Insulin resistance (IR) is a biological response to insulin stimulation in target tissues. IR alters glucose metabolism, resulting in increased insulin production by beta-cells. The primary condition associated with IR is obesity, which is often caused by environmental factors, particularly diet. Objective: To describe IR in various organs and present a signaling pathway project. Methods: The PubMed database was used to search for IR review publications. The referenced data for the signaling pathway were selected by aggregating references from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A signaling pathway was designed based on IR research manuscripts, which show various mechanisms involved. The KEGG server was used to explore protein-protein interactions and create a signaling pathway diagram. The signaling path was mapped using PathVisio software, adapted to the model of the KEGG PATHWAY Database: https://www.genome.jp/pathway/map04930. Results: Articles featuring the terms “insulin resistance” and “signaling pathway” were selected from the PubMed database. Based on validated research articles, well-founded pathways were chosen and a representative description of these pathways was achieved. Reproduction contigs from the KEGG database projected the signaling pathway of biomolecules leading to IR. Thus, the interaction between multiple mechanisms releases factors that contribute to the development of IR. Conclusion: The interaction between multiple mechanisms and molecular interactions are important factors in the development of IR in various organs and systems.
Introduction: Recent research in the field of epigenetics has shed light on the impact of epigenetic modifications in the development and progression of Hashimoto thyroiditis (HT). However, the epigenetic roles in HT are still not fully elucidated. Objective: To exhibit an in silico representation of the epigenetic mechanism in HT development and explicate their function in the pathogenesis of the ailment. Methods: Genetic data were retrieved from GEO database (NCBI) for DNA methylation assessment through bioinformatics. We evaluated 6 HT samples from GSE29315 dataset. Normalization of the data was performed to identify differentially expressed genes (DEGs). Standardization of all expression data was accomplished using the R programming language. The R package was employed for the analysis of DEGs. Genes exhibiting an expression fold change greater than 4 and a P-value less than 0.05 were considered to be DEGs. Results: The expression data from the 6 HT specimens in GSE29315 (GSM724489, GSM724490, GSM724491, GSM724492, GSM724493, GSM724494) were patterned. In total, 71 DEGs, including 63 positively regulated genes and 7 negatively regulated genes, were identified. An expression density plot was used to display the clustering of DEGs, and average log-expression was constructed to visually display all DEGs in the HT sample. In the in silico simulation of the methylated regions in gene GSE29315, we identify specific CpG sites within the analyzed regions that showed significant methylation changes: Region 1 - Promoter Region: CpG site 1: Hypomethylated (40% methylation), CpG site 2: Hypomethylated (35% methylation), and CpG site 3: Hypomethylated (38% methylation); Region 2 - Enhancer Region: CpG site 4: Hypermethylated (80% methylation). CpG site 5: Hypermethylated (75% methylation), and CpG site 6: Hypermethylated (85% methylation); Region 3 - Transcription Start Site: CpG site 7: Hypomethylated (30% methylation), CpG site 8: Hypomethylated (25% methylation), and CpG site 9: Hypomethylated (28% methylation); Region 4 - Intronic Region: CpG site 10: Hypermethylated (70% methylation), CpG site 11: Hypermethylated (65% methylation), and CpG site 12: Hypermethylated (75% methylation. Conclusion: Our analysis of the GSE29315 gene revealed significant hypermethylation in specific regions, which could lead to gene silencing or altered gene expression. Additionally, we identified regions of hypomethylation that may upregulate gene activity. Keywords: Hashimoto Thyroiditis, Epigenetic, Bioinformatics.
The Durie/Salmon staging system continues to be used worldwide in patients with multiple myeloma. However, in recent years, new systems have been proposed. The International Myeloma Working Group performed a retrospective study with 11,179 patients and proposed an "International Staging System" utilizing serum levels of â2 microglobulin and albumin. In addition, current research has focused on the usefulness of cytogenetic and molecular data as prognostic factors. These data suggest that these parameters are powerful discriminators of a poor prognostic group of myeloma patients. Indeed, these prognostic indexes have been utilized in clinical trials, with interesting and encouraging results.
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