Background: Stress occurs when the internal homeostasis is disrupted by external environmental stressors. Salivary Alpha Amylase (sAA) levels are increased in response to stress, and it is frequently used as a biomarker of stress. Aims: To determine the relationship between stress and alpha-amylase levels among presenters by the difference in levels scored in pre and post presentation. Material and Methods: A cross-sectional descriptive study was conducted to achieve the objectives of the study and was achieved to determine the association between stress and salivary alpha amylase levels for presenters during the period from 10th. Jan, 2022 to Jan, 20th. Mar, 2022. The study was conducted by selecting a typical form of non-probability (Purposive) sample. The size of the sample of 70 participants was included in the study. Results: The relationship between stress and the level of alpha amylase concentration was low in post presentation in comparison with pre presentation (0.11±0.03) and (0.13±0.02) respectively. This result was statistically highly significant according to paired t-test and the P-value was < 0.001. Furthermore, the level of Alpha amylase activity was low in post presentation in comparison with pre presentation (289658.5±76490.7) and (321693.9±52219.2) respectively. This result was statistically highly significant according to paired one group t-test and the P-value was<=0.0001. Conclusion: It was concluded Stress was elevated in the post-presentation in compare with the pre-presentation. and the levels of alpha amylase were affected by the presenters’ age groups.

Background: The coronavirus disease 2019 (COVID-19) is an emerging and rapidly evolving profound pandemic, which causes severe acute respiratory syndrome and results in significant case fatality around the world. We conducted this study to identify locally transmitted COVID-19 spatial clusters and hotspots in this phrase of the fourth wave in Vietnam. Data used and Methods: A total of 9,192 locally transmitted cases confirmed in this phrase in the fourth wave were used in study. Global and local Moran’s I and Getis-Ord’s G_i^* statistics were employed to identify spatial autocorrelation and hotspots of COVID-19 cases. Results: It was found that global Moran’s I statistic indicates a robust spatial autocorrelation of COVID-19 cases. Local Moran’s I statistic successfully identified three high-high spatial clusters of COVID-19 cases in Bac Giang (5,083 cases), Bac Ninh (1,407 cases), and Hanoi (464 cases). In addition, hotspots of COVID-19 cases were mainly detected in Bac Giang (5,083 cases), Bac Ninh (1,470 cases), Hanoi (464 cases), Hai Duong (51 cases), and Thai Nguyen (7 cases). Conclusion: The results of this work offer new perspectives on the geostatistical analysis of COVID-19 clusters and hotspots, which could help policy planners anticipate the dynamics of spatiotemporal transmission and develop critical control measures for SARS-CoV-2 in Vietnam. Future pandemics and epidemics can be avoided and controlled with the help of geospatial analysis techniques.

Background: Neem (Azadiractha indica A. Juss) as a tropical and subtropical plant has been widely used in traditional medicine since prehistoric times. Several biological activities, such as antibacterial, anti-inflammatory and antioxidant properties, have been demonstrated in Neem extract. Aim: The study aims to research was carried out on the physicochemical properties of neem leaves (Azadirachta indica A. Juss) using ethyl acetate and n-hexane as solvents. Methode: In this study, Azadiractha indica A. Juss leaves was extracted using a maceration method with two fluids namely ethyl acetate a n-hexane. The extract based on six parameters from determining physicochemical properties, namely % yield, organoleptic, determination of dissolved compound levels, phytochemical screening, determination of drying Shrinkage and determination of specific weight. Result : The results of this study showed, the yield obtained for each solvent is 6.218% ethyl acetate extract and 0.968 % n-hexane extract. Organoleptic examination (form, colour, smell and flavor) for ethyl acetate extract was thick, blackish green, distinctive smell and bitter, and than n-hexan extract was thick, brownish yellow, odorless and bitter. In the ethyl acetate extract, the levels of compounds dissolved in water and ethanol solvents were 16.84 % ± 0.061 and 68.29 % ± 0.042 respectively. The levels of compounds in the n-hexane extract dissolved in water and ethanol were 4.26% ± 0.064 and 23.18% ± 0.049, respectively. The results of the phytochemical screening for ethyl acetate extract of neem leaves are alkaloids and flavonoids. Meanwhile, n-Hexane extract from neem leaves contains alkaloids and terpenoids. The drying loss values obtained from ethyl acetate extract and n-Hexan extract of neem leaves were 4.748% ± 0.257 and 5.219% ± 0.089. Specific gravity obtained from The dilution of ethyl acetate extract and n-hexane extract of neem leaves was 1.0389 g/mL ± 0.039 and 1.0289 g/mL ± 0.038. Conclusion: This study showed that variations in solvents in extraction can affect the physicochemical properties. The extract with ethyl acetate solvent showed better physicochemical properties where the extract obtained in % yield, soluble compound content, phytochemical screening, determination of drying Shrinkage and determination of specific weight was better compared to the extract with n-hexane.

Introduction: Haemorrhage remains one of the leading causes of maternal mortality in Indonesia. One significant factor contributing to bleeding is the prevalence of anemia among pregnant women. Early detection of anemia is crucial in preventing this condition, but the limited knowledge among pregnant women can impede successful treatment of anemia in Indonesia. Objective: The purpose of this community service project is to enhance pregnant women’s understanding of anemia during pregnancy and enhance their mindset so that they recognize the significance of avoiding and treating anemia during pregnancy. Research Method: The study involved conducting a simulation that utilized citrus fruit and organizing small group discussions about anemia. The participants were 30 pregnant women residing in impoverished areas in the Karawang district. Results: The minimal knowledge score showed a significant rise between before and after the activity, rising from a minimum score of 7 to a minimum score of 13. Similarly, the maximum knowledge score climbed from 80 to 100. The majority of respondents expressed a strong consensus that anemia poses a significant risk to pregnancy. Consequently, respondents also strongly concurred on the need for concerted measures to address this issue. To prevent anemia, it is important to take iron supplement tablets and maintain a diet that is rich in nutritious food. Conclusion: Engaging in positive activities outside of pregnancy check-ups with healthcare professionals can serve as a platform for receiving support and fostering mutual sharing among pregnant women. This has the potential to enhance the knowledge and attitudes of pregnant women towards preventing anemia throughout pregnancy.

Background: Tuberculosis (TB) is regarded as one of the leading causes of death globally. It remains a significant cause of morbidity and mortality in Vietnam. This study aims to identify hotspots of TB using boxplot and Getis-Ord’s G_i^* statistic-based hotspot analysis. Data used and Methods: A total of 101,438 TB cases in 2020 collected from 63 provinces/cities in Vietnam was used in study. Boxplot is first used to study distribution of TB cases. Getis-Ord’s G_i^* statistic was then employed to identify hotspots of TB cases. Finally, results and main findings will be discussed and concluded. Results: It was found that a total of 05 hotspots and 04 coldspots of TB cases were detected throughout Vietnam. Five hotspots were detected in 05 provinces in the northeastern region including Ha Nam, Nam Dinh, Hai Phong, Hai Duong, and Hung Yen. Whereas, four coldspots were mainly concentrated in 03 provinces in the northwest region (Cao Bang, Tuyen Quang and Son La), and Dak Lak in the central south region. Conclusion: It can be concluded that the combination of boxplot and Getis-Ord’s G_i^* statistic can help to effectively detect hotspots of TB cases. Findings in this study provide an insight into how to used spatial statistics and spatial analysis in the study of TB distribution.

This research aimed to isolate and identify Staphylococcus aureus and Candida species from throat infections, as well as assess their antibiotic resistance. Samples were collected from both infected patients and healthy individuals, encompassing various ages and genders, in hospitals of Najaf province between December 2022 and March 2023. The findings revealed that S. aureus constituted 36.10% of isolates, followed by S. warneri at 22.81%, and S. lugdunensis at 15.29%. Notably, S. aureus isolates displayed 100% resistance to Penicillin (P), Aztreonam (ATM), and Oxacillin (OX), Amoxicillin (AMC) and Tetracycline (TE) exhibiting resistance rates of 81.95% and 78.19%, respectively. The study concluded that S. aureus was the predominant strain, followed by S. warneri. Antibiotic susceptibility testing on all S. aureus isolates (n=21) was conducted using seven selected antibiotics. Candida species identified included Candida albicans, Candida parapsilosis, and Candida glabrata, with maximum resistance observed against fluconazole (FLU) and polymyxin B (PB), followed by miconazole (MCL).