Journal: Disease Models & Mechanisms

Article Title: Molecular Subtyping Resource: a user-friendly tool for rapid biological discovery from transcriptional data

doi: 10.1242/dmm.049257

Figure Lengend Snippet: Data import and exploratory analysis. (A) Two input files are required to begin the analytical pipeline in the app – a gene expression matrix and a metadata that includes sample group labelling. (B) Following data upload, the data summary on samples will be displayed for quick review. (C,D) Exploratory visualisation of data will be provided in a form of 2D principal component analysis (PCA) plot (C) and a 3D PCA plot (D) with labelled sample groups.

Article Snippet: Instructions are displayed on the left-hand side of the plot, under the Plotly mode bar control, and hovering over the 3D PCA graphic itself will also reveal the built-in adjustable options above the sample labels on the top right.

Techniques: Gene Expression

Journal: BMC Genomics

Article Title: Stage-specific miRNAs regulate gene expression associated with growth, development and parasite-host interaction during the intra-mammalian migration of the zoonotic helminth parasite Fasciola hepatica

doi: 10.1186/s12864-022-08644-z

Figure Lengend Snippet: The Fasciola hepatica miRnome displays temporal expression during the life cycle within the mammalian host. ( a ) Heatmap of the expression of the miRnome across triplicate RNA samples of newly excysted juveniles (NEJ), immature fluke (JUV) and adult parasites (AD) where minimum expression (low expression – blue) and maximum expression (high expression – red) of the individual miRNAs is represented. Hierarchical clustering of the average values of miRNAs and sample types was performed using One Pearson correlation. ( b ) Parallel coordinates of F. hepatica miRNA expression (logCPM) separately analysed based on category; miRBase miRNAs (blue), other published non-miRBase miRNAs (red) and novel miRNAs determined in this study (yellow). ( c ) Principal components analysis (PCA) plots of the total miRNA expression across all sample types and miRNAs in 3D (From left to right – front view, side view, top view). Size of the nodes depicts total miRNA input (miRNA presence) between sample types NEJ (green scale), immature flukes (orange scale) and adult parasites (blue scale).

Article Snippet: Three-dimensional PCA plots were generated using the Partek suite for data visualisation.

Techniques: Expressing

Journal: Analytica chimica acta

Article Title: Expanding the analytical toolbox for identity testing of pharmaceutical ingredients: Spectroscopic screening of dextrose using portable Raman and near infrared spectrometers

doi: 10.1016/j.aca.2016.01.061

Figure Lengend Snippet: SC-based ID test results for dextrose samples and related excipients included in study.

Article Snippet: This is indicated by the clear separation of classes based on manufacturer but the commingling between the classes of Fisher Scientific of different lots. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window caption a7 PCA plots for A) dextrose anhydrous and B) dextrose monohydrate based on the Raman spectra.

Techniques: Maltodextrin, Starch

Journal: Analytica chimica acta

Article Title: Expanding the analytical toolbox for identity testing of pharmaceutical ingredients: Spectroscopic screening of dextrose using portable Raman and near infrared spectrometers

doi: 10.1016/j.aca.2016.01.061

Figure Lengend Snippet: A) Raman and B) NIR spectra for dextrose monohydrate, dextrose anhydrous and other related excipients.

Article Snippet: This is indicated by the clear separation of classes based on manufacturer but the commingling between the classes of Fisher Scientific of different lots. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window caption a7 PCA plots for A) dextrose anhydrous and B) dextrose monohydrate based on the Raman spectra.

Techniques:

Journal: Analytica chimica acta

Article Title: Expanding the analytical toolbox for identity testing of pharmaceutical ingredients: Spectroscopic screening of dextrose using portable Raman and near infrared spectrometers

doi: 10.1016/j.aca.2016.01.061

Figure Lengend Snippet: The Raman first derivative spectra (2nd order, 15 point window) for A) dextrose anhydrous and B) dextrose monohydrate samples from different manufacturers, grades and lots.

Article Snippet: This is indicated by the clear separation of classes based on manufacturer but the commingling between the classes of Fisher Scientific of different lots. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window caption a7 PCA plots for A) dextrose anhydrous and B) dextrose monohydrate based on the Raman spectra.

Techniques:

Journal: Analytica chimica acta

Article Title: Expanding the analytical toolbox for identity testing of pharmaceutical ingredients: Spectroscopic screening of dextrose using portable Raman and near infrared spectrometers

doi: 10.1016/j.aca.2016.01.061

Figure Lengend Snippet: PCA plots for A) dextrose anhydrous and B) dextrose monohydrate based on the Raman spectra. Three principal components were used for the models.

Article Snippet: This is indicated by the clear separation of classes based on manufacturer but the commingling between the classes of Fisher Scientific of different lots. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window caption a7 PCA plots for A) dextrose anhydrous and B) dextrose monohydrate based on the Raman spectra.

Techniques:

Journal: Analytica chimica acta

Article Title: Expanding the analytical toolbox for identity testing of pharmaceutical ingredients: Spectroscopic screening of dextrose using portable Raman and near infrared spectrometers

doi: 10.1016/j.aca.2016.01.061

Figure Lengend Snippet: PCA plots for A) Raman and B) NIR classes used for development of the SIMCA model. The SIMCA model contains two classes, each comprised of five different dextrose anhydrous and monohydrate samples. Two principal components were used for each class in the Raman model and three principal components were used for each class in the NIR model.

Article Snippet: This is indicated by the clear separation of classes based on manufacturer but the commingling between the classes of Fisher Scientific of different lots. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window caption a7 PCA plots for A) dextrose anhydrous and B) dextrose monohydrate based on the Raman spectra.

Techniques:

Journal: Analytica chimica acta

Article Title: Expanding the analytical toolbox for identity testing of pharmaceutical ingredients: Spectroscopic screening of dextrose using portable Raman and near infrared spectrometers

doi: 10.1016/j.aca.2016.01.061

Figure Lengend Snippet: SIMCA results for NIR and Raman.

Article Snippet: This is indicated by the clear separation of classes based on manufacturer but the commingling between the classes of Fisher Scientific of different lots. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window caption a7 PCA plots for A) dextrose anhydrous and B) dextrose monohydrate based on the Raman spectra.

Techniques: Maltodextrin

Journal: Cytotherapy

Article Title: Characterizing human mesenchymal stromal cells’ immune-modulatory potency using targeted lipidomic profiling of sphingolipids

doi: 10.1016/j.jcyt.2021.12.009

Figure Lengend Snippet: Unstimulated and IFN-γ–stimulated BM-MSC SL profile. (A) Schematic illustrating IDO converting tryptophan to kynurenine (kyn), an immunosuppressive metabolite. (B) SL concentrations of unstimulated and IFN-γ–primed MSCs. (C) PCA of high and low IDO unstimulated (Unstim) MSC groups. (D) PCA variable plot of MSC groups. (E) PCA of high and low IDO IFN-γ–primed groups. (F) PCA variable plot of IFN-γ groups. (G) LDA of high and low MSCs from Unstim and IFN-γ groups. *Statistical significance (P < .05). Mann–Whitney U test was used to determine significance. All groups were measured in triplicates (n = 3).

Article Snippet: Graphical illustrations of PCA variable loading plots were generated in RStudio.

Techniques: MANN-WHITNEY