gaussian mixture model (gmm)  (MathWorks Inc)

Journal: Nmr in Biomedicine

Article Title: Cluster Analysis of VERDICT MRI for Cancer Tissue Characterization in Neuroendocrine Tumors

doi: 10.1002/nbm.70050

Figure Lengend Snippet: Scatterplot of R against f IC for all tumor voxels ( n = 11,519) and subjects (A; left side). The black contours show the 2D Gaussian mixture model (GMM) fit with each voxel data point color‐coded based on the probability of belonging to each component (blue, green, and red). Contours of the three individual GMM components are shown as smaller plots (right side). R and f IC maps of tumor ROIs were used to generate color‐coded posterior probability maps of each GMM component (B; Subject 6 shown as example).

Article Snippet: A 2D Gaussian mixture model (GMM) was then fitted to the f IC and R values of all tumor voxels using an algorithm based on the MATLAB function fitgmdist with 20 random initializations to avoid local optima and a regularization value of 3.5 × 10 −3 to avoid overfitting ( mathworks.com/matlabcentral/fileexchange/71496‐identification‐of‐subregions‐in‐parameter‐maps‐by‐gmm ) [ ].

Techniques:

Journal: Nmr in Biomedicine

Article Title: Cluster Analysis of VERDICT MRI for Cancer Tissue Characterization in Neuroendocrine Tumors

doi: 10.1002/nbm.70050

Figure Lengend Snippet: Model fit output of the Gaussian mixture model (GMM) of three clusters fitted to R and f IC for all tumor voxels. The table shows cluster ID as defined by histological analysis (Figures 4 and 6 ), mean values of R and f IC ( μ ) for each cluster, and the cluster fraction indicating the percentage of tumor voxel data that is associated with each Gaussian component.

Article Snippet: A 2D Gaussian mixture model (GMM) was then fitted to the f IC and R values of all tumor voxels using an algorithm based on the MATLAB function fitgmdist with 20 random initializations to avoid local optima and a regularization value of 3.5 × 10 −3 to avoid overfitting ( mathworks.com/matlabcentral/fileexchange/71496‐identification‐of‐subregions‐in‐parameter‐maps‐by‐gmm ) [ ].

Techniques:

Journal: Nmr in Biomedicine

Article Title: Cluster Analysis of VERDICT MRI for Cancer Tissue Characterization in Neuroendocrine Tumors

doi: 10.1002/nbm.70050

Figure Lengend Snippet: Gaussian mixture model (GMM) probability maps from the VERDICT cluster analysis of R and f IC (left columns) and classification maps from the histology analysis (right columns). The colors in the histology classification maps represent different tissue types: necrotic (red), fibrotic (blue), and viable cancer cells (green). Black pixels indicate areas where no stain was present. The colors in the VERDICT cluster maps represent the probability of each voxel belonging to the GMM clusters, with colors chosen for each cluster to best match with the histology maps.

Article Snippet: A 2D Gaussian mixture model (GMM) was then fitted to the f IC and R values of all tumor voxels using an algorithm based on the MATLAB function fitgmdist with 20 random initializations to avoid local optima and a regularization value of 3.5 × 10 −3 to avoid overfitting ( mathworks.com/matlabcentral/fileexchange/71496‐identification‐of‐subregions‐in‐parameter‐maps‐by‐gmm ) [ ].

Techniques: Staining

Journal: Cell reports

Article Title: Molecular basis for the increased fusion activity of the Ebola virus glycoprotein epidemic variant A82V: Insights from simulations and experiments

doi: 10.1016/j.celrep.2025.115521

Figure Lengend Snippet: (A) Schematic of the smFRET assay in which pseudovirions formed with the HIV-1 core are immobilized to enable imaging with TIRF microscopy. (B) A GP CL monomer with the sites of fluorophore attachment indicated (donor, green; acceptor, red. PDB: 5JQ3 with glycan cap removed to reflect GP CL ). (C) Example smFRET trajectories from individual GP CL trimers on pseudovirions with A82 (top) or V82 (bottom) GP CL . The experimental trajectories are shown in blue, overlaid with the idealized trajectory resulting from fitting to the 5-state HMM (red). The prefusion conformation is indicated with a gray bar, along with the observed intermediate conformations. (D) FRET histograms for A82 GP CL smFRET trajectories acquired under the indicated conditions. Histograms reflect the average of three independent groups of trajectories; error bars represent the standard error. Overlaid on the histograms are four Gaussian distributions (gray) for the four non-zero FRET states, with means determined through HMM analysis of the individual smFRET trajectories. The sum of the Gaussians is highlighted by the red line. The 0.8-FRET prefusion conformation and the 0.05-FRET state are indicated. The 0-FRET state has been removed from the histograms to facilitate visualization of the 0.05-FRET state. N indicates the number of smFRET trajectories used to compile each histogram. (E) FRET histograms for V82 GP CL as in (D). (F) Violin plots displaying the occupancy distribution in the 0.8-FRET prefusion conformation for each GP CL population imaged under the given conditions. Horizontal lines indicate the population mean occupancies; the gray circles and whiskers indicate the medians and quantiles, respectively. p values were determined by one-way ANOVA and multiple comparison test (ns, p > 0.05). (G) Violin plots displaying the occupancy distribution in the 0.05-FRET state, displayed as in (F). Numeric data are presented in . (H and I) Histograms of dwell times in the 0.8-FRET prefusion conformation extracted from the HMM analysis of smFRET trajectories (blue circles) acquired for (H) A82 and (I) V82 GP CL , under the indicated conditions. Histograms are displayed with logarithmically spaced bins to assist in visualization of the two time constants. Histograms were fit to double exponential functions A fast e x p t / t fast + A slow e x p t / t slow , where A fast and A slow are amplitudes, and t fast and t slow are the corresponding time constants. Double exponential fits are overlaid in solid red lines with the individual exponentials in dashed red lines. The two time constants are indicated with 95% confidence intervals in parentheses. (J) The amplitudes, A fast and A slow , determined in the exponential fitting in (A) and (B). Bars reflect the fitted values with error bars indicating the 95% confidence intervals. p values are indicated (ns, p > 0.05), determined by one-way ANOVA and multiple comparison test.

Article Snippet: Projection of the simulations into the eigenspace formed by the first three principal components and subsequent clustering using Gaussian mixture models was performed in Matlab.

Techniques: Smfret Assay, Imaging, Microscopy, Glycoproteomics, Comparison

Journal: Scientific Reports

Article Title: Subclonal response heterogeneity to define cancer organoid therapeutic sensitivity

doi: 10.1038/s41598-025-96204-2

Figure Lengend Snippet: FOLFOX resistance monitoring reveals subclonal resistance from a patient with familial adenomatous polyposis. ( a ) Representative therapeutic study (patient LC1) with FOLFOX imaged with brightfield microscopy at 0 h and 48 h annotated with percent difference in individual organoid diameter and ( b ) representative images of organoids with two-photon ORR at 48 h. ( c ) Comparison of PCO location perpendicular to the matrix edge correlated against growth with FOLFOX treatment across three independent cultures (LR4, LR5, MC7) along with the coefficient of determinant (R 2 ). ( d ) Sites of tissue sampling from patient with multiple site polyp (n = 4) and tumor sampling (n = 5). ( e ) Heatmap of pathologic alterations of PCOs derived from individual polyps (P1–P4) and tumors (T1–T5) compared between primary tissue (black, T) and organoids (gray, O) plotted as relative variant allele frequency (rVAF). Denoted are tumor suppressor genes (green) and oncogenes (red) plotted as a function of rVAR. ( f ) Heatmap of expanded PCO subclones selected by individual spikes using NGS profiling. ( g ) Comparison of normalized Δ diameter and FLIRR at 48 h stratified by parent culture, FBXW7 WT (wild type, WT), and FBXW7 R479Q (mutant, MT) using two-sided student t-test ( p > 0.05). ( h ) Representative PCOs metabolism assessed at 48 h by ORR (NAD(P)H/FAD) for control (top panel) and FOLFOX stratified by FBXW7 profile. Scale bar represents 100 µm. ( i ) Heatmap of OMI parameters by FBXW7 status stratified with respective Z-score as compared to parent culture. Significance noted for |GΔ| > 0.75 for individual OMI parameters with corresponding positive (black *) or negative (white *) effect size. Z-score defined by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\overline{\text{x}}}_{{{\text{PCO}}}}$$\end{document} (average value of individual OMI parameter for individual PCO culture), \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\overline{\text{x}}}_{{{\text{population}}}}$$\end{document} (average value of individual OMI parameter across the control population), σ population (standard deviation of an individual OMI parameter across the control population) for the control conditions \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\overline{\text{x}}}_{{{\text{population}}}}$$\end{document} and σ population refer to parent culture values. ( j,k ) Gaussian distribution plots of normalized PCO diameter change assessed from 0 to 48 h including control (gray), 5-FU (blue), oxaliplatin (red), and FOLFOX (purple). Molecular profile at FBXW7 denoted wildtype (WT, solid line) and mutant FBXW7 R479Q (MT, dashed line). Response assessed using effect size (GΔ) relative to untreated control stratified by molecular profile at FBXW7 for ( j ) normalized Δ diameter and ( k ) ORR at 48 h. Scale bars for brightfield (black bar) represent 200 µm, scale bars for OMI (white bar) represent 100 μm.

Article Snippet: Due to expected heterogeneity across mixed populations, the pooled analyses of multiple cultures in response to EGFR inhibition was performed by Gaussian population modeling using GraphPad Prism 9 (GraphPad Software, Boston, MA, USA, www.graphpad.com ).

Techniques: Microscopy, Comparison, Sampling, Derivative Assay, Variant Assay, Mutagenesis, Control, Standard Deviation

Journal: Scientific Reports

Article Title: Subclonal response heterogeneity to define cancer organoid therapeutic sensitivity

doi: 10.1038/s41598-025-96204-2

Figure Lengend Snippet: Validation of PCO response for clinical prediction. ( a ) Representative brightfield microscopy from MTB-3 ovarian (Ov) PCOs at baseline and 48 h; scale bar represents 200 μm for each panel. ( b ) Gaussian distributions for growth at 48 h with respective effect sizes (GΔ) for MTB-3 Ov PCOs treated with gemcitabine 50 μm (24 h, green), paclitaxel 50 nM (48 h, gold) or control (black) as assessed at 48 h. ( c ) Clinical response from the initial restaging CT scan of subject MTB-3 confirming the disease with enlarging retroperitoneal adenopathy after treatment with single agent gemcitabine on CT imaging. ( d ) Representative brightfield microscopy for MC7 PCOs treated with control (top panels), or FOLFOX (5-FU 10 μm and oxaliplatin 5 mμ ( e ) Gaussian distributions of MC7 for Δ diameter over 48 h and respective effect sizes (GΔ) for 5-FU 10 μm (blue), oxaliplatin 5 μm (red), and FOLFOX (violet). ( f ) Restaging CT scan of MC7 shows partial response after FOLFOX. ( g ) Experimental sensitivity with clinical outcome or canonical mechanism of resistance labeled by treatment type including chemotherapy (purple), targeted therapy (blue), canonical EGFRi resistance (RAS MT or RAF MT , red), and radiation (black) with reported significance by two-sided student t-test. ( h,i ) Comparison of FOLFOX effect size (GΔ) between PCOs with disease progression after FOLFOX chemotherapy versus subjects without prior drug exposure assessed using two-sided student t-test with prior established sensitivity thresholds (shaded region). ( h ) Absolute diameter effect size assessed at 48 h for single agent 5-FU (ns), oxaliplatin (ns) and FOLFOX (* p < 0.05) between clinically resistant and unknown cohorts. ( i Effect size of growth (percent Δ diameter) tracked from 0 to 48 h for single agent 5-FU (* p < 0.05), oxaliplatin (** p < 0.005) and FOLFOX (*** p < 0.0005) between clinically resistant and unknown cohorts. ( j ) Bar plot of negative predictive value (NPV) and positive predictive value (PPV) for prospectively treated subjects. ( k ) Receiver operator curve (ROC) in response prediction plotted as false positive rate versus sensitivity with the colored line showing the continuum of effect size (GΔ) for change in diameter and corresponding area under the curve (AUC).

Article Snippet: Due to expected heterogeneity across mixed populations, the pooled analyses of multiple cultures in response to EGFR inhibition was performed by Gaussian population modeling using GraphPad Prism 9 (GraphPad Software, Boston, MA, USA, www.graphpad.com ).

Techniques: Biomarker Discovery, Microscopy, Control, Computed Tomography, Imaging, Labeling, Comparison