A critical review on therapeutic approaches of CRISPR-Cas9 in diabetes mellitus

Dey, Aparajita; Lyngdoh, Antonia; Dhasmana, Archna; Ranjan, Anuj; Kishore, Shristi; Rustagi, Sarvesh; Tuli, Hardeep Singh; Chauhan, Abhishek; Rath, Prangya; Malik, Sumira

doi:10.1007/s00210-023-02631-1

Cited by 4 publications

(2 citation statements)

References 151 publications

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“…This strategy directly tackles genetic factors contributing to T2DM and has the potential not only to manage but also to potentially reverse the condition’s progression. However, thorough research and clinical trials are essential to fully understand its safety, efficacy, and long-term impacts [ 52 ].…”

Section: Discussionmentioning

confidence: 99%

Understanding Type 2 Diabetes Mellitus Risk Parameters through Intermittent Fasting: A Machine Learning Approach

Shazman

2023

Nutrients

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Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by elevated blood glucose levels. Despite the availability of pharmacological treatments, dietary plans, and exercise regimens, T2DM remains a significant global cause of mortality. As a result, there is an increasing interest in exploring lifestyle interventions, such as intermittent fasting (IF). This study aims to identify underlying patterns and principles for effectively improving T2DM risk parameters through IF. By analyzing data from multiple randomized clinical trials investigating various IF interventions in humans, a machine learning algorithm was employed to develop a personalized recommendation system. This system offers guidance tailored to pre-diabetic and diabetic individuals, suggesting the most suitable IF interventions to improve T2DM risk parameters. With a success rate of 95%, this recommendation system provides highly individualized advice, optimizing the benefits of IF for diverse population subgroups. The outcomes of this study lead us to conclude that weight is a crucial feature for females, while age plays a determining role for males in reducing glucose levels in blood. By revealing patterns in diabetes risk parameters among individuals, this study not only offers practical guidance but also sheds light on the underlying mechanisms of T2DM, contributing to a deeper understanding of this complex metabolic disorder.

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Section: Discussionmentioning

confidence: 99%

Understanding Type 2 Diabetes Mellitus Risk Parameters through Intermittent Fasting: A Machine Learning Approach

Shazman

2023

Nutrients

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“…However, it is important to recognize that rabbits may not accurately replicate all pathophysiological processes observed in humans for all diseases. For instance, in humans, type 1 diabetes mellitus (T1DM), a complex autoimmune disease characterized by the destruction of insulin-producing beta cells in the pancreas, typically involves the production of autoantibodies targeting specific pancreatic antigens, which is not consistently observed in rabbit models ( Bora et al, 2023 ; Jing et al, 2018 ). Moreover, when investigating autoimmune diseases such as systemic lupus erythematosus (SLE), characterized by a complex interplay of genetic and environmental factors, rabbits exhibit a limited genetic predisposition to autoimmune responses compared to certain mouse strains that better model this disease ( Ganor et al, 2014 ; Yang et al, 2009 ).…”

Section: Future Perspectives On Genome-edited Rabbit Modelsmentioning

confidence: 99%

Genome-edited rabbits: Unleashing the potential of a promising experimental animal model across diverse diseases

Han,

Zhou,

Zhang

et al. 2024

Zoological Research

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Animal models are extensively used in all aspects of biomedical research, with substantial contributions to our understanding of diseases, the development of pharmaceuticals, and the exploration of gene functions. The field of genome modification in rabbits has progressed slowly. However, recent advancements, particularly in CRISPR/Cas9-related technologies, have catalyzed the successful development of various genome-edited rabbit models to mimic diverse diseases, including cardiovascular disorders, immunodeficiencies, aging-related ailments, neurological diseases, and ophthalmic pathologies. These models hold great promise in advancing biomedical research due to their closer physiological and biochemical resemblance to humans compared to mice. This review aims to summarize the novel gene-editing approaches currently available for rabbits and present the applications and prospects of such models in biomedicine, underscoring their impact and future potential in translational medicine.

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Isolation, Characterization, Chemical Profiling and Evaluation of Antidiabetic and Antioxidant Potential of Innula cappa (Buch.-Ham. ex D. Don) DC Leaves in Alloxan-Induced Type 2 Diabetic Mice

Rahman,

Jan,

Jan

2024

Natural Product Communications

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Background Innula cappa (Buch.-Ham. ex D. Don) DC (Compositae) is used in folkloric medicine to treat diabetes and other ailments. The current study aimed to assess the anti-hyperglycemic and antioxidant effects of methanolic extract and solvent fractions of I. cappa leaves as well as bioassay guided isolation of active compounds from the active extract. Method The α-amylase and α-glucosidase inhibition of the extracts was evaluated by colorimetric assays, and the anti-diabetic activity was tested on alloxan-induced diabetic mice model. Moreover, flame emission and atomic absorption spectrometry techniques were employed to analyze the chemical composition of the plant. Compounds were identified and isolated from the leaf latex of I. cappa using FTIR, GCMS, silica gel column chromatography, and their structures were determined using 1H-NMR, 13C-NMR, and ESI-MS spectral data. Results The results showed that the ME showed significant α-amylase, α-glucosidase inhibitory hyperglycemic activities, significantly improving body weight, glucose tolerance, lipid profiles, and hematological markers. The UV-FTIR spectra revealed diagnostic peaks corresponding to several functional groups whereas GC-MS spectral analysis revealed 35 phytochemical components with different retention times in the ME of I. cappa. Spectroscopic isolation of the ME led to the isolation 5 compounds including ursolic acid, benzoic acid, 2-hydroxybenzoic acid, stigmasterol and β -sitosterol. Conclusion ME exert significant antihyperglycemic and antioxidant effects demonstrating the medicinal value of I. cappa and emphasize its significance as unexplored natural reservoirs of phytogenic chemicals that require further investigation using cutting-edge analytical techniques.

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A critical review on therapeutic approaches of CRISPR-Cas9 in diabetes mellitus

Cited by 4 publications

References 151 publications

Understanding Type 2 Diabetes Mellitus Risk Parameters through Intermittent Fasting: A Machine Learning Approach

Understanding Type 2 Diabetes Mellitus Risk Parameters through Intermittent Fasting: A Machine Learning Approach

Genome-edited rabbits: Unleashing the potential of a promising experimental animal model across diverse diseases

Isolation, Characterization, Chemical Profiling and Evaluation of Antidiabetic and Antioxidant Potential of Innula cappa (Buch.-Ham. ex D. Don) DC Leaves in Alloxan-Induced Type 2 Diabetic Mice

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