👤 Nafiseh Sadat Deheshkar Gooneh Farahani

Sodium-glucose co-transporter-2 (SGLT2) inhibitors are a key treatment for type 2 diabetes mellitus (T2DM), with cardiorenal effects that extend beyond glycemic management. One important mechanism underpinning these pleiotropic effects is their interaction with AMP-activated protein kinase (AMPK), a crucial regulator of cellular energy balance. This review summarizes the strong evidence that SGLT2 inhibitors activate AMPK via both shared and drug-specific mechanisms. Empagliflozin induces on-target energetic stress, dapagliflozin activates the FGFR1-LKB1 axis, and canagliflozin inhibits mitochondrial complex I off-target. We describe how AMPK activation coordinates a protective network that includes PGC-1α-mediated mitochondrial biogenesis, ULK1-driven autophagy, Nrf2-antioxidant responses, and mTOR/NF-κB signaling inhibition. This interaction leads to enhanced insulin sensitivity, decreased oxidative stress, and sustained heart, kidney, and liver function. Furthermore, we conduct a comparative investigation of the distinct AMPK-modulatory profiles of prominent SGLT2 inhibitors and explore the practical applicability of these processes, including possible drawbacks such as the theoretical risk of muscle atrophy associated with persistent AMPK activation. By thoroughly describing the SGLT2-AMPK axis, this review emphasizes its importance as a therapeutic target and offers a framework for understanding the entire range of SGLT2 inhibitor activity in diabetes and associated consequences. Show less

The histologic and molecular changes from intestinal metaplasia (IM) to gastric cancer (GC) have not been fully characterized. The present study sought to identify potential alterations in signaling pathways in IM and GC to predict disease progression; these alterations can be considered therapeutic targets. Seven gene expression profiles were selected from the GEO database. Discriminate differentially expressed genes (DEGs) were analyzed by EnrichR. The STRING database, Cytoscape, Gene Expression Profiling Interactive Analysis (GEPIA), cBioPortal, NetworkAnalyst, MirWalk database, OncomiR, and bipartite miRNA‒mRNA correlation network was used for downstream analyses of selected module genes. Analyses revealed that extracellular matrix-receptor interactions (ITGB1, COL1A1, COL1A2, COL4A1, FN1, COL6A3, and THBS2) in GC and PPAR signaling pathway interactions (FABP1, APOC3, APOA1, HMGCS2, and PPARA and PCK1) in IM may play key roles in both the carcinogenesis and progression of underlying GC from intestinal metaplasia. IM enrichment indicated that this is closely related to digestion and absorption. The TF-hub gene regulatory network revealed that AR, TCF4, SALL4, and ESR1 were more important for hub gene expression. It was revealed that the development and prediction of GC may be affected by hsa-miR-29. It was found that PTGR1, C1orf115, CRYL1, ALDOB, and SULT1B1 were downregulated in GC and upregulated in IM. Therefore, they might have tumor suppressor activity in GC progression. New potential biomarkers and pathways involved in GC and IM were identified that are important for the transformation of GC from IM to adenocarcinoma and can be therapeutic targets for GC. Show less

This study aimed to introduce a biomarker panel to detect pancreatic ductal adenocarcinoma (PDAC) in the early stage, and also differentiate of stages from each other. PDAC is a lethal cancer with poor prognosis and overall survival. Gene expression profiles of PDAC patients were extracted from the Gene Expression Omnibus (GEO) database. The genes that were significantly differentially expressed (DEGs) for Stages I, II, and III in comparison to the healthy controls were identified. The determined DEGs were assessed via protein-protein interaction (PPI) network analysis, and the hub-bottleneck nodes of analyzed networks were introduced. A number of 140, 874, and 1519 significant DEGs were evaluated via PPI network analysis. A biomarker panel including ALB, CTNNB1, COL1A1, POSTN, LUM, and ANXA2 is presented as a biomarker panel to detect PDAC in the early stage. Two biomarker panels are suggested to recognize other stages of illness. It can be concluded that ALB, CTNNB1, COL1A1, POSTN, LUM, and ANXA2 and also FN1, HSP90AA1, LOX, ANXA5, SERPINE1, and WWP2 beside GAPDH, AKT1, EGF, CASP3 are suitable sets of gene to separate stages of PDAC. Show less

This study compared slow freezing and vitrification of ovarian tissue by evaluation of histological changes, WNT signaling pathway and apoptotic genes expression. Ovarian tissue was obtained from women aging 27-38 years old. Ovarian cortex from each patient was divided into three pieces and randomly grouped as slow freezing, vitrification and control groups for investigation of WNT signaling gene expression and β-CATENIN presence as well as histological studies. The stromal structure of all ovaries were preserved. The number of secondary follicles decreased in vitrified group (P < 0.05). WNT-3, β-CATENIN, FZD-2 and GSK-3β expressions were significantly higher in slow frozen and vitrified groups, compared to control group (P < 0.05). On the contrary, AXIN1 expression in slow frozen samples were significantly lower than that of the vitrified and control group. The expression of apoptotic genes, excluding CASP3, was significantly decreased in slow-frozen samples (P < 0.05). Conversely, BAX:BCL-2 percentage significantly increased in vitrification versus slow freezing and control(P < 0.05). Follicles in slow frozen samples displayed nuclear and cytoplasmic β-CATENIN staining, while control and vitrification groups only showed β-CATENIN protein in the cytoplasm. The presented data show that slow freezing results in a better preservation regardless of the type of follicle. Therefore, it is concluded that slow freezing is still an ideal method for ovary cryopreservation. Show less