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Preprocessing and data analysis with cmoRe (A) Overview of cmoRe package functionality. (a) Preprocessing comprises data loading, QC, filtering steps, and addition of secondary features. Data analysis can be done at the single-cell level or bulk population level. (b) An exemplary QC plot for a 96-well plate regarding the number of cells per well. (c) A representative cell cycle plot as used for cell cycle-based filtering of apoptotic cells and to assign cell cycle status as a secondary feature to each cell. Vertical lines indicate determined cutoffs; dashed lines limit high-certainty regions of cutoffs. (B) This boxplot shows the z-transformed cell area for NRCMs incubated with three concentrations of PE in comparison with the control (ctrl). The red line depicts a fitted linear mixed model assuming equidistance between ctrl/dose-levels, as applied in our analyses. The box center shows the median value, and the box limits show the 25th and 75th percentiles. (C) Hierarchical cluster analysis of selected features (ward.D2) for meta-feature construction. Each cluster corresponds to a meta-feature (color coded). (D) The PE phenotype. Radar plots show meta-feature values for PE (colored) against meta-feature values of an unstimulated control (gray) ordered in a circle. For PE, three concentrations are shown (red, low; yellow, intermediate; green, high; control, gray). (E) Numbers of retained features after each selection step for the canonical hypertrophic stimuli: norepinephrine (NE), adrenaline (A), isoproterenol (ISO), endothelin (ET), and angiotensin (AT); Data of 5 independent cell preparations are shown.
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Cellular morphology has the capacity to serve as a surrogate for cellular state and functionality. However, primary cardiomyocytes, the standard model in cardiovascular research, are highly heterogeneous cells and therefore impose methodological challenges to analysis. Hence, we aimed to devise a robust methodology to deconvolute cardiomyocyte morp...
Citations
... Almost all cells remained viable and exhibited a green color after 5 days of culture. Cell morphology serves as one of the indicators of cellular physiological status and function [60]. To further examine the impact of the culture process on cell morphology, Content courtesy of Springer Nature, terms of use apply. ...
Periodontitis is a prevalent chronic inflammatory disease, which leads to gradual degradation of alveolar bone. The challenges persist in achieving effective alveolar bone repair due to the unique bacterial microenvironment’s impact on immune responses. This study explores a novel approach utilizing Metal–Organic Frameworks (MOFs) (comprising magnesium and gallic acid) for promoting bone regeneration in periodontitis, which focuses on the physiological roles of magnesium ions in bone repair and gallic acid's antioxidant and immunomodulatory properties. However, the dynamic oral environment and irregular periodontal pockets pose challenges for sustained drug delivery. A smart responsive hydrogel system, integrating Carboxymethyl Chitosan (CMCS), Dextran (DEX) and 4-formylphenylboronic acid (4-FPBA) was designed to address this problem. The injectable self-healing hydrogel forms a dual-crosslinked network, incorporating the MOF and rendering its on-demand release sensitive to reactive oxygen species (ROS) levels and pH levels of periodontitis. We seek to analyze the hydrogel’s synergistic effects with MOFs in antibacterial functions, immunomodulation and promotion of bone regeneration in periodontitis. In vivo and in vitro experiment validated the system's efficacy in inhibiting inflammation-related genes and proteins expression to foster periodontal bone regeneration. This dynamic hydrogel system with MOFs, shows promise as a potential therapeutic avenue for addressing the challenges in bone regeneration in periodontitis.
Graphical Abstract
... Cell morphology is a crucial parameter for evaluating the health status of cells, as it is closely related to embryonic development, wound healing, and the process of tumor metastasis [29]. Regularly inspecting cell morphology during the culture process helps in identifying signs of contamination, nutritional status, and cell degeneration at an early stage. ...
... Previous studies have highlighted the importance of both tumor cell proliferation and cell mobility in triggering tumor progression [29]. Therefore, an accurate and real-time assessment of these abilities is crucial for effective tumor control [38,39]. ...
Developing a rapid and quantitative method to accurately evaluate the physiological abilities of living cells is critical for tumor control. Many experiments have been conducted in the field of biology in an attempt to measure the proliferation and movement abilities of cells, but existing methods cannot provide real-time and objective data for label-free cells. The quantitative imaging technique, including an automatic segmentation algorithm for individual label-free cells, has been a breakthrough in this regard. In this study, we develop a combined automatic image processing algorithm of CellPose and watershed segmentation for the long-term and real-time imaging of label-free cells. This method shows strong reliability in cell identification regardless of cell densities, allowing us to obtain accurate information about the number and proliferation ability of the target cells. Additionally, our results also suggest that this method is a reliable way to assess real-time data on drug cytotoxicity, cell morphology, and cell movement ability.
... In addition, scRNA-seq is prospective to screen target of immunotherapy, such as CAR-T, CAAR-T and therapeutic antibody. CAR-T chimeric antigen receptor T-cell therapy, CAAR-T chimeric autoantibody receptor T-cell therapy, DEGs differentially expressed genes, IP-MS immunoprecipitation-coupled mass spectrometry, LC-MS/MS liquid chromatography coupled to tandem mass spectrometry, MI myocardial infarction, scRNA-seq single-cell RNA sequencing, snRNA-seq single-nucleus RNA sequencing changes of neonatal rat vCMs after being incubated with plasma from patients and healthy individuals respectively [56]. Regarding risk prediction, scRNA-seq identified IFN stimulated genes (ISGs) alterations in peripheral blood NPs and monocytes of MI patients, and ISG score might be able to predict clinical outcomes as well as sensitivity to anti-cytokine treatments [21]. ...
The mechanisms of cardiovascular diseases (CVDs) remain incompletely elucidated. Single-cell RNA sequencing (scRNA-seq) has enabled the profiling of single-cell transcriptomes at unprecedented resolution and throughput, which is critical for deciphering cardiovascular cellular heterogeneity and underlying disease mechanisms, thereby facilitating the development of therapeutic strategies. In this review, we summarize cellular heterogeneity in cardiovascular homeostasis and diseases as well as the discovery of potential disease targets based on scRNA-seq, and yield new insights into the promise of scRNA-seq technology in precision medicine and clinical application.
... C-MORE is presented as a ready-to-use workflow comprising a standardized experimental protocol including high-throughput image acquisition and analysis, which could be useful for basic research and translational approaches. 1 C-MORE addresses an urgent need of the cardiomyocyte research community. ...
... Caveats include phenotypic changes during isolation and impurity due to contamination with other cardiac cell types (e.g., fibroblasts and endothelial cells), contributing to pheno-typic heterogeneity impeding robust characterization. 1 The use of iPSCs has grown recently, allowing human cells with unique genetic backgrounds to be differentiated into numerous cell types otherwise difficult to obtain (i.e., cardiomyocytes). iPSC-CMs, generated by mimicking developmental cues driving cardiomyocyte differentiation, can be produced directly from patient samples allowing unique insights into genotype-phenotype relationships. ...
... 7 Clinical assessment of cardiomyocyte morphology is an important indicator of disease state and responsiveness to therapeutic interventions. 1 ). Current methodologies lack the capability to comprehensively assess cardiomyocyte morphology in a sufficient number of cells, and often data output is highly variable and lacks comparability. 1 Methods for high-throughput morphological characterization of cells are essential for drug screening, extrapolating huge amounts of data on the phenotypic characteristics of cells imaged by automated microscopy, and profiling effects of novel therapeutics and uncharacterized molecules. ...
Robust, comprehensive assessment of cardiomyocyte morphology is essential from research and clinical perspectives, but current methods predominantly rely on only limited parameters. Addressing this, Furkel et al. present, “C-MORE: A high content single cell morphology assay for cardiovascular medicine” in this issue of Cell Reports Medicine.
Liquid biopsy, which is a minimally invasive procedure as an alternative to tissue biopsy, has been introduced as a new diagnostic/prognostic measure. By screening disease-related markers from the blood or other biofluids, it promises early diagnosis, timely prognostication, and effective treatment of the diseases. However, there will be a long way until its realization due to its conceptual and practical challenges. The biomarkers detected by liquid biopsy, such as circulating tumor cell (CTC) and circulating tumor DNA (ctDNA), are extraordinarily rare and often obscured by an abundance of normal cellular components, necessitating ultra-sensitive and accurate detection methods for the advancement of liquid biopsy techniques. Optical biosensors based on nanomaterials open an important opportunity in liquid biopsy because of their enhanced sensing performance with simple and practical properties. In this review article, we summarized recent innovations in optical nanomaterials to demonstrate the sensitive detection of protein, peptide, ctDNA, miRNA, exosome, and CTCs. Each study prepares the optical nanomaterials with a tailored design to enhance the sensing performance and to meet the requirements of each biomarker. The unique optical characteristics of metallic nanoparticles (NPs), quantum dots, upconversion NPs, silica NPs, polymeric NPs, and carbon nanomaterials are exploited for sensitive detection mechanisms. These recent advances in liquid biopsy using optical nanomaterials give us an opportunity to overcome challenging issues and provide a resource for understanding the unknown characteristics of the biomarkers as well as the mechanism of the disease.
Graphical abstract
m6A mRNA methylation controls cardiomyocyte function and increased overall m6A levels are a stereotyping finding in heart failure independent of the underlying etiology. However, it is largely unknown how the information is read by m6A reader proteins in heart failure. Here we show that the m6A reader protein Ythdf2 controls cardiac function and identified a novel mechanism how reader proteins control gene expression and cardiac function. Deletion of Ythdf2 in cardiomyocytes in vivo leads to mild cardiac hypertrophy, reduced heart function, and increased fibrosis during pressure overload as well as during aging. Similarly, in vitro the knockdown of Ythdf2 results in cardiomyocyte growth and remodeling. Mechanistically, we identified the eucaryotic elongation factor 2 as post-transcriptionally regulated by Ythdf2 using cell type specific Ribo-seq data. Our study expands our understanding on the regulatory functions of m6A methylation in cardiomyocytes and how cardiac function is controlled by the m6A reader protein Ythdf2.
Efficient and fully automatic multi-organ segmentation is of great research and clinical prospect. Deep learning (DL) based methods have recently emerged and proven its effectiveness in various biomedical segmentation tasks. The performance of DL based segmentation models strongly depends on the training dataset and a large, correctly annotated dataset is always crucial. However, gathering annotation for multi-organ segmentation task is difficult and making use of public datasets with existing annotations then becomes one possible solution. In this work we propose a pipeline for training multi-organ segmentation model from partially annotated datasets. The proposed method is evaluated using left, right lungs and liver segmentation task of throat-abdomen CT scans. From average dice score, we found the proposed method can obtain very close performance using only partially annotated datasets (0.93), compared with models using fully annotated datasets (0.96).
