Publication Search

This study explored the analgesic effectiveness of ethanol extract of red betel leaf (Piper crocatum) in white rats (Mus musculus L.) induced with acetic acid. A total of 15 rats were divided into five groups with different treatments, and the number of twitching movements as a pain response was measured for one hour. The extract was prepared using 96% ethanol solvent, and the analgesic effect was analyzed using the writhing test method. The results showed that the extract contained flavonoids, alkaloids, tannins, and saponins, which might contribute to its analgesic properties. It was found that the higher the dose of extract administered, the greater the inhibition of pain that occurred, with a dose of 800 mg/kgBB showing optimal analgesic effectiveness, almost equivalent to paracetamol as a positive control. Statistical analysis showed significant differences between treatment groups, with doses of 200 mg/kgBB and 400 mg/kgBB showing lower effectiveness. This study recommends further exploration of the therapeutic benefits of red betel leaf extract and formulation development for wider medical applications.  

Pain is the body's response to tissue damage that is often addressed using analgesic compounds. Purslane plants (Portulaca oleracea L) are known to contain flavonoids, saponins, tannins, and alkaloids that have potential as analgesics. This study aims to test the analgesic effectiveness of purslane ethanol extract by writhing test method using white mice (Mus musculus) induced by 1% acetic acid. A total of 15 mice were divided into 5 treatment groups, namely negative control, positive control (paracetamol), and three groups with doses of purslane extract 200 mg/kgBB, 400 mg/kgBB, and 800 mg/kgBB. The number of writhes was observed every 15 minutes for 1 hour, and the percentage of protective power was calculated. The results showed that the dose of 800 mg/kgBB gave the highest analgesic effect with a percent protection power of 65.28%, followed by doses of 400 mg/kgBB (52.4%) and 200 mg/kgBB (30.6%). The highest analgesic effect was achieved at a dose of 800 mg/kgBB, almost equivalent to the positive control. This shows the significant potential of purslane ethanol extract as an analgesic agent.

Study This contains about the detection of circular object images. The circular object tested is the moon image object, the moon image was chosen because the moon image has various moon shapes, namely the full moon, half moon and crescent moon. To detect the shape of the circular object image, several stages are carried out by starting the image segmentation process. (1) The segmentation process using the bi-level thresholding method makes the image black and white, (2) after that the image is repaired with the morphological process of the opening and closing methods. (3) For training data, the shape extraction process is carried out, namely the circular nature of the object (circularity) to determine the roundness of an object. For the testing process, the same process is also carried out as the process of obtaining circular image detection.

Due to the variety of types of flowers that exist and having and tracking each variety, making plant lovers and cultivators difficult to distinguish in determining the type of flower, it takes a very long time to find out the type of flower if you only rely on the five senses. With the application of the K-Nearest Neighbor algorithm and feature extraction of color and texture, it is very helpful in image processing to identify flowers more easily and shorten the time, with the greatest accuracy of 71% using the K-7 value, the flower was successfully carried out.

Tooth extraction often triggers anxiety in patients due to the use of invasive medical instruments. Anxiety management can be addressed pharmacologically or non-pharmacologically. Aromatherapy using red ginger essential oil (Gingiber Officinale var. Rubrum) is a non-pharmacological method that has the potential to reduce anxiety effectively. This study aims to determine the effectiveness of red ginger essential oil in reducing the anxiety levels of patients undergoing tooth extraction. This quasi-experimental study employed a pretest-posttest design on 96 tooth extraction patients at RSKDGM Makassar. Anxiety levels were measured using the Modified Dental Anxiety Scale (MDAS) questionnaire before and after inhaling red ginger essential oil aromatherapy for 10 minutes. Data were analyzed using the Wilcoxon test with SPSS 26. The results showed a significant decrease in patients' anxiety levels after inhalation of red ginger essential oil aromatherapy. Before the intervention, the majority of patients had moderate anxiety (58.3%), while after the intervention, mild anxiety increased to 59.4% (p-value = 0.000). Red ginger essential oil (Gingiber Officinale var. Rubrum) is effective in reducing patients' anxiety during tooth extraction procedures.

The present study was aimed at gaining knowledge about the type of pathogen responsible for Vulvovaginal Candidiasis (VVC) infections and evaluating the antimicrobial activity of plant extracts against Candida spp. antibiotic resistance. 112 samples were taken from infected women with VVC of different ages from September to December 2024. All specimens were collected from Al Hussein Teaching Hospital/ Al- Thiqar- governorate. The results showed that 67 (59.82%) of all cases had positive results for Candida spp., while 45 (40.18%) had negative results. Candida spp. Isolated from VVC were C. albicans, the most prevalent 33 (49.26%), C. glabrata, 12 (17.91%), C. krusi and C. kefyr, 9 (13.43%), and C. guilliermondii, 4 (6.90%). The antifungal sensitivity of the pathogenic Candida spp. was tested against five types of antifungals, and the results showed the highest resistance to ketoconazole was 66 (98.51%) of Candida spp. Because of the presence of these physiologically active chemicals, Zizyphus spina-christi L. exhibits antimicrobial capabilities. In this study, the main aim is to study the antifungal activity of Ziziphus spina-christi leaf extract on some resistant candida and conduct analysis to confirm that the Ziziphus spina-christi leaves have phytochemical contents. Gas chromatography-mass spectrometry (GC-MS) was used to find the bioactive components present in extracts of Z. spina-christi leaves. Finally, we decided the inhibitory activity of Ziziphus spina-christi leaves extract. The extract of Ziziphus spina-christi had alkaloids, saponins, flavonoids, phenols, tannic acid, and terpenoids, according to a preliminary phytochemical screen. In addition, GC-MS analysis of the extract confirmed the presence of many beneficial chemicals. The extract showed promising antimicrobial activity for Candida spp. (C. albicans, C. glabrata,C. krusi , C. kefyr, and C. guilliermondii)  . These results show that the Ziziphus spina-christi leaves extract is a valuable resource for bioactive chemicals with potential uses in a variety of biological contexts.

Liver damage induced by hepatotoxic compounds such as N-acetyl-p-aminophenol (N-APAP) remains a significant global health concern. Hepatotoxicity caused by N-APAP, particularly in cases of overdose or prolonged use, can lead to a reduction in glutathione levels in the liver, resulting in oxidative stress and cellular damage. This condition contributes to an increased incidence of liver diseases, including toxic hepatitis and acute liver failure, which can lead to serious complications and even death. Although various pharmacological therapies, such as N-acetylcysteine (NAC), are available to address N-APAP-induced liver damage, limitations such as side effects, high costs, and variable efficacy have driven the search for safer and more affordable therapeutic alternatives. Therefore, research on natural hepatoprotective agents, such as extracts from the rhizomes of fingerroot (Boesenbergia rotunda), has become increasingly relevant in addressing this issue. The aim of this study was to evaluate the hepatoprotective potential of ethanol extract from fingerroot rhizomes (Boesenbergia rotunda) in protecting the liver from N-acetyl-p-aminophenol (N-APAP)-induced damage. Specifically, this research focuses on measuring glutathione levels as a key indicator of the liver's protective mechanism against oxidative stress. In this study, 30 male White rats were randomly divided into six groups, each consisting of five rats. All rats were orally administered the extract at predetermined doses for 10 consecutive days, except for the negative and positive control groups. On the 10th day, all groups (except group 1) were treated with paracetamol (800 mg/kg body weight) to induce liver damage. Twenty-four hours after induction, the rats were sacrificed and liver samples were collected. Glutathione levels were measured using the ELISA immunosorbent assay. Statistical analysis showed that administering the ethanol extract of Fingerroot rhizomes (EERTK) for 10 days prior to N-APAP induction significantly increased the average antioxidant enzyme GSH-Px levels in the liver homogenate of rats in the EERTK 250 mg/kg BW (43.36 ± 1.34 U/mg protein), EERTK 500 mg/kg BW (55.70 ± 2.15 U/mg protein), and 750 mg/kg BW (53.14 ± 2.57 U/mg protein) group compared to the negative control group (N-APAP 800 mg/kg BW), which had the lowest average antioxidant enzyme GSH-Px level (33.86 ± 3.52 U/mg protein).

Acne is a common skin condition caused by excessive oil production that clogs pores and leads to inflammation. Acne-prone skin care can be done using facial masks, one of which is the practical and effective peel-off mask. This study aims to analyze the effect of using a peel-off mask containing corn and jasmine flower extract on acne-prone skin care. The research method used is a quasi-experimental design with a nonequivalent control group design. The sample consisted of six female students from Universitas Negeri Padang aged 17-25 years with acne-prone skin, divided into control and experimental groups. The research variables include the number, shape, color, and volume of acne. Data analysis techniques include normality, homogeneity, and hypothesis testing. The results show that the experimental group using the peel-off mask with corn and jasmine flower extract experienced a significant reduction in acne count, improvement in acne shape, and a decrease in redness and acne volume. In contrast, the control group showed no significant changes. Hypothesis testing indicated significance values for color (0.006), shape (0.000), volume (0.000), and number (0.000) <0.05, proving the effectiveness of the mask in treating acne-prone skin. In conclusion, the peel-off mask containing corn and jasmine flower extract is effective in reducing acne and improving facial skin condition.

This search intended to speculate the role of lavender ethanolic extract by reducing the toxicity of manganese in male rats. 32 white male Norwegian rats were divided into 4 equal groups. Group 1: as a control group left without treatments (only 1 ml of distilled water/ animal/ day). Group 2: were dosed manganese chloride at a concentration of 100 mg/ kg b.w. / day. Animals in Group 3 and Group 4 were dosed Manganese chloride at a concentration of 100 mg/kg b.w. then lavender ethanolic extract at a concentration of 200 and 400 mg/kg respectively, all by oral gavages and treated daily for six weeks. Then the next criteria were investigated: Neurotransmitters (dopamine and Ach (acetylcholine) in the mid brain) serotonin in serum. Oxidation indicators (glutathione and malondialdehyde in the brain and superoxide dismutase and catalase in serum). The results exhibited in both groups 3 and 4 there were a significant decrease in the concentrations of Ach accompanied by a significant increase in levels of dopamine and serotonin, also return levels of MDA (Malondialdehyde) to normal, as well as a significant increase in GSH (Glutathione) concentrations in rats mid brain. Moreover, the significant rising of SOD (Superoxide dismutase) and CAT (Catalase) levels in serum of rats in these groups indicated a noticeable improvement was achieved by lavender ethanolic extraction as compared to group 2. Conclusion, the antioxidant and antitoxic activity of lavender ethanolic extract promises in grate achievement in various health fields, including medicine, food industries and cosmetics.

Advances in information and internet technologies have significantly transformed the business environment, including the financial sector. The COVID-19 pandemic has further accelerated this digital adoption, expanding the e-commerce industry and highlighting the necessity for secure online transactions. Credit Card Fraud Detection (CCFD) stands critical as the prevalence of fraudulent activities continues to rise with the increasing volume of online transactions. Traditional methods for detecting fraud, such as rule-based systems and basic machine learning models, tend to fail to keep pace with fraudsters' evolving tactics. This study proposes a novel ensemble deep learning-based approach that combines Convolutional Neural Networks (CNN), Gated Recurrent Units (GRU), and Multilayer Perceptron (MLP) with the Synthetic Minority Oversampling Technique and Edited Nearest Neighbors (SMOTE-ENN) to address class imbalance and improve detection accuracy. The methodology integrates CNN for feature extraction, GRU for sequential transaction analysis, and Multilayer Perceptron (MLP) as a meta-learner in a stacking framework. By leveraging SMOTE-ENN, the proposed approach enhances data balance and prevents overfitting. With synthetic data, the robustness and accuracy of the model have been improved, particularly in scenarios where fraudulent examples are scarce. The experiments conducted on real-world credit card transaction datasets have established that our approach outperforms existing methods, achieving higher metrics performance.

spam is posting unsolicited messages or advertising on social media, particularly Twitter. These messages are normally designed to sell specific products and services or links. In this research, we developed a fuzzy control system to detect Arabic spam tweets based on deep learning with a large language model. Initially, we performed text cleaning and further transformed text into vectors with the help of AraGpt and AraBert. Subsequently, we employed a multi-layer perceptron network model in feature extraction of essential features. Finally, we adopted the fuzzy logic control system for classifying spam tweets using features filtered from deep networks. Employing the proposed Fuzzy logic control system provided nearly a 100% comparative to only utilizing the deep neural networks, which yielded an almost 99% throughput for both large language models Aragpt and Arabert, with a 100% F1 score for the Aragpt model and 99% for Arabert model respectively.

This study aims to optimize the implementation of the K-Nearest Neighbors (K-NN) algorithm for medical image classification by focusing on selecting the optimal KKK parameter and applying dimensionality reduction techniques to improve accuracy and efficiency. The data used was sourced from public medical image repositories such as The Cancer Imaging Archive (TCIA) and Medical Image Analysis datasets, covering various diseases, including brain tumors, lung cancer, and kidney lesions. The research process involves data collection, data preprocessing, dimensionality reduction using Principal Component Analysis (PCA), applying the K-NN algorithm with Euclidean, Minkowski, and Cosine distance metrics, and performance evaluation using accuracy, precision, recall, and F1-score. Experimental results demonstrate that K=5with the Euclidean distance metric provides the best performance, achieving an accuracy of 90%. Additionally, PCA effectively reduces computational time by 30% without significantly compromising accuracy. This study proves that K-NN is an effective method for medical image classification. However, further research is needed to integrate K-NN with deep learning models to enhance performance and feature extraction capabilities.

Origanum majorana demonstrates a broad spectrum of effectiveness against various diseases, exerting antimicrobial effects against different pathogenic microorganisms. The goals of this research are to provide light on how Origanum majorana extract inhibits human pathogenic bacteria, how it may prevent biofilm development, and how it affects bacterial adhesion. The antibacterial activity of the water-based Origanum majorana extract was assessed in this research using two different methodologies. "Antibiotics were compared to its effectiveness using an agar-well diffusion assay and disc diffusion method," the first step. Additionally, the extract's ability to inhibit biofilm formation and bacterial adherence was assessed through specialized tests. All bacterial isolates of Gram negative, Gram-positive bacterial types were sensitive to Origanum majorana extract and the range of inhibition zone (30 to 24) mm. Although floxacin was effective against some of these isolates, the majority of them were resistant. Most bacterial Gram negative types were exhibit moderate adherence and biofilm activity to this extracts and some bacterial isolated of bacteria were exhibit high adherence and biofilm activity to the watery extracts of Origanum majorana. This research confirms previous findings that Origanum majorana extracts are very effective against a wide variety of clinical isolates of bacteria, including Gram-negative as well as Gram-positive varieties. Notably, the extracts were found to be more effective than commercially available antibiotics. Furthermore, the extracts displayed significant inhibition of bacterial adherence and biofilm formation. Based on these findings, Origanum majorana extracts have great promise as an effective antibacterial and anti-biofilm agent.

Milkwood bark (Alstonia scholaris (L.) R. Br.) is one of the medicinal plants of the genus Alstonia. This plant is traditionally used by the community as a medicine for diarrhea, diabetes, malaria, hemorrhoids, and antihypertensives. This plant contains secondary metabolites that have the potential as antibacterial such as alkaloids, flavonoids, saponins and tannins. The purpose of this study was to determine the inhibition of antibacterial activity and the most effective concentration in inhibiting Staphylococcus aureus and Escherichia coli. The sample used in this study was milkwood bark, the sample was extracted by maceration method using 96% ethanol as solvent. The antibacterial testing method used in this study was disc diffusion. The study used a completely randomized design with 9 treatments, namely 1000 ppm, 750 ppm, 500 ppm, 250 ppm, 100 ppm, 50 ppm, 10 ppm, Ciprofloxacin (positive control), sterile distilled water (negative control). The results of the antibacterial activity test at a concentration of 500 ppm showed that milkwood bark extract could inhibit the growth of S. aureus by 8.22 mm and at a concentration of 250 ppm showed that milkwood bark extract could inhibit the growth of E. coli by 8.75 mm. From the test results, it can be concluded that milkwood bark (A. scholaris (L.) R. Br.) has antibacterial activity that has moderate potential in inhibiting S. aureus and E. coli.

Leishmaniasis is recognized as a significant health concern in Iraq. The disease begins with minor elevations (papules) and progresses into ulcers. Epidemiological investigations play a crucial role in managing and implementing effective preventive strategies for this disease. This study examines the epidemiology of cutaneous leishmaniasis in Iraq over the past 7 years. This descriptive-analytical cross-sectional inquiry analyzed data concerning patients with cutaneous leishmaniasis over the previous 7 years at the Iraq Health Center. Demographic and epidemiological data of the patients were collected from healthcare centers in Iraq through collaborative efforts with healthcare facilities. Using SPSS software, epidemiological records of the patients were extracted and subjected to statistical analysis employing the chi-square test. Out of 175 patients examined, 88 were male (53%), and 87 were female (47%). The majority of patients belonged to the age bracket of 9 months to 4 years, with the lowest number of cases in the age group of 40 to 49 years. Mainly, the manifestations of the disease were observed on the facial region and limbs. Furthermore, a statistically significant correlation was observed between age groups and the type of leishmaniasis (P > 0.05), as well as between gender and the type of leishmaniasis (P > 0.05). According to the conducted analysis, the prevalence of the disease in Iraq showed a declining trend from 2008 to 2014. This reduction in the disease incidence can be attributed to the improvement in health education status and the adherence to personal hygiene practices among the population

The cultivation of pisang kepok (Musa paradisiaca, L.) faces major challenges due to pest and disease attacks that can reduce productivity and threaten the sustainability of agricultural ecosystems. This study aims to identify and evaluate environmentally friendly pest and disease control strategies in banana cultivation. The research method used was a literature review of various recent studies (2019-2025) on biological and technical culture approaches in pest and disease control. The results showed that the use of natural enemies such as Beauveria bassiana and Trichoderma spp., crop rotation, application of vegetable pesticides based on neem and soursop extracts, and planting refugia plants can effectively suppress pest populations without damaging the balance of the ecosystem. In addition, sustainable agriculture policies supported by the government play an important role in encouraging the adoption of these methods at the farm level. This approach not only increases kepok banana production but also maintains environmental sustainability and public health.

Tooth extraction is a minor surgical procedure involving hard and soft tissues in the oral cavity. The level of anxiety towards dental treatment procedures ranks fifth among several other common symptoms that can cause anxiety. Treatment to reduce the level of patient anxiety can be done with pharmacological and non-pharmacological approaches. Jasmine flower essential oil (Jasminun grandiflorum) is one of the non-pharmacological methods used to reduce the level of anxiety in tooth extraction patients. To determine the effectiveness of using jasmine flower essential oil (Jasminum grandiflorum) on the level of anxiety in tooth extraction patients. This study was conducted at the Regional Special Hospital for Teeth and Mouth (RSKDGM) in Makassar. This study is a quasi-experimental study with a pretest-posttest approach. The measuring instrument used was the Modified Dental Anxiety Scale (MDAS) questionnaire which was given before and after giving jasmine flower essential oil for 10 minutes to reduce the level of anxiety in tooth extraction patients. Based on the results of the Wilcoxon test, it showed a significant decrease in the level of anxiety in patients after inhalation of jasmine flower essential oil aromatherapy. Before treatment, the majority of patients had moderate anxiety (47.9%), while after treatment, mild anxiety increased to 89.6% (p-value 0.000). Jasmine Flower (Jasminun Grandiflorum) essential oil is effective in reducing the level of anxiety in tooth extraction patients.

Soursop leaves contain active compounds annonaceous acetogenins which are known to have cytotoxic activity against cancer cells. This study aims to evaluate the effect of soursop leaf methanol extract (EMDS) on the viability and growth inhibition of PC3 prostate cancer cells. The research method used was an in vitro experiment with subjects in the form of PC3 cell lines divided into five groups, namely the cell control group, the treatment group with EMDS at concentrations of 6.25; 12.5; and 25 mg/mL, and the group given doxorubicin as a positive control. Cell viability was analyzed using the MTT assay method after incubation for 0 and 24 hours, and cell morphology was observed. Data analysis was carried out using the ANOVA test. The results showed that the EMDS group with concentrations of 6.25 and 12.5 µg/mL experienced a decrease in OD values, although statistically there was no significant difference. The concentration of 12.5 µg/mL had the highest inhibitory effect on cell viability with an OD value of 0.94. Observation of cell morphology indicates the presence of cytotoxic effects. Conclusion: methanol extract of soursop leaves has potential as an anticancer agent against PC3 prostate cancer cells, although the inhibitory effect is relatively small.

The healing process of a tooth socket after extraction involves various stages, including the proliferation of fibroblasts that play a role in the formation of new tissue. Natural ingredients have long been used in accelerating wound healing, but their effectiveness in increasing the number of fibroblast cells still needs to be studied further. To determine the effectiveness of natural ingredients in increasing the number of fibroblast cells in the tooth socket of Wistar rats after tooth extraction. Methods: This is a literature review that collects and analyzes scientific articles from various databases such as PubMed, Google Scholar, DOAJ, Garuda Portal, and CrossRef. The selected articles met the predetermined inclusion criteria, including studies conducted on Wistar rats and using natural ingredients as interventions. Red ginger extract at 10% concentration was found to be the most effective ingredient in increasing the number of fibroblasts and accelerating wound healing. Red ginger extract (Zingiber officinale var. rubrum) is the most effective natural ingredient in increasing the number of fibroblast cells in the tooth socket of Wistar rats after tooth extraction.

This study aims to analyze the application of Deep Neural Networks (DNN) as an artificial intelligence approach in processing weather data to support more accurate and stable climate predictions. Increasingly unpredictable and fluctuating weather patterns demand modern analytical methods capable of capturing non-linear relationships among atmospheric variables. DNN is utilized due to its ability to learn complex data structures through multilayer representations that extract deeper features from input variables. Weather data such as temperature, humidity, rainfall, air pressure, and wind speed are processed through several preprocessing stages to ensure optimal model performance. This research employs a descriptive qualitative method based on literature studies to examine the role of DNN in weather prediction systems. The findings indicate that DNN demonstrates strong generalization abilities, robustness to fluctuating data, and more stable predictive outputs compared to conventional statistical approaches. Thus, DNN is considered a promising component for the development of early warning systems and modern data-driven climate analysis, offering improved reliability in understanding and forecasting atmospheric conditions.