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Sin SQ, Mohan CD, Goh RMWJ, You M, Nayak SC, Chen L, Sethi G, Rangappa KS, Wang L. Hypoxia signaling in hepatocellular carcinoma: Challenges and therapeutic opportunities. Cancer Metastasis Rev 2023; 42:741-764. [PMID: 36547748 DOI: 10.1007/s10555-022-10071-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 11/25/2022] [Indexed: 12/24/2022]
Abstract
Hepatocellular carcinoma (HCC) is one of the most common cancers with a relatively high cancer-related mortality. The uncontrolled proliferation of HCC consumes a significant amount of oxygen, causing the development of a hypoxic tumor microenvironment (TME). Hypoxia-inducible factors (HIFs), crucial regulators in the TME, activate several cancer hallmarks leading to the hepatocarcinogenesis of HCC and resistance to current therapeutics. As such, HIFs and their signaling pathways have been explored as potential therapeutic targets for the future management of HCC. This review discusses the current understanding of the structure and function of HIFs and their complex relationship with the various cancer hallmarks. To address tumor hypoxia, this review provides an insight into the various potential novel therapeutic agents for managing HCC, such as hypoxia-activated prodrugs, HIF inhibitors, nanomaterials, antisense oligonucleotides, and natural compounds, that target HIFs/hypoxic signaling pathways in HCC. Because of HCC's relatively high incidence and mortality rates in the past decades, greater efforts should be put in place to explore novel therapeutic approaches to improve the outcome for HCC patients.
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Affiliation(s)
- Shant Qinxiang Sin
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | | | | | - Mingliang You
- Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Hangzhou Cancer Institute, Hangzhou, 31002, China
- Affiliated Hangzhou Cancer Hospital, Zhejiang University School of Medicine, Hangzhou, 31002, China
| | - Siddaiah Chandra Nayak
- Department of Studies in Biotechnology, University of Mysore, Manasagangotri, Mysore, 570006, India
| | - Lu Chen
- College of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
- Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
| | - Gautam Sethi
- NUS Centre for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | - Lingzhi Wang
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.
- NUS Centre for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
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Jadimurthy R, Jagadish S, Nayak SC, Kumar S, Mohan CD, Rangappa KS. Phytochemicals as Invaluable Sources of Potent Antimicrobial Agents to Combat Antibiotic Resistance. Life (Basel) 2023; 13:life13040948. [PMID: 37109477 PMCID: PMC10145550 DOI: 10.3390/life13040948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 03/04/2023] [Accepted: 03/29/2023] [Indexed: 04/08/2023] Open
Abstract
Plants have been used for therapeutic purposes against various human ailments for several centuries. Plant-derived natural compounds have been implemented in clinics against microbial diseases. Unfortunately, the emergence of antimicrobial resistance has significantly reduced the efficacy of existing standard antimicrobials. The World Health Organization (WHO) has declared antimicrobial resistance as one of the top 10 global public health threats facing humanity. Therefore, it is the need of the hour to discover new antimicrobial agents against drug-resistant pathogens. In the present article, we have discussed the importance of plant metabolites in the context of their medicinal applications and elaborated on their mechanism of antimicrobial action against human pathogens. The WHO has categorized some drug-resistant bacteria and fungi as critical and high priority based on the need to develope new drugs, and we have considered the plant metabolites that target these bacteria and fungi. We have also emphasized the role of phytochemicals that target deadly viruses such as COVID-19, Ebola, and dengue. Additionally, we have also elaborated on the synergetic effect of plant-derived compounds with standard antimicrobials against clinically important microbes. Overall, this article provides an overview of the importance of considering phytogenous compounds in the development of antimicrobial compounds as therapeutic agents against drug-resistant microbes.
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Affiliation(s)
- Ragi Jadimurthy
- Department of Studies in Molecular Biology, University of Mysore, Manasagangotri, Mysore 570006, India
| | - Swamy Jagadish
- Department of Studies in Molecular Biology, University of Mysore, Manasagangotri, Mysore 570006, India
| | - Siddaiah Chandra Nayak
- Department of Studies in Biotechnology, University of Mysore, Manasagangotri, Mysore 570006, India
| | - Sumana Kumar
- Department of Microbiology, Faculty of Life Sciences, JSS Academy of Higher Education and Research, Mysore 570015, India
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Kundu N, Rani G, Dhaka VS, Gupta K, Nayak SC, Verma S, Ijaz MF, Woźniak M. IoT and Interpretable Machine Learning Based Framework for Disease Prediction in Pearl Millet. Sensors (Basel) 2021; 21:5386. [PMID: 34450827 PMCID: PMC8397940 DOI: 10.3390/s21165386] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 07/23/2021] [Accepted: 07/28/2021] [Indexed: 12/02/2022]
Abstract
Decrease in crop yield and degradation in product quality due to plant diseases such as rust and blast in pearl millet is the cause of concern for farmers and the agriculture industry. The stipulation of expert advice for disease identification is also a challenge for the farmers. The traditional techniques adopted for plant disease detection require more human intervention, are unhandy for farmers, and have a high cost of deployment, operation, and maintenance. Therefore, there is a requirement for automating plant disease detection and classification. Deep learning and IoT-based solutions are proposed in the literature for plant disease detection and classification. However, there is a huge scope to develop low-cost systems by integrating these techniques for data collection, feature visualization, and disease detection. This research aims to develop the 'Automatic and Intelligent Data Collector and Classifier' framework by integrating IoT and deep learning. The framework automatically collects the imagery and parametric data from the pearl millet farmland at ICAR, Mysore, India. It automatically sends the collected data to the cloud server and the Raspberry Pi. The 'Custom-Net' model designed as a part of this research is deployed on the cloud server. It collaborates with the Raspberry Pi to precisely predict the blast and rust diseases in pearl millet. Moreover, the Grad-CAM is employed to visualize the features extracted by the 'Custom-Net'. Furthermore, the impact of transfer learning on the 'Custom-Net' and state-of-the-art models viz. Inception ResNet-V2, Inception-V3, ResNet-50, VGG-16, and VGG-19 is shown in this manuscript. Based on the experimental results, and features visualization by Grad-CAM, it is observed that the 'Custom-Net' extracts the relevant features and the transfer learning improves the extraction of relevant features. Additionally, the 'Custom-Net' model reports a classification accuracy of 98.78% that is equivalent to state-of-the-art models viz. Inception ResNet-V2, Inception-V3, ResNet-50, VGG-16, and VGG-19. Although the classification of 'Custom-Net' is comparable to state-of-the-art models, it is effective in reducing the training time by 86.67%. It makes the model more suitable for automating disease detection. This proves that the proposed model is effective in providing a low-cost and handy tool for farmers to improve crop yield and product quality.
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Affiliation(s)
- Nidhi Kundu
- Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur 303007, India; (N.K.); (V.S.D.); (K.G.)
| | - Geeta Rani
- Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur 303007, India; (N.K.); (V.S.D.); (K.G.)
| | - Vijaypal Singh Dhaka
- Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur 303007, India; (N.K.); (V.S.D.); (K.G.)
| | - Kalpit Gupta
- Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur 303007, India; (N.K.); (V.S.D.); (K.G.)
| | | | - Sahil Verma
- Department of Computer Science and Engineering, Chandigarh University, Mohali 140413, India;
| | - Muhammad Fazal Ijaz
- Department of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea
| | - Marcin Woźniak
- Faculty of Applied Mathematics, Silesian University of Technology, 44-100 Gliwice, Poland;
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Madan Kumar S, Kumar V, Al-Ghorbani M, Shivaram Holla B, Poojary B, Praveen P, Chandra Nayak S, Mohan JS, Thamotharan S, Shamprasad VR, Lokanath NK, Al-Zaqri N, Alsalme A. Theoretical and experimental solid state studies of Ethyl 1-benzyl-2-(thiophen-3-yl)-1H-benzo[d]imidazole-5-carboxylate. Z KRIST-CRYST MATER 2020. [DOI: 10.1515/zkri-2020-0052] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
The title compound Ethyl 1-benzyl-2-(thiophen-3-yl)-1H-benzo[d]imidazole-5-carboxylate (BI) is prepared and characterized using spectroscopic methods. The theoretical optimization and three dimensional molecular structure are confirmed by X-ray diffraction method (single crystal). The C–H…π intermolecular interactions stabilize the crystal structure. The intermolecular contacts in the crystal structure are quantified using Hirshfeld surfaces and the crystal packing is elucidated using 3D energy frameworks analysis. In the frameworks, the dispersion energy term is dominated over the electrostatic energy term. The structural optimization was carried out with B3LYP/6-311++G (d, p) level of theory. The visual representations of positive and negative potentials (electrostatic potential) are mapped on the electron density isosurface. The band gap energy (HOMO-LUMO) of the molecule is calculated to be 4.36 eV. Structural conformation of BI is compared with similar structures.
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Affiliation(s)
| | - Vasantha Kumar
- Department of Chemistry , SDM College (Autonomous) , Ujire 574240, India
- Department of Chemistry , Mangalore University , Mangalagangothri 574199, India
| | | | | | - Boja Poojary
- Department of Chemistry , Mangalore University , Mangalagangothri 574199, India
| | | | | | - Janani S. Mohan
- Biomolecular Crystallography Laboratory, Department of Bioinformatics, School of Chemical and Biotechnology , SASTRA Deemed University 613401, Thanjavur , India
| | - Subbiah Thamotharan
- Biomolecular Crystallography Laboratory, Department of Bioinformatics, School of Chemical and Biotechnology , SASTRA Deemed University 613401, Thanjavur , India
| | - Varija Raghu Shamprasad
- Neurogenetics Laboratory, Department of Applied Zoology , Mangalore University , Mangalagangothri 574199, India
| | | | - Nabil Al-Zaqri
- Department of Chemistry, College of Science , King Saud University , P. O. Box 2455 , Riyadh 11451, Saudi Arabia
| | - Ali Alsalme
- Department of Chemistry, College of Science , King Saud University , P. O. Box 2455 , Riyadh 11451, Saudi Arabia
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