Literature DB >> 30079614

In vitro cytotoxicity evaluation of cadmium by label-free holographic microscopy.

Martina Mugnano1, Pasquale Memmolo1, Lisa Miccio1, Simonetta Grilli1, Francesco Merola1, Alejandro Calabuig1, Alessia Bramanti1,2, Emanuela Mazzon2, Pietro Ferraro1.   

Abstract

Among all environmental pollutants, the toxic heavy metal cadmium is considered as a human carcinogen. Cadmium may induce cell death by apoptosis in various cell types, although the underlying mechanisms are still unclear. In this paper we show how a label-free digital holography (DH)-based technique is able to quantify the evolution of key biophysical parameters of cells during the exposure to cadmium for the first time. Murine embryonic fibroblasts NIH 3T3 are chosen here as cellular model for studying the cadmium effects. The results demonstrate that DH is able to retrieve the temporal evolution of different key parameters such as cell volume, projected area, cell thickness and dry mass, thus providing a full quantitative characterization of the cell physical behaviour during cadmium exposure. Our results show that the label-free character of the technique would allow biologists to perform systematic and reliable studies on cell death process induced by cadmium and we believe that more in general this can be easily extended to others heavy metals, thus avoiding the time-consuming, expensive and invasive label-based procedures used nowadays in the field. In fact, pollution by heavy metals is severe issue that needs rapid and reliable methods to be settled.
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  cadmium-induced apoptosis; cell morphology; digital holography; imaging cytometry; quantitative phase imaging

Mesh:

Substances:

Year:  2018        PMID: 30079614     DOI: 10.1002/jbio.201800099

Source DB:  PubMed          Journal:  J Biophotonics        ISSN: 1864-063X            Impact factor:   3.207


  8 in total

1.  Automated single cardiomyocyte characterization by nucleus extraction from dynamic holographic images using a fully convolutional neural network.

Authors:  Ezat Ahmadzadeh; Keyvan Jaferzadeh; Seokjoo Shin; Inkyu Moon
Journal:  Biomed Opt Express       Date:  2020-02-20       Impact factor: 3.732

2.  Cell-to-cell influence on growth in large populations.

Authors:  Mikhail E Kandel; Wenlong Lu; Jon Liang; Onur Aydin; Taher A Saif; Gabriel Popescu
Journal:  Biomed Opt Express       Date:  2019-08-20       Impact factor: 3.732

3.  Morphological changes in the ovarian carcinoma cells of Wistar rats induced by chemotherapy with cisplatin and dioxadet.

Authors:  A A Zhikhoreva; A V Belashov; V G Bespalov; A L Semenov; I V Semenova; G V Tochilnikov; N T Zhilinskaya; O S Vasyutinskii
Journal:  Biomed Opt Express       Date:  2018-10-29       Impact factor: 3.732

4.  Machine Learning with Optical Phase Signatures for Phenotypic Profiling of Cell Lines.

Authors:  Van K Lam; Thanh Nguyen; Thuc Phan; Byung-Min Chung; George Nehmetallah; Christopher B Raub
Journal:  Cytometry A       Date:  2019-04-22       Impact factor: 4.355

5.  Chemotherapy drug potency assessment method of ovarian cancer cells by digital holography microscopy.

Authors:  Yakun Liu; Wen Xiao; Huanzhi Zhang; Lu Xin; Xiaoping Li; Feng Pan
Journal:  Biomed Opt Express       Date:  2022-07-27       Impact factor: 3.562

6.  An optical study of drug resistance detection in endometrial cancer cells by dynamic and quantitative phase imaging.

Authors:  Tian Yao; Runyu Cao; Wen Xiao; Feng Pan; Xiaoping Li
Journal:  J Biophotonics       Date:  2019-04-02       Impact factor: 3.207

7.  Label-Free Digital Holographic Microscopy for In Vitro Cytotoxic Effect Quantification of Organic Nanoparticles.

Authors:  Kai Moritz Eder; Anne Marzi; Álvaro Barroso; Steffi Ketelhut; Björn Kemper; Jürgen Schnekenburger
Journal:  Cells       Date:  2022-02-12       Impact factor: 6.600

8.  Label-free viability assay using in-line holographic video microscopy.

Authors:  Rostislav Boltyanskiy; Mary Ann Odete; Fook Chiong Cheong; Laura A Philips
Journal:  Sci Rep       Date:  2022-07-26       Impact factor: 4.996

  8 in total

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