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Melandso, F.

Publications and source records attributed to Melandso, F..

2 recordsLinked to original sources

Label-free acoustic and optical microscopy of live tumor spheroids in hydrogel for high-throughput 3D In-vitro drug screening

3D cell cultures, including spheroids, have become essential tools in cancer research and drug discovery due to their ability to more accurately mimic in-vivo tissue environments compared to traditional 2D cultures. However, imaging these thick, complex structures remains a challenge, as conventional optical microscopy techniques are limited by shallow depth penetration. This study explores the complementary use of gradient light interference microscopy (GLIM) and scanning acoustic microscopy (SAM) for label-free imaging of 3D spheroid clusters embedded in hydrogels. GLIM offers high-resolution optical imaging but struggles with depth in dense samples, while SAM provides greater depth penetration and a larger field of view, albeit with lower resolution. By correlating SAM and GLIM imaging, this study demonstrates how the two techniques can be synergistically used to enhance the visualization of spheroids, capturing both large-scale structural features and fine cellular details. The benefits make such a platform suitable for screening high-number multi-well plates and evaluating necrotic and angiogenic features from the core of the thick sample. Such platforms have the potential of combining acoustic and optical imaging modalities for high-throughput screening and physical characterization in 3D cell culture research, advancing our understanding of drug efficacy in complex biological systems.

bioengineering↗

Uncertainty Quantification in Acoustic Impedance ofAtlantic Salmon Fish Scale using Scanning AcousticMicroscopy

Scanning Acoustic Microscopy (SAM) emerges as a versatile label-free imaging technology with broad applications in biomedical imaging, non-destructive testing, and material research. This article presents a framework for the estimation of stochastic impedance through SAM, with a particular focus on its application to the salmon fish scale. The framework leverages uncertain reflectance, marking its pioneering application to uncertainty quantification in the acoustic impedance of fish scales through acoustic responses. The study uses maximal overlap discrete wavelet transform, to decompose acoustic responses effectively and is further processed to predict the acoustic impedance. To establish the effectiveness of the proposed framework, well-known materials like a pair of target medium (polyvinylidene fluoride) and reference medium (polyimide) are employed for impedance characterization. Results demonstrate over 90%accuracy in PVDF impedance estimation, validating the framework. A stochastic impedance map, using Kriging with a Gaussian variogram, offers insights into the complex biomechanics of a fishs scale.

biophysics↗