RESULT: SPME GC-MS analysis showed the highest terpenoid accumulation on the 6th day post-inoculation (dpi) compared to the other treatment time points (0 dpi, 3 dpi, and 9 dpi). Among the increased terpenoid compounds, α-cedrene, valencene and β-bisabolene were prominent. P. minor inoculated for 6 days was selected for miRNA library construction using next generation sequencing. Differential gene expression analysis showed that 58 miRNAs belonging to 30 families had significantly altered regulation.
Among these 58 differentially expressed genes (DEGs), 27 [corrected] miRNAs were upregulated, whereas 31 [corrected] miRNAs were downregulated. Two putative novel pre-miRNAs were identified and validated through reverse transcriptase PCR. Prediction of target transcripts potentially involved in the mevalonate pathway (MVA) was carried out by psRobot software, resulting in four miRNAs: pmi-miR530, pmi-miR6173, pmi-miR6300 and a novel miRNA, pmi-Nov_13. In addition, two miRNAs, miR396a and miR398f/g, were predicted to have their target transcripts in the non-mevalonate pathway (MEP). In addition, a novel miRNA, pmi-Nov_12, was identified to have a target gene involved in green leaf volatile (GLV) biosynthesis. RT-qPCR analysis showed that pmi-miR6173, pmi-miR6300 and pmi-nov_13 were downregulated, while miR396a and miR398f/g were upregulated. Pmi-miR530 showed upregulation at 9 dpi, and dynamic expression was observed for pmi-nov_12. Pmi-6300 and pmi-miR396a cleavage sites were detected through degradome sequence analysis. Furthermore, the relationship between miRNA metabolites and mRNA metabolites was validated using correlation analysis.
CONCLUSION: Our findings suggest that six studied miRNAs post-transcriptionally regulate terpenoid biosynthesis in P. minor. This regulatory behaviour of miRNAs has potential as a genetic tool to regulate terpenoid biosynthesis in P. minor.
METHODS: We searched the Cochrane Central Register of Controlled Trials and Epistemonikos, as well as MEDLINE from 1966 till August 2019. Screening of full texts, evaluation for eligibility, and data extraction were done by four independent reviewers. We estimated risk ratios (RR) and mean differences (MD) using a random-effects model with 95% confidence intervals (CI). The primary outcomes included the number of participants who achieved the target mean arterial pressure (MAP), time to achieve the target MAP, and number of participants with all-cause 28-day mortality. The secondary outcomes included the length of stay in the intensive care unit, length of hospital stay, incidence of arrhythmia and myocardial infarction, vasopressor-free days, and number of participants with all-cause 90-day mortality.
RESULTS: We identified 11 randomized controlled trials with a total of 4,803 participants. There was no difference in the number of participants who achieved the target MAP between those patients receiving norepinephrine and other vasopressors (RR 1.44; 95% CI, 0.32 to 6.54; P = 0.640; I2 = 94%; two trials, 116 participants). There was no significant difference in time to achieve the target MAP (MD -0.05; 95%, CI, -0.32 to 0.21; P = 0.690; I2 = 26%; two trials, 1763 participants) and all-cause 28-day mortality (RR 0.95; 95% CI, 0.89 to 1.02; P = 0.160; I2 = 0%; seven trials, 4,139 participants). Regarding the secondary outcome, norepinephrine may significantly reduce the incidence of arrhythmia as compared to other vasopressors (RR 0.64; 95% CI, 0.42 to 0.97; P = 0.030; I2 = 64%; six trials, 3974 participants). There was no difference in the incidence of myocardial infarction (RR 1.28; 95% CI, 0.79 to 2.09), vasopressor-free day (RR 0.46; 95% CI, -1.82 to 2.74) and all-cause 90-day mortality (RR 1.08; 95% CI, 0.96 to 1.21) between norepinephrine and vasopressors.
CONCLUSION: In minimizing the occurrence of an arrhythmia, norepinephrine is superior to other vasopressors, making it safe to be used in septic shock. However, there was insufficient evidence concerning mortality and achievement of the target MAP outcomes.