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Mitochondria: the cell powerhouse and nexus of stress

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889192830 Year: Pages: 121 DOI: 10.3389/978-2-88919-283-0 Language: English
Publisher: Frontiers Media SA
Subject: Biology --- Physiology --- Science (General)
Added to DOAB on : 2015-12-10 11:59:06
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Abstract

Mitochondrion, a sub-cellular organelle originated from primary endosymbiosis, plays a vital role in energy metabolism of eukaryotic cells. The transfer of electrons through the electron transport chain (ETC) to molecular oxygen accompanied by the extrusion of protons from the matrix generate an electrochemical gradient across the inner mitochondrial membrane (IMM) that is used for ATP synthesis by oxidative phosphorylation. Despite many aspects of ATP synthesis have been delineated, regulatory mechanisms responsible for energy synthesis and transfer still remain to be uncovered. In addition to energy function, mitochondria play a crucial role in cell metabolism under both physiological and pathological conditions through their participation in many intracellular signaling pathways. Studies over the last 30 years provide strong evidence that mitochondria are the nexus of various stresses which initiate cell death through apoptosis, oncosis, necrosis and autophagy depending on the severity of the stress and cellular energy status. The release of several pro-apoptotic proteins such as cytochrome c, Smac/DIABLO, AIF, endonuclease G from intermembrane space initiates both caspase-dependent and caspase-independent apoptosis. The formation of the mitochondrial permeability transition pore in the IMM promotes cell death mostly through necrosis whereas a mild stress activates autophagy. Due to their critical roles in both cell death and survival mitochondria have been widely considered as an important target for various pharmacological and conditional therapeutic approaches. Currently, a large number of mitochondria-targeted agents are suggested to prevent (in ischemia reperfusion injury, cardiovascular, neurodegenerative and other diseases) or stimulate (in various cancers) cell death. This Research Topic focuses on the role of mitochondria in the regulation of cell metabolism and signaling under physiological and pathological conditions. Studies performed on cultured cells and isolated organs/tissues using different animal and cellular models of various diseases are also included and discussed.

Application of Bioinformatics in Cancers

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ISBN: 9783039217885 / 9783039217892 Year: Pages: 418 DOI: 10.3390/books978-3-03921-789-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-12-09 11:49:16
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Abstract

This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible.

Keywords

comorbidity score --- mortality --- locoregionally advanced --- HNSCC --- curative surgery --- traditional Chinese medicine --- health strengthening herb --- cancer treatment --- network pharmacology --- network target --- high-throughput analysis --- brain metastases --- colorectal cancer --- KRAS mutation --- PD-L1 --- tumor infiltrating lymphocytes --- drug resistance --- gefitinib --- erlotinib --- biostatistics --- bioinformatics --- Bufadienolide-like chemicals --- molecular mechanism --- anti-cancer --- bioinformatics --- cancer --- brain --- pathophysiology --- imaging --- machine learning --- extreme learning --- deep learning --- neurological disorders --- pancreatic cancer --- TCGA --- curation --- DNA --- RNA --- protein --- single-biomarkers --- multiple-biomarkers --- cancer-related pathways --- colorectal cancer --- DNA sequence profile --- Monte Carlo --- mixture of normal distributions --- somatic mutation --- tumor --- mutable motif --- activation induced deaminase --- AID/APOBEC --- transcriptional signatures --- copy number variation --- copy number aberration --- TCGA mining --- cancer CRISPR --- firehose --- gene signature extraction --- gene loss biomarkers --- gene inactivation biomarkers --- biomarker discovery --- chemotherapy --- microarray --- ovarian cancer --- predictive model --- machine learning --- overall survival --- observed survival interval --- skin cutaneous melanoma --- The Cancer Genome Atlas --- omics --- breast cancer prognosis --- artificial intelligence --- machine learning --- decision support systems --- cancer prognosis --- independent prognostic power --- omics profiles --- histopathological imaging features --- cancer --- intratumor heterogeneity --- genomic instability --- epigenetics --- mitochondrial metabolism --- miRNAs --- cancer biomarkers --- breast cancer detection --- machine learning --- feature selection --- classification --- denoising autoencoders --- breast cancer --- feature extraction and interpretation --- concatenated deep feature --- cancer modeling --- interaction --- histopathological imaging --- clinical/environmental factors --- oral cancer --- miRNA --- bioinformatics --- datasets --- biomarkers --- TCGA --- GEO DataSets --- hormone sensitive cancers --- breast cancer --- StAR --- estrogen --- steroidogenic enzymes --- hTERT --- telomerase --- telomeres --- alternative splicing --- network analysis --- hierarchical clustering analysis --- differential gene expression analysis --- cancer biomarker --- diseases genes --- variable selection --- false discovery rate --- knockoffs --- bioinformatics --- copy number variation --- cell-free DNA --- methylation --- mutation --- next generation sequencing --- self-organizing map --- head and neck cancer --- treatment de-escalation --- HP --- molecular subtypes --- tumor microenvironment --- Bioinformatics tool --- R package --- machine learning --- meta-analysis --- biomarker signature --- gene expression analysis --- survival analysis --- functional analysis --- bioinformatics --- machine learning --- artificial intelligence --- Network Analysis --- single-cell sequencing --- circulating tumor DNA (ctDNA) --- Neoantigen Prediction --- precision medicine --- Computational Immunology

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