Journal of Current Science and Technology

In Vitro Biological Activity of Tiliacora triandra (Colebr.) Diels Root Extract

Nalinee Pradubyat — 2024-12-20

In this study, we explore the phytochemical properties of Tiliacora triandra (Colebr.) Diels, commonly known as Yanang, a herb traditionally used for treating fever and malaria. Our objective is to isolate and analyze bioactive compounds from T. triandra's root extract, with a specific focus on tiliacorinine (T1), assessing its antioxidant, and anticancer capabilities. The antioxidant activity of T. triandra extract (TTE) was evident, with IC₅₀ values of 196.32 ± 10.51 µg/mL and 88.22 ± 1.95 µg/mL in the DPPH and ABTS assays, respectively. The results also demonstrated that TTE and T1 had a significant cytotoxic effect, with IC₅₀ values varying in a concentration-dependent manner against A549 with the IC₅₀ of 48.25 μg/mL and 26.38 μg/mL, respectively. Additionally, both TTE and T1 displayed anti-inflammatory effects, with the most effective inhibition of nitric oxide production observed at a concentration of 40 μg/mL. This study underlines the potential of T. triandra, and its compound tiliacorinine in developing treatments with antioxidant, anti-inflammatory, and anticancer properties.

Interdisciplinary Research for Predictive Maintenance of MRI Machines Using Machine Learning

Swapnali N Jagtap — 2024-12-19

Predictive maintenance is crucial for ensuring the reliability and availability of medical equipment, particularly MRI machines in healthcare facilities. This study presents a comprehensive approach to predictive maintenance of MRI machines using machine learning techniques. The objective of this research is to develop and evaluate predictive models capable of identifying patterns and indicators of impending equipment failures, thereby improving the operational efficiency and reliability of MRI machines. We utilized a dataset comprising historical maintenance records, sensor readings, and environmental conditions collected from three 1.5 T Siemens MRI machines at MGM Hospital, Warangal, Telangana, India. The dataset, initially consisting of 96 records and expanded to 1000 through computer-generated data, encompasses various operational aspects, including temperature, humidity, vibration, power consumption, and coolant flow rate. This study investigated the efficacy of multiple machine learning algorithms for predicting equipment failures, including Random Forest, Gradient Boosting, Long Short-Term Memory (LSTM) networks, and Support Vector Machines (SVM). Model performance was evaluated using standard metrics such as F1-score, accuracy, recall, and precision. Results indicate that LSTM networks achieved the highest accuracy at 89%, while SVM displayed the lowest at 82%. These findings validate the potential of machine learning in anticipating equipment breakdowns and enabling proactive maintenance strategies for MRI machines. The outcomes of this research have significant implications for enhancing the reliability and operational efficiency of medical imaging equipment in healthcare settings.

Artificial Intelligence, Cybersight Detection of Diabetic Retinopathy in the Elderly in Vietnam

Ha Luong Thi Hai — 2024-12-19

Diabetic retinopathy (DR) is a highly prevalent cause of vision loss worldwide. Detection of DR requires substantial human resources and high medical costs. Therefore, the use of diagnostic software has been recently explored. The study aimed to assess the results of DR diagnoses by Cybersight, an artificial intelligence software. A total of 1,012 patients with type 2 diabetes mellitus (1,943 eyes) with a mean age of 74.61 ± 6.73 years were included. Comprehensive demographic and clinical data were gathered, and all patients underwent color fundus photography following Cybersight's standardized protocols. The study compared Cybersight's accuracy with that of ophthalmologists in identifying key DR lesions, including retinal microvascular changes, exudates, hemorrhages, the diagnosis and staging of DR, using sensitivity, specificity, and weighted Kappa metrics. The prevalence of DR was 16.2%. A high level of agreement was found between Cybersight and ophthalmologists in DR diagnosis, with a sensitivity of 85.0%, specificity of 95.8%, and a weighted Kappa of 0.78. The presence of cataracts and the degree of pupil dilation notably impacted on the accuracy of DR diagnosis. The results have important implications for the potential application of Cybersight as a low-cost and effective tool for diabetic eye screening.

Evaluation of Phytoconstituents, Nutritional Quality, and In Vitro Biological Activities of Red Rice Ethanolic Extract from Different Regions of Chiang Rai and Phayao

Wanisa Punfa — 2024-12-21

Red rice, a pigmented rice, is a staple food in Thailand that has beneficial biological properties for the consumer. The objective of this research was to assess the phytochemical composition, macro- and micro-nutritional quality, as well as the anti-glycation and in vitro antioxidant properties of three planting sites located in Chiang Rai and three planting sites located in Phayao. Raw red rice was extracted with 70% ethanol, and the phytoconstituents were evaluated using colorimetric analysis and HPLC techniques. The antioxidant activity, ROS production, lipid peroxidation, and in vitro anti-glycation properties were examined. According to the results, the greatest levels of total phenolic and total flavonoid contents were detected in CRR1 and PYR1. The amounts of fat, protein, fiber, and carbohydrates were comparable in red rice extracts. The PYR3 had the greatest quantities of iron and zinc, whereas the CRR3 had the highest levels of magnesium and potassium. The CRR1 and PYR1 had the highest amounts of vitamin E compounds and γ-oryzanol. Additionally, CRR1 and PYR1 had greater antioxidant capacities in comparison to the other red rice extracts. In the RAW264.7 macrophage cell, it was demonstrated that CRR1 and PYR1 prevented the generation of AGE at higher concentrations and had the strongest inhibitory effects on linoleic acid peroxidation and ROS production. The study's findings offered additional valuable sources of red rice from Chiang Rai and Phayao, giving consumers the option to choose red rice as beneficial for their health.

In Vitro Assessment of Antimicrobial Activity and Synergistic Effects of Ethanolic Extracts from Six Medicinal Plants

Tak Karuncharoenpanich — 2024-12-21

This in vitro experimental study examines and evaluates the antimicrobial and synergistic effects of the ethanolic extract of six plants: Biancaea sappan (L.) Tod, Bauhinia malabarica Roxb, Carthamus tinctorius L., Derris scandens (Roxb.) Benth, Hibiscus sabdariffa L., and Piper nigrum L. against common microbial species representing gram-positive, gram-negative bacteria, and fungi, consisting of Staphylococcus aureus, Escherichia coli, Staphylococcus epidermidis, Pseudomonas aeruginosa, and Candida albicans. The plants were extracted using 90% ethanol. According to the standard method of agar diffusion assay, the micro-dilution method for minimal inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were determined. This study found that among the six plants, only B. sappan and B. malabarica exhibited moderate inhibitory effects against S. aureus and S. epidermidis. B. sappan had MIC values of 250 µg/ mL and 125 µg/ mL, respectively, and B. malabarica showed MIC values of 62.50 µg/ mL and 31.25 µg/ mL, respectively. The synergistic effects of a combination of B. sappan and B. malabarica extracts at a ratio of 25:75 were analyzed, and it was found that the combination inhibited S. aureus and S. epidermidis with MIC values of 250 µg/ mL and 125 µg/ mL, respectively. The fractional inhibitory concentration index (FICI) and the fractional bactericidal concentration index (FBCI) indicated antagonistic or synergistic effects of the combination, with FICI and FBCI values of 2.5–5.0 for both B. sappan and B. malabarica extracts in the 25:75 mixture. In conclusion, single plant ethanolic extracts of B. sappan and B. malabarica possess potent antimicrobial activity to varying degrees. However, the antimicrobial potency of the 25:75 ratio mixture of these extracts was shown to decrease against the same organisms, with in vitro antimicrobial activity and antagonistic effects observed only against the tested gram-positive bacteria.