In the aging process, the presence of interleukin (IL)-17-producing CD4+CD28-NKG2D+T cells (called pathogenic CD4+ T cells) is strongly associated with inflammation and the development of various diseases. Thus, their presence needs to be monitored. The emergence of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy empowered with machine learning is a breakthrough in the field of medical diagnostics. This study aimed to discriminate between the elderly with a low percentage (LP; ≤3%) and a high percentage (HP; ≥6%) of pathogenic CD4+CD28-NKG2D+IL17+ T cells by utilizing ATR-FTIR coupled with machine learning algorithms. ATR spectra of serum, exosome, and HDL from both groups were explored in this study. Only exosome spectra in the 1700–1500 cm⁻¹ region exhibited possible discrimination for the LP and HP groups based on principal component analysis (PCA). Furthermore, partial least square-discriminant analysis (PLS-DA) could differentiate both groups using the 1700–1500 cm⁻¹ region of exosome ATR spectra with 64% accuracy, 69% sensitivity, and 61% specificity. To obtain better classification performance, several spectral models were then established using advanced machine learning algorithms, including J48 decision tree, support vector machine (SVM), random forest (RF), and neural network (NN). Herein, NN was considered to be the best model with an accuracy of 100%, sensitivity of 100%, and specificity of 100% using serum spectra in the region of 1800–900 cm⁻¹. Exosome spectra in the 1700–1500 and combined 3000–2800 and 1800–900 cm⁻¹ regions using the NN algorithm gave the same accuracy performance of 95% with a variation in sensitivity and specificity. HDL spectra with the NN algorithm also showed excellent test performance in the 1800–900 cm⁻¹ region with 97% accuracy, 100% sensitivity, and 95% specificity. This study demonstrates that ATR-FTIR coupled with machine learning algorithms can be used to study immunosenescence. Furthermore, this approach can possibly be applied to monitor the presence of pathogenic CD4+ T cells in the elderly. Due to the limited number of samples used in this study, it is necessary to conduct a large-scale study to obtain more robust classification models and to assess the true clinical diagnostic performance.

Background: Prostate cancer is the most common oncological disease in men and one of leading causes of death worldwide. Growing evidence has demonstrated the effectiveness of mung bean bioactive compounds in suppressing various cancer cells. However, their effects and underlying mechanisms on prostate cancer have not been verified. The present study aimed to investigate the therapeutical effects and underlying mechanisms of mung bean compounds against prostate cancer. Results: The results revealed that 56 proteins related to prostate cancer could be modulated by mung bean, including several vital proteins of SRC (Sarcoma), Mitogen-Activated Protein Kinase 8 (MAPK8), Heat shock protein 90 kDa alpha member A1 (HSP90AA1), and Harvey Rat sarcoma virus (HRAS). It was also found that the potential pathways associated with prostate cancer pathogenesis comprising pyrimidine metabolism, nitrogen metabolism, and prolactin signaling pathways. Of 19 mung bean compounds docked to four key proteins reveal three promising compound (dulcinoside, peonidin-3-glucoside, and chlorogenic acid) with lower binding affinity score of − 7.7, − 12.2, − 9.0, and − 6.5 kcal/mol against SRC, MAPK8, HSP90AA1, and HRAS, respectively in their site of action. Dynamic simulation results also showed values of − 36.52 ± 2.93, − 35.93 ± 1.67, and − 35.77 ± 1.17 kJ/mol for Dulcinoside-SRC, Dulcinoside-MAPK8, and P3G-HSP90AA1 complexes, respectively. The binding of the compound occur in stable and flexible with the proteins. Moreover, all mung bean compounds predicted to have good ADMET properties. Conclusions: The study concluded that dulcinoside, peonidin-3-glucoside, and chlorogenic acid potentially exhibited anticancer activity against prostate cancer in silico. Nevertheless, further studies such as in vitro and in vivo are needed to optimize and prove the efficacy of the mung brand and its compounds against prostate cancer. Graphical

High-density lipoprotein (HDL) and exosomes are promising sources of biomarkers. However, the limited sample volume and access to the ultracentrifuge equipment are still an issue during HDL and exosome isolation. This study aimed to isolate HDL and exosomes using an ultracentrifugation-free method with various small serum volumes. HDL was isolated from 200 µL (HDL200) and 500 µL (HDL500) of sera. Three different volumes: 50 µL (Exo50), 100 µL (Exo100), and 250 µL (Exo250) were used for exosome isolation. HDL and exosomes were isolated using commercial kits with the modified method and characterized by multiple approaches. The HDL levels of HDL200 and HDL500 were not significantly different (p > 0.05), with percent recoveries of >90%. HDL200 and HDL500 had the same protein pattern with a biochemical similarity of 99.60 ± 0.10%. The particle sizes of Exo50, Exo100, and Exo250 were in the expected range. All isolated exosomes exhibited a similar protein pattern with a biochemical similarity of >99%. In conclusion, two different serum volumes (200 and 500 µL) and three different serum volumes (50, 100, and 250 µL) can be employed for HDL and exosome isolation, respectively. The possibility of HDL and exosome isolation with small volumes will accelerate biomarker discoveries with various molecular diagnostic approaches.

Vibrio cholerae is an infectious agent causing cholera disease with a high prevalence in various developing countries. V. cholerae is a pathogen with broad spectrum host that can infect humans and animals, especially aquaculture. The existence of this disease in Indonesia has long been identified in several outbreaks. Various reports in Indonesia have succeeded in finding the existence of V. cholerae in the environment, aquaculture, food and beverage, as well as in clinical cases of V. cholerae infection. The presence of V. cholerae in environment such as water source is commonly related with contamination. However, V. cholerae can be found in aquatic environment as this environment is natural habitat for V. cholerae. Thus, aquaculture is prone to be infected with V. cholerae because the presence of this pathogen is abundant in aquatic environment. Contaminated food and beverage are associated with hygiene and sanitation and human is commonly infected after consuming contaminated food or beverage. This brief review has the main focus to discuss the existence of V. cholerae from environmental to clinical aspects found in Indonesia.

Purpose: Traumatic brain injury is associated with adverse prognoses and significant neurological impairments that negatively affect patients' quality of life and physiological well-being. The aim of this study was to compare various computed tomography (CT) scoring systems in order to evaluate their effectiveness in predicting mortality and in risk stratification.Methods: The evolution and trends in the use of CT scoring systems were analyzed through a bibliometric analysis of 72 Scopus-indexed documents using VOSviewer ver. 1.6.19. A systematic review was conducted following the 2020 PRISMA guidelines, with data obtained from PubMed Advance, Scopus, and Google Scholar for the period 2003–2024. A total of 198 journals were identified and subsequently filtered down to 6 that met the inclusion criteria.Results: The bibliometric analysis revealed a progressive shift toward the use of CT scoring systems for novel diagnostic purposes and mortality prediction. The Rotterdam CT score demonstrated the highest total link strength and was most frequently published in 2017. In contrast, the Marshall CT score was more widely referenced in studies published after 2020. Despite being recognized for its sensitivity, the Helsinki CT score has not garnered equivalent research attention. Furthermore, the review suggested that the Rotterdam CT score is superior in predicting mortality among traumatic brain injury patients, with the Marshall CT score also demonstrating potential.Conclusions: A review of the extant literature indicates that the Helsinki CT score exhibits the highest predictive accuracy, effectively estimating both mortality probability and long-term prognosis. Since 2015, research on the Helsinki CT score has steadily increased.

Background: Cardiovascular diseases, including hypertension, pose significant health challenges globally. Physical activity has long been recognized as a modifiable factor that can influence various aspects of cardiovascular health, including blood pressure. However, the relationship between physical activity and blood pressure is complex and can be influenced by various factors such as cultural and regional differences. Aims: The primary objective of this research was to examine the association between physical activity and blood pressure using a quasi-experimental design. Methods: This study utilized a quasi-experimental design with a one-group pre-test post-test approach. The sample was selected using a total sampling technique. The independent and dependent variables in this research were physical activity and blood pressure. Data collection instruments employed in this study consisted of observation sheets, an aneroid sphygmomanometer, and a stethoscope. Data analysis was performed using the Wilcoxon test. Results: This study showed that there was an association between physical activity and blood pressure. Conclusion: this research sheds light on the relationship between physical activity and blood pressure. The findings underscore the importance of considering cultural and regional factors in designing health interventions. Received: 20 November 2023, Reviewed: 21 November 2023, Revised: 14 March 2024, Accepted: 03 April 2024.