Light-sheet Microscopy Imaging Research Articles

Clearing-enabled light sheet microscopy as a novel method for three-dimensional mapping of the sensory innervation of the mouse knee.

A major barrier that hampers our understanding of the precise anatomic distribution of pain sensing nerves in and around the joint is the limited view obtained from traditional two dimensional (D) histological approaches. Therefore, our objective was to develop a workflow that allows examination of the innervation of the intact mouse knee joint in 3D by employing clearing-enabled light sheet microscopy. We first surveyed existing clearing protocols (SUMIC, PEGASOS, and DISCO) to determine their ability to clear the whole mouse knee joint, and discovered that a DISCO protocol provided the optimal transparency for light sheet microscopy imaging. We then modified the DISCO protocol to enhance binding and penetration of antibodies used for labeling nerves. Using the pan-neuronal PGP9.5 antibody, our protocol allowed 3D visualization of innervation in and around the mouse knee joint. We then implemented the workflow in mice intra-articularly injected with nerve growth factor (NGF) to determine whether changes in the nerve density can be observed. Both 3D and 2D analytical approaches of the light sheet microscopy images demonstrated quantifiable changes in midjoint nerve density following 4 weeks of NGF injection in the medial but not in the lateral joint compartment. We provide, for the first time, a comprehensive workflow that allows detailed and quantifiable examination of mouse knee joint innervation in 3D.

Automated analysis of scattering-based light sheet microscopy images of anal squamous intraepithelial lesions.

We developed an algorithm for automatically analyzing scattering-based light sheet microscopy (sLSM) images of anal squamous intraepithelial lesions. We developed a method for automatically segmenting sLSM images for nuclei and calculating seven features: nuclear intensity, intensity slope as a function of depth, nuclear-to-nuclear distance, nuclear-to-cytoplasm ratio, cell density, nuclear area, and proportion of pixels corresponding to nuclei. 187 images from 80 anal biopsies were used for feature analysis and classifier development. The automated nuclear segmentation method provided reliable performance with the precision of 0.97 and recall of 0.91 when compared with the manual segmentation. Among the seven features, six showed statistically significant differences between high-grade squamous intraepithelial lesion (HSIL) and non-HSIL (non-dysplastic or low-grade squamous intraepithelial lesion, LSIL). A classifier using linear support vector machine (SVM) achieved promising performance in diagnosing HSIL versus non-HSIL: sensitivity of 90%, specificity of 70%, and area under the curve (AUC) of 0.89 for per-image diagnosis, and sensitivity of 90%, specificity of 80%, and AUC of 0.92 for per-biopsy diagnosis.

Light Sheet Microscopy Imaging and Mounting Strategies for Early Zebrafish Embryos.

Light sheet microscopy has become the methodology of choice for live imaging of zebrafish embryos over long time scales with minimal phototoxicity. In particular, a multiview system, which allows sample rotation, enables imaging of entire embryos from different angles. However, in most imaging sessions with a multiview system, sample mounting is a troublesome process as samples are usually prepared in a polymer tube. To aid in this process, this protocol describes basic mounting strategies for imaging early zebrafish development between the 70% epiboly and early somite stages. Specifically, the study provides statistics on the various positions the embryos default to at the 70% epiboly and bud stages within the chorion. Furthermore, it discusses the optimum number of angles and the interval between angles required for imaging whole zebrafish embryos at the early stages of development so that cellular-scale information can be extracted by fusing the different views. Finally, since the embryo covers the entire field of view of the camera, which is required to obtain a cellular-scale resolution, this protocol details the process of using bead information from above or below the embryo for the registration of the different views.

Clearing-enabled light sheet microscopy as a novel method for three-dimensional mapping of the sensory innervation of the mouse knee.

A major barrier that hampers our understanding of the precise anatomic distribution of pain sensing nerves in and around the joint is the limited view obtained from traditional two dimensional (D) histological approaches. Therefore, our objective was to develop a workflow that allows examination of the innervation of the intact mouse knee joint in 3D by employing clearing-enabled light sheet microscopy. We first surveyed existing clearing protocols (SUMIC, PEGASOS, and DISCO) to determine their ability to clear the whole mouse knee joint, and discovered that a DISCO protocol provided the most optimal transparency for light sheet microscopy imaging. We then modified the DISCO protocol to enhance binding and penetration of antibodies used for labeling nerves. Using the pan-neuronal PGP9.5 antibody, our protocol allowed 3D visualization of innervation in and around the mouse knee joint. We then implemented the workflow in mice intra-articularly injected with nerve growth factor (NGF) to determine whether changes in the nerve density can be observed. Both 3D and 2D analytical approaches of the light sheet microscopy images demonstrated quantifiable changes in midjoint nerve density following 4 weeks of NGF injection in the medial but not in the lateral joint compartment. We provide, for the first time, a comprehensive workflow that allows detailed and quantifiable examination of mouse knee joint innervation in 3D.

Ultra high frequency ultrasound enables real-time visualization of blood supply from chorioallantoic membrane to human autosomal dominant polycystic kidney tissue

Ultra high frequency (UHF) ultrasound enables the visualization of very small structures that cannot be detected by conventional ultrasound. The utilization of UHF imaging as a new imaging technique for the 3D-in-vivo chorioallantoic membrane (CAM) model can facilitate new insights into tissue perfusion and survival. Therefore, human renal cystic tissue was grafted onto the CAM and examined using UHF ultrasound imaging. Due to the unprecedented resolution of UHF ultrasound, it was possible to visualize microvessels, their development, and the formation of anastomoses. This enabled the observation of anastomoses between human and chicken vessels only 12 h after transplantation. These observations were validated by 3D reconstructions from a light sheet microscopy image stack, indocyanine green angiography, and histological analysis. Contrary to the assumption that the nutrient supply of the human cystic tissue and the gas exchange happens through diffusion from CAM vessels, this study shows that the vasculature of the human cystic tissue is directly connected to the blood vessels of the CAM and perfusion is established within a short period. Therefore, this in-vivo model combined with UHF imaging appears to be the ideal platform for studying the effects of intravenously applied therapeutics to inhibit renal cyst growth.

Abstract 1069: Novel Approaches Dissecting Human Thrombus Composition

Introduction: Thrombus formation is a key contributor to ischemic stroke and cardiovascular diseases. Variations in thrombus composition involving platelets, fibrin, and leukocytes play a pivotal role in the pathophysiology, impacting clinical outcomes. Understanding its character and the interplay with Neutrophil Extracellular Traps (NETs) is clinically vital due to treatment response and outcome. This study introduces light-sheet microscopy and holotomography to dissect clot composition, aiming to enhance clinical insights into thrombosis. Unraveling these complexities holds promise for targeted interventions and improved patient outcomes. Aims: This study aimed to enhance our understanding of human blood thrombus composition by employing a novel approach using light-sheet microscopy and holotomography. Methods: Human thrombus samples were obtained by mechanical thrombectomy from acute ischemic stroke patients. To access the thrombus structure, the samples were cleared by a tissue-clearing rapid system, and light-sheet microscope imaging was obtained with CitH3, CD45, P-selectin, and fibrin. Holotomography images were obtained from cryosectioned thrombus at 5μm thickness and stained with DAPI and CitH3. Holotomography provided quantitative information on the refractive index of thrombus components. Comparative analysis with traditional imaging methods was performed to assess the advantages of the novel approaches. Results: The results revealed a comprehensive visualization of the spatial arrangement of human thrombus composition through light-sheet microscopy imaging. Holotomography successfully acquired a three-dimensional image of a thrombus section sample. HT images were used to qualitatively distinguish differences in neutrophil RI distribution by NETosis and differences in RI values within the immune cell population. Conclusion: This study demonstrates the efficacy of combining light sheet microscopy and holotomography to comprehensively dissect human thrombus composition. The integration of these advanced imaging techniques provides an understanding of thrombosis, surpassing the limitations of traditional methods.

Scattering-Based Light-Sheet Microscopy Imaging of Human Papillomavirus–Associated Squamous Lesions of the Anal Canal: A Proof-of-Principle Study

Demand for anal cancer screening is expected to rise following the recent publication of the Anal Cancer–HSIL Outcomes Research trial, which showed that treatment of high-grade squamous intraepithelial lesions significantly reduces the rate of progression to anal cancer. While screening for human papillomavirus–associated squamous lesions in the cervix is well established and effective, this is less true for other sites in the lower anogenital tract. Current anal cancer screening and prevention rely on high-resolution anoscopy with biopsies. This procedure has a steep learning curve for providers and may cause patient discomfort. Scattering-based light-sheet microscopy (sLSM) is a novel imaging modality with the potential to mitigate these challenges through real-time, microscopic visualization of disease-susceptible tissue. Here, we report a proof-of-principle study that establishes feasibility of dysplasia detection using an sLSM device. We imaged 110 anal biopsy specimens collected prospectively at our institution’s dysplasia clinic (including 30 nondysplastic, 40 low-grade squamous intraepithelial lesion, and 40 high-grade squamous intraepithelial lesion specimens) and found that these optical images are highly interpretable and accurately recapitulate histopathologic features traditionally used for the diagnosis of human papillomavirus–associated squamous dysplasia. A reader study to assess diagnostic accuracy suggests that sLSM images are noninferior to hematoxylin and eosin images for the detection of anal dysplasia (sLSM accuracy = 0.87; hematoxylin and eosin accuracy = 0.80; P = .066). Given these results, we believe that sLSM technology holds great potential to enhance the efficacy of anal cancer screening by allowing accurate sampling of diagnostic tissue at the time of anoscopy. While the current imaging study was performed on ex vivo biopsy specimens, we are currently developing a handheld device for in vivo imaging that will provide immediate microscopic guidance to high-resolution anoscopy providers.

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images.

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By changing the cross-entropy weights and using augmentation, we demonstrate a generally improved adjusted F1-score over using the originally trained TrailMap model within our test datasets.

Second Wave, Late-Stage Neuroinflammation in Cleared Brains of Aged 5xFAD Alzheimer’s Mice Detected by Macrolaser Light Sheet Microscopy Imaging

This study leverages the innovative imaging capabilities of macrolaser light-sheet microscopy to elucidate the 3D spatial visualization of AD-associated neuropathologic networks in the transparent brains of 44-week-old 5xFAD mice. Brain samples from ten AD and seven control mice were prepared through a hydrophilic tissue-clearing pipeline and immunostained with thioflavin S (β-amyloid), anti-CD11b antibody (microglia), and anti-ACSA-2 antibody (astrocytes). The 5xFAD group exhibited significantly higher average total surface volumes of β-amyloid accumulation than the control group (AD, 898,634,368 µm3 [383,355,488–1,324,986,752]; control, 33,320,178 µm3 [11,156,785–65,390,988], p = 0.0006). Within the AD group, there was significant interindividual and interindividual variability concerning the number and surface volume of individual amyloid particles throughout the entire brain. In the context of neuroinflammation, the 5xFAD group showed significantly higher average total surface volumes of anti-ACSA-2-labeled astrocytes (AD, 59,064,360 µm3 [27,815,500–222,619,280]; control, 20,272,722 µm3 [9,317,288–27,223,352], p = 0.0047) and anti-CD11b labeled microglia (AD, 51,210,100 µm3 [15,309,118–135,532,144]; control, 23,461,593 µm3 [14,499,170–27,924,110], p = 0.0162) than the control group. Contrary to the long-standing finding that early-stage neuroinflammation precedes the subsequent later-stage of neurodegeneration, our data reveal that the second wave, late-stage active neuroinflammation persists in the aged AD brains, even as they continue to show signs of ongoing neurodegeneration and significant amyloid accumulation.

Cell fragmentation in mouse preimplantation embryos induced by ectopic activation of the polar body extrusion pathway

Cell fragmentation is commonly observed in human preimplantation embryos and is associated with poor prognosis during assisted reproductive technology (ART) procedures. However, the mechanisms leading to cell fragmentation remain largely unknown. Here, light sheet microscopy imaging of mouse embryos reveals that inefficient chromosome separation due to spindle defects, caused by dysfunctional molecular motors Myo1c or dynein, leads to fragmentation during mitosis. Extended exposure of the cell cortex to chromosomes locally triggers actomyosin contractility and pinches off cell fragments. This process is reminiscent of meiosis, during which small GTPase‐mediated signals from chromosomes coordinate polar body extrusion (PBE) by actomyosin contraction. By interfering with the signals driving PBE, we find that this meiotic signaling pathway remains active during cleavage stages and is both required and sufficient to trigger fragmentation. Together, we find that fragmentation happens in mitosis after ectopic activation of actomyosin contractility by signals emanating from DNA, similar to those observed during meiosis. Our study uncovers the mechanisms underlying fragmentation in preimplantation embryos and, more generally, offers insight into the regulation of mitosis during the maternal‐zygotic transition.

Automated contour extraction for light-sheet microscopy images of zebrafish embryos based on object edge detection algorithm.

Embryo contour extraction is the initial step in the quantitative analysis of embryo morphology, and it is essential for understanding the developmental process. Recent developments in light-sheet microscopy have enabled the in toto time-lapse imaging of embryos, including zebrafish. However, embryo contour extraction from images generated via light-sheet microscopy is challenging owing to the large amount of data and the variable sizes, shapes, and textures of objects. In this report, we provide a workflow for extracting the contours of zebrafish blastula and gastrula without contour labeling of an embryo. This workflow is based on the edge detection method using a change point detection approach. We assessed the performance of the edge detection method and compared it with widely used edge detection and segmentation methods. The results showed that the edge detection accuracy of the proposed method wassuperior to those of the Sobel, Laplacian of Gaussian, adaptive threshold, Multi Otsu, and k-means clustering-based methods, and the noise robustness of the proposed method was superior to those of the Multi Otsu and k-means clustering-based methods. The proposed workflow was shown to be useful for automating small-scale contour extractions of zebrafish embryos that cannot be specifically labeled owing to constraints, such as the availability of microscopic channels. This workflow may offer an option for contour extraction when deep learning-based approaches or existing non-deep learning-based methods cannot be applied.

Restoring morphology of light sheet microscopy data based on magnetic resonance histology.

The combination of cellular-resolution whole brain light sheet microscopy (LSM) images with an annotated atlas enables quantitation of cellular features in specific brain regions. However, most existing methods register LSM data with existing canonical atlases, e.g., The Allen Brain Atlas (ABA), which have been generated from tissue that has been distorted by removal from the skull, fixation and physical handling. This limits the accuracy of the regional morphologic measurement. Here, we present a method to combine LSM data with magnetic resonance histology (MRH) of the same specimen to restore the morphology of the LSM images to the in-skull geometry. Our registration pipeline which maps 3D LSM big data (terabyte per dataset) to MRH of the same mouse brain provides registration with low displacement error in ∼10 h with limited manual input. The registration pipeline is optimized using multiple stages of transformation at multiple resolution scales. A three-step procedure including pointset initialization, automated ANTs registration with multiple optimized transformation stages, and finalized application of the transforms on high-resolution LSM data has been integrated into a simple, structured, and robust workflow. Excellent agreement has been seen between registered LSM data and reference MRH data both locally and globally. This workflow has been applied to a collection of datasets with varied combinations of MRH contrasts from diffusion tensor images and LSM with varied immunohistochemistry, providing a routine method for streamlined registration of LSM images to MRH. Lastly, the method maps a reduced set of the common coordinate framework (CCFv3) labels from the Allen Brain Atlas onto the geometrically corrected full resolution LSM data. The pipeline maintains the individual brain morphology and allows more accurate regional annotations and measurements of volumes and cell density.

Characterization of microparticles of iron oxide for magnetic resonance imaging

Microparticles of iron oxide (MPIOs) are increasingly used for contrast generation in magnetic resonance imaging (MRI). In particular, Dynabeads® MyOne™ Tosylactivated MPIOs have enabled sensitive and targeted molecular imaging, e.g., to detect vascular inflammation. For the first time we measured the relaxivities as well as the molar susceptibility χM of these MPIOs at 7 T in agarose gels. They are r1 = 0.69 ± 0.03 s−1/mM, r2 = 220 ± 6 s−1/mM, r2* = 679 ± 14 s−1/mM, and χM = 0.66 ± 0.05 ppm/mM, when expressed with respect to the iron concentration. These material parameters are essential to optimize MRI protocols and progress toward quantitative imaging. To address the heterogeneous nature of the MPIO distributions over the size of a typical MRI voxel, we coupled the MPIOs to a fluorophore to create a bimodal phantom that can be imaged by both Light Sheet microscopy and MRI. In this phantom, the MPIOs produced contrast similar to that found in vivo . The submicron resolution of Light Sheet microscopy images provided a precise measurement of the MPIO spatial distribution in phantoms also imaged by MRI. MPIO aggregates occupying less than one MRI voxel were responsible for alterations in R2* and magnetic susceptibility χ across several MRI voxels. In these cases, the sum of R2* or χ over the affected MRI volume correlated better with the microscopically determined number of MPIOs. These findings were confirmed with simulations performed in the static dephasing regime. The microscopically determined MPIO distribution was also entered directly into the simulation framework, indicating that the bimodal phantom is a useful tool to test theoretical models against experimental measurements.

GIANI - open-source software for automated analysis of 3D microscopy images.

ABSTRACTThe study of cellular and developmental processes in physiologically relevant three-dimensional (3D) systems facilitates an understanding of mechanisms underlying cell fate, disease and injury. While cutting-edge microscopy technologies permit the routine acquisition of 3D datasets, there is currently a limited number of open-source software packages to analyse such images. Here, we describe General Image Analysis of Nuclei-based Images (GIANI; https://djpbarry.github.io/Giani), new software for the analysis of 3D images. The design primarily facilitates segmentation of nuclei and cells, followed by quantification of morphology and protein expression. GIANI enables routine and reproducible batch-processing of large numbers of images, and comes with scripting and command line tools. We demonstrate the utility of GIANI by quantifying cell morphology and protein expression in confocal images of mouse early embryos and by segmenting nuclei from light-sheet microscopy images of the flour beetle embryo. We also validate the performance of the software using simulated data. More generally, we anticipate that GIANI will be a useful tool for researchers in a variety of biomedical fields.

Distinct spatial arrangements of ACE2 and TMPRSS2 expression in Syrian hamster lung lobes dictates SARS-CoV-2 infection patterns.

SARS-CoV-2 attaches to angiotensin-converting enzyme 2 (ACE2) to gain entry into cells after which the spike protein is cleaved by the transmembrane serine protease 2 (TMPRSS2) to facilitate viral-host membrane fusion. ACE2 and TMPRSS2 expression profiles have been analyzed at the genomic, transcriptomic, and single-cell RNAseq levels. However, transcriptomic data and actual protein validation convey conflicting information regarding the distribution of the biologically relevant protein receptor in whole tissues. To describe the organ-level architecture of receptor expression, related to the ability of ACE2 and TMPRSS2 to mediate infectivity, we performed a volumetric analysis of whole Syrian hamster lung lobes. Lung tissue of infected and control animals was stained using antibodies against ACE2 and TMPRSS2, combined with SARS-CoV-2 nucleoprotein staining. This was followed by light-sheet microscopy imaging to visualize their expression and related infection patterns. The data demonstrate that infection is restricted to sites containing both ACE2 and TMPRSS2, the latter is expressed in the primary and secondary bronchi whereas ACE2 is predominantly observed in the bronchioles and alveoli. Conversely, infection completely overlaps where ACE2 and TMPRSS2 co-localize in the tertiary bronchi, bronchioles, and alveoli.

Segmentation of Tissues and Proliferating Cells in Light-Sheet Microscopy Images of Mouse Embryos Using Convolutional Neural Networks.

A variety of genetic mutations affect cell proliferation during organism development, leading to structural birth defects. However, the mechanisms by which these alterations influence the development of the face remain unclear. Cell proliferation and its relation to shape variation can be studied using Light-Sheet Microscopy (LSM) imaging across a range of developmental time points using mouse models. The aim of this work was to develop and evaluate accurate automatic methods based on convolutional neural networks (CNNs) for: (i) tissue segmentation (neural ectoderm and mesenchyme), (ii) cell segmentation in nuclear-stained images, and (iii) segmentation of proliferating cells in phospho-Histone H3 (pHH3)-stained LSM images of mouse embryos. For training and evaluation of the CNN models, 155 to 176 slices from 10 mouse embryo LSM images with corresponding manual segmentations were available depending on the segmentation task. Three U-net CNN models were trained optimizing their loss functions, among other hyper-parameters, depending on the segmentation task. The tissue segmentation achieved a macro-average F-score of 0.84, whereas the inter-observer value was 0.89. The cell segmentation achieved a Dice score of 0.57 and 0.56 for nuclear-stained and pHH3-stained images, respectively, whereas the corresponding inter-observer Dice scores were 0.39 and 0.45, respectively. The proposed pipeline using the U-net CNN architecture can accelerate LSM image analysis and together with the annotated datasets can serve as a reference for comparison of more advanced LSM image segmentation methods in future.

Segmentor: a tool for manual refinement of 3D microscopy annotations

BackgroundRecent advances in tissue clearing techniques, combined with high-speed image acquisition through light sheet microscopy, enable rapid three-dimensional (3D) imaging of biological specimens, such as whole mouse brains, in a matter of hours. Quantitative analysis of such 3D images can help us understand how changes in brain structure lead to differences in behavior or cognition, but distinguishing densely packed features of interest, such as nuclei, from background can be challenging. Recent deep learning-based nuclear segmentation algorithms show great promise for automated segmentation, but require large numbers of accurate manually labeled nuclei as training data.ResultsWe present Segmentor, an open-source tool for reliable, efficient, and user-friendly manual annotation and refinement of objects (e.g., nuclei) within 3D light sheet microscopy images. Segmentor employs a hybrid 2D-3D approach for visualizing and segmenting objects and contains features for automatic region splitting, designed specifically for streamlining the process of 3D segmentation of nuclei. We show that editing simultaneously in 2D and 3D using Segmentor significantly decreases time spent on manual annotations without affecting accuracy as compared to editing the same set of images with only 2D capabilities.ConclusionsSegmentor is a tool for increased efficiency of manual annotation and refinement of 3D objects that can be used to train deep learning segmentation algorithms, and is available at https://www.nucleininja.org/ and https://github.com/RENCI/Segmentor.

Effects of excitation light polarization on fluorescence emission in two-photon light-sheet microscopy.

Light-sheet microscopy (LSM) is a powerful imaging technique that uses a planar illumination oriented orthogonally to the detection axis. Two-photon (2P) LSM is a variant of LSM that exploits the 2P absorption effect for sample excitation. The light polarization state plays a significant, and often overlooked, role in 2P absorption processes. The scope of this work is to test whether using different polarization states for excitation light can affect the detected signal levels in 2P LSM imaging of typical biological samples with a spatially unordered dye population. Supported by a theoretical model, we compared the fluorescence signals obtained using different polarization states with various fluorophores (fluorescein, EGFP and GCaMP6s) and different samples (liquid solution and fixed or living zebrafish larvae). In all conditions, in agreement with our theoretical expectations, linear polarization oriented parallel to the detection plane provided the largest signal levels, while perpendicularly-oriented polarization gave low fluorescence signal with the biological samples, but a large signal for the fluorescein solution. Finally, circular polarization generally provided lower signal levels. These results highlight the importance of controlling the light polarization state in 2P LSM of biological samples. Furthermore, this characterization represents a useful guide to choose the best light polarization state when maximization of signal levels is needed, e.g. in high-speed 2P LSM.

N-acetylcysteine inhibits bacterial lipopeptide-mediated neutrophil transmigration through the choroid plexus in the developing brain

The etiology of neurological impairments associated with prematurity and other perinatal complications often involves an infectious or pro-inflammatory component. The use of antioxidant molecules have proved useful to protect the neonatal brain from injury. The choroid plexuses-CSF system shapes the central nervous system response to inflammation at the adult stage, but little is known on the neuroimmune interactions that take place at the choroidal blood-CSF barrier during development. We previously described that peripheral administration to neonatal mice of the TLR2 ligand PAM3CSK4 (P3C), a prototypic Gram-positive bacterial lipopeptide, induces the migration of innate immune cells to the CSF. Here we showed in neonatal rats exposed to P3C that the migration of neutrophils into the CSF, which occurred through the choroid plexuses, is abolished following administration of the antioxidant drug N-acetylcysteine. Combining light sheet microscopy imaging of choroid plexus, a differentiated model of the blood-CSF barrier, and multiplex cytokine assays, we showed that the choroidal epithelium responds to the bacterial insult by a specific pattern of cytokine secretion, leading to a selective accumulation of neutrophils in the choroid plexus and to their trafficking into CSF. N-acetylcysteine acted by blocking neutrophil migration across both the endothelium of choroidal stromal vessels and the epithelium forming the blood-CSF barrier, without interfering with neutrophil blood count, neutrophil tropism for choroid plexus, and choroidal chemokine-driven chemotaxis. N-acetylcysteine reduced the injury induced by hypoxia-ischemia in P3C-sensitized neonatal rats. Overall, the data show that a double endothelial and epithelial check point controls the transchoroidal migration of neutrophils into the developing brain. They also point to the efficacy of N-acetylcysteine in reducing the deleterious effects of inflammation-associated perinatal injuries by a previously undescribed mechanism, i.e. the inhibition of innate immune cell migration across the choroid plexuses, without interfering with the systemic inflammatory response to infection.

Large Scale Simulations of Cell Resolved Tissue by a Cellular Potts Model

Multicellular organisms all face the same fundamental challenge during tissue development: the generation of distinct cell types, structures and organs at specific positions in the body. Advanced imaging techniques provide detailed insight into processes on a single-cell and sub-cell level. Still, a thorough mathematical model of cellular dynamics and differentiation has not been identified. Cellular Potts models are a commonly used tool to describe the cellular behavior. Due to the large computational effort the scale of those simulations has so far been very limited to small and mostly two-dimensional simulation setups. Here, we developed a framework with a fully parallelized implementation of the cellular Potts model, enabling simulations orders of magnitude larger than possible to date and improvements on spatial isotropy. Through parallelization our framework is able to run effectively on large cluster architectures making the simulation of up to 109 individually resolved cells possible. We present our simulations of tumorigenesis and tumor internal signaling with explicit modeling of the surrounding tissue. Benchmarking with experimental data, such as light sheet microscopy images, becomes possible as the simulated areas reach experimentally relevant sizes. Therefore, our framework is a promising tool to study tissue development, effects of medication, formation of metastasis and other tissue internal processes to identify underlying base principles.