IBM SPSS Statistics for Windows, V.25.0 (IBM Corp.) was used to perform statistical analysis and Origin(Pro), Version 2019b (OriginLab Corporation, Northampton, Massachusetts, USA) was utilised for graphs. Means and SD were calculated for continuing variables, which were normally distributed. Medians and IQR were used for continuing variables which were not normally distributed. Group differences of continuous variables were tested by using independent samples t-test and variance analyses or Mann-Whitney U test. Differences in the categorised variables were calculated with χ2 or Fisher’s exact test. Survival was estimated by using Kaplan-Meier curves and the groups were compared with each other by using log rank tests. Log rank test with a linear trend for factor levels was used when the survival differences of five different FILD subgroups were evaluated. The effects of gender, age, PFT results, smoking status and corticosteroid treatment preceding hospitalisation on survival were assessed with Cox regression analysis. As this was a register-based retrospective study and the majority of study subjects were deceased, no patient consent forms were gathered in accordance with Finnish legislation.
Origin pro version 2019b
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OriginLab's Origin(Pro), Version 2019b is a comprehensive data analysis and graphing software. It provides a suite of tools for visualizing, analyzing, and presenting scientific and engineering data. The software offers a wide range of features for data manipulation, curve fitting, statistical analysis, and publication-quality graph creation.
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10 protocols using origin pro version 2019b
1
Comprehensive Statistical Analysis of FILD Prognosis
2
Metabolic Phenotypes and Gut Microbiome Analysis
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Analyses were conducted and graphed using Prism 8.0.2 (GraphPad Software, La Jolla, CA, USA). Normality of data was determined by Shapiro–Wilks test. Outliers were removed using ROUT's test (Q = 1%). Significant differences for metabolic phenotypes were assessed via 2-way analysis of variance (ANOVA) (where time was a factor) or parametric 1-way ANOVA or nonparametric Kruskal–Willis test followed by Dunnett's post hoc test using the HFD group as a control so only 1 factor (ie, % fat or GP supplementation) was assessed in each comparison. For gene expression, metabolite analyses, and immunoassays the difference between HFD and HFD-GP groups was assessed by unpaired, 2-tailed, Student's t test or for nonparametric data, a Mann–Whitney test. P < .05 was considered significant. Statistical analysis of α- and β-diversity metrics was calculated using QIIME 2. ADONIS and permutation analysis were conducted using R Studio V.3.4.2 (R Studio Software, Boston, MA, USA). The Galaxy web application was used to perform LefSe differential analysis and to plot linear discriminant analysis effect size (huttenhower.sph.harvard.edu/lefse ). Graphs were created using Prism 8.0.2 or Origin (Pro), Version 2019b (OriginLab Corporation, Northampton, MA, USA).
3
Analyzing Mast Cell Density for AE-IPF
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IBM SPSS Statistics for Windows, Version 27.0 (Armonk, NY: IBM Corp.) was used to perform statistical analysis, and Origin(Pro), Version 2019b (OriginLab Corporation, Northampton, MA, USA), was utilized for preparing the graphs. Means and standard deviations were calculated for parameters that were normally distributed. Medians and interquartile ranges were determined for parameters that were not normally distributed. We used independent samples t-test or paired samples t-test to compare means when appropriate. The intraclass correlation coefficient was determined to evaluate the interrater reliability of MC counts. Survival analysis was performed by using Kaplan–Meier curves, and risk for earlier death or earlier episode of AE-IPF was evaluated by using Cox regression model. Medians and quartiles of MC densities were utilized to determine the cutoff values for Kaplan–Meier and Cox regression analyses. We included MC densities of SLB samples, not autopsy samples, in the Kaplan–Meier and Cox regression analyses.
4
Nanoparticle Formulation Optimization
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If not stated differently, results are displayed as mean values (n) ± standard deviation (SD). A minimum of three independent experiments was performed for each nanoparticle formulation. Statistical significance was tested by an analysis of variance (ANOVA). It was performed as one-way ANOVA followed by Bonferroni multiple comparisons test to assess the differences between the different examined formulations. Statistical difference was assumed when p < 0.05. Statistical evaluations were made by OriginPro Version 2019b (OriginLab Corporation, Northampton, MA, USA).
5
Statistical analysis of hospitalization outcomes
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IBM SPSS Statistics for Windows, Version 25.0 (Armonk, NY: IBM Corp.) was used to perform statistical analysis and Origin(Pro), Version 2019b (OriginLab Corporation, Northampton, MA, USA) was utilized for graphs. Means and standard deviations were calculated for continuing variables, which were normally distributed. Medians and inter-quartile range (IQR) were utilized for continuing variables which were not normally distributed. Group differences of continuous variables were tested by using independent samples t-test and variance analyses or Mann-Whitney U-test. Differences in the categorized variables were calculated with Chi-Square or Fisher’s Exact test. Survival was estimated by using Kaplan-Meier curves and the groups were compared with each other by using log rank tests. Log rank test with a linear trend for factor levels was used, when the survival differences of patients were evaluated according to the cause of the hospitalization. Cox regression model was utilized for the assessment of risk factors for death and AE-ILD.
6
MMP-9 Expression in HCE-T Cells with Serum
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MMP9 protein expression was analyzed with the Human MMP-9 DuoSet ELISA following the manufacturer’s protocol. HCE-T cells were seeded into 6-well plates (250,000 cells per well) and cultivated for ten days. HCE-T cells were induced with TNFα (10 ng/mL) for 24 h, and simultaneously, 1%, 2.5%, 5%, 10%, 20% and 50% human allogeneic serum was added. Dexamethasone (100 µM) served as a positive control. HCE-T-cell supernatants were obtained and stored at −20 °C until use. Serum samples diluted with reagent diluent served as a positive control. The values of the positive controls were subtracted from the sample values. Absorbance was measured at 450 nm, and the reference wavelength was 540 nm using a microplate reader (Infinite M Plex, Tecan, Männedorf, Switzerland). The standard curve of the standard dilution series was exponentially fitted using Origin(Pro) (Version 2019b, OriginLab Corporation, Northampton, MA, USA).
7
Survival Analysis in Idiopathic Pulmonary Fibrosis
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IBM SPSS Statistics for Windows, Version 25.0 (IBM Corp, Armonk, NY) was used to perform statistical analysis. OriginPro, Version 2019b (OriginLab Corporation, Northampton, MA, USA) was used for preparing graphs. The data were presented as median values with 25 and 75% quartiles for skewed variables, or as the means with standard deviation for those with a normal distribution. Comparisons of parameters that were not normally distributed between more than two groups were performed using the Kruskal–Wallis test and post hoc analysis (Dunn’s test with Bonferroni correction) and between two groups using Mann–Whitney U test. FVC% and DLCO% were divided in two groups based on median values (75% and 53%, respectively) in IPF patients at a stable phase of the disease. Survival was evaluated using the Kaplan–Meier method and differences in survival curves were evaluated using the log-rank test. The associations of relative immunohistochemical NHLRC2 expression and the number of NHLRC2-positive FF/cm2 with survival or future AE were analysed using univariate Cox regression analysis. Median values of relative NHLRC2 expression and NHLRC2-positive FF/cm2 in IPF patients were used as cut-off values for Kaplan-Meyer and Cox regression analysis. Values of p < 0.05 were considered statistically significant.
8
Statistical Analysis of Experimental Data
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Experimental data were statistically analyzed using SAS university edition (3.5 basic ed., SAS Institute Inc., Cary, NC, USA), with the PROC ANOVA and PROC GLM procedures. Data obtained were evaluated using analysis of variance (ANOVA) at p < 0.05 significance levels. Mean values were compared using least significant difference (LSD) test at p < 0.05 [45 (link),56 (link)]. Origin Pro version 2019b (Origin Lab Corporation, Wellesley Hills, Wellesley, MA, USA) was used to prepare graphs.
9
DNA-PAINT Signal Localization and Drift Correction
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After recording a DNA-PAINT stack, the center position of signals (localizations) emitted by imager probes, transiently binding to DNA origami docking strands, were identified using the ImageJ ThunderSTORM plugin33 (link). The localizations were rendered and then drift corrected using the Picasso-Render software package, as described by Schnitzbauer et al.17 (link). Data visualization and peak fitting of image data for PSF analysis were performed using OriginPro Version 2019b (OriginLab).
10
Phenotypic Variation of Himalayan Flora
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Extensive field surveys were carried out across different habitats of Kashmir Himalaya to identify the specific areas. Five distinct sites including four natural sites (Kangan (1850 m asl), Drang (2230 m asl), Betab valley (2350 m asl), Gulmarg (2450 m asl), and one control site at Kashmir University Botanical Garden (KUBG) ̶ ̶ ̶ 1595 m asl were selected for the present study. Geographical coordinates, characteristics, and distribution of these selected sites (Table 1; Figure 2). To study the phenotypic traits (microscopic and macroscopic characteristics), 10 plants were selected and tagged from each selected population site [17] . The marked individuals across different study sites were monitored on regular basis. Further, the plants were collected at the reproductive stage for analyzing the selected traits.
For statistical analysis, OriginPro (version 2019b) software was used. Multivariate ordination was performed to depict the impact of habitat variability on different phenotypic traits of the plant while regression analysis was performed to analyze the correlation between two different traits. Different populations were statistically analyzed for various phenotypic traits such as stem length, leaf length, number of branches per plant, plant height, and branch length. The propagules and seedlings were transferred to the Kashmir University Botanical Garden (KUBG).
For statistical analysis, OriginPro (version 2019b) software was used. Multivariate ordination was performed to depict the impact of habitat variability on different phenotypic traits of the plant while regression analysis was performed to analyze the correlation between two different traits. Different populations were statistically analyzed for various phenotypic traits such as stem length, leaf length, number of branches per plant, plant height, and branch length. The propagules and seedlings were transferred to the Kashmir University Botanical Garden (KUBG).
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