Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Accurate non-invasive image-based cytotoxicity assays for cultured cells.

ABSTRACT:

Background

The CloneSelect Imager system is an image-based visualisation system for cell growth assessment. Traditionally cell proliferation is measured with the colorimetric MTT assay.

Results

Here we show that both the CloneSelect Imager and the MTT approach result in comparable EC50 values when assaying the cytotoxicity of cisplatin and oxaliplatin on various cell lines. However, the image-based technique was found non-invasive, considerably quicker and more accurate than the MTT assay.

Conclusions

This new image-based technique has the potential to replace the cumbersome MTT assay when fast, unbiased and high-throughput cytotoxicity assays are requested.

SUBMITTER: Marques-Gallego P

PROVIDER: S-EPMC2906423 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Accurate non-invasive image-based cytotoxicity assays for cultured cells.

Marqués-Gallego Patricia P den Dulk Hans H Backendorf Claude C Brouwer Jaap J Reedijk Jan J Burke Julian F JF

BMC biotechnology 20100617

<h4>Background</h4>The CloneSelect Imager system is an image-based visualisation system for cell growth assessment. Traditionally cell proliferation is measured with the colorimetric MTT assay.<h4>Results</h4>Here we show that both the CloneSelect Imager and the MTT approach result in comparable EC50 values when assaying the cytotoxicity of cisplatin and oxaliplatin on various cell lines. However, the image-based technique was found non-invasive, considerably quicker and more accurate than the M ...[more]

PMID: 20565747

Similar Datasets

BioFlow: a non-invasive, image-based method to measure speed, pressure and forces inside living cells.

Project description:Cell motility is governed by a complex molecular machinery that converts physico-chemical cues into whole-cell movement. Understanding the underlying biophysical mechanisms requires the ability to measure physical quantities inside the cell in a simple, reproducible and preferably non-invasive manner. To this end, we developed BioFlow, a computational mechano-imaging method and associated software able to extract intracellular measurements including pressure, forces and velocity everywhere inside freely moving cells in two and three dimensions with high spatial resolution in a non-invasive manner. This is achieved by extracting the motion of intracellular material observed using fluorescence microscopy, while simultaneously inferring the parameters of a given theoretical model of the cell interior. We illustrate the power of BioFlow in the context of amoeboid cell migration, by modelling the intracellular actin bulk flow of the parasite Entamoeba histolytica using fluid dynamics, and report unique experimental measures that complement and extend both theoretical estimations and invasive experimental measures. Thanks to its flexibility, BioFlow is easily adaptable to other theoretical models of the cell, and alleviates the need for complex or invasive experimental conditions, thus constituting a powerful tool-kit for mechano-biology studies. BioFlow is open-source and freely available via the Icy software.

| S-EPMC5569094 | biostudies-literature

Non-invasive image-based cytometry for high throughput NK cell cytolysis analysis.

Project description:Natural Killer (NK) cells are lymphocytes that are the first line of defense against malignantly transformed cells, virally infected cells and other stressed cell types. To study the cytolytic function of NK cells in vitro, a cytotoxicity assay is normally conducted against a target cancerous cell line. Current assay methods are typically performed in mixed 2D cocultures with destructive endpoints and low throughput, thereby limiting the scale, time-resolution, and relevance of the assay to in vivo conditions. Here, we evaluated a novel, non-invasive, quantitative image-based cytometry (qIBC) assay for detection of NK-mediated killing of target cells in 2D and 3D environments in vitro and compared its performance to two common flow cytometry- and fluorescence-based cytotoxicity assays. Similar to the other methods evaluated, the qIBC assay allowed for reproducible detection of target cell killing across a range of effector-to-target ratios with reduced variability. The qIBC assay also allowed for detection of NK cytolysis in 3D spheroids, which enabled scalable measurements of cell cytotoxicity in 3D models. Our findings suggest that quantitative image-based cytometry would be suitable for rapid, high-throughput screening of NK cytolysis in vitro, including in quasi-3D structures that model tissue environments in vivo.

| S-EPMC8112353 | biostudies-literature

Diagnostic performance of non-invasive, stool-based molecular assays in patients with paucibacillary tuberculosis.

Project description:Timely diagnosis of paucibacillary tuberculosis (TB) which includes smear-negative pulmonary TB (PTB) and extra-pulmonary TB (EPTB) remains a challenge. This study was performed to assess the diagnostic utility of stool as a specimen of choice for detection of mycobacterial DNA in paucibacillary TB patients in a TB-endemic setting. Stool samples were collected from 246 subjects including 129 TB patients (62 PTB and 67 EPTB) recruited at TB hospital in Delhi, India. Diagnostic efficacy of stool IS6110 PCR (n?=?228) was measured, using microbiologically/clinically confirmed TB as the reference standard. The clinical sensitivity of stool PCR was 97.22% (95% confidence interval (CI), 85.47-99.93) for detection of Mycobacterium tuberculosis in stool samples of smear-positive PTB patients and 76.92% (CI, 56.35-91.03) in samples from smear-negative PTB patients. Overall sensitivity of PCR for EPTB was 68.66% (CI, 56.16-79.44), with the highest sensitivity for stool samples from patients with lymph node TB (73.5%), followed by abdominal TB (66.7%) and pleural effusion (56.3%). Stool PCR presented a specificity of 95.12%. The receiver operating characteristic curve also indicated the diagnostic utility of stool PCR in TB detection (AUC: 0.882). The performance characteristic of the molecular assay suggests that stool DNA testing has clinical value in detection of TB.

| S-EPMC7188812 | biostudies-literature

Protocol for machine-learning-based 3D image analysis of nuclear envelope tubules in cultured cells.

Project description:The nuclear envelope can form complex structures in physiological and pathological contexts. Current approaches to quantify nuclear envelope structures can be time-consuming or inaccurate. Here, we present a protocol to measure nuclear envelope tubules induced by DNA double-strand breaks using a mid-throughput approach. We describe steps for the induction of these nuclear envelope structures and 3D image analysis using machine-learning-based image segmentation. This protocol can be applied to analyze various nuclear envelope structures in contexts beyond DNA repair. For complete details on the use and execution of this protocol, please refer to Shokrollahi et al.1.

| S-EPMC11342193 | biostudies-literature

Non-invasive cardiac pacing with image-guided focused ultrasound.

Project description:Currently, no non-invasive cardiac pacing device acceptable for prolonged use in conscious patients exists. High Intensity Focused Ultrasound (HIFU) can be used to perform remote pacing using reversibility of electromechanical coupling of cardiomyocytes. Here we described an extracorporeal cardiac stimulation device and study its efficacy and safety. We conducted experiments ex vivo and in vivo in a large animal model (pig) to evaluate clinical potential of such a technique. The stimulation threshold was determined in 10 different ex vivo hearts and different clinically relevant electrical effects such as consecutive stimulations of different heart chambers with a single ultrasonic probe, continuous pacing or the inducibility of ventricular tachycardia were shown. Using ultrasonic contrast agent, consistent cardiac stimulation was achievable in vivo for up to 1?hour sessions in 4 different animals. No damage was observed in inversion-recovery MR sequences performed in vivo in the 4 animals. Histological analysis revealed no differences between stimulated and control regions, for all ex vivo and in vivo cases.

| S-EPMC5101517 | biostudies-literature

Non-Invasive, Label-free Image Approaches to Predict Multimodal Molecular Markers in Pluripotency Assessment

Project description:We detail an innovative non-invasive technique to predict gene and protein expression in pluripotent stem cells using advanced bright-field microscopy. The method employs machine learning algorithms to classify cells based on brightfield images, avoiding the need for traditional staining and manual annotation. Our approach uses DeepLearning technology to predict the gene expression (qPCR, RNA-seq) and protein expression (immunostaining, Flowcytometry) of cells from brightfield microscopy images. It provides a robust tool for non-destructive and continuous monitoring of the pluripotency status of stem cells, which will greatly advance regenerative medicine. It will be an approach that will contribute significantly to the manufacturing process of cellular products, especially where non-destructive and continuous monitoring is required.

2024-08-08 | GSE256303 | GEO

Accurate image-based CSF volume calculation of the lateral ventricles.

Project description:The size/volume of the brain's ventricles is essential in diagnosing and treating many neurological disorders, with various forms of hydrocephalus being some of the most common. Initial ventricular size and changes, if any, in response to disease progression or therapeutic intervention are monitored by serial imaging methods. Significant variance in ventricular size is readily noted, but small incremental changes can be challenging to appreciate. We have previously reported using artificial intelligence to determine ventricular volume. The values obtained were compared with those calculated using the inaccurate manual segmentation as the "gold standard". This document introduces a strategy to measure ventricular volumes where manual segmentation is not employed to validate the estimations. Instead, we created 3D printed models that mimic the lateral ventricles and measured those 3D models' volume with a tuned water displacement device. The 3D models are placed in a gel and taken to the magnetic resonance scanner. Images extracted from the phantoms are fed to an artificial intelligence-based algorithm. The volumes yielded by the automation must equal those yielded by water displacement to assert validation. Then, we provide certified volumes for subjects in the age range (1-114) months old and two hydrocephalus patients.

| S-EPMC9287564 | biostudies-literature

Oxidative degradation of polyamines by serum supplement causes cytotoxicity on cultured cells.

Project description:Serum is a common supplement for cell culture due to it containing the essential active components for the growth and maintenance of cells. However, the knowledges of the active components in serum are incomplete. Apart from the direct influence of serum components on cultured cells, the reaction of serum components with tested drugs cannot be ignored, which usually results in the false conclusion on the activity of the tested drugs. Here we report the toxicity effect of polyamines (spermidine and spermine) on cultured cells, especially on drug-resistant cancer cell lines, which resulted from the oxidative degradation of polyamines by amine oxidases in serum supplement. Upon adding spermidine or spermine, high concentration of H2O2, an enzyme oxidation product of polyamines, was generated in culture media containing ruminant serum, such as fetal bovine serum (FBS), calf serum, bovine serum, goat serum or horse serum, but not in the media containing human serum. Drug-resistant cancer cell lines showed much higher sensitivity to the oxidation products of polyamines (H2O2 and acrolein) than their wild cell lines, which was due to their low antioxidative capacity.

| S-EPMC6039494 | biostudies-literature

Applying Deep Neural Network Analysis to High-Content Image-Based Assays.

Project description:The etiological underpinnings of many CNS disorders are not well understood. This is likely due to the fact that individual diseases aggregate numerous pathological subtypes, each associated with a complex landscape of genetic risk factors. To overcome these challenges, researchers are integrating novel data types from numerous patients, including imaging studies capturing broadly applicable features from patient-derived materials. These datasets, when combined with machine learning, potentially hold the power to elucidate the subtle patterns that stratify patients by shared pathology. In this study, we interrogated whether high-content imaging of primary skin fibroblasts, using the Cell Painting method, could reveal disease-relevant information among patients. First, we showed that technical features such as batch/plate type, plate, and location within a plate lead to detectable nuisance signals, as revealed by a pre-trained deep neural network and analysis with deep image embeddings. Using a plate design and image acquisition strategy that accounts for these variables, we performed a pilot study with 12 healthy controls and 12 subjects affected by the severe genetic neurological disorder spinal muscular atrophy (SMA), and evaluated whether a convolutional neural network (CNN) generated using a subset of the cells could distinguish disease states on cells from the remaining unseen control-SMA pair. Our results indicate that these two populations could effectively be differentiated from one another and that model selectivity is insensitive to batch/plate type. One caveat is that the samples were also largely separated by source. These findings lay a foundation for how to conduct future studies exploring diseases with more complex genetic contributions and unknown subtypes.

| S-EPMC6710615 | biostudies-literature

Intra-beat biomarker for accurate continuous non-invasive blood pressure monitoring.

Project description:Accurate continuous non-invasive blood pressure (CNIBP) monitoring is the holy grail of digital medicine but remains elusive largely due to significant drifts in signal and motion artifacts that necessitate frequent device recalibration. To address these challenges, we developed a unique approach by creating a novel intra-beat biomarker (Diastolic Transit Time, DTT) to achieve highly accurate blood pressure (BP) estimations. We demonstrated our approach's superior performance, compared to other common signal processing techniques, in eliminating stochastic baseline wander, while maintaining signal integrity and measurement accuracy, even during significant hemodynamic changes. We applied this new algorithm to BP data collected using non-invasive sensors from a diverse cohort of high acuity patients and demonstrated that we could achieve close agreement with the gold standard invasive arterial line BP measurements, for up to 20 min without recalibration. We established our approach's generalizability by successfully applying it to pulse waveforms obtained from various sensors, including photoplethysmography and capacitive-based pressure sensors. Our algorithm also maintained signal integrity, enabling reliable assessments of BP variability. Moreover, our algorithm demonstrated tolerance to both low- and high-frequency motion artifacts during abrupt hand movements and prolonged periods of walking. Thus, our approach shows promise in constituting a necessary advance and can be applied to a wide range of wearable sensors for CNIBP monitoring in the ambulatory and inpatient settings.

| S-EPMC9537243 | 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