Stroke and myocardial infarction induce neutrophil extracellular trap release disrupting lymphoid organ structure and immunoglobulin secretion.

Post-injury dysfunction of humoral immunity accounts for infections and poor outcomes in cardiovascular diseases. Among immunoglobulins (Ig), IgA, the most abundant mucosal antibody, is produced by plasma B cells in intestinal Peyer's patches (PP) and lamina propria. Here we show that patients with stroke and myocardial ischemia (MI) had strongly reduced IgA blood levels. This was phenocopied in experimental mouse models where decreased plasma and fecal IgA were accompanied by rapid loss of IgA-producing plasma cells in PP and lamina propria. Reduced plasma IgG was detectable in patients and experimental mice 3-10 d after injury. Stroke/MI triggered the release of neutrophil extracellular traps (NETs). Depletion of neutrophils, NET degradation or blockade of NET release inhibited the loss of IgA+ cells and circulating IgA in experimental stroke and MI and in patients with stroke. Our results unveil how tissue-injury-triggered systemic NET release disrupts physiological Ig secretion and how this can be inhibited in patients.

Arterial specification precedes microvascular restitution in the peri-infarct cortex that is driven by small microvessels.

Evaluation of microvascular networks was impeded until recently by the need of histological tissue sectioning, which precluded 3D analyses. Using light-sheet microscopy, we investigated microvascular network characteristics in the peri-infarct cortex of mice 3-56 days after transient middle cerebral artery occlusion. In animal subgroups, the sphingosine-1-phosphate analog FTY720 (Fingolimod) was administered starting 24 hours post-ischemia. Light-sheet microscopy revealed a striking pattern of microvascular changes in the peri-infarct cortex, that is, a loss of microvessels, which was most prominent after 7 days and followed by the reappearance of microvessels over 56 days which revealed an increased branching point density and shortened branches. Using a novel AI-based image analysis algorithm we found that the length density of microvessels expressing the arterial specification marker α-smooth muscle actin markedly increased in the peri-infarct cortex already at 7 days post-ischemia. The length and branch density of small microvessels, but not of intermediate or large microvessels increased above pre-ischemic levels within 14-56 days. FTY720 increased the length and branch density of small microvessels. This study demonstrates long-term alterations of microvascular architecture post-ischemia indicative of increased collateralization most notably of small microvessels. Light-sheet microscopy will greatly advance the assessment of microvascular responses to restorative stroke therapies.

Erratum to 'B4GALNT1 promotes hepatocellular carcinoma stemness and progression via integrin α2ß1-mediated FAK and AKT activation' (JHEP Reports 5 [2023] 100903).

[This corrects the article DOI: 10.1016/j.jhepr.2023.100903.].

Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories.

To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days, and developed open-source tools for image and data analysis and an interactive timelapse viewer for exploring quantitative features of nuclear size and shape. We performed a data-driven analysis of nuclear growth variations across timescales. We found that individual nuclear volume growth trajectories arise from short timescale variations attributable to their spatiotemporal context within the colony. We identified a strikingly time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited.

Multisensory Extended Reality Applications Offer Benefits for Volumetric Biomedical Image Analysis in Research and Medicine.

3D data from high-resolution volumetric imaging is a central resource for diagnosis and treatment in modern medicine. While the fast development of AI enhances imaging and analysis, commonly used visualization methods lag far behind. Recent research used extended reality (XR) for perceiving 3D images with visual depth perception and touch but used restrictive haptic devices. While unrestricted touch benefits volumetric data examination, implementing natural haptic interaction with XR is challenging. The research question is whether a multisensory XR application with intuitive haptic interaction adds value and should be pursued. In a study, 24 experts for biomedical images in research and medicine explored 3D medical shapes with 3 applications: a multisensory virtual reality (VR) prototype using haptic gloves, a simple VR prototype using controllers, and a standard PC application. Results of standardized questionnaires showed no significant differences between all application types regarding usability and no significant difference between both VR applications regarding presence. Participants agreed to statements that VR visualizations provide better depth information, using the hands instead of controllers simplifies data exploration, the multisensory VR prototype allows intuitive data exploration, and it is beneficial over traditional data examination methods. While most participants mentioned manual interaction as the best aspect, they also found it the most improvable. We conclude that a multisensory XR application with improved manual interaction adds value for volumetric biomedical data examination. We will proceed with our open-source research project ISH3DE (Intuitive Stereoptic Haptic 3D Data Exploration) to serve medical education, therapeutic decisions, surgery preparations, or research data analysis.

Understanding metric-related pitfalls in image analysis validation.

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multistage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides a reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Although focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation.

Asymmetric Ion-Pairing Photoredox Catalysis for Stereoselective Cationic Polymerization under Light Control.

By virtue of noninvasive regulations by light, photocontrolled polymerizations have attracted considerable attention for the precision synthesis of macromolecules. However, a cationic polymerization with simultaneous photocontrol and tacticity-regulation remains elusive so far. Herein, we introduce an asymmetric ion-pairing photoredox catalysis strategy that allows for the development of a stereoselective cationic polymerization with concurrent light regulation for the first time. By employing an ion pair catalyst (PC+/*A-) consisting of a photoredox active cation (PC+) and a sterically confined chiral anion (*A-) to deliver the stereochemical control, the cationic polymerization of vinyl ethers can be achieved with photocontrol and high isotactic selectivity (up to 91% m) at a remarkable low catalyst loading (50 ppm).

Microvascular Network Remodeling in the Ischemic Mouse Brain Defined by Light Sheet Microscopy.

BACKGROUND: Until now, the analysis of microvascular networks in the reperfused ischemic brain has been limited due to tissue transparency challenges. METHODS: Using light sheet microscopy, we assessed microvascular network remodeling in the striatum from 3 hours to 56 days post-ischemia in 2 mouse models of transient middle cerebral artery occlusion lasting 20 or 40 minutes, resulting in mild ischemic brain injury or brain infarction, respectively. We also examined the effect of a clinically applicable S1P (sphingosine-1-phosphate) analog, FTY720 (fingolimod), on microvascular network remodeling. RESULTS: Over 56 days, we observed progressive microvascular degeneration in the reperfused striatum, that is, the lesion core, which was followed by robust angiogenesis after mild ischemic injury induced by 20-minute middle cerebral artery occlusion. However, more severe ischemic injury elicited by 40-minute middle cerebral artery occlusion resulted in incomplete microvascular remodeling. In both cases, microvascular networks did not return to their preischemic state but displayed a chronically altered pattern characterized by higher branching point density, shorter branches, higher unconnected branch density, and lower tortuosity, indicating enhanced network connectivity. FTY720 effectively increased microvascular length density, branching point density, and volume density in both models, indicating an angiogenic effect of this drug. CONCLUSIONS: Utilizing light sheet microscopy together with automated image analysis, we characterized microvascular remodeling in the ischemic lesion core in unprecedented detail. This technology will significantly advance our understanding of microvascular restorative processes and pave the way for novel treatment developments in the stroke field.

MMV_Im2Im: an open-source microscopy machine vision toolbox for image-to-image transformation.

Over the past decade, deep learning (DL) research in computer vision has been growing rapidly, with many advances in DL-based image analysis methods for biomedical problems. In this work, we introduce MMV_Im2Im, a new open-source Python package for image-to-image transformation in bioimaging applications. MMV_Im2Im is designed with a generic image-to-image transformation framework that can be used for a wide range of tasks, including semantic segmentation, instance segmentation, image restoration, image generation, and so on. Our implementation takes advantage of state-of-the-art machine learning engineering techniques, allowing researchers to focus on their research without worrying about engineering details. We demonstrate the effectiveness of MMV_Im2Im on more than 10 different biomedical problems, showcasing its general potentials and applicabilities. For computational biomedical researchers, MMV_Im2Im provides a starting point for developing new biomedical image analysis or machine learning algorithms, where they can either reuse the code in this package or fork and extend this package to facilitate the development of new methods. Experimental biomedical researchers can benefit from this work by gaining a comprehensive view of the image-to-image transformation concept through diversified examples and use cases. We hope this work can give the community inspirations on how DL-based image-to-image transformation can be integrated into the assay development process, enabling new biomedical studies that cannot be done only with traditional experimental assays. To help researchers get started, we have provided source code, documentation, and tutorials for MMV_Im2Im at [https://github.com/MMV-Lab/mmv_im2im] under MIT license.

Understanding metric-related pitfalls in image analysis validation.

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.

ComplexEye: a multi-lens array microscope for high-throughput embedded immune cell migration analysis.

Autonomous migration is essential for the function of immune cells such as neutrophils and plays an important role in numerous diseases. The ability to routinely measure or target it would offer a wealth of clinical applications. Video microscopy of live cells is ideal for migration analysis, but cannot be performed at sufficiently high-throughput (HT). Here we introduce ComplexEye, an array microscope with 16 independent aberration-corrected glass lenses spaced at the pitch of a 96-well plate to produce high-resolution movies of migrating cells. With the system, we enable HT migration analysis of immune cells in 96- and 384-well plates with very energy-efficient performance. We demonstrate that the system can measure multiple clinical samples simultaneously. Furthermore, we screen 1000 compounds and identify 17 modifiers of migration in human neutrophils in just 4 days, a task that requires 60-times longer with a conventional video microscope. ComplexEye thus opens the field of phenotypic HT migration screens and enables routine migration analysis for the clinical setting.

B4GALNT1 promotes hepatocellular carcinoma stemness and progression via integrin α2ß1-mediated FAK and AKT activation.

Background & Aims: ß-1,4-N-Acetyl-galactosaminyltransferase 1 (B4GALNT1) has been reported to contribute to the development of human malignancies. However, its role in hepatocellular carcinoma (HCC) remains uncharacterised. In this study, we aimed to elucidate the role of B4GALNT1 in HCC stemness and progression. Methods: Immunohistochemical staining was used to evaluate B4GALNT1 expression in HCC tissues and adjacent normal liver tissues. Flow cytometry analysis and sphere formation analysis were performed to investigate the role of B4GALNT1 in HCC stemness. Colony formation, Incucyte, wound-healing, Transwell migration, and invasion assays, and an animal model were used to study the role of B4GALNT1 in HCC progression. RNA-sequencing and co-immunoprecipitation were used to investigate the downstream targets of B4GALNT1. Results: B4GALNT1 was upregulated in HCC and associated with poor clinical outcome of patients with the disease. Moreover, B4GALNT1 promoted HCC stemness, migration, invasion, and growth. Mechanistically, B4GALNT1 not only promoted the expression of the integrin α2ß1 ligand THBS4, but also directly interacted with the ß subunit of integrin α2ß1 ITGB1 to inhibit its ubiquitin-independent proteasomal degradation, resulting in activation of FAK and AKT. Ophiopogonin D inhibited HCC stemness and progression by reducing ITGB1 and THBS4 expression and inhibiting FAK and AKT activation. Conclusions: Our study suggests the B4GALNT1/integrin α2ß1/FAK/PI3K/AKT axis as a therapeutic target for the inhibition of HCC stemness and tumour progression. Impact and implications: The role and regulatory mechanism of B4GALNT1 in HCC have not been studied previously. Here, we reveal that B4GALNT1 has a crucial role in HCC stemness and progression by activating the integrin α2ß1/FAK/PI3K/AKT axis, providing a potential target for HCC therapy. In addition, we find Ophiopogonin D as a potential therapeutic drug for patients with HCC.

SETD1A drives stemness by reprogramming the epigenetic landscape in hepatocellular carcinoma stem cells.

Cancer stem cells (CSCs) are responsible for tumor progression and recurrence. However, the mechanisms regulating hepatocellular carcinoma (HCC) stemness remain unclear. Applying a genome-scale CRISPR knockout screen, we identified that the H3K4 methyltransferase SETD1A and other members of Trithorax group proteins drive cancer stemness in HCC. SET domain containing 1A (SETD1A) was positively correlated with poor clinical outcome in patients with HCC. Combination of SETD1A and serum alpha fetoprotein substantially improved the accuracy of predicting HCC relapse. Mechanistically, SETD1A mediates transcriptional activation of various histone-modifying enzymes, facilitates deposition of trimethylated H3K4 (H3K4me3) and H3K27me3, and activates oncogenic enhancers and super-enhancers, leading to activation of oncogenes and inactivation of tumor suppressor genes simultaneously in liver CSCs. In addition, SETD1A cooperates with polyadenylate-binding protein cytoplasmic 1 to regulate H3K4me3 modification on oncogenes. Our data pinpoint SETD1A as a key epigenetic regulator driving HCC stemness and progression, highlighting the potential of SETD1A as a candidate target for HCC intervention and therapy.

Rapid and fully automated blood vasculature analysis in 3D light-sheet image volumes of different organs.

Light-sheet fluorescence microscopy (LSFM) can produce high-resolution tomograms of tissue vasculature with high accuracy. However, data processing and analysis is laborious due to the size of the datasets. Here, we introduce VesselExpress, an automated software that reliably analyzes six characteristic vascular network parameters including vessel diameter in LSFM data on average computing hardware. VesselExpress is ∼100 times faster than other existing vessel analysis tools, requires no user interaction, and integrates batch processing and parallelization. Employing an innovative dual Frangi filter approach, we show that obesity induces a large-scale modulation of brain vasculature in mice and that seven other major organs differ strongly in their 3D vascular makeup. Hence, VesselExpress transforms LSFM from an observational to an analytical working tool.

Integrated intracellular organization and its variations in human iPS cells.

Understanding how a subset of expressed genes dictates cellular phenotype is a considerable challenge owing to the large numbers of molecules involved, their combinatorics and the plethora of cellular behaviours that they determine1,2. Here we reduced this complexity by focusing on cellular organization-a key readout and driver of cell behaviour3,4-at the level of major cellular structures that represent distinct organelles and functional machines, and generated the WTC-11 hiPSC Single-Cell Image Dataset v1, which contains more than 200,000 live cells in 3D, spanning 25 key cellular structures. The scale and quality of this dataset permitted the creation of a generalizable analysis framework to convert raw image data of cells and their structures into dimensionally reduced, quantitative measurements that can be interpreted by humans, and to facilitate data exploration. This framework embraces the vast cell-to-cell variability that is observed within a normal population, facilitates the integration of cell-by-cell structural data and allows quantitative analyses of distinct, separable aspects of organization within and across different cell populations. We found that the integrated intracellular organization of interphase cells was robust to the wide range of variation in cell shape in the population; that the average locations of some structures became polarized in cells at the edges of colonies while maintaining the 'wiring' of their interactions with other structures; and that, by contrast, changes in the location of structures during early mitotic reorganization were accompanied by changes in their wiring.

Organocatalytic [2 + 2] Photopolymerization under Visible Light: Accessing Sustainable Polymers from Cinnamic Acids.

Herein, the successful development of a metal-free, solution [2 + 2] photopolymerization of natural cinnamic acid-derived bisolefinic monomers is reported, which is enabled by a strategy based on direct triplet state access via energy transfer catalysis. 2,2'-Methoxythioxanthone has been identified as an effective organic photocatalyst for the [2 + 2] photopolymerization in solution, which can be excited by visible light and activate the biscinnamate monomers via triplet energy transfer. This method features its metal-free conditions, visible light utilization, solution polymerization, and abundant biomass-based feedstock, as well as processable polymer products, which is different from the rigid, insoluble products obtained from solid-state photopolymerization. This solution polymerization method also shows a good compatibility to monomer structures; cinnamic acid-derived bisolefinic monomers with different linkers, including diamine, natural diol, and bisphenol, can all readily undergo [2 + 2] photopolymerization, and be transformed into colorless, sustainable polymers.