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.

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.

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.

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).

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.

Cooperation of ATF4 and CTCF promotes adipogenesis through transcriptional regulation.

Adipogenesis is a multi-step process orchestrated by activation of numerous TFs, whose cooperation and regulatory network remain elusive. Activating transcription factor 4 (ATF4) is critical for adipogenesis, yet its regulatory network is unclarified. Here, we mapped genome-wide ATF4 binding landscape and its regulatory network by Chip-seq and RNA-seq and found ATF4 directly modulated transcription of genes enriching in fat cell differentiation. Motifs of TFs especially CTCF were found from ATF4 binding sites, suggesting a direct role of ATF4 in regulating adipogenesis associated with CTCF and other TFs. Deletion of CTCF attenuated adipogenesis while overexpression enhanced adipocyte differentiation, indicating CTCF is indispensable for adipogenesis. Intriguingly, combined analysis of Chip-seq data of these two TFs showed that ATF4 co-localized with CTCF in the promoters of key adipogenic genes including Cebpd and PPARg and co-regulated their transactivation. Moreover, ATF4 directly regulated CTCF expression and interacted with CTCF in differentiated 3T3-L1 cells. In vivo, downregulation of ATF4 suppressed the expression of CTCF, Cebpd, and PPARg, leading to reduced adipose tissue expansion in refeeding mice. Consistently, mRNA expression of ATF4 and CTCF was positively correlated with each other in human subcutaneous adipose tissue and inversely associated with BMI, indicating a possible involvement of these two TFs in adipose development. Taken together, our data propose for the first time that ATF4 and CTCF work cooperatively to control adipogenesis and adipose development via orchestrating transcription of adipogenic genes. Our findings reveal novel therapeutic targets in obesity treatment.

Decoding Calcium Signaling Dynamics during Drosophila Wing Disc Development.

The robust specification of organ development depends on coordinated cell-cell communication. This process requires signal integration among multiple pathways, relying on second messengers such as calcium ions. Calcium signaling encodes a significant portion of the cellular state by regulating transcription factors, enzymes, and cytoskeletal proteins. However, the relationships between the inputs specifying cell and organ development, calcium signaling dynamics, and final organ morphology are poorly understood. Here, we have designed a quantitative image-analysis pipeline for decoding organ-level calcium signaling. With this pipeline, we extracted spatiotemporal features of calcium signaling dynamics during the development of the Drosophila larval wing disc, a genetic model for organogenesis. We identified specific classes of wing phenotypes that resulted from calcium signaling pathway perturbations, including defects in gross morphology, vein differentiation, and overall size. We found four qualitative classes of calcium signaling activity. These classes can be ordered based on agonist stimulation strength Gαq-mediated signaling. In vivo calcium signaling dynamics depend on both receptor tyrosine kinase/phospholipase C γ and G protein-coupled receptor/phospholipase C ß activities. We found that spatially patterned calcium dynamics correlate with known differential growth rates between anterior and posterior compartments. Integrated calcium signaling activity decreases with increasing tissue size, and it responds to morphogenetic perturbations that impact organ growth. Together, these findings define how calcium signaling dynamics integrate upstream inputs to mediate multiple response outputs in developing epithelial organs.

Single Cells Exhibit Differing Behavioral Phases during Early Stages of Pseudomonas aeruginosa Swarming.

Pseudomonas aeruginosa is among the many bacteria that swarm, where groups of cells coordinate to move over surfaces. It has been challenging to determine the behavior of single cells within these high-cell-density swarms. To track individual cells within P. aeruginosa swarms, we imaged a fluorescently labeled subset of the larger population. Single cells at the advancing swarm edge varied in their motility dynamics as a function of time. From these data, we delineated four phases of early swarming prior to the formation of the tendril fractals characteristic of P. aeruginosa swarming by collectively considering both micro- and macroscale data. We determined that the period of greatest single-cell motility does not coincide with the period of greatest collective swarm expansion. We also noted that flagellar, rhamnolipid, and type IV pilus motility mutants exhibit substantially less single-cell motility than the wild type.IMPORTANCE Numerous bacteria exhibit coordinated swarming motion over surfaces. It is often challenging to assess the behavior of single cells within swarming communities due to the limitations of identifying, tracking, and analyzing the traits of swarming cells over time. Here, we show that the behavior of Pseudomonas aeruginosa swarming cells can vary substantially in the earliest phases of swarming. This is important to establish that dynamic behaviors should not be assumed to be constant over long periods when predicting and simulating the actions of swarming bacteria.

Hypoxia exacerbates nonalcoholic fatty liver disease via the HIF-2α/PPARα pathway.

This study aimed to investigate whether hypoxia can affect nonalcoholic fatty liver disease (NAFLD) progression and the associated mechanisms, specifically regarding the hypoxia-inducible factor (HIF)-2α/peroxisome proliferator-activated receptor (PPAR)α pathway in vitro and in vivo. Recent studies have reported that, compared with HIF-1α, HIF-2α has different effects on lipid metabolism. We propose hypoxia may exacerbate NAFLD by the HIF-2α upregulation-induced suppression of PPARα in the liver. To verify this hypothesis, a steatotic human hepatocyte (L02) cell line treated with free fatty acids and a mouse model of NAFLD fed a high-fat diet were used. Steatotic hepatocytes were treated with hypoxia, HIF-2α siRNA, PPARα agonists, and inhibitors, respectively. Meanwhile, the NAFLD mice were exposed to intermittent hypoxia or intermittent hypoxia with PPARα agonists. The relative gene expression levels of HIF-1α, HIF-2α, mitochondrial function, fatty acid ß-oxidation and lipogenesis were examined. Evidence of lipid accumulation was observed, which demonstrated that, compared with normal hepatocytes, steatotic hepatocytes exhibited higher sensitivity to hypoxia. This phenomenon was closely associated with HIF-2α. Moreover, lipid accumulation in hepatocytes was ameliorated by HIF-2α silencing or a PPARα agonist, despite the hypoxia treatment. HIF-2α overexpression under hypoxic conditions suppressed PPARα, leading to PGC-1α, NRF-1, ESRRα downregulation, and mitochondrial impairment. Additionally, ß-oxidation genes such as CPT1α, CPT2α, ACOX1, and ACOX2 were downregulated and lipogenesis genes including LXRα, FAS, and SCD1 were upregulated by hypoxia. Therefore, we concluded that HIF-2α overexpression induced by hypoxia aggravated NAFLD progression by suppressing fatty acid ß-oxidation and inducing lipogenesis in the liver via PPARα.

miR-429 suppresses cell proliferation, migration and invasion in nasopharyngeal carcinoma by downregulation of TLN1.

BACKGROUND: miR-429 and TLN1 have been shown to affect the biological behaviours of many carcinomas. However, their effects in nasopharyngeal carcinoma (NPC) are not yet clear. Here, we investigated their regulatory relationships and effects on NPC cells. METHODS: TargetScan was used to predict the regulatory relationships of miR-429 and TLN1 in NPC cells. Then, Western blotting and quantitative real-time PCR (qPCR) were performed to examine TLN1 levels, and qPCR was used to determine miR-429 levels in NPC cell lines with different metastatic characteristics (5-8F, CNE-2, CNE-1, 6-10B and NP69), to investigate whether TLN1 and miR-429 are correlated with the metastatic characteristics of these cells. Next, we upregulated or downregulated miR-429 in 5-8F and 6-10B cells, which have different tumourigenicity and transferability, and examined TLN1 expression by western blotting and qPCR after transfection. QPCR was also performed to confirm successful transfection of miR-429 mimic into 5-8F and 6-10B cells. Dual luciferase reporter gene assay was performed to investigate whether miR-429 regulates TLN1 by binding to its 3'UTR. After transfection, Cell Counting Kit-8 (CCK8) and IncuCyte were used to examine the proliferation of these cells, and wound-healing assay, Transwell migration assay, and invasion assays were performed to investigate the changes in migration and invasion after transfection. RESULTS: Western blotting and qPCR analyses showed that the protein level of TLN1 was negatively correlated with miR-429 in NPC cell lines (P < 0.05), while the mRNA level showed no relation with miR429 expression (P > 0.05). In addition, cells with high transferability showed high TLN1 expression at the protein level, while miR429 expression showed the opposite trend (P < 0.05), but there were no differences at the mRNA level between the different cell lines. Overexpression of miR429 in 5-8F and 6-10B cells was accompanied by downregulation of TLN1 at the protein level (P < 0.05), while there were no significant differences at the mRNA level (P > 0.05). In addition, transferability, proliferation, and invasion were downregulated by miR429 overexpression (P < 0.05). However, dual-luciferase reporter gene assay indicated that TLN1 was not a direct target of miR-429. CONCLUSION: This study showed that miR-429 functions as a tumour suppressor in NPC by downregulation of TLN1, although the relationship is not direct.

Potential Five-MicroRNA Signature Model for the Prediction of Prognosis in Patients with Wilms Tumor.

BACKGROUND Wilms tumor (WT) is the most common type of pediatric renal malignancy, and is associated with poor prognosis. The aim of the present study was to identify microRNA (miRNA) signatures which might predict prognosis and categorize WTs into high- and low-risk subgroups. MATERIAL AND METHODS The miRNA expression profiles of WT patients and normal samples were obtained from the Therapeutically Applicable Research to Generate Effective Treatment database. Differentially expressed miRNAs between WT patients and normal samples were identified using the EdgeR package. Subsequently, correlations between differentially expressed miRNAs and the prognosis of overall survival were analyzed. Enrichment analyses for the targeted mRNAs were conducted via the Database for Annotation, Visualization, and Integration Discovery. RESULTS A total of 154 miRNAs were identified as differentially expressed in WT. Of those, 18 miRNAs were associated with overall survival (P<0.05). A prognostic signature of 5 differentially expressed miRNAs (i.e., has-mir-149, has-mir-7112, has-mir-940, has-mir-1248, and has-mir-490) was constructed to classify the patients into high- and low-risk subgroups. The targeted mRNAs of these prognostic miRNAs were primarily enriched in Gene Ontology terms (i.e., protein autophosphorylation, protein dephosphorylation, and stress-activated MAPK cascade) and the Kyoto Encyclopedia of Genes and Genomes signaling pathways (i.e., MAPK, AMPK, and PI3K-Akt). CONCLUSIONS The 5-miRNA signature model might be useful in determining the prognosis of WT patients. As a promising prediction tool, this prognosis signature might serve as a potential biomarker for WT patients.

Kinetic Transition Networks for the Thomson Problem and Smale's Seventh Problem.

The Thomson problem, arrangement of identical charges on the surface of a sphere, has found many applications in physics, chemistry and biology. Here, we show that the energy landscape of the Thomson problem for N particles with N=132, 135, 138, 141, 144, 147, and 150 is single funneled, characteristic of a structure-seeking organization where the global minimum is easily accessible. Algorithmically, constructing starting points close to the global minimum of such a potential with spherical constraints is one of Smale's 18 unsolved problems in mathematics for the 21st century because it is important in the solution of univariate and bivariate random polynomial equations. By analyzing the kinetic transition networks, we show that a randomly chosen minimum is, in fact, always "close" to the global minimum in terms of the number of transition states that separate them, a characteristic of small world networks.

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.

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.

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.

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.

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.