Abstract: Methods, systems, and apparatuses for detecting and describing heterogeneity in a cell sample are disclosed herein. A plurality of fields of view (FOV) are generated for one or more areas of interest (AOI) within an image of the cell sample are generated. Hyperspectral or multispectral data from each FOV is organized into an image stack containing one or more z-layers, with each z-layer containing intensity data for a single marker at each pixel in the FOV. A cluster analysis is applied to the image stacks, wherein the clustering algorithm groups pixels having a similar ratio of detectable marker intensity across layers of the z-axis, thereby generating a plurality of clusters having similar expression patterns.

Abstract: Methods, systems, and apparatuses for detecting and describing heterogeneity in a cell sample are disclosed herein. A plurality of fields of view (FOV) are generated for one or more areas of interest (AOI) within an image of the cell sample are generated. Hyperspectral or multispectral data from each FOV is organized into an image stack containing one or more z-layers, with each z-layer containing intensity data for a single marker at each pixel in the FOV. A cluster analysis is applied to the image stacks, wherein the clustering algorithm groups pixels having a similar ratio of detectable marker intensity across layers of the z-axis, thereby generating a plurality of clusters having similar expression patterns.

Abstract: Methods, systems, and apparatuses for detecting and describing heterogeneity in a cell sample are disclosed herein. A plurality of fields of view (FOV) are generated for one or more areas of interest (AOI) within an image of the cell sample are generated. Hyperspectral or multispectral data from each FOV is organized into an image stack containing one or more z-layers, with each z-layer containing intensity data for a single marker at each pixel in the FOV. A cluster analysis is applied to the image stacks, wherein the clustering algorithm groups pixels having a similar ratio of detectable marker intensity across layers of the z-axis, thereby generating a plurality of clusters having similar expression patterns.

Abstract: Methods, systems, and apparatuses for detecting and describing heterogeneity in a cell sample are disclosed herein. A plurality of fields of view (FOV) are generated for one or more areas of interest (AOI) within an image of the cell sample are generated. Hyperspectral or multispectral data from each FOV is organized into an image stack containing one or more z-layers, with each z-layer containing intensity data for a single marker at each pixel in the FOV. A cluster analysis is applied to the image stacks, wherein the clustering algorithm groups pixels having a similar ratio of detectable marker intensity across layers of the z-axis, thereby generating a plurality of clusters having similar expression patterns.

Abstract: Methods, systems, and apparatuses for detecting and describing heterogeneity in a cell sample are disclosed herein. A plurality of fields of view (FOV) are generated for one or more areas of interest (AOI) within an image of the cell sample are generated. Hyperspectral or multispectral data from each FOV is organized into an image stack containing one or more z-layers, with each z-layer containing intensity data for a single marker at each pixel in the FOV. A cluster analysis is applied to the image stacks, wherein the clustering algorithm groups pixels having a similar ratio of detectable marker intensity across layers of the z-axis, thereby generating a plurality of clusters having similar expression patterns.

Abstract: Methods, systems, and apparatuses for detecting and describing heterogeneity in a cell sample are disclosed herein. A plurality of fields of view (FOV) are generated for one or more areas of interest (AOI) within an image of the cell sample are generated. Hyperspectral or multispectral data from each FOV is organized into an image stack containing one or more z-layers, with each z-layer containing intensity data for a single marker at each pixel in the FOV. A cluster analysis is applied to the image stacks, wherein the clustering algorithm groups pixels having a similar ratio of detectable marker intensity across layers of the z-axis, thereby generating a plurality of clusters having similar expression patterns.

Abstract: Embodiments herein provide methods, apparatuses, and systems for detecting, monitoring, measuring, and/or characterizing the activity of phosphoproteins such as tyrosine kinases (TKs) and downstream proteins in TK signal transduction pathways (e.g., TK pathway proteins). In various embodiments, the methods, apparatuses, and systems may use nanoparticles, such as quantum dots (QD), to detect and/or characterize the abnormally overactive TK signaling pathways that underlie tumorgenesis and tumor progression. In various embodiments, the QD-based methods, apparatuses, and systems may have a sufficiently high degree of sensitivity to enable the identification of new TK signaling pathway markers, for example for use in diagnosing, staging, monitoring, and/or prognosing cancers, or in evaluating the efficacy of cancer therapeutics.

Abstract: Embodiments herein provide methods, apparatuses, and systems for detecting, monitoring, measuring, and/or characterizing the activity of phosphoproteins such as tyrosine kinases (TKs) and downstream proteins in TK signal transduction pathways (e.g., TK pathway proteins). In various embodiments, the methods, apparatuses, and systems may use nanoparticles, such as quantum dots (QD), to detect and/or characterize the abnormally overactive TK signaling pathways that underlie tumorgenesis and tumor progression. In various embodiments, the QD-based methods, apparatuses, and systems may have a sufficiently high degree of sensitivity to enable the identification of new TK signaling pathway markers, for example for use in diagnosing, staging, monitoring, and/or prognosing cancers, or in evaluating the efficacy of cancer therapeutics.

Abstract: Methods and systems for quantifying cellular activity using labeled probes, e.g., quantum dots, are disclosed. In one example approach, a method for quantifying cellular activity in a sample containing intact cells having labeled complexes comprises receiving images of the sample at a plurality of depths and detecting individual intact cells in the images of the sample at the plurality of depths. For each detected cell, discrete labels may be detected and localized in the cell at each depth, a total number of detected and localized labels may be calculated in the cell, and an activity level of the target molecule for the labeled probe in the cell determined.

Abstract: Methods, systems, and apparatuses for detecting and describing heterogeneity in a cell sample are disclosed herein. A plurality of fields of view (FOV) are generated for one or more areas of interest (AOI) within an image of the cell sample are generated. Hyperspectral or multispectral data from each FOV is organized into an image stack containing one or more z-layers, with each z-layer containing intensity data for a single marker at each pixel in the FOV. A cluster analysis is applied to the image stacks, wherein the clustering algorithm groups pixels having a similar ratio of detectable marker intensity across layers of the z-axis, thereby generating a plurality of clusters having similar expression patterns.

Abstract: Embodiments herein provide methods, apparatuses, and systems for detecting, monitoring, measuring, and/or characterizing the activity of phosphoproteins such as tyrosine kinases (TKs) and downstream proteins in TK signal transduction pathways (e.g., TK pathway proteins). In various embodiments, the methods, apparatuses, and systems may use nanoparticles, such as quantum dots (QD), to detect and/or characterize the abnormally overactive TK signaling pathways that underlie tumorgenesis and tumor progression. In various embodiments, the QD-based methods, apparatuses, and systems may have a sufficiently high degree of sensitivity to enable the identification of new TK signaling pathway markers, for example for use in diagnosing, staging, monitoring, and/or prognosing cancers, or in evaluating the efficacy of cancer therapeutics.

Abstract: Methods and systems for quantifying cellular activity using labeled probes, e.g., quantum dots, are disclosed. In one example approach, a method for quantifying cellular activity in a sample containing intact cells having labeled complexes comprises receiving images of the sample at a plurality of depths and detecting individual intact cells in the images of the sample at the plurality of depths. For each detected cell, discrete labels may be detected and localized in the cell at each depth, a total number of detected and localized labels may be calculated in the cell, and an activity level of the target molecule for the labeled probe in the cell determined.

Abstract: Embodiments herein provide methods, apparatuses, and systems for detecting, monitoring, measuring, and/or characterizing the activity of phosphoproteins, such as tyrosine kinases (TKs) and downstream proteins in TK signal transduction pathways (e.g., TK pathway proteins). In various embodiments, the methods, apparatuses, and systems may use nanoparticles, such as quantum dots (QD), to detect and/or characterize the abnormally overactive TK signaling pathways that underlie tumorgenesis and tumor progression. In various embodiments, the QD-based methods, apparatuses, and systems may have a sufficiently high degree of sensitivity to enable the identification of new TK signaling pathway markers, for example for use in diagnosing, staging, monitoring, and/or prognosing cancers, or in evaluating the efficacy of cancer therapeutics.