Patterns of glucose transporter expression have been well-characterized in mammals. However, data for birds is currently restricted to isolated cells, domestic chickens and chicks, and ducklings. Therefore, in the present study, protein and gene expression of various glucose transporters (GLUTs) in English sparrow extensor digitorum communis, gastrocnemius and pectoralis muscles as well as heart, kidney, and brain tissues were examined. The hypothesis is that the expression pattern of avian GLUTs differs from mammals to maintain the high plasma glucose levels of birds and insulin insensitivity. Our studies failed to identify a GLUT4-like insulin responsive transporter in sparrows. GLUT1 gene expression was identified in all tissues examined and shares 88% homology with chicken and 84% homology with human GLUT1. Compared to the rat control, GLUT1 immunostaining of sparrow extensor digitorum communis muscle was weak and appeared to be localized to blood vessels whereas immunostaining of gastrocnemius muscles was comparable to rat muscle controls. Gene expression of GLUT3 was identified in all tissues examined and shares 90% gene sequence homology with chicken embryonic fibroblast and 75% homology with human GLUT3. Protein expression of GLUT3 was not determined as an avian antibody is not available. Moreover, the C-terminus of the mammalian GLUT3 transporter, against which antibodies are typically designed, differs significantly among species. The predominant difference of chicken and sparrow GLUT expression patterns from that of mammals is the lack of an avian GLUT4. The absence of this insulin responsive GLUT in birds may be a contributing factor to the observed high blood glucose levels and insulin insensitivity.
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Brief Bioinform
November 2024
Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, United States.
Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.
View Article and Find Full Text PDFClin Cancer Res
January 2025
Stanford University, Palo Alto, CA, United States.
Purpose: After failing primary and secondary hormonal therapy, castration-resistant and neuroendocrine prostate cancer metastatic to the bone is invariably lethal, although treatment with docetaxel and carboplatin can modestly improve survival. Therefore, agents targeting biologically relevant pathways in PCa and potentially synergizing with docetaxel and carboplatin in inhibiting bone metastasis growth are urgently needed.
Experimental Design: Phosphorylated (activated) AXL expression in human prostate cancer bone metastases was assessed by immunohistochemical staining.
STAR Protoc
January 2025
Department of Statistics, University of Georgia, 310 Herty Drive, Athens, GA 30602, USA. Electronic address:
Spatial transcriptomics enhances our understanding of cellular organization by mapping gene expression data to precise tissue locations. Here, we present a protocol for using weighted ensemble method for spatial transcriptomics (WEST), which uses ensemble techniques to boost the robustness and accuracy of existing algorithms. We describe steps for preprocessing data, obtaining embeddings from individual algorithms, and ensemble integrating all embeddings as a similarity matrix.
View Article and Find Full Text PDFSci Transl Med
January 2025
Department of Cell Biology and Physiology, Washington University School of Medicine, Saint Louis, MO 63110, USA.
Sci Transl Med
January 2025
Graduate Program in Human Genetics, University of Miami Miller School of Medicine, 1501 NW 10th Avenue (M-860), Miami, FL 33136, USA.
Primary mitochondrial disorders are most often caused by deleterious mutations in the mitochondrial DNA (mtDNA). Here, we used a mitochondrial DddA-derived cytosine base editor (DdCBE) to introduce a compensatory edit in a mouse model that carries the pathological mutation in the mitochondrial transfer RNA (tRNA) alanine (mt-tRNA) gene. Because the original m.
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