The sample size (n) of the whole study was established in 6 independent biological replicas from different patients or cell passes and 3 dependent technical replicas. The availability of non-primary cells of early pass was unlimited. On the contrary, the availability of primary cells isolated from OA patients or healthy corpses was very limited. Patients were excluded from the study (CAEIG-2016/258) if they were diagnosed with microcrystalline arthritis or any other infectious process. Moreover, even if they were not diagnosed, a further analysis of the fresh sample was also needed. Similarly, the presence of any other pathology apart from OA directly excluded those samples. All included samples presented sufficient cartilage and bone to perform the cell isolation. Nevertheless, only 3 healthy samples and 3 OA samples presented sufficient synovium to be removed and processed to isolate synoviocytes. Biochemical assays (Griess and MTT) required 104 cells (P96 plate), transcriptomics (RT-qPCRs) required 105 cells (P12), metabolic assays required 3 × 105 cells (P6) and proteomics (ELISA and MALDI-TOF) required 3.5 × 106 cells (P100) per data point. Overall, the use of primary cells was optimized to acquire the largest amount of data points. MALDI-TOF proteomics analysis was the most cell-demanding technique and, considering that thousands of technical replicas runs are performed, we optimized its sample size to 3 independent biological replicas.
All datasets were expressed as the mean ± standard error mean (SEM) and normalized by the “Control” treatment data. Gene expression (mRNA) data was obtained by the RT-qPCR threshold cycle (ΔΔCt), also known as the ΔΔ quantification cycle (ΔΔCq). Gene expression was normalized by reference gene HPRT1 and analyzed by comparative transcriptomics. Fold-change (log2) units were used in the proteome heatmaps or column charts.
The whole manuscript used The New England Journal of Medicine (NEJM)’s statistical significance method of representation. Specifically, a p-value of: <0.001 (***), <0.002 (**), <0.033 (*), and <0.12 (blank space or ns). Data distribution (Shapiro–Wilk and Kolmogorov–Smirnov normality tests) determined the use of parametric or non-parametric tests. Data from primary human cells were analyzed by non-parametric Kruskal–Wallis or Mann–Whitney test if needed. Otherwise, data were analyzed by parametric One Way-ANOVA and Tukey post-test or unpaired t-test Welch’s correction if needed.
All datasets were expressed as the mean ± standard error mean (SEM) and normalized by the “Control” treatment data. Gene expression (mRNA) data was obtained by the RT-qPCR threshold cycle (ΔΔCt), also known as the ΔΔ quantification cycle (ΔΔCq). Gene expression was normalized by reference gene HPRT1 and analyzed by comparative transcriptomics. Fold-change (log2) units were used in the proteome heatmaps or column charts.
The whole manuscript used The New England Journal of Medicine (NEJM)’s statistical significance method of representation. Specifically, a p-value of: <0.001 (***), <0.002 (**), <0.033 (*), and <0.12 (blank space or ns). Data distribution (Shapiro–Wilk and Kolmogorov–Smirnov normality tests) determined the use of parametric or non-parametric tests. Data from primary human cells were analyzed by non-parametric Kruskal–Wallis or Mann–Whitney test if needed. Otherwise, data were analyzed by parametric One Way-ANOVA and Tukey post-test or unpaired t-test Welch’s correction if needed.
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