OBJECTIVES: The objectives of this study were to identify the top differentially expressed miRNAs (DE-miRNAs) and their corresponding targets in hub gene-miRNA networks, as well as identify novel DE-miRNAs by analyzing three distinct microarray datasets. Additionally, functional enrichment analysis was performed using bioinformatics approaches. Finally, interactions between the 5 top-ranked hub genes and drugs were investigated.
METHODS: Using bioinformatics approaches, three GC profiles from the gene expression omnibus (GEO), namely gene expression omnibus series (GSE)-34526, GSE114419, and GSE137684, were analyzed. Targets of the top DE-miRNAs were predicted using the multiMiR R package, and only miRNAs with validated results were retrieved. Genes that were common between the "DE-miRNA prediction results" and the "existing tissue DE-mRNAs" were designated as differentially expressed genes (DEGs). Gene ontology (GO) and pathway enrichment analyses were implemented for DEGs. In order to identify hub genes and hub DE-miRNAs, the protein-protein interaction (PPI) network and miRNA-mRNA interaction network were constructed using Cytoscape software. The drug-gene interaction database (DGIdb) database was utilized to identify interactions between the top-ranked hub genes and drugs.
RESULTS: Out of the top 20 DE-miRNAs that were retrieved from the GSE114419 and GSE34526 microarray datasets, only 13 of them had "validated results" through the multiMiR prediction method. Among the 13 DE-miRNAs investigated, only 5, namely hsa-miR-8085, hsa-miR-548w, hsa-miR-612, hsa-miR-1470, and hsa-miR-644a, demonstrated interactions with the 10 hub genes in the hub gene-miRNA networks in our study. Except for hsa-miR-612, the other 4 DE-miRNAs, including hsa-miR-8085, hsa-miR-548w, hsa-miR-1470, and hsa-miR-644a, are novel and had not been reported in PCOS pathogenesis before. Also, GO and pathway enrichment analyses identified "pathogenic E. coli infection" in the Kyoto encyclopedia of genes and genomes (KEGG) and "regulation of Rac1 activity" in FunRich as the top pathways. The drug-hub gene interaction network identified ACTB, JUN, PTEN, KRAS, and MAPK1 as potential targets to treat PCOS with therapeutic drugs.
CONCLUSIONS: The findings from this study might assist researchers in uncovering new biomarkers and potential therapeutic drug targets in PCOS treatment.
METHODS: The dataset includes 1,009 cases and 1,009 controls, with comprehensive data on lifestyle, health-behavior, reproductive and sociodemographic factors. Different machine learning models, namely Random Forest (RF), Neural Networks (NN), Bootstrap Aggregating Classification and Regression Trees (Bagged CART), and Extreme Gradient Boosting Tree (XGBoost), were employed to analyze the data.
RESULTS: The findings highlight the significance of a chest X-ray history, deliberate weight loss, abortion history, and post-menopausal status as predictors. Factors such as second-hand smoking, lower education, menarche age (>14), occupation (employed), first delivery age (18-23), and breastfeeding duration (>42 months) were also identified as important predictors in multiple models. The RF model exhibited the highest Area Under the Curve (AUC) value of 0.9, as indicated by the Receiver Operating Characteristic (ROC) curve. Following closely was the Bagged CART model with an AUC of 0.89, while the XGBoost model achieved a slightly lower AUC of 0.78. In contrast, the NN model demonstrated the lowest AUC of 0.74. On the other hand, the RF model achieved an accuracy of 83.9% and a Kappa coefficient of 67.8% and the XGBoost, achieved a lower accuracy of 82.5% and a lower Kappa coefficient of 0.6.
CONCLUSION: This study could be beneficial for targeted preventive measures according to the main risk factors for BC among high-risk women.
MATERIAL AND METHODS: Matrix metalloproteinases (MMPs) are enzymes involved in cancer progression and are regarded as major oncotargets. Among others, MMP9 plays critical roles in tumour progression, angiogenesis, and invasion of cutaneous SCC. We aimed to determine whether the MMP9 gene is a suitable gene target for anti-cancer therapy for cutaneous SCC. We performed clustered regularly interspaced short palindromic repeat (CRISPR)-Cas9 transfection of guide RNA (gRNA) targeting the MMP9 gene into human cutaneous SCC cell line A431.
RESULTS: Following CRISPR transfection treatment, the viability (p < 0.01) and migratory activities (p < 0.0001) of in vitro cutaneous SCC cells were found to be reduced significantly. The use of quantitative polymerase chain reaction (qPCR) also revealed downregulation of the mRNA expression levels of cancer-promoting genes TGF-β, FGF, PI3K, VEGF-A, and vimentin. Direct inhibition of the MMP9 gene was shown to decrease survivability and metastasis of cutaneous SCC cell line A431.
CONCLUSIONS: Our findings provided direct evidence that MMP9 is important in the viability, proliferation, and metastasis of cutaneous SCC cells. It serves as a positive foundation for future CRISPR-based targeted anti-cancer therapies in treating skin cancer and other forms of malignancies that involve MMPs as the key determinants.
KEY POINTS: UPLC data of soil interfere with baseline drifts.BC can improve the quality of the pixel-level UPLC data.MW emerges as the most desired algorithm in improving the quality of UPLC data of soil.
MATERIALS AND METHODS: Yeast isolates were collected from Sultan Abdul Halim Hospital, Kedah, Malaysia, from October 2020 to October 2021. Molecular identification of the isolates was performed by one enzyme-based polymerase chain reaction-restriction fragment length polymorphism method.
RESULTS: Candida albicans was the most prevalent species, accounting for 120 isolates (59%) in total. The most prevalent non-albicans Candida species were C. tropicalis (n=33, 16%), C. krusei (Pichia kudriavzevii) (n=12, 5.8%), C. glabrata (n=12, 5.8%), and C. parapsilosis (n=6, 3%). Other unusual Candida species were C. guilliermondii (2), C. metapsilosis (2), C. orthopsilosis (1), C. lusitaniae (1), C. rugosa (1), C. haemulonii (1), C. bracarensis (1), and C. dubliniensis (1). Moreover, Talaromyces marneffei (1), Kodamaea ohmeri (1), Cryptococcus neoformans (3), and Cryptococcus laurentii (1) were among the other yeasts identified.
CONCLUSION: The Molecular technique used in this study identified 96% of isolates, including mixed species. According to the findings, the most prevalent species are C. albicans, C. tropicalis, C. krusei, and C. glabrata.
METHODS: This study presents a framework for assessing fire risks in EVs using Fault Tree Analysis (FTA). By integrating disparate data sources into a unified dataset, the proposed methodology offers a holistic approach to understanding potential hazards. The study embarked on a comprehensive exploration of EV fire causes through qualitative FTA.
RESULTS: Through this approach, the work discerned five major causes: human factors, vehicle factors, management factors, external factors, and unknown factors. Using a meticulous weighted average approach, the annual EV fire frequency for each country was deduced, revealing an average annual EV fire rate of 2.44 × 10 -4 fires per registered EV. This metric provides a significant benchmark, reflecting both the probability and inherent risk of such incidents. However, uncertainties in data quality and reporting discrepancies highlight the imperative of continued research.
CONCLUSIONS: As EV adoption surges, this study underscores the importance of comprehensive, data-driven insights for proactive risk management, emphasizing the necessity for vigilant and adaptive strategies. The findings emphasize the pivotal role of this assessment in shaping response strategies, particularly for first responders dealing with EV fires. In essence, this research not only elevates the understanding of EV fire risks but also offer a foundation for future safety measures and policies in the domain.
MATERIALS AND METHODS: To obtain the bacterial microbial composition, deoxyribonucleic acid extraction was carried out using amplicon-sequencing of the 16S-rRNA gene in the V3-V4 region from two types of Budu and carried out in duplicate.
RESULTS: Budu prepared with fresh (Pariaman) or frozen (Pasaman) fish was dominated by Firmicutes (78.455%-92.37%) and Proteobacteria (6.477%-7.23%) phyla. The total microbial species in Budu from Pariaman were higher (227 species) than in Pasaman (153 species). The bacterial species found are Lentibacillus kimchi (1.878%-2.21%), Staphylococcus cohnii (0.597%-0.70%), Peptostreptococcus russeli (0.00%-0.002%), Clostridium disporicum (0.073%-0.09%), Clostridium novyi (0.00%-0.01%), Nioella sediminis (0.00%-0.001%), and Shewanella baltica (0.00%-0.003%). Lentibacillus kimchi, S. cohnii, and C. disporicum are found in both Budu. Nioella sediminis and S. baltica are found in Budu Pariaman. Peptostreptococcus russeli and C. novyi were found in Budu Pasaman.
CONCLUSION: Metagenomic analysis of Budu from different fish, Pariaman (fresh fish) and Pasaman (frozen fish) showed that the biodiversity of bacteria was barely different. Both Budu found lactic acid bacteria from the Enterococcaceae family, genus Vagococcus, and pathogenic bacteria, such as S. cohnii, P. russeli, C. disporicum, and S. baltica. The discovery of various species of pathogenic bacteria indicates that development is still needed in the Budu production process to improve Budu quality.
MATERIALS AND METHOD: A total of 563 sequences from eight countries (Laos, Myanmar, Vietnam, Malaysia, Indonesia, Cambodia, the Philippines, and Thailand) in Southeast Asia are used in this study. Data collected from National Center for Biotechnology Information (NCBI) regarding the genus Gallus sp. in a Southeast Asian country. Data analysis was performed using MEGA 7.2 and DnaSP v6.
RESULTS: In the haplotype found in Gallus sp. in Southeast Asia, there are 89 haplotypes. Using a neighbor-joining (Nj) analysis, 89 haplotypes found three haplogroups for Gallus sp. in Southeast Asia. In Southeast Asia, the genetic diversity of the d-loop is exceptionally high, with a haplotype diversity value of 0.524 to 1.
CONCLUSION: D-loop cannot be used as a specific marker for breeds or country-specifics.
AIM: Hence, this study was planned to study the impact of psychiatry clinical posting on attitude toward psychiatry of undergraduate medical students.
MATERIALS AND METHODS: Undergraduate medical students undergoing psychiatry posting were assessed on the first and last day of clinical posting with the help of semi-structured proforma consisting of sociodemographic information, favored future career choice, the relevance of psychiatry to their future careers, the usefulness of particular knowledge and skills, the value of knowledge of psychiatric specialties and the utility of different settings for learning psychiatry.
RESULTS: After their clinical posting, students had a more positive attitude towards the usefulness of psychiatry knowledge in future general practice and the usefulness of psychiatry knowledge from undergraduate training in the future. Knowledge of alcohol withdrawal management, detection and management of delirium, and Mental Health Acts were perceived more essential in the future. Also, specialties such as deaddiction and child and adolescent psychiatry were felt more useful in future practice. After posting, students perceived that psychiatry can also be learned at medical and surgical wards as well as during home visits. However, despite some positive changes in attitude toward psychiatry, there was no significant change in choosing psychiatry as a career by the students after posting.
CONCLUSION: Undergraduate psychiatry training during clinical posting was able to make some positive changes in the knowledge and attitude of students. However, still, there were lacunae in some areas of concern. Preference of psychiatry as a branch of specialization was not increased after posting. This indicates the need for better reforms in psychiatry education at the undergraduate level to improve the perception of undergraduate students about psychiatry.