Effects of metformin on cancers in experimental and clinical studies: Focusing on autophagy and AMPK/mTOR signaling pathways.

Metformin (MET) is a preferred drug for the treatment of type 2 diabetes mellitus. Recent studies show that apart from its blood glucose-lowering effects, it also inhibits the development of various tumours, by inducing autophagy. Various studies have confirmed the inhibitory effects of MET on cancer cell lines' propagation, migration, and invasion. The objective of the study was to comprehensively review the potential of MET as an anticancer agent, particularly focusing on its ability to induce autophagy and inhibit the development and progression of various tumors. The study aimed to explore the inhibitory effects of MET on cancer cell proliferation, migration, and invasion, and its impact on key signaling pathways such as adenosine monophosphate-activated protein kinase (AMPK), mammalian target of rapamycin (mTOR), and PI3K. This review noted that MET exerts its anticancer effects by regulating key signalling pathways such as phosphoinositide 3-kinase (PI3K), LC3-I and LC3-II, Beclin-1, p53, and the autophagy-related gene (ATG), inhibiting the mTOR protein, downregulating the expression of p62/SQSTM1, and blockage of the cell cycle at the G0/G1. Moreover, MET can stimulate autophagy through pathways associated with the 5' AMPK, thereby inhibiting he development and progression of various human cancers, including hepatocellular carcinoma, prostate cancer, pancreatic cancer, osteosarcoma, myeloma, and non-small cell lung cancer. In summary, this detailed review provides a framework for further investigations that may appraise the autophagy-induced anticancer potential of MET and its repurposing for cancer treatment.

Discovery of common molecular signatures and drug repurposing for COVID-19/Asthma comorbidity: ACE2 and multi-partite networks.

Angiotensin-converting enzyme 2 (ACE2) is identified as the functional receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing global coronavirus disease-2019 (COVID-19) pandemic. This study aimed to elucidate potential therapeutic avenues by scrutinizing approved drugs through the identification of the genetic signature associated with SARS-CoV-2 infection in individuals with asthma. This exploration was conducted through an integrated analysis, encompassing interaction networks between the ACE2 receptor and common host (co-host) factors implicated in COVID-19/asthma comorbidity. The comprehensive analysis involved the identification of common differentially expressed genes (cDEGs) and hub-cDEGs, functional annotations, interaction networks, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and module construction. Interaction networks were used to identify overlapping disease modules and potential drug targets. Computational biology and molecular docking analyzes were utilized to discern functional drug modules. Subsequently, the impact of the identified drugs on the expression of hub-cDEGs was experimentally validated using a mouse model. A total of 153 cDEGs or co-host factors associated with ACE2 were identified in the COVID-19 and asthma comorbidity. Among these, seven significant cDEGs and proteins - namely, HRAS, IFNG, JUN, CDH1, TLR4, ICAM1, and SCD-were recognized as pivotal host factors linked to ACE2. Regulatory network analysis of hub-cDEGs revealed eight top-ranked transcription factors (TFs) proteins and nine microRNAs as key regulatory factors operating at the transcriptional and post-transcriptional levels, respectively. Molecular docking simulations led to the proposal of 10 top-ranked repurposable drug molecules (Rapamycin, Ivermectin, Everolimus, Quercetin, Estradiol, Entrectinib, Nilotinib, Conivaptan, Radotinib, and Venetoclax) as potential treatment options for COVID-19 in individuals with comorbid asthma. Validation analysis demonstrated that Rapamycin effectively inhibited ICAM1 expression in the HDM-stimulated mice group (p < 0.01). This study unveils the common pathogenesis and genetic signature underlying asthma and SARS-CoV-2 infection, delineated by the interaction networks of ACE2-related host factors. These findings provide valuable insights for the design and discovery of drugs aimed at more effective therapeutics within the context of lung disease comorbidities.

Performance Analysis of IoT and Long-Range Radio-Based Sensor Node and Gateway Architecture for Solid Waste Management.

Long-range radio (LoRa) communication is a widespread communication protocol that offers long range transmission and low data rates with minimum power consumption. In the context of solid waste management, only a low amount of data needs to be sent to the remote server. With this advantage, we proposed architecture for designing and developing a customized sensor node and gateway based on LoRa technology for realizing the filling level of the bins with minimal energy consumption. We evaluated the energy consumption of the proposed architecture by simulating it on the Framework for LoRa (FLoRa) simulation by varying distinct fundamental parameters of LoRa communication. This paper also provides the distinct evaluation metrics of the the long-range data rate, time on-air (ToA), LoRa sensitivity, link budget, and battery life of sensor node. Finally, the paper concludes with a real-time experimental setup, where we can receive the sensor data on the cloud server with a customized sensor node and gateway.