A review for discovering hepatoprotective herbal drugs with least side effects on kidney

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Introduction: Breast milk jaundice is considered as the most common cause for neonatal jaundice; however, its epidemiological aspects in some population remain unclear. Objectives: The present study aimed to assess the prevalence of breast milk jaundice and its main determinant among a group of neonates in western Iran. Patients and Methods: This cross-sectional study was conducted on 413 neonates hospitalized due to prolonged jaundice in Besat hospital in Hamadan, Iran. The study information was collected by reviewing the hospital’s recorded files. Results: In total, 413 neonates hospitalized were assessed in this study. The main reason for appearing jaundice included; 72.4% of cases of jaundice were due to breast milk, urinary tract infection in 4.2% of cases, glucose-6-phosphate dehydrogenase deficiency (G6PD) in 5.8% of cases, hypothyroidism in 1.2% of cases. Out of 299 neonates suffering from breast milk jaundice, 126 (42.1%) were male, and 173 (57.9%) were female with the overall average age of 16.68 ± 2.14 days. Jaundice appeared at less than two days of age in 29.4% of neonates, between 15 to 20 days of age in 64.9%, and more than 20 days of age in 5.7% of cases. Conclusion: Breast milk jaundice is considered as the most common reason for neonatal jaundice in our population, which affects more than two-thirds of our neonates. Additionally, the peak age of this phenomenon is between 15 and 20 days. The appearing breast milk jaundice is independent of gender, age, and birth weight or baseline total serum bilirubin level.

Background: Acute lymphoblastic leukemia (ALL) as the most common malignancy in children is associated with high mortality and significant relapse. Currently, the non-invasive diagnosis of pediatric ALL is a main challenge in the early detection of patients. In the present study, a systems biology approach was used through network-based analysis to identify the key candidate genes related to ALL development and relapse. Materials and methods: In this systems biology (experimental) study, main and validating datasets were retrieved from a gene expression omnibus (GEO). Gene expression analyses were done using a bioinformatics array research tool (BART) and ExAtlas. Gene ontology and pathway enrichment analysis were also performed via Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the Search Tool for the Retrieval of Interacting Genes (STRING) and cytoscape V.3.9.1 were used to network construction and analysis. The MCODE and NCMine Plugin of cytoscape were applied to find clusters and a functional module in the network. The Kaplan Myer curve was applied in order to survival analysis of the validated candidate genes. A P-value of < 0.05 was considered as significant. Results: A total of 671 differentially expressed genes (DEGs) mainly involved in transporter/channel activity functions, cell communication/signaling processes and fatty acid transport/PPAR signaling/eicosanoid metabolism pathways were identified (P-value < 0.05). The main cellular compartments were plasma membrane, cell periphery and cell surface (P-value <0.05). The network analysis revealed 68 hub genes, 29 of which were candidate genes. Five candidate genes were also validated in two independent experiments. These genes were considered as key candidate genes, and three of them (BCL2L11, IGF1, PDE5A) were predictors of pediatric ALL patients survival (P-value < 0.05).  Conclusion: BCL2L11, IGF1 and PDE5A genes, as key candidate genes, are potentially good diagnostic biomarkers and therapeutic targets for pediatric ALL.

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