Journal Of Advanced Zoology
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Population Density Of Trigoniulus Coralline Worm At Pandharpur, Dist. Solapur (MS)
Get PDFRusty millipedes (Trigoniulus coralline worm) are widely distributed species of millipede. They inhabit compost during monsoon season. Population density of Trigoniulus coralline worm was observed and calculated in the present study. The population density is (Dp) 02.
A Comprehensive Exploration of Oedipodinae Grasshoppers in the Nara Desert Ecosystem
Get PDFThis study explores the Orthoptera community in the Nara Desert, Sindh, focusing on Oedipodinae species: Hilethera aeolopoides, Aiolopus thalassinus thalassinus, Acrotylus humbertianus, Acrotylus longipes longipes, Sphingonotus rubescens rubescens, Sphingonotus savignyi, Locusta migratoria, and Oedaleus senegalensis. We assessed their population dynamics, including diversity, density, and reproductive success, using field and laboratory methods. Our results show considerable species variation S. savignyi had the highest reproductive success (Net Reproduction Rate Ro = 9.0) and largest population (27 individuals), while A. longipes longipes had the lowest reproductive rate (0.5 births per pair) and highest mortality (0.3 deaths per pair), resulting in the smallest population (5 individuals). Density varied, with L. migratoria being the least dense, and A. longipes longipes and O. senegalensis being the densest. Dominance and evenness analyses showed S.rubescens rubescens and H. aeolopoides as more ecologically influential, while A.longipes longipes and L.migratoria had higher evenness.
These findings highlight the impact of reproductive efficiency and density on species abundance and ecological roles, offering key insights for conservation and management in the Nara Desert to preserve biodiversity and ecological balance
Seasonal Dynamics Of Butterfly Species In Jiwaji University Campus Gwalior, Madhya Pradesh
Get PDFThe present study was carried out to document and analyze the common structure, diversity and abundance of butterfly in Jiwaji University, Campus, Gwalior Madhya Pradesh, India from July, 2023 to June, 2024. Direct visual encounter method used for recorded butterfly and photographs were taken for identification of butterfly species. A total of 40 species of butterflies belonging to 5 families were recorded. Nymphalidae family consists of maximum number (13) of butterfly species followed by Pieridae (11), Lycaenidae (9), Papilionidae (4) and Heperiidae (3) respectively. Total 496 number of butterfly captured among them Eurema brigitta recorded highest number of butterfly (14) of total abundance. Present study will help to assess the habitat and effective conservation of butterfly diversity in University campus
Evaluating The Malignant Transformation Of Tobacco-Induced Oral Leukoplakia Using Tissue P53 As A Prognostic Marker
Get PDFBackground: Oral leukoplakia, a potentially precancerous lesion primarily attributed to tobacco use, poses a significant health concern worldwide. Identifying reliable prognostic markers for predicting the malignant transformation of oral leukoplakia is essential for early intervention and improved patient outcomes. This study explores the use of tissue p53 expression as a potential prognostic marker for assessing the risk of malignant transformation in individuals with tobacco-induced oral leukoplakia.
Materials and Methods: In this retrospective cohort study, tissue samples from 150 patients with tobacco-induced oral leukoplakia were collected and analyzed for p53 expression using immunohistochemistry. Clinical data, including age, gender, tobacco consumption history, and follow-up information, were also gathered. Patients were categorized into two groups based on p53 expression: high p53 and low p53. The follow-up period ranged from 2 to 5 years.
Results: Among the 150 patients, 65 (43.3%) exhibited high p53 expression in their oral leukoplakia tissue samples, while the remaining 85 (56.7%) had low p53 expression. During the follow-up period, 20 out of 65 patients (30.8%) with high p53 expression experienced malignant transformation, whereas only 8 out of 85 patients (9.4%) with low p53 expression developed malignancies. The odds ratio for malignant transformation in the high p53 group compared to the low p53 group was 4.12 (95% CI: 1.79-9.47, p < 0.001).
Conclusion: This study demonstrates that tissue p53 expression is a valuable prognostic marker for assessing the risk of malignant transformation in individuals with tobacco-induced oral leukoplakia. Patients with high p53 expression in their oral lesions are significantly more likely to experience malignant transformation compared to those with low p53 expression. These findings underscore the importance of regular monitoring and early intervention for individuals with high p53 expression to reduce the risk of oral cancer development
Detection And Growth Estimation Of Indo–Pacific Eel (Anguilla marmorata Quoy & Gaimard, 1824) Using Machine Learning In Central Vietnam
Get PDFContext. The Indo–Pacific eel (Anguilla marmorata) is a widely distributed and commercially valuable species across ecological regions worldwide. Overfishing and habitat loss are leaving the Indo–Pacific eel in a risky situation and raising a high demand for conservation. Previous research has found relationships between the Indo–Pacific eel’s migration patterns and environmental factors. However, there is still a need to advance the discovery of its spatial distribution by using diverse environmental and ecological datasets and modelling its growth in terms of different environmental characterizations.
Aims & Methods. Here, we compared machine learning (ML) CatBoost (CB) and the multivariate linear model to investigate the relationship between spatial distribution, Indo–Pacific eel development stages, and environmental factors in central Vietnam.
Key results. Our results show that CB detected the Indo–Pacific eel at high accuracy (Overall Accuracy (OA) = 0.9, F1 = 0.88, AUC = 0.97) and estimated the total length at different confidence levels (R2 ranging from 0.51 to 0.70), demonstrating superior performance to the multivariate linear model.
Conclusions & implications. This study highlights the potential use of ML models in species distribution mapping and modelling growth patterns to support conservation efforts of Indo–Pacific eels in their natural habitats
“Regulatory Challenges For The Development Of Probiotics As Foods And Drugs And Cmc (Chemistry Manufacturing And Control) Considerations For Probiotics”
Get PDFThe purpose of this study is to elucidate the importance of probiotics, regulatory challenges that are faced in developing probiotics as foods and drugs and as well as the Chemistry, Manufacturing and control (CMC)considerations for probiotics. Probiotics are friendly live microorganisms (in most cases, bacteria) that are similar to the beneficial microorganisms found in the human gut and, when consumed, have the potential to improve or maintain the intestinal microbial flora of consumers, thereby benefiting their health. The utilization of probiotics has been in existence for a very long time. Lactobacilli, bifidobacterial, and lactococciare are the examples of probiotics have long been assumed to be safe whereas the most important determinant for probiotics selection is human health safety. Probiotics can be consumed by consumers largely in the form of food and dietary supplements. They are also even available in the form of tablets, capsules and powders and in some other forms as well, yet, their claims of health advantages could put the conventional distinction between food and medicine in jeopardy. The position of the regulatory environment for probiotics within the existing categories has become hazy and quite unclear as a result of the introduction of numerous probiotic products into the global marke
Machine Learning Approach For Early Prediction Of Low Birth Weight Cases
Get PDFPredicting baby birth weight is an important component of prenatal care since it allows for early intervention and personalised healthcare for pregnant mothers and their infants. This project introduces "Birth Weight Predictor," a user-friendly web application developed using Flask and powered by machine learning that estimates birth weight depending on maternal characteristics. The application makes use of a large dataset that includes maternal health variables such as age, weight, height, medical history, habits, and more. Machine learning methods are used to analyse these maternal characteristics and predict birth weight accurately. The following are some of the application\u27s key features: Maternal Data Input: Users can enter maternal data such as age, weight, height, and other pertinent parameters to get a personalised birth weight prediction Sophisticated machine learning methods, such as voting classifier with Random forest, Boosting algorithm, and logistic regression, are used to process the maternal data, allowing the model to uncover relevant patterns and associations for accurate predictions. Flask Web Interface: The user-friendly Flask-based web interface makes birth weight projections accessible and instructive for both healthcare providers and pregnant parents. This software is a useful tool for healthcare providers, expectant parents, and researchers, as it provides early insights into prospective birth weight outcomes. It contributes to improving prenatal care, minimising problems, and maintaining the well-being of both moms and newborns by leveraging the power of machine learning and Flask
Application Of Modified Mine Waste For The Sustainable Management Of Fluoride In Drinking Water
Get PDFWaste rocks obtained from mining operations are typically stockpiled due to the lack of their economic value. This practice resulted in significant land occupation and potential for secondary pollution risks due to the lack of probability of leaching. This study investigates the potential use of waste rocks as a new type of adsorbent for groundwater that is enriched in fluoride. Ferrous chloride was added to shale, a coal mining refuse, at a 3:1 ratio to change its chemical makeup. By using batch adsorption, the adsorption process was optimised. Using energy-dispersive X-ray (EDS), X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared spectrophotometer (FTIR), the adsorbent\u27s surface morphological characterisation was carried out. The best results were obtained when polluted water was defluoridated for 60 minutes at a neutral pH using 100 mg/L. A 32% clearance efficiency was achieved at a 10 ppm fluoride contamination level. Post characterization and optimization the adsorbent was tested for Langmuir and Freundlich isotherm together with kinetics pseudo first and second order to ensure its adsorption capacit
A Study On The Pharmacological Effects Of A Flavonoid-Rich Costus Igneus And Trigonella Foenum-Graecum Foliage On A Diet-Induced Obese Zebrafish (Danio Rerio)
Get PDFThe prevalence rates of Obesity and diabetes are steadily increasing worldwide for the past several decades. Many commercial drugs are available for use in the management of diabetes. However, their side effects and high costs emphasize the need for herbal alternative drugs. The present study was designed to evaluate the effect of a flavonoid-rich extract of insulin plant (Costus igneus) and Fenugreek (Trigonella foenum-graecum) foliage extract on diet-induced zebrafish. Methods: Adult zebrafish were divided into four diet groups: (i) control fed (CF); (ii) overfed (OF); (iii) OF supplemented with insulin plant (OF+I); and (iv) OF supplemented with fenugreek foliage (OF+F). The euthanized zebrafish were analyzed for body weight, BMI, Blood glucose, and Triglyceride (TG) level at the end of the fourth week. Results: Fenugreek foliage significantly decreased BW, BMI, Blood glucose, and Triglyceride levels in OF zebrafish. Moreover, Histopathological evaluation showed excessive fat accumulation in obese zebrafish liver indicating Non-alcoholic Fatty Liver Disease (NAFLD) when compared with insulin plant. Conclusion: This study adds a new insight into the anti-obesity properties of insulin plant and fenugreek foliage and its flavonoids, as weight management agents
An overview on major diseases, damage pattern, and management of Mango (Mangifera indica L.) fruit and tree
Get PDFMango is one of the most important tropical fruits grown throughout the world particularly in Asia with high economic and nutritional value. However, several diseases and pests cause significant damages to different parts of mango trees and mango fruits, resulting in severe economic losses to farmers and the agricultural sector. Some of the major mango diseases are anthracnose, powdery mildew, die back, and mango malformation. These diseases affect various parts of mango tree, including leaves, flowers, fruits, stems, and roots. The causative organisms of mango diseases include fungi, bacteria, and viruses. Of these, the majority is caused by fungi. Some of the common fungal diseases of mango include anthracnose, powdery mildew, stem-end rot, and sooty mould. Therefore, it is a pressing need to accurately identify the causative organisms for determination of the best management strategy for an effective control. To manage mango diseases, farmers and researchers use several approaches, including cultural practices, chemical control, biological control, and genetic resistance. In this article, the major mango diseases, damage patterns, and management strategies for sustainable mango production has been critically reviewed and presented