A number of heavy metals are known to be essential for life, but most of these can also be toxic to cells under certain circumstances, or at elevated levels. Metals can directly induce gene expression through the actions of metal-responsive transcription factors. However, metals can also influence the response to non-metal extracellular signals. Cells respond to extracellular signals through a variety of different, but often interacting, signal transduction pathways. Metals can alter cell behaviour by interacting with transcription factors and transduction molecules, many of which are dependent on metals (primarily zinc) for their action. In addition, metals can affect cells in more nonspecific ways, for example, by inducing a generalized stress response or by cross-linking cell surface thiol groups. The prominent role of zinc in signal transduction combined with low intracellular free zinc levels has lead to the speculation that cellular signaling and gene expression may be regulated, in part, by zinc bioavailability. Experimental modification of the levels of the intracellular metal-binding protein, metallothionein (MT), results in altered responsiveness to extracellular signals. This observation suggests that MT is capable of influencing gene expression, perhaps by regulating the level of intracellular free zinc.
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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.
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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.
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