X-Ray Diffraction (XRD) has been developed to analyze a crystal structure in the material. XRD is then improved for determining and identifying the presence of a compound, crystallinity, and crystal properties. XRD works by observing the ray refraction pattern as a result of the beam being refracted by a material that has an atomic arrangement in its crystal lattice. Until now, there is less information regarding detailed information on how to read the XRD spectrum and peak. This study aims to demonstrate how to calculate and interpret the crystallite size based on the XRD spectra. The step-by-step method in the calculation based on the XRD data is presented, which can help especially students and first-time users in understanding XRD results. This study is prospective to be used as standard information on how to read and interpret XRD spectra.

Background: Probiotics have numerous health benefits to the digestive system, one of them being clinically able to prevent and treat diarrhea. The growing scientific evidence of probiotic benefits has led to increased production of probiotic products. Health science students, as future healthcare professionals (HCPs), should have more knowledge about probiotics to be able to give the right recommendation to their future patients and the larger community. This study aims to assess the knowledge, attitude, and practice towards probiotics of health science students in Universitas Padjadjaran, Indonesia. Methods: A cross-sectional study was conducted on 87 students from Medical Studies, Midwifery, Pharmacy, and Nursing majors in 2020. Proportional cluster random sampling was used to select the study subjects, and an online survey was used to collect the data. Final data were exported to statistics software for analysis. Scores of each variable were categorized. Kruskal-Wallis test was used to analyze the statistical differences among the four groups. Spearman's rank correlation coefficient was used to analyze the relationship between knowledge, attitude, and practice variables. Results: Of all respondents, 80% had adequate knowledge. More than half (52.9%) had a positive attitude, and most (62.1%) had a positive practice. There were significant correlations between knowledge-attitude and attitude-practice variables. Most respondents gained information on probiotics from the Internet (26%) and their lecturer (24%). P-value from Kruskal-Wallis test for knowledge, attitude, and practice are 0.466, 0.801, and 0.324, respectively. Conclusion: Most respondents had an adequate level of knowledge, a positive attitude, and a positive practice towards probiotics. Incorporating scientific evidence regarding probiotics from various studies into all health science majors' academic curricula and media may help equip the students with a better understanding of probiotics, therefore improving probiotics usage to prevent and treat digestive system diseases in the future.

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Recently, there was an abundance of studies being conducted on the metabolomic profiling of tuberculosis patients. Amino acids are critical metabolites for the immune system, as they might contribute to providing nutrients for the host intracellular pathway. In tuberculosis, several amino acids play important roles in both the mycobacteria infection mechanism and the host. Individual studies showed how the dynamics of metabolite products that result from interactions between Mycobacterium tuberculosis (Mtb) and the host play important roles in different stages of infection. In this review, we focus on the dynamics of amino-acid metabolism and identify the prominent roles of amino acids in the diagnostics and treatment of tuberculosis infection. Online resources, including PubMed, ScienceDirect, Scopus, and Clinical Key, were used to search for articles with combination keywords of amino acids and TB. The inclusion criteria were full-text articles in English published in the last 10 years. Most amino acids were decreased in patients with active TB compared with those with latent TB and healthy controls. However, some amino acids, including leucine, isoleucine, valine, phenylalanine, aspartate, and glutamate, were found to be at higher levels in TB patients. Additionally, the biomarkers of Mtb infection included the ratios of kynurenine to tryptophan, phenylalanine to histidine, and citrulline to arginine. Most amino acids were present at different levels in different stages of infection and disease progression. The search for additional roles played by those metabolomic biomarkers in each stage of infection might facilitate diagnostic tools for staging TB infection.