Ferroptosis has recently been shown to play a significant role in the progression of intervertebral disk degeneration (IDD), although the underlying mechanism is still unknown. The objective of this work was to use stringent bioinformatic techniques to clarify the crucial roles played by genes associated with ferroptosis in the emergence of IDD. For additional study, the microarray data pertinent to the IDD were acquired from the Gene Expression Omnibus database. The ferroptosis-related and IDD-related genes (FIDDRGs) were identified using a variety of bioinformatic techniques, which were also used to carry out function enrichment analysis, protein-protein correlation analysis, build the correlation regulatory network, and examine the potential connections between ferroptosis and immune abnormalities and inflammatory responses in IDD. A total of 16 FIDDRGs were eliminated for the further function enrichment analysis, and 10 hub FIDDRGs were chosen to build the correlation regulatory network. Hub FIDDRGs were shown to be highly associated with M2 macrophages and hub inflammatory response-related genes in IDD. When seen as a whole, our findings can give fresh perspectives on the mechanistic studies of ferroptosis in the emergence of IDD and new prospective targets for the therapeutic approaches.
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http://dx.doi.org/10.1080/15257770.2024.2332403 | DOI Listing |
Anim Cells Syst (Seoul)
December 2024
Yunkang School of Medicine and Health, Nanfang College, Guangzhou, People's Republic of China.
Diabetic cardiomyopathy (DCM) is a major complication of type 2 diabetes mellitus (T2DM), but its effective prevention and treatment are still limited. We investigated the effects of GYY4137, a slow-releasing hydrogen sulfide donor, and its downstream mediator forkhead box protein O1 (FOXO1) on T2DM-associated DCM. , T2DM mice were induced by a high-fat diet coupled with streptozotocin injection.
View Article and Find Full Text PDFFront Chem
December 2024
African Society for Bioinformatics and Computational Biology, Cape Town, South Africa.
Introduction: Dengue Fever continues to pose a global threat due to the widespread distribution of its vector mosquitoes, and . While the WHO-approved vaccine, Dengvaxia, and antiviral treatments like Balapiravir and Celgosivir are available, challenges such as drug resistance, reduced efficacy, and high treatment costs persist. This study aims to identify novel potential inhibitors of the Dengue virus (DENV) using an integrative drug discovery approach encompassing machine learning and molecular docking techniques.
View Article and Find Full Text PDFVirus Genes
January 2025
College of Agronomy, Key Laboratory of Prevention and Control of Invasive Alien Species in Agriculture & Forestry of the North-Western Desert Oasis, Ministry of Agriculture and Rural Affairs, Xinjiang Agricultural University, Urumqi, 830052, China.
A novel plant virus was identified in fig trees exhibiting ring spot symptoms through high-throughput sequencing (HTS). The complete genome sequence was successfully determined using PCR and RT-PCR techniques. The virus features a circular DNA genome of 7233 nucleotides (nt) in length, encompassing four open reading frames (ORFs).
View Article and Find Full Text PDFJ Mol Model
January 2025
National Institute of Technology Durgapur, Durgapur, India.
Context: Protein secondary structure prediction is essential for understanding protein function and characteristics and can also facilitate drug discovery. Traditional methods for experimentally determining protein structures are both time-consuming and costly. Computational biology offers a viable alternative by predicting protein structures from their sequences.
View Article and Find Full Text PDFMol Inform
January 2025
Faculty of Information Technology, HUTECH University, 700000, Ho Chi Minh City, Vietnam.
In recent times, graph representation learning has been becoming a hot research topic which has attracted a lot of attention from researchers. Graph embeddings have diverse applications across fields such as information and social network analysis, bioinformatics and cheminformatics, natural language processing (NLP), and recommendation systems. Among the advanced deep learning (DL) based architectures used in graph representation learning, graph neural networks (GNNs) have emerged as the dominant and highly effective framework.
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