Agilent feature extraction software v12

Initial relative fluorescent units (RFUs) were aquired utilizing the using Agilent Feature Extraction Software V12.0 (Agilent, Santa Clara, CA, USA) with their normalisation and calibration performed using the SomaLogic software.
No studies are available detailing the changes in HSP response to hypoglycemia on which a power calculation could be based. log₂ RFU values were derived using R version 3.5.2 (R Foundation for Statistical Computing, Vienna, Austria), as documented previously [29 (link)]. Protein changes were determined using limma models that contained contrasts between timepoints, as well as contrasts between groups at single timepoints. The Benjamini–Hochberg method was used to correct limma-obtained p-values [30 (link)]. A p-value of <0.05 was considered to be significant. A visual evaluation of data trends was undertaken. The Kolmogorov–Smirnov test was used to identify non-normal data and non-parametric tests were then applied. Student’s t-test was used to compare data at each timepoint between groups and between timepoints within groups. GraphPad Prism (San Diego, CA, USA) was used for statistical analysis [27 (link),28 (link)].

Total RNA containing miRNAs (100 ηg) from a total of 16 plasma exosome samples (SC(−): n = 8 and SF(−): n = 8) were reverse transcribed. Each sample was prepared according to the Agilent's miRNA recommended approach using the one-color technique. miRNA was dephosphorylated with calf intestine alkaline phosphatase (GE Healthcare Europe GmbH), denatured with dimethyl sulfoxide, and labeled with pCp-Cy3 using T4 RNA ligase (GE Healthcare Europe GmbH). The labeled miRNAs were hybridized to custom 8 × 60 K mouse microarrays, consisting of 60-mer DNA probes synthesized in situ that represent 2006 miRNA (Version 19.0) and each of them represented by 40 features probes (Agilent), Santa Clara, CA). After hybridization and washing, the arrays were scanned with an Agilent microarray scanner using high dynamic range settings as specified by the manufacturer. Microarray results were extracted using Agilent Feature Extraction software (v12.0). Bioconductor package AgiMicroRna [53 (link)] was used to perform the data preprocessing and limma [54 (link)] was also used for the differential expression analysis. The p-values were corrected for multiple testing by false discovery rate (FDR) using Benjamini-Hochberg procedure [55 ].