ABSTRACT
Cancer-related deadly diseases affect both developed and underdeveloped nations worldwide. Effective network learning is crucial to more reliably identify and categorize breast carcinoma in vast and unbalanced image datasets. The absence of early cancer symptoms makes the early identification process challenging. Therefore, from the perspectives of diagnosis, prevention, and therapy, cancer continues to be among the healthcare concerns that numerous researchers work to advance. It is highly essential to design an innovative breast cancer detection model by considering the complications presented in the classical techniques. Initially, breast cancer images are gathered from online sources and it is further subjected to the segmentation region. Here, it is segmented using Adaptive Trans-Dense-Unet (A-TDUNet), and their parameters are tuned using the developed Modified Sheep Flock Optimization Algorithm (MSFOA). The segmented images are further subjected to the breast cancer detection stage and effective breast cancer detection is performed by Multiscale Dilated Densenet with Attention Mechanism (MDD-AM). Throughout the result validation, the Net Present Value (NPV) and accuracy rate of the designed approach are 96.719% and 93.494%. Hence, the implemented breast cancer detection model secured a better efficacy rate than the baseline detection methods in diverse experimental conditions.
ABSTRACT
OBJECTIVE: The aim of the study is to design N5-(1H-pyrazol-3-yl)-3H-benzo[d]imidazole-2,5-diamine derivatives and evaluate its anti-obesity activity. MATERIALS AND METHODS: A few pyrazole-fused benzimidazole derivatives were designed as potential Pancreatic Lipase (PL) inhibitors. The designed N5-(1H-pyrazol-3-yl)-3H-benzo[d]imidazole-2,5-diamine derivatives have been screened using the Lipinski rule of five, ADMET analysis, acute toxicity prediction, and molecular docking. Later on, the derivatives which possess the most drug-likeness properties and displayed the most potent inhibition of the enzyme in molecular docking were synthesized. Then, in vitro enzyme assay was performed. RESULTS: Orlistat used as the standard exhibited 91±1.68% inhibition of the enzyme, displayed binding affinity (BA) of only -4.5 kcal/mol with Pancreatic Lipase (PL), and made only one salt bridge attractive charge and carbon-hydrogen bond with ASP79 and TRP252, respectively. Compound 9 displayed the most potent activity (93±1.12% inhibition of P.L. and -9.5 kcal/mol BA). It has formed five conventional H- bonds with GLU253, ILE78, ASP79, PHE258, and one Pi-donor H- bond with ILE78. From the present investigation, we hereby reported (E)-N2-((naphthalene-1-yl)methylene)-N5-(1H-pyrazol-3-yl)-3H-benzo[d]imidazole-2,5-diamine as most potent PL inhibitor for the treatment of obesity, which can be further optimized by undergoing more studies using in vivo and in vitro models. CONCLUSIONS: (E)-N2-((naphthalene-1-yl)methylene)-N5-(1H-pyrazol-3-yl)-3H-benzo[d]imidazole-2,5-diamine as most potent PL inhibitor for the treatment of obesity which can be further optimized better using more in vivo and in vitro models. PL plays a critical role in digesting dietary fat. Therefore, PL inhibitors are verified as a potential therapy for treating obesity.
Subject(s)
Diamines , Lipase , Molecular Docking Simulation , Orlistat/pharmacology , Pyrazoles/pharmacology , Imidazoles , Benzimidazoles/pharmacology , Naphthalenes , Dietary Fats , Carbon , Structure-Activity RelationshipABSTRACT
The present paper deals with the athnomedicobotany of crude drugs used by a seminomadic ethnic group, the Yanadis, found in Cuddapah district of Andhra Pradesh. This aboriginal group is considered to be the conservators of folklore medicine. Fourteen plant species available in the locality, used by this tribe to cure ailments like epilepsy, hysteria fits and insanity were collected. The valid scientific and vernacular names, plant parts used, therapeutic combinations, mode of administration were enumerated.