Mito-RFP) that detects mitochondria or constitutive MAM stabilizers MAM 1X or MAM 9X that stabilize tight (6 nm ± 1 nm gap width) or loose (24 nm ± 3 nm gap width) MAMs, respectively.
View Article and Find Full Text PDFBioinformatics
January 2025
Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, 37099, Germany.
Motivation: Histone modifications play an important role in transcription regulation. Although the general importance of some histone modifications for transcription regulation has been previously established, the relevance of others and their interaction is subject to ongoing research. By training Machine Learning models to predict a gene's expression and explaining their decision making process, we can get hints on how histone modifications affect transcription.
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