Investigation Into the Antidiabetic Effects of a Developed Polyherbal Nanosuspension and Its Assessment

This study focuses on the development and evaluation of a nanosuspension containing ethanolic extracts of Tinospora cordifolia and Syzygium cumini for managing Diabetes mellitus. The main objective is to create an effective polyherbal nanosuspension by combining Tinospora cordifolia and Syzygium cumini with an optimal concentration of chitosan polymer to address Diabetes mellitus. Furthermore, both in vitro and in vivo assessments of the synthesized nanosuspensions were conducted to determine the best formulation. Methods and Findings: The ethanolic extracts of the mentioned plants were obtained using a maceration technique, followed by preliminary phytochemical screening, HPTLC analysis, and FTIR-based incompatibility assessments. The nanosuspension was prepared using the ionic gelation method by varying the chitosan polymer concentration. Comprehensive in vitro assessments were carried out, including measurements of pH, viscosity, drug content, entrapment efficiency, loading capacity, and in vitro release profiles for different formulations. The formulation with the highest drug content and optimal release characteristics was selected for further analysis of particle size, zeta potential, and surface morphology. Subsequently, the antidiabetic efficacy of the polyherbal nanosuspension was evaluated using wistar albino rats. Discussion: FTIR analysis indicated no significant interaction between the drug and the polymer. The in vitro drug release and kinetic analyses suggested that the F5 formulation exhibited superior drug release and an improved release mechanism. The particle size was determined to be approximately 420nm, and SEM imaging revealed particles that were nearly spherical in shape. Stability assessments of formulation F5 demonstrated consistent physical and chemical parameters over time

Status of marine fisheries of Kerala

Kerala with a coastline of 590 km is a significant contributor to the total marine fish landings of the country. A picture of the marine fisheries sector in Kerala during the years 2005 and 2010 is presented below (Table 1). With a continental shelf of about 40,000 km2 marine fisheries plays a vital role in the livelihood of the people

Deep Learning-Based BoVW–CRNN Model for Lung Tumor Detection in Nano-Segmented CT Images

One of the most common oncologies analyzed among people worldwide is lung malignancy. Early detection of lung malignancy helps find a suitable treatment for saving human lives. Due to its high resolution, greater transparency, and low noise and distortions, Computed Tomography (CT) images are most commonly used for processing. In this context, this research work mainly focused on the multifaceted nature of lung cancer diagnosis, a quintessential, fascinating, and risky subject of oncology. The input used here has been nano-image, enhanced with a Gabor filter and modified color-based histogram equalization. Then, the image of lung cancer was segmented by using the Guaranteed Convergence Particle Swarm Optimization (GCPSO) algorithm. A graphical user interface nano-measuring tool was designed to classify the tumor region. The Bag of Visual Words (BoVW) and a Convolutional Recurrent Neural Network (CRNN) were employed for image classification and feature extraction processes. In terms of findings, we achieved the average precision of 96.5%, accuracy of 99.35%, sensitivity of 97%, specificity of 99% and F1 score of 95.5%. With the proposed solution, the overall time required for the segmentation of images was much smaller than the existing solutions. It is also remarkable that biocompatible-based nanotechnology was developed to distinguish the malignancy region on a nanometer scale and has to be evaluated automatically. That novel method succeeds in producing a proficient, robust, and precise segmentation of lesions in nano-CT images

Dermal fibroma in a tawny nurse shark, Nebrius ferrugineus (Lesson, 1831)

Sharks are ecologically and economically significant group of fishes which invite both domestic as well as international demand. The tawny nurse shark, Nebrius ferrugineus, is a commonly occurring species in the landings in India forming about 1.4% of the shark catches in the region. Besides, N. ferrugineus is one among the shark species which are listed as ‘vulnerable’ by the International Union for Conservation of Nature (IUCN) in their Global Red List assessment (Pillans, 2003). Tumours in both captive and feral fishes are not uncommon and most of the tumours that occur in terrestrial animals have been reported in fishes. Presently, there is a growing interest to study fish neoplasms as a means of detecting injurious agents in the environment. Furthermore, the usefulness of fish as a model for studying human diseases including neoplasms has also prompted researchers to pay much interest in unravelling tumorigenesis in fish (Schmale, Nairn, & Winn, 2007). While there are no systematic studies on fish neoplasms from India, some of the reported tumours include odontoma in pickhandle barracuda, Sphyraena jello (Singaravel et al., 2017), cutaneous myxoma in blackfin sea catfish (Singaravel, Gopalakrishnan, Vijayakumar, & Raja, 2015), and lipoma in a gold fish (Sood et al., 2017). Fibromas are benign neoplasms of mesenchymal origin composed of fibrous connective tissue. Different types of mesenchymal tumours have been reported in many fish species which include but not limited to fibrosarcoma in Goldfish (Ahmed, 1980) and red band parrot fish (Rezaie, Dezfuly, & Peyghan, 2017)

Detecting Plant Disease in Corn Leaf Using EfficientNet Architecture—An Analytical Approach

The various corn diseases that affect agriculture go unnoticed by farmers. Each day, more crops fail due to diseases as there is no effective treatment or a way to identify the illness. Common rust, blight, and the northern leaf grey spot are the most prevalent corn diseases. The presence of a disease cannot be accurately detected by simply looking at the plant. This will lead to improper pesticide use, which harms people by bringing on chronic diseases. Therefore, maintaining food security depends on accurate and automatic disease detection. It might be possible to save time and stop crop degradation before it takes place by utilising digital technologies. Hence, applying modern digital technologies to identify the disease in the damaged corn fields automatically will be more advantageous to the farmers. Many academics have recently become interested in deep learning, which has aided in creating an exact and autonomous picture classification scheme. The use of deep learning techniques and their adjustments for detecting corn illnesses can greatly assist contemporary agriculture. To find plant leaf diseases, we employ image acquisition, preprocessing, and classification processes. Preprocessing includes procedures such as reading images, resizing images, and data augmentation. The suggested project is based on EfficientNet and improves the precision of the database of corn leaf diseases by tweaking the variables. Tests are run using DenseNet and Resnet on the test dataset to confirm the precision and robustness of this approach. The recognition accuracy of 98.85% that can be achieved using this method, according to experimental results, is significantly higher than those of other cutting-edge techniques

VALIDATION AND APPLICATION OF RP- HPLC METHOD FOR QUANTIFICATION OF ENROFLOXACIN IN PURE AND VETERINARY DOSAGE FORMS

Objective: The main objective of this study is to develop and validate a simple, new, fast, sensitive, precise and accurate RP-HPLC analytical methods have been established for the estimation of enrofloxacin in bulk and pharmaceutical dosage forms. Methods: The present method was developed and validated on a Waters HPLC system using Phenomenex make Shimadzu C18 column (250mm × 4.6mm i.d., 5μm particle size) column was used for the separation. Best results were obtained with the mobile phase composition consisting of Acetonitrile-water (80:20, v/v). The system was regulated at 1.0 ml/min flow rate at 270 nm UV detection. Results: Enrofloxacin was eluted at 3.405 min retention time. The analytical parameters such as accuracy, precision, linearity, LOD, LOQ, ruggedness, and robustness were used for validating the developed method according to ICH guidelines. Linearity was exhibited over the concentration range of 0.1-0.6µg/ml and the Limit of Detection and Quantitation values for Enrofloxacin was 0.001µg/ml and 0.03µg/ml respectively. The result of analysis shows that the amount of drugs present in the formulation has a very good correlation with the label claim of the formulation and %RSD will be less than 2 for all the validation parameters. Recoveries studies revealed that results within the specified limits. Conclusion: The developed methods were validated for various parameters as per ICH guidelines. Hence the proposed method was found to be satisfactory and could be used for the routine analysis of enrofloxacin in their marketed formulation

Magnetic shielding using high-temperature superconductors

Magnetic shields of various high-temperature superconductors, YBa2Cu3O7-x (YBCO), YBa2Cu3O7-x -Ag composites (random inclusions as well as non-random coatings) and Bi2Sr2Ca2Cu3OX(BSCCO) were prepared by uniaxial as well as isostatic compression with various dimensions. The shielding properties were measured at 77 K for dc and ac magnetic fields in the range of frequencies from 100 Hz to 10 kHz. The critical penetration field (CPF), defined as the value of the applied magnetic field at which a detectable field was observed inside the cylinder, varied from cylinder to cylinder and also with the ageing of the cylinders in the case of YBCO shields. The highest value of CPF was 16 G at 77 K for YBCO shield prepared by isostatic compression. Even though the stability of BSCCO shields with respect to ageing is good, the CPF values are very low compared to those for YBCO. Detailed studies were performed in the case of YBCO shields. The CPF decreased as a function of time over a period of 90 days. The CPF decreased as the frequency of the applied field was increased. The wave form of the field inside the pot for a sinusoidal applied field was highly distorted and showed the presence of higher harmonics with appreciable amplitude. The wave form was Fourier-analysed to yield the field inside the shield along with the harmonics. The shields with Ag addition seem to give better performance at high fields