Assessment of Safety Performance in Banana Alcoholic Beverage Processing Factories in Rwanda

Although the Rwandan competent authorities are putting effort to improve the safety of traditional banana alcoholic beverages, safety problems still exist. This study aimed to apply customized diagnostic tool to gain an insight into the performance of food safety in traditional banana alcoholic beverage factories as an evidence based to support the selection of suitable interventions for improvement to assure sustainability and meet growing market of traditional banana alcoholic beverages. Literature search was used to identify context factors, quality assurance and control activities that can influence safety of banana alcoholic beverage products and validated by processors through interview and participant observation. The data were collected in eleven factories located in Kigali city and four provinces of Rwanda using an assessment tool. Data analysis was performed using Microsoft Office Excel. All factories have shown to operate in relatively high risk context (score 2-3), most of control activities were at basic level (score 1), whereas assurance activities were at relatively average level (score 1-2) which resulted into poor food safety performance (score 1). This shows that, the modern food safety practices can’t be applied in traditional food processing factories due to traditional methods and equipment, low level of science-based knowledge related to processing technology, food safety and hygiene. Therefore, there is a need to design modern equipment that are easy to clean and disinfect to replace traditional ones, to train technical staff on processing technology, safety and hygiene, and to change behaviors towards making decisions based on scientific knowledge.

Construction of an miRNA-Regulated Pathway Network Reveals Candidate Biomarkers for Postmenopausal Osteoporosis

We aimed to identify risk pathways for postmenopausal osteoporosis (PMOP) via establishing an microRNAs- (miRNA-) regulated pathway network (MRPN). Firstly, we identified differential pathways through calculating gene- and pathway-level statistics based on the accumulated normal samples using the individual pathway aberrance score (iPAS). Significant pathways based on differentially expressed genes (DEGs) using DAVID were extracted, followed by identifying the common pathways between iPAS and DAVID methods. Next, miRNAs prediction was implemented via calculating TargetScore values with precomputed input (log fold change (FC), TargetScan context score (TSCS), and probabilities of conserved targeting (PCT)). An MRPN construction was constructed using the common genes in the common pathways and the predicted miRNAs. Using false discovery rate (FDR) < 0.05, 279 differential pathways were identified. Using the criteria of FDR < 0.05 and log⁡FC≥2, 39 DEGs were retrieved, and these DEGs were enriched in 64 significant pathways identified by DAVID. Overall, 27 pathways were the common ones between two methods. Importantly, MAPK signaling pathway and PI3K-Akt signaling pathway were the first and second significantly enriched ones, respectively. These 27 common pathways separated PMOP from controls with the accuracy of 0.912. MAPK signaling pathway and PI3K/Akt signaling pathway might play crucial roles in PMOP.