Probing Entanglement with Holography

Quantum entanglement is one of the biggest mysteries in physics. In gauge field theories, the amount of entanglement can be measured with certain quantities. For an entangled system, there are correlations with these measured quantities in both time and spatial coordinates that do not fit into the understanding we currently hold about the locality of the measures and correlations. Difficulties in obtaining probes for entanglement in gauge theories arise from the problem of nonlocality. It can be stated as the problem of decomposing the space of the physical states into different regions. In this thesis, we focus on a particular supersymmetric Yang-Mills theory that is holographically dual to a classical gravity theory in an asymptotically anti de Sitter spacetime. We introduce the most important holographic probes of entanglement and discuss the inequalities obtained from the dual formulation of the entanglement entropy. We introduce the subregion duality as an interesting conjecture of holography that remains under research. The understanding of the subregion duality is not necessarily solid in arbitrary geometries, as new results that suggest either a violation of the subregion duality or act against our common knowledge of the holography by reconstructing the bulk metric beyond the entanglement wedge. This thesis will investigate this aspect of subregion duality by evaluating the bulk probes such as Wilson loop for two different geometries (deconfining and confining). We aim to find whether or not these probes remain inside of the entanglement wedge. We find that, for both geometries in four dimensions, the subregion duality is not violated. In other words, the reduced CFT state does not encode information about the bulk beyond the entanglement wedge. However, we can not assume this is the case with arbitrary geometries and therefore, this topic will remain under our interest for future research

ShapeMetrics: a userfriendly pipeline for 3D cell segmentation and spatial tissue analysis

The demand for single-cell level data is constantly increasing within life sciences. In order to meet this demand, robust cell segmentation methods that can tackle challenging in vivo tissues with complex morphology are required. However, currently available cell segmentation and volumetric analysis methods perform poorly on 3D images. Here, we generated ShapeMetrics, a MATLAB-based script that segments cells in 3D and, by performing unbiased clustering using a heatmap, separates the cells into subgroups according to their volumetric and morphological differences. The cells can be accurately segregated according to different biologically meaningful features such as cell ellipticity, longest axis, cell elongation, or the ratio between cell volume and surface area. Our machine learning based script enables dissection of a large amount of novel data from microscope images in addition to the traditional information based on fluorescent biomarkers. Furthermore, the cells in different subgroups can be spatially mapped back to their original locations in the tissue image to help elucidate their roles in their respective morphological contexts. In order to facilitate the transition from bulk analysis to single-cell level accuracy, we emphasize the user-friendliness of our method by providing detailed step-by-step instructions through the pipeline hence aiming to reach users with less experience in computational biology.Peer reviewe

Three-dimensional imaging for the quantification of spatial patterns in microbiota of the intestinal mucosa

Improving our understanding of host-microbe relationships in the gut requires the ability to both visualize and quantify the spatial organization of microbial communities in their native orientation with the host tissue. We developed a systematic procedure to quantify the three-dimensional (3D) spatial structure of the native mucosal microbiota in any part of the intestines with taxonomic and high spatial resolution. We performed a 3D biogeographical analysis of the microbiota of mouse cecal crypts at different stages of antibiotic exposure. By tracking eubacteria and four dominant bacterial taxa, we found that the colonization of crypts by native bacteria is a dynamic and spatially organized process. Ciprofloxacin treatment drastically reduced bacterial loads and eliminated Muribaculaceae (or all Bacteroidetes entirely) even 10 d after recovery when overall bacterial loads returned to preantibiotic levels. Our 3D quantitative imaging approach revealed that the bacterial colonization of crypts is organized in a spatial pattern that consists of clusters of adjacent colonized crypts that are surrounded by unoccupied crypts, and that this spatial pattern is resistant to the elimination of Muribaculaceae or of all Bacteroidetes by ciprofloxacin. Our approach also revealed that the composition of cecal crypt communities is diverse and that Lactobacilli were found closer to the lumen than Bacteroidetes, Ruminococcaceae, and Lachnospiraceae, regardless of antibiotic exposure. Finally, we found that crypts communities with similar taxonomic composition were physically closer to each other than communities that were taxonomically different.Peer reviewe

3D Imaging for the Quantification of Spatial Patterns in Microbiota of the Intestinal Mucosa

Please scroll down to see download links. Data and scripts for "3D Imaging for the Quantification of Spatial Patterns in Microbiota of the Intestinal Mucosa" submitted as a preprint to bioRxiv and accepted to PNAS (doi pending). Contents (see also DataList document in download): ****Confocal imaging of bacteria, mucus and murine epithelium in the proximal colon of a specific-pathogen free mouse (Fig. 3A-F) Raw multi-color confocal imaging of bacteria embedded in mucus over folds in the epithelium of the proximal colon. ****Multiplexed, spectral confocal imaging of bacterial communities in the cecal crypts of a specific-pathogen free mouse (Fig. 5C-Q) Raw spectral imaging Linear unmixing of spectral imaging Processing and analysis of unmixed spectral imaging in arivis Vision4D 3.0 ****Raw spectral confocal imaging of cecum Spectral confocal imaging of cecum after linear unmixing Confocal imaging of cecum after linear unmixing, and processed in arivis Vision4D 3.0 ****Spectral and standard confocal imaging of bacterial communities in cecal crypts at different stages of antibiotic exposure: unexposed (2 mice), antibiotic (3 mice), and recovery (3 mice). (Figs. 6-7) Raw spectral imaging Linear unmixing of spectral imaging Processing and analysis of unmixed spectral imaging in arivis Vision4D 3.0 ****Mouse unexposed to ciprofloxacin #1 Raw spectral confocal imaging of cecum Spectral confocal imaging of cecum after linear unmixing Confocal imaging of cecum after linear unmixing, and processed in arivis Vision4D 3.0 ****Mouse unexposed to ciprofloxacin #2 Raw spectral confocal imaging of cecum Spectral confocal imaging of cecum after linear unmixing Confocal imaging of cecum after linear unmixing, and processed in arivis Vision4D 3.0 ****Mouse exposed to ciprofloxacin #1 Raw spectral confocal imaging of cecum Spectral confocal imaging of cecum after linear unmixing Confocal imaging of cecum after linear unmixing, and processed in arivis Vision4D 3.0 ****Mouse exposed to ciprofloxacin #2 Standard confocal imaging of cecum Confocal imaging of cecum processed in arivis Vision4D 3.0 ****Mouse exposed to ciprofloxacin #3 Raw spectral confocal imaging of cecum Spectral confocal imaging of cecum after linear unmixing Confocal imaging of cecum after linear unmixing, and processed in arivis Vision4D 3.0 ****Mouse that recovered from ciprofloxacin for 10 days #1 Raw spectral confocal imaging of cecum Spectral confocal imaging of cecum after linear unmixing Confocal imaging of cecum after linear unmixing, and processed in arivis Vision4D 3.0 ****Mouse that recovered from ciprofloxacin for 10 days #2 Raw spectral confocal imaging of cecum Spectral confocal imaging of cecum after linear unmixing Confocal imaging of cecum after linear unmixing, and processed in arivis Vision4D 3.0 ****Mouse that recovered from ciprofloxacin for 10 days #3 Raw spectral confocal imaging of cecum Spectral confocal imaging of cecum after linear unmixing Confocal imaging of cecum after linear unmixing, and processed in arivis Vision4D 3.0Related Publication: 3D Imaging for the Quantification of Spatial Patterns in Microbiota of the Intestinal Mucosa https://doi.org/10.1101/2021.10.07.463215 engFiles available via S3 at https://renc.osn.xsede.org/ini210004tommorrell/0_D1.20077/Antibiotic_01/AC1_20X_01.czi 4.98 GB Download AC1_20X_01_Linear%20unmixing.czi 0 GB Download AC1_20X_02.czi 5.04 GB Download AC1_20X_02_Linear%20unmixing.czi 0 GB Download AC1_20X_03.czi 5.6 GB Download AC1_20X_03_Linear%20unmixing.czi 0 GB Download AC1_20X_04.czi 5.63 GB Download AC1_20X_04_Linear%20unmixing.czi 0 GB Download AC1_20X_05.czi 6.13 GB Download AC1_20X_05_Linear%20unmixing.czi 0 GB Download AC1_20X_06.czi 6.12 GB Download AC1_20X_06_Linear%20unmixing.czi 0 GB Download AC1_20X_07.czi 6.45 GB Download AC1_20X_07_Linear%20unmixing.czi 0 GB Download AC1_20X_08.czi 5.16 GB Download AC1_20X_08_Linear%20unmixing.czi 0 GB Download AC1_20X_09.czi 4.98 GB Download AC1_20X_09_Linear%20unmixing.czi 0 GB Download AC1_20X_10_Linear%20unmixing.czi 0 GB Download AC1_vision4D.zip 4.99 GB Download AC2_20X_01.czi 0.25 GB Download AC2_20X_02.czi 0.18 GB Download AC2_20X_03.czi 0.24 GB Download AC2_20X_04.czi 0.3 GB Download AC2_20X_05.czi 0.41 GB Download AC2_20X_06.czi 0.29 GB Download AC2_20X_07.czi 0.4 GB Download AC2_20X_08.czi 0.24 GB Download AC2_20X_09.czi 0.31 GB Download AC2_20X_10.czi 0.28 GB Download AC2_vision4D.zip 2.11 GB Download AC3_20X_01.czi 5.29 GB Download AC3_20X_01_Linear%20unmixing.czi 0 GB Download AC3_20X_02.czi 6.09 GB Download AC3_20X_02_Linear%20unmixing.czi 0 GB Download AC3_20X_03.czi 5.21 GB Download AC3_20X_03_Linear%20unmixing.czi 0 GB Download AC3_20X_04.czi 5.85 GB Download AC3_20X_04_Linear%20unmixing.czi 0 GB Download AC3_20X_05_Linear%20unmixing.czi 0 GB Download AC3_20X_06.czi 3.74 GB Download AC3_20X_06_Linear%20unmixing.czi 0 GB Download AC3_vision4D.zip 5.0 GB Download S7_PT3_01.czi 6.18 GB Download S7_PT3_01_Linear%20unmixing.czi 0 GB Download S7_PT3_01_vision4D.zip 0.83 GB Download S7_PT3_02.czi 5.62 GB Download S7_PT3_02_Linear%20unmixing.czi 0 GB Download S7_PT3_02_vision4D.zip 1.0 GB Download S7_PT3_03.czi 5.62 GB Download S7_PT3_03_Linear%20unmixing.czi 0 GB Download S7_PT3_03_vision4D.zip 0.73 GB Download S14_01.czi 0.6 GB Download S14_02.czi 0.74 GB Download S14_03.czi 0.55 GB Download S14_04.czi 0.82 GB Download RC1_20X_01.czi 6.45 GB Download RC1_20X_01_Linear%20unmixing.czi 0 GB Download RC1_20X_02.czi 5.27 GB Download RC1_20X_02_Linear%20unmixing.czi 0 GB Download RC1_20X_03.czi 6.01 GB Download RC1_20X_03_Linear%20unmixing.czi 0 GB Download RC1_20X_04.czi 6.7 GB Download RC1_20X_04_Linear%20unmixing.czi 0 GB Download RC1_20X_05.czi 5.84 GB Download RC1_20X_05_Linear%20unmixing.czi 0 GB Download RC1_20X_06.czi 8.68 GB Download RC1_20X_06_Linear%20unmixing.czi 0 GB Download RC1_20X_07.czi 6.93 GB Download RC1_20X_07_Linear%20unmixing.czi 0 GB Download RC1_20X_08.czi 5.87 GB Download RC1_20X_08_Linear%20unmixing.czi 0 GB Download RC1_20X_09.czi 5.7 GB Download RC1_20X_09_Linear%20unmixing.czi 0 GB Download RC1_20X_10.czi 4.93 GB Download RC1_20X_10_Linear%20unmixing.czi 0 GB Download RC1_20X_12.czi 5.87 GB Download RC1_20X_12_Linear%20unmixing.czi 0 GB Download RC1_20X_13.czi 4.79 GB Download RC1_20X_13_Linear%20unmixing.czi 0 GB Download RC1_20X_14.czi 6.85 GB Download RC1_20X_14_Linear%20unmixing.czi 0 GB Download RC1_20X_15.czi 4.41 GB Download RC1_20X_15_Linear%20unmixing.czi 0 GB Download RC1_20X_16.czi 5.23 GB Download RC1_20X_16_Linear%20unmixing.czi 0 GB Download RC1_20X_17.czi 5.38 GB Download RC1_20X_17_Linear%20unmixing.czi 0 GB Download RC1_vision4D.zip 14.72 GB Download RC2_20X_01.czi 4.4 GB Download RC2_20X_01_Linear%20unmixing.czi 0 GB Download RC2_20X_02.czi 4.69 GB Download RC2_20X_02_Linear%20unmixing.czi 0 GB Download RC2_20X_03.czi 6.07 GB Download RC2_20X_03_Linear%20unmixing.czi 0 GB Download RC2_20X_04.czi 4.04 GB Download RC2_20X_04_Linear%20unmixing.czi 0 GB Download RC2_20X_05.czi 4.35 GB Download RC2_20X_05_Linear%20unmixing.czi 0 GB Download RC2_20X_06.czi 5.76 GB Download RC2_20X_06_Linear%20unmixing.czi 0 GB Download RC2_20X_07.czi 5.43 GB Download RC2_20X_07_Linear%20unmixing.czi 0 GB Download RC2_20X_08.czi 5.37 GB Download RC2_20X_08_Linear%20unmixing.czi 0 GB Download RC2_20X_09.czi 4.79 GB Download RC2_20X_09_Linear%20unmixing.czi 0 GB Download RC2_20X_10.czi 4.68 GB Download RC2_20X_10_Linear%20unmixing.czi 0 GB Download RC2_20X_11.czi 5.1 GB Download RC2_20X_11_Linear%20unmixing.czi 0 GB Download RC2_20X_12.czi 5.41 GB Download RC2_20X_12_Linear%20unmixing.czi 0 GB Download RC2_20X_13.czi 4.79 GB Download RC2_20X_13_Linear%20unmixing.czi 0 GB Download RC2_20X_14.czi 3.74 GB Download RC2_20X_14_Linear%20unmixing.czi 0 GB Download RC2_20X_15.czi 5.63 GB Download RC2_20X_15_Linear%20unmixing.czi 0 GB Download RC2_20X_16.czi 5.9 GB Download RC2_20X_16_Linear%20unmixing.czi 0 GB Download RC2_20X_17.czi 4.79 GB Download RC2_20X_17_Linear%20unmixing.czi 0 GB Download RC2_vision4D.zip 13.89 GB Download RC3_20X_02.czi 4.07 GB Download 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RC3_20X_15.czi 5.4 GB Download RC3_20X_15_Linear%20unmixing.czi 0 GB Download RC3_20X_16.czi 6.57 GB Download RC3_20X_16_Linear%20unmixing.czi 0 GB Download RC3_vision4D.zip 14.12 GB Download CM1_20X_01.czi 6.1 GB Download CM1_20X_01_Linear%20unmixing.czi 0 GB Download CM1_20X_02.czi 4.63 GB Download CM1_20X_02_Linear%20unmixing.czi 0 GB Download CM1_20X_03_Linear%20unmixing.czi 0 GB Download CM1_20X_04_Linear%20unmixing.czi 0 GB Download CM1_20X_05.czi 6.74 GB Download CM1_20X_05_Linear%20unmixing.czi 0 GB Download CM1_20X_06.czi 5.55 GB Download CM1_20X_06_Linear%20unmixing.czi 0 GB Download CM1_20X_07.czi 6.45 GB Download CM1_20X_07_Linear%20unmixing.czi 0 GB Download CM1_20X_08.czi 5.35 GB Download CM1_20X_08_Linear%20unmixing.czi 0 GB Download CM1_20X_09.czi 5.76 GB Download CM1_20X_09_Linear%20unmixing.czi 0 GB Download CM1_20X_10.czi 5.19 GB Download CM1_20X_10_Linear%20unmixing.czi 0 GB Download CM1_20X_11.czi 5.65 GB Download CM1_20X_11_Linear%20unmixing.czi 0 GB Download CM1_20X_12.czi 6.24 GB Download CM1_20X_12_Linear%20unmixing.czi 0 GB Download CM1_20X_13.czi 4.57 GB Download CM1_20X_13_Linear%20unmixing.czi 0 GB Download CM1_20X_14.czi 5.77 GB Download CM1_20X_14_Linear%20unmixing.czi 0 GB Download CM1_20X_15.czi 6.85 GB Download CM1_20X_15_Linear%20unmixing.czi 0 GB Download CM1_20X_3-4.czi 9.42 GB Download CM2_20X_01.czi 5.3 GB Download CM2_20X_01_Linear%20unmixing.czi 0 GB Download CM2_20X_02.czi 6.07 GB Download CM2_20X_02_Linear%20unmixing.czi 0 GB Download CM2_20X_03.czi 5.96 GB Download CM2_20X_03_Linear%20unmixing.czi 0 GB Download CM2_20X_04.czi 5.96 GB Download CM2_20X_04_Linear%20unmixing.czi 0 GB Download CM2_20X_05.czi 4.47 GB Download CM2_20X_05_Linear%20unmixing.czi 0 GB Download CM2_20X_06.czi 4.6 GB Download CM2_20X_06_Linear%20unmixing.czi 0 GB Download CM2_20X_07.czi 4.02 GB Download CM2_20X_07_Linear%20unmixing.czi 0 GB Download CM2_20X_08.czi 4.16 GB Download CM2_20X_08_Linear%20unmixing.czi 0 GB Download CM2_20X_09.czi 4.44 GB Download CM2_20X_09_Linear%20unmixing.czi 0 GB Download CM2_20X_10.czi 5.19 GB Download CM2_20X_10_Linear%20unmixing.czi 0 GB Download CM2_20X_11.czi 4.63 GB Download CM2_20X_11_Linear%20unmixing.czi 0 GB Download CM2_20X_12.czi 3.54 GB Download CM2_20X_12_Linear%20unmixing.czi 0 GB Download CM2_20X_13.czi 4.8 GB Download CM2_20X_13_Linear%20unmixing.czi 0 GB Download CM2_20X_14.czi 3.82 GB Download CM2_20X_14_Linear%20unmixing.czi 0 GB Download CM2_20X_15.czi 4.22 GB Download CM2_20X_15_Linear%20unmixing.czi 0 GB Download CM2_20X_16.czi 5.3 GB Download CM2_20X_16_Linear%20unmixing.czi 0 GB Download CM2_20X_17.czi 5.05 GB Download CM2_20X_17_Linear%20unmixing.czi 0 GB Download CM2_20X_18.czi 4.85 GB Download CM2_20X_18_Linear%20unmixing.czi 0 GB Download CM2_vision4D.zip 13.78 GB Downloa

Quantitative whole-tissue 3D imaging reveals bacteria in close association with mouse jejunum mucosa

Raw and processed data and imaging files [0.42 TB total] for the bioRxiv preprint "Quantitative whole-tissue 3D imaging reveals bacteria in close association with mouse jejunum mucosa"Related Publication: Quantitative whole-tissue 3D imaging reveals bacteria in close association with mouse jejunum mucosa bioRxiv engFiles available via S3 at https://renc.osn.xsede.org/ini210004tommorrell/0_D1.20199/DataSummary.xlsx 0.0 GB Download Fig01-DataAnalysis-GrowthCurves.zip 0.0 GB Download Fig01-DataAnalysis-RTqPCR.zip 0.0 GB Download Fig02-DataAnalysis.zip 0.0 GB Download Fig03-DataAnalysis.zip 0.27 GB Download Fig04-Fig06-DataAnalysis.zip 0.07 GB Download FigS07-DataAnalysis.zip 0.29 GB Download FigS08-DataAnalysis.zip 0.64 GB Download FigS09-DataAnalysis.zip 0.23 GB Download FigS11-DataAnalysis.zip 0.0 GB Download R4P-p091-20xC-ImarisSurfaceFiles.zip 0.0 GB Download R4P-p091-D28C3M1-EJ-5x_Stitch.czi 2.69 GB Download R4P-p091-D29C2M1-EJ-5x_Stitch.czi 2.4 GB Download R4P-p091-D29C4M2-EJ-1.czi 6.81 GB Download R4P-p091-D29C4M2-EJ-1.ims 10.38 GB Download R4P-p091-D29C4M2-EJ-3.czi 4.25 GB Download R4P-p091-D29C4M2-EJ-3.ims 7.5 GB Download R4P-p091-D29C4M2-EJ-5x_Stitch.czi 1.82 GB Download R4P-p091-D31C1M1-EJ-5x_Stitch.czi 3.13 GB Download R4P-p121-Bfrag-v3EC-v3BAC-20x.czi 1.43 GB Download R4P-p121-Ecoli-v3EC-v3BAC-20x.czi 1.42 GB Download R4P-p124-20xC-ImarisSurfaceFiles.zip 0.0 GB Download R4P-p124-D28C1M1-EJ-5x_Stitch.czi 0.99 GB Download R4P-p124-D28C2M1-EJ-5x_Stitch.czi 1.31 GB Download R4P-p124-D28C3M1-EJ-1.czi 4.96 GB Download R4P-p124-D28C3M1-EJ-1.ims 6.88 GB Download R4P-p124-D28C3M1-EJ-2.czi 4.8 GB Download R4P-p124-D28C3M1-EJ-2.ims 7.07 GB Download R4P-p124-D28C3M1-EJ-3.czi 3.97 GB Download R4P-p124-D28C3M1-EJ-3.ims 5.96 GB Download R4P-p124-D28C3M1-EJ-5x_Stitch.czi 1.0 GB Download R4P-p124-D28C4M1-EJ-1.czi 4.51 GB Download R4P-p124-D28C4M1-EJ-1.ims 9.0 GB Download R4P-p124-D28C4M1-EJ-2.czi 4.5 GB Download R4P-p124-D28C4M1-EJ-2.ims 6.52 GB Download 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