Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A quantitative image-based protocol for morphological characterization of cellular solids in feather shafts.

ABSTRACT: During morphogenesis, cellular sheets undergo dynamic folding to build functional forms. Here, we develop an image-based quantitative morphology field (QMorF) protocol that quantifies the morphological features of cellular structures and associated distributions. Using feather shafts with different rigidities as examples, QMorF performs coarse-graining statistical measurements of the fitted cellular objects over a micro-image stack, revealing underlying mechanical coupling and developmental clues. These images give intuitive representations of mechanical forces and should be useful for analyzing tissue images showing clear cellular features. For complete details on the use and execution of this protocol, please refer to Chang et al. (2019).

SUBMITTER: Wu H

PROVIDER: S-EPMC8271172 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A quantitative image-based protocol for morphological characterization of cellular solids in feather shafts.

Wu Hao H Chiu Yu-Kun YK Tsai Jih-Chiang JC Chuong Cheng-Ming CM Juan Wen-Tau WT

STAR protocols 20210706 3

During morphogenesis, cellular sheets undergo dynamic folding to build functional forms. Here, we develop an image-based quantitative morphology field (QMorF) protocol that quantifies the morphological features of cellular structures and associated distributions. Using feather shafts with different rigidities as examples, QMorF performs coarse-graining statistical measurements of the fitted cellular objects over a micro-image stack, revealing underlying mechanical coupling and developmental clue ...[more]

PMID: 34278338

Similar Datasets

Comparison of methods for image-based profiling of cellular morphological responses to small-molecule treatment.

Project description:Quantitative microscopy has proven a versatile and powerful phenotypic screening technique. Recently, image-based profiling has shown promise as a means for broadly characterizing molecules' effects on cells in several drug-discovery applications, including target-agnostic screening and predicting a compound's mechanism of action (MOA). Several profiling methods have been proposed, but little is known about their comparative performance, impeding the wider adoption and further development of image-based profiling. We compared these methods by applying them to a widely applicable assay of cultured cells and measuring the ability of each method to predict the MOA of a compendium of drugs. A very simple method that is based on population means performed as well as methods designed to take advantage of the measurements of individual cells. This is surprising because many treatments induced a heterogeneous phenotypic response across the cell population in each sample. Another simple method, which performs factor analysis on the cellular measurements before averaging them, provided substantial improvement and was able to predict MOA correctly for 94% of the treatments in our ground-truth set. To facilitate the ready application and future development of image-based phenotypic profiling methods, we provide our complete ground-truth and test data sets, as well as open-source implementations of the various methods in a common software framework.

| S-EPMC3884769 | biostudies-literature

Cellular Therapy: Shafts of Light Emerging for COVID-19.

Project description:The COVID-19 pandemic has presented with debilitating respiratory consequences especially more pronounced in high risk individuals. Individuals with underlying systemic diseases are more prone and vulnerable to suffer severe consequences of SARS-CoV-2 infectivity. The pathophysiological changes identified cytokine storm mechanism for out setting the series of adverse clinical conditions. Thereby, associating it with high mortality rates. This warrants urgent consideration of divergent modalities such as the cellular therapy. Cellular therapy (CT) is a new medical paradigm wherein cellular material is administered to patients for therapeutic purposes. In this regard, mesenchymal stem cells (MSCs) have yielded the most promising results among stromal vascular fraction (SVF); placental cells; natural killer (NK) cell and platelet lysate respectively. Following the administration of the CT as per preferred route, these play pivotal role in modifying the microenvironment of the lung tissue with their distinct sets of mechanism. Evidences have shown how their immunomodulatory action repairs and prevents lung injury which in turn improvise the compliance of lungs. In this review article we have discussed these emerging novel approaches and their target step serving as a ray of hope to combat severe form of COVID-19. Currently these aren't approved for preventing or treating COVID-19 cases, however clinical trials are afoot to dispense the utmost understanding in terms of efficacy and safety concerns.

| S-EPMC7367471 | biostudies-literature

A novel image-based quantitative method for the characterization of NETosis.

Project description:NETosis is a newly recognized mechanism of programmed neutrophil death. It is characterized by a stepwise progression of chromatin decondensation, membrane rupture, and release of bactericidal DNA-based structures called neutrophil extracellular traps (NETs). Conventional 'suicidal' NETosis has been described in pathogenic models of systemic autoimmune disorders. Recent in vivo studies suggest that a process of 'vital' NETosis also exists, in which chromatin is condensed and membrane integrity is preserved. Techniques to assess 'suicidal' or 'vital' NET formation in a specific, quantitative, rapid and semiautomated way have been lacking, hindering the characterization of this process. Here we have developed a new method to simultaneously assess both 'suicidal' and 'vital' NETosis, using high-speed multi-spectral imaging coupled to morphometric image analysis, to quantify spontaneous NET formation observed ex-vivo or stimulus-induced NET formation triggered in vitro. The use of imaging flow cytometry allows automated, quantitative and rapid analysis of subcellular morphology and texture, and introduces the potential for further investigation using NETosis as a biomarker in pre-clinical and clinical studies.

| S-EPMC4522197 | biostudies-literature

Morphological Analysis of Metacarpal Shafts With Respect to Retrograde Intramedullary Headless Screw Fixation.

Project description:Background: The use of retrograde intramedullary headless compression screw fixation for metacarpal neck and shaft fractures has been described in the literature. The purpose of this study was to perform a computed tomography (CT)-based morphological analysis of metacarpal size to help surgeons anticipate expected hardware needs. Methods: In all, 108 consecutive hand CT scans were evaluated for the medullary diameter in the volar-dorsal and radial-ulnar planes at the narrowest point of the canal, as well as for the distance from the articular surface to this point. Results were then analyzed by finger and by sex. Results: The ring finger had the smallest average medullary canal diameter for both men and women (2.7 and 2.6 mm, respectively); the small finger had the largest average diameter (3.9 mm) for men and the middle finger (3.6 mm) for women. Radial-ulnar was the rate-limiting dimension in the index, middle, and ring fingers, whereas volar-dorsal was the smallest dimension in the small finger, regardless of sex. Medullary diameter tended to be larger in patients aged more than 50 years. More than 50% of fingers have diameters >3.0 mm, and at least 40% of index, middle, and small fingers have diameters >3.5 mm, which are common diameters of commercially available headless compression screws. Conclusions: When preparing to perform open reduction internal fixation of a metacarpal using retrograde intramedullary headless compression screws, the surgeon needs to be prepared with screws of larger diameters to optimize fixation. Screws of larger diameters are needed to achieve endosteal purchase, regardless of sex.

| S-EPMC9274869 | biostudies-literature

Enhanced Morphological Characterization of Cellulose Nano/Microfibers through Image Skeleton Analysis.

Project description:The present paper proposes a novel approach for the morphological characterization of cellulose nano and microfibers suspensions (CMF/CNFs) based on the analysis of eroded CMF/CNF microscopy images. This approach offers a detailed morphological characterization and quantification of the micro and nanofibers networks present in the product, which allows the mode of fibrillation associated to the different CMF/CNF extraction conditions to be discerned. This information is needed to control CMF/CNF quality during industrial production. Five cellulose raw materials, from wood and non-wood sources, were subjected to mechanical, enzymatic, and (2,2,6,6-Tetramethylpiperidin-1-yl)oxyl (TEMPO)-mediated oxidative pre-treatments followed by different homogenization sequences to obtain products of different morphologies. Skeleton analysis of microscopy images provided in-depth morphological information of CMF/CNFs that, complemented with aspect ratio information, estimated from gel point data, allowed the quantification of: (i) fibers peeling after mechanical pretreatment; (ii) fibers shortening induced by enzymes, and (iii) CMF/CNF entanglement from TEMPO-mediated oxidation. Being mostly based on optical microscopy and image analysis, the present method is easy to implement at industrial scale as a tool to monitor and control CMF/CNF quality and homogeneity.

| S-EPMC8398699 | biostudies-literature

Image-based identification and isolation of micronucleated cells to dissect cellular consequences

Project description:Recent advances in isolating cells based on visual phenotypes have transformed our ability to identify the mechanisms and consequences of complex traits. Micronucleus (MN) formation is a frequent outcome of genome instability, triggers extensive disease-associated changes in genome structure and signaling coincident with MN rupture, and is almost exclusively defined by visual analysis. Automated MN detection in microscopy images has proved extremely challenging, limiting unbiased discovery of the mechanisms and consequences of MN formation and rupture. In this study we describe two new MN segmentation modules: a rapid model for classifying micronucleated cells and their rupture status (VCS MN), and a robust model for accurate MN segmentation (MNFinder) from a broad range of fluorescence microscopy images. As a proof-of- concept, we define the transcriptome of non-transformed human cells with intact or ruptured MN after inducing chromosome missegregation by combining VCS MN with photoactivation-based cell isolation and RNASeq. Surprisingly, we find that neither MN formation nor rupture triggers a strong unique transcriptional response. Instead, transcriptional changes appear correlated with small increases in aneuploidy in these cell classes. Our MN segmentation modules overcome a significant challenge with reproducible MN quantification, and, joined with visual cell sorting, enable the application of powerful functional genomics assays, including pooled CRISPR screens and time-resolved analyses of cellular and genetic consequences, to a wide-range of questions in MN biology.

2025-04-15 | GSE291811 | GEO

Protocol for automated multivariate quantitative-image-based cytometry analysis by fluorescence microscopy of asynchronous adherent cells.

Project description:Here, we present a protocol for multivariate quantitative-image-based cytometry (QIBC) analysis by fluorescence microscopy of asynchronous adherent cells. We describe steps for the preparation, treatment, and fixation of cells, sample staining, and imaging for QIBC. We then detail image analysis with our open source Fiji script developed for QIBC and present multiparametric data visualization. Our QIBC Fiji script integrates modern artificial-intelligence-based tools, applying deep learning, for robust automated nuclei segmentation with minimal user adjustments, a major asset for efficient QIBC analysis. For complete details on the use and execution of this protocol, please refer to Besse et al. (2023).1.

| S-EPMC10365954 | biostudies-literature

Protocol for deriving proximity, affinity, and stoichiometry of protein interactions using image-based quantitative two-hybrid FRET.

Project description:Two-hybrid Förster resonance energy transfer (FRET) provides proximity, affinity, and stoichiometry information in binding interactions. We present an image-based approach that surpasses traditional two-hybrid FRET assays in precision and robustness. We outline instrument setup and image acquisition and further describe steps for image preprocessing and two-hybrid FRET analysis using provided software to simplify the workflow. This protocol is compatible with confocal microscopes for high-precision and imaging plate readers for high-throughput applications. A plasmid-based reference system supports fast establishment of the protocol. For complete details on the use and execution of this protocol, please refer to Rivas et al.1.

| S-EPMC10400964 | biostudies-literature

Image-Based Morphological Profiling Identifies a Lysosomotropic, Iron-Sequestering Autophagy Inhibitor.

Project description:Chemical proteomics is widely applied in small-molecule target identification. However, in general it does not identify non-protein small-molecule targets, and thus, alternative methods for target identification are in high demand. We report the discovery of the autophagy inhibitor autoquin and the identification of its molecular mode of action using image-based morphological profiling in the cell painting assay. A compound-induced fingerprint representing changes in 579 cellular parameters revealed that autoquin accumulates in lysosomes and inhibits their fusion with autophagosomes. In addition, autoquin sequesters Fe2+ in lysosomes, resulting in an increase of lysosomal reactive oxygen species and ultimately cell death. Such a mechanism of action would have been challenging to unravel by current methods. This work demonstrates the potential of the cell painting assay to deconvolute modes of action of small molecules, warranting wider application in chemical biology.

| S-EPMC7154763 | biostudies-literature

Quantitative mappings between symmetry and topology in solids.

Project description:The study of spatial symmetries was accomplished during the last century and had greatly improved our understanding of the properties of solids. Nowadays, the symmetry data of any crystal can be readily extracted from standard first-principles calculation. On the other hand, the topological data (topological invariants), the defining quantities of nontrivial topological states, are in general considerably difficult to obtain, and this difficulty has critically slowed down the search for topological materials. Here we provide explicit and exhaustive mappings from symmetry data to topological data for arbitrary gapped band structure in the presence of time-reversal symmetry and any one of the 230 space groups. The mappings are completed using the theoretical tools of layer construction and symmetry-based indicators. With these results, finding topological invariants in any given gapped band structure reduces to a simple search in the mapping tables provided.

| S-EPMC6117291 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data