Background and Purpose-Recently, there has been great interest in adult neurogenesis. We investigated whether transient forebrain ischemia could influence the proliferation of neuronal progenitor in the subgranular zone (SGZ) of the rat hippocampus and whether aging could influence the neurogenesis after ischemia. Methods-Male Wistar rats were subjected to 4-vessel occlusion model. We used a bromodeoxyuridine (BrdU) labeling method to identify the postproliferation cells and double-immunostaining with confocal microscopy to determine the cell phenotype. Results-The number of BrdU-positive cells in the SGZ increased Ϸ5.7-fold 8 days after ischemia, compared with the control. BrdU-positive cells formed clusters, which suggested that these cells had divided from an original progenitor cell, and expressed Musashi1 (Msi1), a marker of neural stem/progenitor cells. Although astrocytes also expressed Msi1 in the adult brain, Msi1-positive cells that formed clusters in the SGZ did not express glial fibrillary acidic protein, an astrocyte marker. About 70% of all BrdU-positive cells in the SGZ represented the neuronal phenotype 4 weeks after the BrdU injection. Although proliferation of progenitor cells was stimulated in both young and older animals, aging accelerated the reduction in newborn cells after ischemia. Conclusions-Our results indicate that ischemic stress stimulated the proliferation of neuronal progenitor cells in the SGZ of both young and old rats but resulted in increased neurogenesis only in young animals. Our findings will be important in developing therapeutic intervention to enhance endogenous neurogenesis after brain injury.
Recent studies demonstrated that neurogenesis in the adult hippocampus increased after transient global ischemia; however, the molecular mechanism underlying increased neurogenesis after ischemia remains unclear. The finding that proliferation of progenitor cells occurred at least a week after ischemic insult suggests that the stimulus was not an ischemic insult to progenitor cells. To clarify whether focal ischemia increases the rate of neurogenesis in the remote area, the authors examined the contralateral hemisphere in rats subjected to permanent occlusion of the middle cerebral artery. In the subgranular zone of the hippocampal dentate gyrus, the numbers of bromodeoxyuridine (BrdU)-positive cells increased approximately sixfold 7 days after ischemia. In double immunofluorescence staining, more than 80% of newborn cells expressed Musashi1, a marker of neural stem/progenitor cells, but only approximately 10% of BrdU-positive cells expressed glial fibrillary acidic protein (GFAP), a marker of astrocytes. The number of BrdU-positive cells markedly decreased 28 days after BrdU administration after ischemia, but it was still elevated compared with that of sham-operated rats. In double immunofluorescence staining, 80% of newborn cells expressed NeuN, a marker of differentiated neurons, and 10% of BrdU-positive cells expressed GFAP. However, in the other areas of the contralateral hemisphere including the rostral subventricular zone, the number of BrdU-positive cells remained unchanged. These results showed that focal ischemia stimulated the proliferation of neuronal progenitor cells, but did not support survival of newborn cells in the contralateral hippocampus.
In recent years, advances in artificial intelligence (AI) technology have led to the rapid clinical implementation of devices with AI technology in the medical field. More than 60 AI-equipped medical devices have already been approved by the Food and Drug Administration (FDA) in the United States, and the active introduction of AI technology is considered to be an inevitable trend in the future of medicine. In the field of oncology, clinical applications of medical devices using AI technology are already underway, mainly in radiology, and AI technology is expected to be positioned as an important core technology. In particular, “precision medicine,” a medical treatment that selects the most appropriate treatment for each patient based on a vast amount of medical data such as genome information, has become a worldwide trend; AI technology is expected to be utilized in the process of extracting truly useful information from a large amount of medical data and applying it to diagnosis and treatment. In this review, we would like to introduce the history of AI technology and the current state of medical AI, especially in the oncology field, as well as discuss the possibilities and challenges of AI technology in the medical field.
To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core discipline of precision medicine, and currently, the clinical application of cutting-edge genomic medicine aimed at improving the prevention, diagnosis and treatment of a wide range of diseases is promoted. However, although the Human Genome Project was completed in 2003 and large-scale genetic analyses have since been accomplished worldwide with the development of next-generation sequencing (NGS), explaining the mechanism of disease onset only using genetic variation has been recognized as difficult. Meanwhile, the importance of epigenetics, which describes inheritance by mechanisms other than the genomic DNA sequence, has recently attracted attention, and, in particular, many studies have reported the involvement of epigenetic deregulation in human cancer. So far, given that genetic and epigenetic studies tend to be accomplished independently, physiological relationships between genetics and epigenetics in diseases remain almost unknown. Since this situation may be a disadvantage to developing precision medicine, the integrated understanding of genetic variation and epigenetic deregulation appears to be now critical. Importantly, the current progress of artificial intelligence (AI) technologies, such as machine learning and deep learning, is remarkable and enables multimodal analyses of big omics data. In this regard, it is important to develop a platform that can conduct multimodal analysis of medical big data using AI as this may accelerate the realization of precision medicine. In this review, we discuss the importance of genome-wide epigenetic and multiomics analyses using AI in the era of precision medicine.
Sleep apnea syndrome (SAS) is characterized by intermittent hypoxia (IH) during sleep. SAS and obesity are strongly related to each other. Here, we investigated the effect of IH on the expression of major appetite regulatory genes in human neuronal cells. We exposed NB-1, SH-SY5Y, and SK-N-SH human neuronal cells to IH (64 cycles of 5 min hypoxia and 10 min normoxia), normoxia, or sustained hypoxia for 24 h and measured the mRNA levels of proopiomelanocortin (POMC), cocaine- and amphetamine-regulated transcript (CART), galanin, galanin-like peptide, ghrelin, pyroglutamylated RFamide peptide, agouti-related peptide, neuropeptide Y, and melanocortin 4 receptor by real-time RT-PCR. IH significantly increased the mRNA levels of POMC and CART in all the neuronal cells. Deletion analysis revealed that the -705 to -686 promoter region of POMC and the -950 to -929 region of CART were essential for the IH-induced promoter activity. As possible GATA factor binding sequences were found in the two regions, we performed real-time RT-PCR to determine which GATA family members were expressed and found that GATA2 and GATA3 mRNAs were predominantly expressed. Therefore, we introduced siRNAs against GATA2 and GATA3 into NB-1 cells and found that GATA2 and GATA3 siRNAs abolished the IH-induced up-regulation of both POMC and CART mRNAs. These results indicate that IH stress up-regulates the mRNA levels of anorexigenic peptides, POMC and CART, in human neuronal cells via GATA2 and GATA3. IH can have an anorexigenic effect on SAS patients through the transcriptional activation of POMC and CART in the central nervous system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.