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Articles de revues sur le sujet « 3D cell »

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Auteur : Grafiati
Publié le 14 mars 2023

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1

Bikmulina, Polina, Nastasia Kosheleva, Yuri Efremov, Artem Antoshin, Zahra Heydari, Valentina Kapustina, Valery Royuk et al. « 3D or not 3D : a guide to assess cell viability in 3D cell systems ». Soft Matter 18, no 11 (2022) : 2222–33. http://dx.doi.org/10.1039/d2sm00018k.

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The study aims at revealing the influence of particular 3D cell systems’ parameters such as the components’ concentration, gel thickness, cell density, on the cell viability and applicability of standard assays based on different cell properties.
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Ylostalo, Joni H. « 3D Stem Cell Culture ». Cells 9, no 10 (27 septembre 2020) : 2178. http://dx.doi.org/10.3390/cells9102178.

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Much interest has been directed towards stem cells, both in basic and translational research, to understand basic stem cell biology and to develop new therapies for many disorders. In general, stem cells can be cultured with relative ease, however, most common culture methods for stem cells employ 2D techniques using plastic. These cultures do not well represent the stem cell niches in the body, which are delicate microenvironments composed of not only stem cells, but also supporting stromal cells, extracellular matrix, and growth factors. Therefore, researchers and clinicians have been seeking optimal stem cell preparations for basic research and clinical applications, and these might be attainable through 3D culture of stem cells. The 3D cultures recapitulate the in vivo cell-to-cell and cell-to-matrix interactions more effectively, and the cells in 3D cultures exhibit many unique and desirable characteristics. The culture of stem cells in 3D may employ various matrices or scaffolds, in addition to the cells, to support the complex structures. The goal of this Special Issue is to bring together recent research on 3D cultures of various stem cells to increase the basic understanding of stem cells and culture techniques, and also highlight stem cell preparations for possible novel therapeutic applications.
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Souza, Rhonda F., Robert E. Schwartz et Hiroshi Mashimo. « Esophageal stem cells and 3D-cell culture models ». Annals of the New York Academy of Sciences 1232, no 1 (septembre 2011) : 316–22. http://dx.doi.org/10.1111/j.1749-6632.2011.06070.x.

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Sapet, Cédric, Cécile Formosa, Flavie Sicard, Elodie Bertosio, Olivier Zelphati et Nicolas Laurent. « 3D-fection : cell transfection within 3D scaffolds and hydrogels ». Therapeutic Delivery 4, no 6 (juin 2013) : 673–85. http://dx.doi.org/10.4155/tde.13.36.

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Kiberstis, P. A. « Heart Cell Signaling in 3D ». Science Signaling 3, no 115 (30 mars 2010) : ec93-ec93. http://dx.doi.org/10.1126/scisignal.3115ec93.

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Bouchet, Benjamin P., et Anna Akhmanova. « Microtubules in 3D cell motility ». Journal of Cell Science 130, no 1 (1 janvier 2017) : 39–50. http://dx.doi.org/10.1242/jcs.189431.

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Harunaga, Jill S., et Kenneth M. Yamada. « Cell-matrix adhesions in 3D ». Matrix Biology 30, no 7-8 (septembre 2011) : 363–68. http://dx.doi.org/10.1016/j.matbio.2011.06.001.

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Glaser, Vicki. « Novel 3D Cell Culture Systems ». Genetic Engineering & ; Biotechnology News 33, no 16 (15 septembre 2013) : 1, 22, 24–25. http://dx.doi.org/10.1089/gen.33.16.09.

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Even-Ram, Sharona, et Kenneth M. Yamada. « Cell migration in 3D matrix ». Current Opinion in Cell Biology 17, no 5 (octobre 2005) : 524–32. http://dx.doi.org/10.1016/j.ceb.2005.08.015.

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Rangarajan, Rajagopal, et Muhammad H. Zaman. « Modeling cell migration in 3D ». Cell Adhesion & ; Migration 2, no 2 (avril 2008) : 106–9. http://dx.doi.org/10.4161/cam.2.2.6211.

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Yamada, Kenneth M., et Michael Sixt. « Mechanisms of 3D cell migration ». Nature Reviews Molecular Cell Biology 20, no 12 (3 octobre 2019) : 738–52. http://dx.doi.org/10.1038/s41580-019-0172-9.

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Khoruzhenko, A. I. « 2D- and 3D-cell culture ». Biopolymers and Cell 27, no 1 (20 janvier 2011) : 17–24. http://dx.doi.org/10.7124/bc.00007d.

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Shamloo, Amir, et Leyla Amirifar. « A microfluidic device for 2D to 3D and 3D to 3D cell navigation ». Journal of Micromechanics and Microengineering 26, no 1 (30 novembre 2015) : 015003. http://dx.doi.org/10.1088/0960-1317/26/1/015003.

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Ravi, Maddaly, Aishwarya Pargaonkar, Anuradha Ramesh, Gatika Agrawal, Jennifer Sally, SriVijayaGanapathy Srinivasan et Abhishek Kalra. « Three-dimensional prints from 3-dimensional cell culture aggregates of human cancer cell lines ». Sri Ramachandra Journal of Health Sciences 1 (24 décembre 2021) : 10–15. http://dx.doi.org/10.25259/srjhs_5_2021.

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Objectives: Three-dimensional (3D) printing has gained significance for human health-care applications in recent years. Some of these applications include obtaining models which mimic anatomical parts. One other parallel development in the biological research area is the development of 3D cell cultures. Such cultures are now becoming the material of choice for in vitro experiments, fast replacing the traditional adherent/monolayer 2D culture approaches. We present here, a method to obtain 3D prints of 3D aggregates of three human cancer cell lines. Such 3D prints can be useful models to understand solid tumor morphologies and also as effective teaching models. Materials and Methods: Photomicrographs of the 3D aggregates of the human cancer cell lines SiHa, MCF-7, and A549 (human cervical cancer, breast cancer, and non-small cell lung cancer cell lines, respectively) were obtained using inverted phase contrast microscopy. Conversion of normal jpeg images into 3D files was performed using the lithophane method and CAD files obtained. The CAD files thus generated were used to print the objects using the Stratasys Polyjet J750 3D Printer. Results: We could obtain 3D prints of SiHa, MCF-7, and A549 (human cervical cancer, breast cancer, and non-small cell lung cancer cell lines, respectively) 3D aggregates/spheroids. Conclusion: It is hoped that this approach will be useful for studying solid tumor morphologies in finer details. Furthermore, other benefits of such 3D prints would be in them being excellent models for teaching purposes.
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Pan, Yuxiang, Ning Hu, Xinwei Wei, Lin Gong, Bin Zhang, Hao Wan et Ping Wang. « 3D cell-based biosensor for cell viability and drug assessment by 3D electric cell/matrigel-substrate impedance sensing ». Biosensors and Bioelectronics 130 (avril 2019) : 344–51. http://dx.doi.org/10.1016/j.bios.2018.09.046.

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Rimann, Markus, Brigitte Angres, Isabel Patocchi-Tenzer, Susanne Braum et Ursula Graf-Hausner. « TEDD – Innovation Network for 3D Cell Cultivation 3D Cell Culture is Ready for Drug Development ». CHIMIA International Journal for Chemistry 67, no 11 (27 novembre 2013) : 822–24. http://dx.doi.org/10.2533/chimia.2013.822.

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Bauer, Magdalena, Magdalena Metzger, Marvin Corea, Barbara Schädl, Johannes Grillari et Peter Dungel. « Novel 3D-Printed Cell Culture Inserts for Air–Liquid Interface Cell Culture ». Life 12, no 8 (10 août 2022) : 1216. http://dx.doi.org/10.3390/life12081216.

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In skin research, widely used in vitro 2D monolayer models do not sufficiently mimic physiological properties. To replace, reduce, and refine animal experimentation in the spirit of ‘3Rs’, new approaches such as 3D skin equivalents (SE) are needed to close the in vitro/in vivo gap. Cell culture inserts to culture SE are commercially available, however, these inserts are expensive and of limited versatility regarding experimental settings. This study aimed to design novel cell culture inserts fabricated on commercially available 3D printers for the generation of full-thickness SE. A computer-aided design model was realized by extrusion-based 3D printing of polylactic acid filaments (PLA). Improvements in the design of the inserts for easier and more efficient handling were confirmed in cell culture experiments. Cytotoxic effects of the final product were excluded by testing the inserts in accordance with ISO-norm procedures. The final versions of the inserts were tested to generate skin-like 3D scaffolds cultured at an air–liquid interface. Stratification of the epidermal component was demonstrated by histological analyses. In conclusion, here we demonstrate a fast and cost-effective method for 3D-printed inserts suitable for the generation of 3D cell cultures. The system can be set-up with common 3D printers and allows high flexibility for generating customer-tailored cell culture plastics.
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Wu, Pei-Hsun, Daniele M. Gilkes et Denis Wirtz. « The Biophysics of 3D Cell Migration ». Annual Review of Biophysics 47, no 1 (20 mai 2018) : 549–67. http://dx.doi.org/10.1146/annurev-biophys-070816-033854.

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Three-dimensional (3D) cell culture systems have gained increasing interest not only for 3D migration studies but also for their use in drug screening, tissue engineering, and ex vivo modeling of metastatic behavior in the field of cancer biology and morphogenesis in the field of developmental biology. The goal of studying cells in a 3D context is to attempt to more faithfully recapitulate the physiological microenvironment of tissues, including mechanical and structural parameters that we envision will reveal more predictive data for development programs and disease states. In this review, we discuss the pros and cons of several well-characterized 3D cell culture systems for performing 3D migration studies. We discuss the intracellular and extracellular signaling mechanisms that govern cell migration. We also describe the mathematical models and relevant assumptions that can be used to describe 3D cell movement.
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Mehl, Benjamin T., et R. Scott Martin. « Integrating 3D cell culture of PC12 cells with microchip-based electrochemical detection ». Analytical Methods 11, no 8 (2019) : 1064–72. http://dx.doi.org/10.1039/c8ay02672f.

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Xu, Zhongjuan, Xingzhi Liu, Yu Wei, Zhe Zhao, Junjun Cao, Yong Qiao, Yanzhen Yu, Junjie Zhong et Guangli Suo. « Mesenchymal stem cell spheroids : potential cell materials for cell therapy ». STEMedicine 2, no 5 (13 décembre 2020) : e67. http://dx.doi.org/10.37175/stemedicine.v2i5.67.

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Mesenchymal stromal/stem cells (MSCs) have been applied in clinical trials with an increasing number in recent years. MSCs showed their great potentials in regenerative medicine for their extensive sources, multilineage differentiation potential, low immunogenicity and self-renewal ability. However, the clinical application of MSCs still confronts many challenges including the requirement of large quantity of cells, low survival ability in vivo and the loss of main original characteristics due to two-dimensional (2D) culture although it is beneficial to cells fast expansion. Three-dimensional (3D) culture artificially creates an environment that permits cells to grow or interact with their surroundings in all three dimensions. Therefore, 3D culture was widely regarded as a more preferable and closer physiological microenvironment for cells growth. Recently, many different 3D spheroid culture methods have been developed to optimize MSCs biological characteristics to meet the demand of regenerative medicine. In this review, we comprehensively discussed the merits and demerits of different spheroid formation methods, expounded the mechanisms of spheroid formation and its microenvironment, and illustrated their optimized biological functions and the pre-clinical applications in various tissue injury and regeneration. In the end, we prospected the trends of this research field and proposed the key problems needed to be solved in the future.
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Alföldi, Balog, Faragó, Halmai, Kotogány, Neuperger, Nagy, Fehér, Szebeni et Puskás. « Single Cell Mass Cytometry of Non-Small Cell Lung Cancer Cells Reveals Complexity of In vivo And Three-Dimensional Models over the Petri-dish ». Cells 8, no 9 (16 septembre 2019) : 1093. http://dx.doi.org/10.3390/cells8091093.

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Single cell genomics and proteomics with the combination of innovative three-dimensional (3D) cell culture techniques can open new avenues toward the understanding of intra-tumor heterogeneity. Here, we characterize lung cancer markers using single cell mass cytometry to compare different in vitro cell culturing methods: two-dimensional (2D), carrier-free, or bead-based 3D culturing with in vivo xenografts. Proliferation, viability, and cell cycle phase distribution has been investigated. Gene expression analysis enabled the selection of markers that were overexpressed: TMEM45A, SLC16A3, CD66, SLC2A1, CA9, CD24, or repressed: EGFR either in vivo or in long-term 3D cultures. Additionally, TRA-1-60, pan-keratins, CD326, Galectin-3, and CD274, markers with known clinical significance have been investigated at single cell resolution. The described twelve markers convincingly highlighted a unique pattern reflecting intra-tumor heterogeneity of 3D samples and in vivo A549 lung cancer cells. In 3D systems CA9, CD24, and EGFR showed higher expression than in vivo. Multidimensional single cell proteome profiling revealed that 3D cultures represent a transition from 2D to in vivo conditions by intermediate marker expression of TRA-1-60, TMEM45A, pan-keratin, CD326, MCT4, Gal-3, CD66, GLUT1, and CD274. Therefore, 3D cultures of NSCLC cells bearing more putative cancer targets should be used in drug screening as the preferred technique rather than the Petri-dish.
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Yang, L., G. Trivedi, A. F. Adcock et W. Tyson. « Cell-Based Sensing : From 2D to 3D Cell Culture ». ECS Transactions 64, no 1 (12 août 2014) : 125–32. http://dx.doi.org/10.1149/06401.0125ecst.

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Tasnadi, Ervin A., Timea Toth, Maria Kovacs, Akos Diosdi, Francesco Pampaloni, Jozsef Molnar, Filippo Piccinini et Peter Horvath. « 3D-Cell-Annotator : an open-source active surface tool for single-cell segmentation in 3D microscopy images ». Bioinformatics 36, no 9 (17 janvier 2020) : 2948–49. http://dx.doi.org/10.1093/bioinformatics/btaa029.

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Abstract Summary Segmentation of single cells in microscopy images is one of the major challenges in computational biology. It is the first step of most bioimage analysis tasks, and essential to create training sets for more advanced deep learning approaches. Here, we propose 3D-Cell-Annotator to solve this task using 3D active surfaces together with shape descriptors as prior information in a semi-automated fashion. The software uses the convenient 3D interface of the widely used Medical Imaging Interaction Toolkit (MITK). Results on 3D biological structures (e.g. spheroids, organoids and embryos) show that the precision of the segmentation reaches the level of a human expert. Availability and implementation 3D-Cell-Annotator is implemented in CUDA/C++ as a patch for the segmentation module of MITK. The 3D-Cell-Annotator enabled MITK distribution can be downloaded at: www.3D-cell-annotator.org. It works under Windows 64-bit systems and recent Linux distributions even on a consumer level laptop with a CUDA-enabled video card using recent NVIDIA drivers. Supplementary information Supplementary data are available at Bioinformatics online.
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UMEZU, Shinjiro, Tomohiko AOKI et Hitoshi OHMORI. « Patterning collagen for 3D cell structures ». Journal of Advanced Science 24, no 1+2 (2012) : 11–15. http://dx.doi.org/10.2978/jsas.24.11.

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Huang, John. « 3D Cell Culture On VitroGel System ». Cytology and Tissue Biology 6, no 1 (1 juillet 2019) : 1–10. http://dx.doi.org/10.24966/ctb-9107/s1001.

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Vogt, Nina. « Super-resolution 3D live cell imaging ». Nature Methods 18, no 3 (mars 2021) : 232. http://dx.doi.org/10.1038/s41592-021-01096-5.

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Helena Macedo, Maria, Ana Baião, Soraia Pinto, Andreia S. Barros, Helena Almeida, Andreia Almeida, José das Neves et Bruno Sarmento. « Mucus-producing 3D cell culture models ». Advanced Drug Delivery Reviews 178 (novembre 2021) : 113993. http://dx.doi.org/10.1016/j.addr.2021.113993.

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Schneckenburger, Herbert, et Verena Richter. « Challenges in 3D Live Cell Imaging ». Photonics 8, no 7 (13 juillet 2021) : 275. http://dx.doi.org/10.3390/photonics8070275.

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A short overview on 3D live cell imaging is given. Relevant samples are described and various problems and challenges—including 3D imaging by optical sectioning, light scattering and phototoxicity—are addressed. Furthermore, enhanced methods of wide-field or laser scanning microscopy together with some relevant examples and applications are summarized. In the future one may profit from a continuous increase in microscopic resolution, but also from molecular sensing techniques in the nanometer range using e.g., non-radiative energy transfer (FRET).
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Andersen, Therese, Pia Auk-Emblem et Michael Dornish. « 3D Cell Culture in Alginate Hydrogels ». Microarrays 4, no 2 (24 mars 2015) : 133–61. http://dx.doi.org/10.3390/microarrays4020133.

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Redi, Carlo Alberto. « 3D cell culture - Methods and protocols ». European Journal of Histochemistry 55, no 2 (17 juin 2011) : 4. http://dx.doi.org/10.4081/ejh.2011.br4.

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Mišković Špoljarić, Katarina, Marijana Jukić, Teuta Opačak-Bernardi et Ljubica Glavaš-Obrovac. « 3D Cell Technology in Biomedical Research ». Collegium antropologicum 44, no 3 (2020) : 171–74. http://dx.doi.org/10.5671/ca.44.3.10.

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Traditional two dimensional cell culture has enabled great strides in biomedicine but needs to be improved to be able to keep up with the demands of modern biomedical research. 2D monolayer culture cannot replicate tissue responses and needs to be supplemented with extensive animal research. Growing cells in three dimensional scaffolds provides a more functional model for biomedical research than traditional monolayer culture. Depending on the needs and the complexity of the model there are several ways that 3D models can be initiated. Simple spheroids can be grown in low adherence plates and in hanging drops while larger spheroids and co-cultured ones need to be grown in systems with greater support such as hydro gels. The system that offers the greatest flexibility is the magnetic levitation approach. In the paper we offer a brief resume to various 3D methods and their characteristics to ease the choice of methods for implementing 3D cell culture techniques.
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Mullard, Asher. « Eukaryotic cell, now showing in 3D ». Nature Reviews Molecular Cell Biology 8, no 4 (avril 2007) : 273. http://dx.doi.org/10.1038/nrm2157.

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Guima, Katia-Emiko, Pedro-Henrique L. Coelho, Magno A. G. Trindade et Cauê Alves Martins. « 3D-Printed glycerol microfluidic fuel cell ». Lab on a Chip 20, no 12 (2020) : 2057–61. http://dx.doi.org/10.1039/d0lc00351d.

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Frimat, Jean-Philippe, Sijia Xie, Alex Bastiaens, Bart Schurink, Floor Wolbers, Jaap den Toonder et Regina Luttge. « Advances in 3D neuronal cell culture ». Journal of Vacuum Science & ; Technology B, Nanotechnology and Microelectronics : Materials, Processing, Measurement, and Phenomena 33, no 6 (novembre 2015) : 06F902. http://dx.doi.org/10.1116/1.4931636.

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Ewald, Andrew J. « 3D cell biology – the expanding frontier ». Journal of Cell Science 130, no 1 (1 janvier 2017) : 1. http://dx.doi.org/10.1242/jcs.200543.

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Sun, Wei, et Tao Xu. « Special issue on 3D cell printing ». Biofabrication 7, no 4 (20 janvier 2016) : 043001. http://dx.doi.org/10.1088/1758-5090/7/4/043001.

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Choudhury, Debaditya, William T. Ramsay, Robert Kiss, Nicholas A. Willoughby, Lynn Paterson et Ajoy K. Kar. « A 3D mammalian cell separator biochip ». Lab on a Chip 12, no 5 (2012) : 948. http://dx.doi.org/10.1039/c2lc20939j.

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Driscoll, Meghan K., et Gaudenz Danuser. « Quantifying Modes of 3D Cell Migration ». Trends in Cell Biology 25, no 12 (décembre 2015) : 749–59. http://dx.doi.org/10.1016/j.tcb.2015.09.010.

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Araujo, W. W. R., F. S. Teixeira, G. N. da Silva, D. M. F. Salvadori, M. C. Salvadori et I. G. Brown. « Cell growth on 3D microstructured surfaces ». Materials Science and Engineering : C 63 (juin 2016) : 686–89. http://dx.doi.org/10.1016/j.msec.2016.03.026.

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Larson, Brad. « Analysis of 3D Cell Culture Models ». Genetic Engineering & ; Biotechnology News 35, no 16 (15 septembre 2015) : 24–25. http://dx.doi.org/10.1089/gen.35.16.11.

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Liszewski, Kathy. « New Dimensions in 3D Cell Culture ». Genetic Engineering & ; Biotechnology News 36, no 13 (juillet 2016) : 1, 12, 14. http://dx.doi.org/10.1089/gen.36.13.01.

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Koc, Isil, et Merve Turan. « “Constructing” the Cell Cycle in 3D ». Science Activities : Classroom Projects and Curriculum Ideas 49, no 4 (septembre 2012) : 117–27. http://dx.doi.org/10.1080/00368121.2012.737659.

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Ewald, Andrew J. « 3D cell biology – the expanding frontier ». Development 144, no 2 (15 janvier 2017) : e1.1-e1.1. http://dx.doi.org/10.1242/dev.148395.

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Chaudhuri, Ovijit. « Viscoelastic hydrogels for 3D cell culture ». Biomaterials Science 5, no 8 (2017) : 1480–90. http://dx.doi.org/10.1039/c7bm00261k.

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Tasnim, Nishat, Laura De la Vega, Shweta Anil Kumar, Laila Abelseth, Matthew Alonzo, Meitham Amereh, Binata Joddar et Stephanie M. Willerth. « 3D Bioprinting Stem Cell Derived Tissues ». Cellular and Molecular Bioengineering 11, no 4 (21 mai 2018) : 219–40. http://dx.doi.org/10.1007/s12195-018-0530-2.

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Gretzinger, Sarah, Nicole Beckert, Andrew Gleadall, Cornelia Lee-Thedieck et Jürgen Hubbuch. « 3D bioprinting – Flow cytometry as analytical strategy for 3D cell structures ». Bioprinting 11 (septembre 2018) : e00023. http://dx.doi.org/10.1016/j.bprint.2018.e00023.

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Hussain, Lubna. « Advancing 3D Cell Culture for Biomedical Research Using Primary Cells ». Genetic Engineering & ; Biotechnology News 37, no 13 (1 juillet 2017) : 8–9. http://dx.doi.org/10.1089/gen.37.13.06.

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Arun Anand, Arun Anand, et Bahram Javidi Bahram Javidi. « Digital holographic microscopy for automated 3D cell identification : an overview (Invited Paper) ». Chinese Optics Letters 12, no 6 (2014) : 060012–60017. http://dx.doi.org/10.3788/col201412.060012.

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Song, Jun Ho, Sun-Mi Lee et Kyung-Hwa Yoo. « Label-free and real-time monitoring of human mesenchymal stem cell differentiation in 2D and 3D cell culture systems using impedance cell sensors ». RSC Advances 8, no 54 (2018) : 31246–54. http://dx.doi.org/10.1039/c8ra05273e.

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3D impedance cell sensors are developed to monitor hMSC differentiation in label-free and real-time. Analyzing capacitance and conductance with these sensors shows that osteoblast and adipocyte lineages can be discriminated non-invasively in 3D cell culture systems.
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Hu, Zheng, Shaoli Kang et Xin Su. « Limited Feedback for 3D Massive MIMO under 3D-UMa and 3D-UMi Scenarios ». International Journal of Antennas and Propagation 2015 (2015) : 1–11. http://dx.doi.org/10.1155/2015/176202.

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For three-dimensional (3D) massive MIMO utilizing the uniform rectangular array (URA) in the base station (BS), we propose a limited feedback transmission scheme in which the channel state information (CSI) feedback operations for horizontal domain and vertical domain are separate. Compared to the traditional feedback scheme, the scheme can reduce the feedback overhead, code word index search complexity, and storage requirement. Also, based on the zenith of departure angle (ZoD) distribution in 3D-Urban Macro Cell (3D-UMa) and 3D-Urban Micro Cell (3D-UMi) scenarios, we propose the angle quantization codebook for vertical domain, while the codebook of long term evolution-advanced (LTE-Advanced) is still adopted in horizontal domain to preserve compatibility with the LTE-Advanced. Based on the angle quantization codebook, the subsampled 3-bit DFT codebook is designed for vertical domain. The system-level simulation results reveal that, to compromise the feedback overhead and system performance, 2-bit codebook for 3D-UMa scenario and 3-bit codebook for 3D-UMi scenario can meet requirements in vertical domain. The feedback period for vertical domain can also be extended appropriately to reduce the feedback overhead.
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