Full-Field and Quantitative Analysis of a Thin Liquid Film at the Nanoscale by Combining Digital Holography and White Light Interferometry

Visualizing and measuring thin-film thickness at the nanoscale during dynamic evolution has been an open challenge for long term. Here, a joint-imaging method and the thereof innovative procedure are presented for merging digital holography (DH) and white light colorimetric interferometry (WLCI) measurement data in a single intelligent tool. This approach allows a complete quantitative study of the dynamic evolution of freestanding thin films under high spatial resolution and full-field modality over a large area. By merging interferometric and holographic fringes, it is possible to overcome the lack of DH in thickness measurements of ultrathin layers, providing a reliable reference for full-field quantitative mapping of the whole film with interferometric accuracy. Thanks to the proposed approach, the time-related and concentration-related evolution of surfactant film thickness can be studied. The thickness distribution curves reveal the small changes in the film thickness with time and concentration. The reported tool opens a route for comprehending deeply the physics behind the behavior of freestanding thin liquid films as it provides an in situ, continuous monitoring of film formation and dynamic evolution without limits of thickness range and in full-field mode. This can be of fundamental importance to many fields of applications, such as fluids, polymers, biotechnology, bottom-up fabrication, etc

Label-Free Intracellular Multi-Specificity in Yeast Cells by Phase-Contrast Tomographic Flow Cytometry

: In-flow phase-contrast tomography provides a 3D refractive index of label-free cells in cytometry systems. Its major limitation, as with any quantitative phase imaging approach, is the lack of specificity compared to fluorescence microscopy, thus restraining its huge potentialities in single-cell analysis and diagnostics. Remarkable results in introducing specificity are obtained through artificial intelligence (AI), but only for adherent cells. However, accessing the 3D fluorescence ground truth and obtaining accurate voxel-level co-registration of image pairs for AI training is not viable for high-throughput cytometry. The recent statistical inference approach is a significant step forward for label-free specificity but remains limited to cells' nuclei. Here, a generalized computational strategy based on a self-consistent statistical inference to achieve intracellular multi-specificity is shown. Various subcellular compartments (i.e., nuclei, cytoplasmic vacuoles, the peri-vacuolar membrane area, cytoplasm, vacuole-nucleus contact site) can be identified and characterized quantitatively at different phases of the cells life cycle by using yeast cells as a biological model. Moreover, for the first time, virtual reality is introduced for handling the information content of multi-specificity in single cells. Full fruition is proofed for exploring and interacting with 3D quantitative biophysical parameters of the identified compartments on demand, thus opening the route to a metaverse for 3D microscopy

3D imaging lipidometry in single cell by in-flow holographic tomography

The most recent discoveries in the biochemical field are highlighting the increasingly important role of lipid droplets (LDs) in several regulatory mechanisms in living cells. LDs are dynamic organelles and therefore their complete characteriza- tion in terms of number, size, spatial positioning and relative distribution in the cell volume can shed light on the roles played by LDs. Until now, fluorescence microscopy and transmission electron microscopy are assessed as the gold standard methods for identifying LDs due to their high sensitivity and specificity. However, such methods generally only provide 2D assays and partial measurements. Furthermore, both can be destructive and with low productivity, thus limit- ing analysis of large cell numbers in a sample. Here we demonstrate for the first time the capability of 3D visualization and the full LD characterization in high-throughput with a tomographic phase-contrast flow-cytometer, by using ovarian cancer cells and monocyte cell lines as models. A strategy for retrieving significant parameters on spatial correlations and LD 3D positioning inside each cell volume is reported. The information gathered by this new method could allow more in depth understanding and lead to new discoveries on how LDs are correlated to cellular functions

Wavefronts matching: A novel paradigm for three-dimensional holographic particle tracking

Digital Holography (DH) in microscopy allows to retrieve in an accurate way the spatial coordinates of multiple moving particles, performing 3D tracking of the sample in the entire field of view. In particular, a posteriori quantitative multi-focus phase-contrast imaging, suitable for 3D tracking of micro-objects, is one of the main features of the holographic approach. However, classical methods need to decouple amplitude and phase contributions of the reconstructed complex wavefronts to calculate target positions in 3D, due to the fact that the lateral displacements can be calculated only after refocusing step. In order to overcome this limitation, recently, a novel method of the simultaneous calculation of both axial and lateral coordinates of moving particles has been proposed. This is based on the novel concept of wavefronts matching, i.e. the 3D positions of micro-object, moving in 3D volume, are obtained by aligning wo subsequent holographic complex reconstructions, calculated at the same distance. We test this approach in different experimental conditions in order to highlight its effectiveness in bio-microfluidic applications

Holographic tracking of living cells by three-dimensional reconstructed complex wavefronts alignment

We propose here a new three-dimensional (3D) holographic tracking method capable to track, simultaneously and in a single step, all the spatial coordinates of micro-objects. The approach is based on the enhanced correlation coefficient (ECC) maximization method but applied, for the first time to the best of our knowledge, directly on the holographic reconstructed complex wave fields. The key novelty of the proposed strategy is its ability to calculate simultaneously the 3D coordinates of cells, without decoupling the contribution of amplitude and phase. The proposed strategy is tested on living cells (i.e., NIH 3T3 mouse fibroblast) flowing into a microfluidic channel and compared with classical holographic tracking approach. Theoretical description and experimental validation of the proposed strategy are reported

Investigation on 3D morphological changes of in vitro cells through digital holographic microscopy

We report the investigation of the identification and measurement of region of interest (ROI) in quantitative phase-contrast maps (QPMs) of biological cells by digital holographic microscopy (DHM), with the aim to analyze the 3D positions and 3D morphology together. We consider as test case for our tool the in vitro bull sperm head morphometry analysis. Extraction and measurement of various morphological parameters are performed by using two methods: the anisotropic diffusion filter, that is based on the Gaussian diffusivity function which allows more accuracy of the edge position, and the simple thresholding filter. In particular we consider the calculation of area, ellipticity, perimeter, major axis, minor axis and shape factor as a morphological parameter, instead, for the estimation of 3D position, we compute the centroid, the weighted centroid and the maximum phase values. A statistical analysis on a data set composed by N = 14 holograms relative to bovine spermatozoa and its reference holograms is reported