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55 results for “In vitro testing”
An inflamed human alveolar model for testing the efficiency of anti-inflammatory drugs in vitro
<p>The data set accompanies the study where we developed an inflamed human alveolar epithelium model and to test the resolution<strong><em> </em></strong>lipopolysaccharide (LPS)-induced inflammation <em>in vitro</em> with a corticosteroid, methylprednisolone (MP). A specific focus of the study was in macrophage phenotype shifts in response to these stimuli.</p> <p>The data set includes:</p> <p>- Pro-inflammatory marker (interleukin (IL)-8, tumor necrosis factor α (TNFα), IL1β) secretion data, analysed via ELISA, and cell viability (analysed via lactate dehydrogenase assay) of both monocultures (human monocyte-derived macrophages) and of the multicellular human alveolar model, composed of macrophages, dendritic cells, and epithelial cells. </p> <p>- Barrier permeability data of the multicellular model, assessed via labeled-dextran permeability assay. </p> <p>All the above-stated data is joined in the file: DraslerB_Frontiers 2020_Inflammatory model. Sample codes are explained int he first tabs. </p> <p>- Pro-inflammatory marker gene expression data of the multicellular model, assessed via real time RT-qPCR. The data prepared for analysis and analysed is joined to the above-mentioned folder, whereas the direct PCR runs are joined in the file: DraslerB_Frontiers 2020_Inflammatory model_PCR runs. </p> <p>- Confocal laser scanning microscopy raw files (lsm) of the multicellular model can be opened with an open source software Fiji, based on ImageJ. </p>
JRC COVID-19 In Vitro Diagnostic Devices and Test Methods Database
<p>SUMMARY</p> <p>The <em>JRC COVID-19 In Vitro Diagnostic Devices and Test Methods Database</em>, aimed to collect in a single place all publicly available information on performance of CE-marked <em>in vitro</em> diagnostic medical devices (IVDs) as well as <em>in house</em> laboratory-developed devices and related test methods for COVID-19, is here presented. The database, manually curated and regularly updated, has been developed as a follow-up to the Communication from the European Commission “Guidelines on <em>in vitro</em> diagnostic tests and their performance” of 15 April 2020 and is freely accessible at <a href="https://covid-19-diagnostics.jrc.ec.europa.eu/">https://covid-19-diagnostics.jrc.ec.europa.eu/</a>.</p>
[DATASET] Design and characterization of an RF applicator for in vitro tests of electromagnetic hyperthermia doi.org/10.3390/s22103610
<p>[DATASET] Design and characterization of an RF applicator for in vitro tests of electromagnetic hyperthermia <a href="https://doi.org/10.3390/s22103610">doi.org/10.3390/s22103610</a></p> <p>The data used in the paper are dived in separate folder for each published figure.</p>
Fig. 1 in 17,20β-P and cortisol are the main in vitro metabolites of 17-hydroxyprogesterone produced by spermiating testes of Micropogonias furnieri (Desmarest, 1823) (Perciformes: Sciaenidae)
Fig. 1. Radiochromatogram after TLC analysis of spermiating testes of Micropogonias furnieri males 1, 2 and 3 after toluene/cyclohexane 50/50 v/v (system I) and benzene/acetone 80/20 v/v (system II). The TLC zones further analyzed by HPLC are shown as A, B and C. The peak of precursor is shown as D. The authentic standards used were: 1 = 20-dihydrocortisone; 2 = 17,20,21-P; 3 = 17,20α-P; 4 = 11KT; 5 = 17,20ss-P; 6 = 11ssOH-A; 7 = Ad; 8 = testosterone; 9 = 17-P; 10 = A.
Underlying data for "Microscale 3D Liver Bioreactor for In Vitro Hepatotoxicity Testing under Perfusion Conditions"
<p>Underlying data for the paper "Microscale 3D Liver Bioreactor for In Vitro Hepatotoxicity Testing under Perfusion Conditions" published in the journal <em>Bioengineering</em>.</p>
Fig. 1. The Kruskal-Wallis rank sum test for the boxplot returned a in Comparison of in vitro methods to inhibit growth of a virulent strain of Batrachochytrium dendrobatidis (Longcore, Pessier, and Nichols 1999)
Fig. 1. The Kruskal-Wallis rank sum test for the boxplot returned a chi-squared value = 2, degrees of freedom (df) = 2, and P = 0.3679. The Wilcoxon rank sum test for the positive control and the highest concentration of amphotericin B returned W = 9, P = 0.1. These analyses show that the alternative hypothesis is true and assumes that there is information in the magnitudes and signs of the differences between paired observations, because the mean (location shift) is not equal to 0. Observed differences in mean cell count between the three groups (0.0, 1.6, and 3.2 µg/mL) are not statistically significant (P> 0.05).
Systematic Scoping Literature Review of Embryonic Stem Cells In Vitro Developmental Toxicity Tests: Included publications library
<p>The publications included in the systematic scoping review conducted according to the protocol:<a href="https://zenodo.org/record/2528920">https://zenodo.org/record/2528920</a></p> <p> </p>
In vitro genotoxicity testing using γH2AX biomarker, Microscopy Dataset
<p>The Dataset was used and is supplementary to the paper "<em>In vitro genotoxicity testing using γH2AX biomarker, microscopy and automatic image analysis in ImageJ - a pilot study with valinomycin</em>". It contains both RAW single-channel images and numerical results obtained with BioImage Analysis and evaluation available through the GitHub repository: <a href="https://github.com/martinschatz-cz/genotoxicity-bia">https://github.com/martinschatz-cz/genotoxicity-bia</a>.</p> <p><strong>Naming Convention for images</strong><br> ChannelName_YYYYMMD_Well_PossitionInWell_AcqRun.tiff</p> <p><strong>Naming Convention for results</strong><br> Well_AllResults_YYYY-MM-DD_Results.csv</p> <p>The csv are ‘,’ separated, and automatically named by analysis script.</p> <p><br> </p> <p><strong>Folder Structure</strong></p> <ul> <li> <p>Images (1069 files, as Images.zip)</p> <ul> <li> <p>4H - all images for all wells</p> </li> <li> <p>24H - all images for all wells</p> </li> </ul> </li> <li> <p>Results (36 files)</p> <ul> <li> <p>Results_4H (as Results_4h.zip)</p> </li> <li> <p>Results_24H (as Results_24h.zip)</p> </li> </ul> </li> </ul> <p> </p> <p><strong>Measurement Settings</strong></p> <ul> <li> <p>Manufacturer and model of microscope: Olympus IX83 P2ZF</p> </li> <li> <p>Objective lens magnification, NA: 10x Olympus IX3 Nosepiece, LensNA=0.3</p> </li> <li> <p>Excitation filters (mounted in the light source)</p> <ul> <li> <p>Violet: 395/25nm LED module 1, DAPI</p> </li> <li> <p>Green: 555/28nm LED module 5, Cy3</p> </li> </ul> </li> <li> <p>Quad band filter set for DAPI/FITC/Cy3/Cy5</p> </li> <li> <p>Quad band polychroic mirror (mounted in the filter turret):</p> <ul> <li> <p>BP 411-454nm,</p> </li> <li> <p>BP 495-536nm,</p> </li> <li> <p>BP 577-617nm</p> </li> <li> <p>BP 655-810nm</p> </li> </ul> </li> <li> <p>Emission filters (mounted in the fast emission filter wheel, infront the camera):</p> <ul> <li> <p>DAPI: BP 421-445nm</p> </li> <li> <p>Cy3: BP 581-619nm</p> </li> </ul> </li> <li> <p>Illumination light source: Lumencor Lumencor Spectra X Lamp</p> </li> <li> <p>Pixel size: 650nm x 650nm</p> </li> <li> <p>Camera manufacturer and model: Hamamatsu ORCA-Flash4.0</p> </li> <li> <p>Software program(s) and version: OLYMPUS cellSens Dimension 3.2 (Build 23706)</p> </li> <li> <p>Image acquisition settings </p> <ul> <li> <p>expposure 500 ms</p> </li> <li> <p>gain: 0</p> </li> <li> <p>binning: 4 x 4</p> </li> </ul> </li> <li> <p>Experiment manager: ZDC + autofocus, two channels: DAPI and Cy3</p> </li> </ul> <p> </p> <p><strong>Image Processing and Analysis</strong><br> The data analysis workflow consists of several stages, each of which was executed by a specific script. Firstly, the raw data were manually cleaned and automatically sorted and organized using <em>sort_wells.ijm</em> in FIJI. Secondly, image analysis was performed using <em>Process_WFolder_macro_v1.ijm</em> in FIJI, which processed the image data and extracted the relevant features. Finally, the results were further processed using S<em>F_dataVis_and_statistics_mean_XYh.ipynb</em> in Python (Jupyter Notebook), which generated the final output in the form of a CSV file.</p> <p> </p> <p>In this repository, you can access the resulting CSV file, which contains the final results of our analysis. Additionally, we have provided the scripts used to process the data, which are available on our GitHub repository (LINK). You will find instruction how to create local Jupyter Hub for Python scripts. These scripts are accompanied by a short manual that provides an overview of the data analysis workflow and helps users navigate through the code. By making our scripts available, we hope to facilitate transparency and reproducibility of our research. If you encounter any issues, please report them through the GitHub repository: <a href="https://github.com/martinschatz-cz/genotoxicity-bia">https://github.com/martinschatz-cz/genotoxicity-bia</a>.</p> <p>We believe that our work can be useful for other researchers and analysts who are interested in studying similar datasets. We invite you to explore the contents of this repository and use the data and scripts provided here to further your research.</p> <p> </p> <p><strong>Cell lines and culture conditions</strong><br> Human cervical adenocarcinoma (HeLa) and a Chinese hamster ovary (CHO-K1) cell lines were obtained from American Type Culture Collection (ATCC). The HeLa cells were grown MEM supplemented with 10 % FBS and NEAA. CHO-K1 cells were cultivated with DMEM supplemented with L-proline (final concentration 35 mg/l). The cell incubation took place in a humidified atmosphere of 5% CO2 at 37 °C.</p> <p> </p> <p><strong>Direct measurement of DNA DSBs</strong><br> The cells were seeded in concentration 0,5 × 105 cells/ml into the 96-well plate (VWR, 10062-900). The cells were rinsed by phosphate buffered saline (PBS;) after 24h incubation, and medium with reduced FBS content (5 %) was added. Valinomycin was dissolved in DMSO and added to cells in two final concentrations (30 and 15 𝞵M). After 4h/24h incubation the visualization was done using and following protocol of HCS DNA Damage Kit. The cells were fixed by 4% paraformaldehyde solution for 15 min at room temperature. The cells were rinsed once by PBS and the permeabilization was performed using Triton® X-100 () solution by incubation for 15 min at room temperature. The wells were rinsed with PBS once and the plate was blocked by 1% BSA blocking solution. After 1 hour incubation at room temperature the blocking solution was removed and 100 𝞵l of pH2AX mouse monoclonal antibody solution (1:1000 in BSA) was pipetted into each well incubated for 1 hour at room temperature. After three times rinsing by PBS the 100 𝞵l of Alexa Fluor® 555 goat anti-mouse IgG (H+L; 1:2000) and Hoechst 33342 (1:6000) solution was incubated for 1 hour at room temperature protected from light. After the incubation the wells were rinsed three times by PBS. The plate was stored with 100 𝞵l in the refrigerator (4 °C) until the image analysis was performed.</p>
Results of the mechanical characterization by tensile tests and the in vitro cell-biomaterial interaction analyses by WST-1 and Live/Dead of 3D-printed scaffolds generated by PLA, PCL, FF, FD and GelMA
<p>Dataset containing the quantitative results of the mechanical characterization, and the in vitro cell-biomaterial interaction analyses with neural cells after 72 hours and 7 days of cell culture of the following 3D printed scaffolds:</p> <ul> <li>Polylactic acid (PLA)</li> <li>Polycaprolactone (PCL)</li> <li>Conductive Filaflex (FF)</li> <li>Flexdym (FD)</li> <li>GelMA (G)</li> </ul> <p>The Live/Dead results were quantified using ImageJ software to determine area fractions corresponding to live (green) and dead (red) cells.</p>
Fig. 1 Screening flow, testing 1600 FDA compounds against S in Assessment of FDA-approved drugs against StrongyloideS rAtti in vitro and in vivo to identify potentially active drugs against strongyloidiasis
Fig. 1 Screening flow, testing 1600 FDA compounds against S. ratti
Evaluation of in vitro genotoxicity tests
<p>In human health risk assessment of chemicals and pharmaceuticals, assessment of genetic toxicity for regulatory purposes usually starts with a standard battery of in vitro genotoxicity tests. This battery is needed to cover the different genetic toxicity endpoints. The tests included in the battery (partly) differ in biology, due to which resulting data may seem contradictory, thereby complicating accurate interpretation of the findings. This could be overcome through application of mathematical modelling. One of the advantages of mathematical modelling is that strengths and weaknesses of each test are taken into account. Furthermore, the generated predictions are objective and inform on the associated uncertainties. This approach was explored by the working group “Predictivity of In Vitro Genotoxicity Testing”, formed in the context of the 8th International Workshop on Genotoxicity Testing (IWGT). We applied mathematical modelling to a database with (partly) publicly available in vitro and in vivo data for genotoxicity. The results indicate that a mammalian in vitro clastogenicity test and a mammalian cell gene mutation test together provide the strongest weight-of-evidence for predicting genotoxic potential. Remarkably, the Ames bacterial mutation test appeared to contribute very little to these predictions when used in combination with in vitro genetic toxicity tests using cells of mammalian origin. Further research comparing additional in vitro genotoxicity data with in vivo data will provide additional insights whether it is indeed time to reconsider the composition of the standard in vitro genotoxicity battery.</p>
Transcriptomic characterization of 2D and 3D human induced pluripotent stem cell-based in vitro models as New Approach Methodologies for developmental neurotoxicity testing
<p><strong>Abstract:</strong> The safety and developmental neurotoxicity (DNT) potential of chemicals remain critically understudied due to limitations of current in vivo testing guidelines, which are low throughput, resource-intensive, and hindered by species differences that limit their relevance to human health. To address these issues, robust new approach methodologies (NAMs) using deeply characterized cell models are essential. This study presents the comprehensive transcriptomic characterization of two advanced human-induced pluripotent stem cell (hiPSC)-derived models: a 2D adherent and a 3D neurosphere model of human neural progenitor cells (hiNPCs) differentiated up to 21 days. Using high-throughput RNA sequencing, we compared gene expression profiles of 2D and 3D models at three developmental stages (3, 14, and 21 days of differentiation). Both models exhibit maturation towards post-mitotic neurons, with the 3D model maturing faster and showing a higher prevalence of GABAergic neurons, while the 2D model is enriched with glutamatergic neurons. Both models demonstrate broad applicability domains, including excitatory and inhibitory neurons, astrocytes, and key endocrine and especially the understudied cholinergic receptors. Comparison with human fetal brain samples confirms their physiological relevance. This study provides novel in-depth applicability insights into the temporal and dimensional aspects of hiPSC-derived neural models for DNT testing. The complementary use of these two models is highlighted: the 2D model excels in synaptogenesis assessment, while the 3D model is particularly suited for neural network formation as observed as well in previous functional studies with these models. This research marks a significant advancement in developing human-relevant, high-throughput DNT assays for regulatory purposes.</p> <p><strong>This data sets contains:</strong></p> <p><strong>Tab. S1</strong> - Significant genes results</p> <p><strong>Tab. S2</strong> - Enriched pathways_GO_Biological Processes</p> <p><strong>Tab. S3</strong> - Enriched pathways_GO_Cellular Components</p> <p><strong>Tab. S4</strong> - Enriched pathways_GO_Molecular Function</p> <p><strong>Tab. S5</strong> - Enriched pathways_KEGG</p> <p><strong>Tab. S6</strong> - EnrichEnriched pathways_Panther</p> <p><strong>Tab. S7</strong> - Enriched pathways_Reactome</p> <p><strong>Tab. S8</strong> - Gene counts</p> <p><strong>Tab. S9</strong> - Gene selection for targeted analysis</p>
Test data for "Imaging of cellular dynamics in vitro and in situ: from a whole organism to sub-cellular imaging with self-driving, multi-scale microscopy"
<p>This repository contains test data associated with analysis code of low- and high-resolution self-driving multi-scale data from our manuscript "Imaging of cellular dynamics <em>in vitro</em> and <em>in situ</em>: from a whole organism to sub-cellular imaging with self-driving, multi-scale microscopy"</p> <p>by Stephan Daetwyler, Hanieh Mazloom-Farsibaf, Felix Y. Zhou, Dagan Segal, Etai Sapoznik, Bingying Chen, Jill M. Westcott, Rolf A. Brekken, Gaudenz Danuser and Reto Fiolka</p> <p> </p> <p>Code repository: <a href="https://github.com/DaetwylerStephan/multi-scale-image-analysis">https://github.com/DaetwylerStephan/multi-scale-image-analysis</a></p> <p>Documentation: <a href="https://daetwylerstephan.github.io/multi-scale-image-analysis/">https://daetwylerstephan.github.io/multi-scale-image-analysis/</a></p> <p>Preprint: <a href="https://www.biorxiv.org/content/10.1101/2024.02.28.582579v1.full">https://www.biorxiv.org/content/10.1101/2024.02.28.582579v1.full</a></p>
The Path from Nasal Tissue to Nasal Mucosa on Chip Part 2- Advanced Microfluidic Nasal In Vitro Model for Drug Absorption Testing
<p><strong>Abstract: </strong>The nasal mucosa, being accessible and highly vascularized, opens up new opportunities for the systemic administration of drugs. However, due to several protective functions like the mucociliary clearance, this physiological barrier is a difficult obstacle for drug candidates to overcome. For this reason, effective testing procedures are required in the preclinical phase of pharmaceutical development. Based on a recently reported immortalized porcine nasal epithelial cell line, we developed a test platform based on a tissue-compatible microfluidic chip. A biomimetic glass chip equipped with a controlled bidirectional airflow to induce a physiologically relevant wall shear stress on the epithelial cell layer was microfabricated. By developing a membrane transfer technique, the epithelial cell layer could be pre-cultivated in a static holder prior to cultivation in the microfluidic environment. The dynamic cultivation within the chip showed a homogenous distribution of the mucus film on top of the cell layer and a significant increase of cilia formation compared to static cultivation condition. In addition, the recording of the ciliary transport mechanism by micro particle image velocimetry was successful. Using FITC-dextran 4000 as an example, it was shown that this nasal mucosa on a chip is suitable for permeation studies. The obtained permeation coefficient was in the range of values determined by means of other established in vitro and in vivo models. The novel nasal mucosa on chip can in future be automated and used as a substitute for animal testing.</p>
In Vitro Diagnostic Test for DOAC in Urine
ClinicalTrials.gov study NCT03182829. IPD Sharing: NO. Countries: 1. Publications: 5.
Uso Racional dos Testes de Diagnóstico in vitro
<p><span>A importância central dos testes de diagnóstico <em>in vitro</em> (DIV) e da informação por eles proporcionada é hoje inquestionável, constituindo-se numa ferramenta essencial na prática clínica, influenciando entre 60-70% das decisões clínicas. São ainda requeridos por cerca de 80% das <em>guidelines</em> clínicas para estabelecer um diagnóstico ou gerir o processo de doença ou via terapêutica (<em>Clinical Pathway</em>). Por outro lado, a evidência recente sugere que aproximadamente 25-40% dos testes solicitados são de alguma forma questionáveis num determinado contexto clínico, e que até 30% podem ser considerados inapropriados. Num contexto de recursos financeiros limitados, torna-se por isso uma prioridade do laboratório clínico a implementação de estratégias de uso racional de uma forma holística e que inclua as partes interessadas relevantes. Apresenta-se como modelo a <em>guideline</em> CLSI-49 e incluem-se propostas de melhoria que qualquer laboratório clínico pode perseguir.</span></p>
Identifying in vitro toxicity testing approaches for (novel) proteins in the context of food and feed risk assessment
<p>Annexes to EFSA external scientific report Identifying <em>in vitro</em> toxicity testing approaches for (novel) proteins in the context of food and feed risk assessment</p>
Evaluation of in vitro rat and human airway epithelial models for acute inhalation toxicity testing
<p><em>In vivo</em> models (mostly rodents) are currently accepted by regulatory authorities for assessing acute inhalation toxicity. Considerable efforts have been made in recent years to evaluate in vitro human airway epithelial models (HAEM) as replacements for <em>in vivo</em> testing. In the current work, an organotypic <em>in vitro</em> rat airway epithelial model (RAEM), rat EpiAirway™, was developed and characterized to allow a direct comparison with the available HAEM, human EpiAirway™, in order to address potential interspecies variability in responses to harmful agents. The rat and human models were evaluated in two independent laboratories with 14 reference chemicals, selected to cover a broad range of chemical structures and reactive groups, as well as known acute animal and human toxicity responses, in three replicate rounds of experiments. Toxicity endpoints included changes in tissue viability (MTT assay), epithelial barrier integrity (TEER, transepithelial electrical resistance), and tissue morphology (histopathology). The newly developed rat EpiAirway™ model produced reproducible results across all replicate experiments in both testing laboratories. Furthermore, a high level of concordance was observed between the RAEM and HAEM toxicity responses (determined by IC<sub>25</sub>) in both laboratories, with R<sup>2</sup> = 0.78 and 0.88 when analyzed by TEER; and R<sup>2</sup> = 0.92 for both when analyzed by MTT. These results indicate that rat and human airway epithelial tissues respond similarly to acute exposures to chemicals. The new in vitro RAEM will help extrapolate to<em> in vivo</em> rat toxicity responses and support screening as part of a 3Rs program.</p>
Evaluation of in Vitro Devices on Self-collected Vaginal Swab and Urine Sample for Testing of Human Papilloma Virus
ClinicalTrials.gov study NCT04312737. IPD Sharing: Not stated. Countries: 3. Publications: 1.
In-vitro Diagnostic Test to Predict COVID-19 Mortality and Disease Severity
ClinicalTrials.gov study NCT04368897. IPD Sharing: NO. Countries: 1. Publications: 4.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.