UNASSIGNED: The emergence of label-free microscopy techniques has significantly improved our ability to precisely characterize biochemical targets, enabling non-invasive visualization of cellular organelles and tissue organization. However, understanding each label-free method with respect to the specific benefits, drawbacks, and varied sensitivities under measurement conditions across different types of specimens remains a challenge.
UNASSIGNED: We link all of these disparate label-free optical interactions together and compare the detection sensitivity within the framework of statistical estimation theory.
UNASSIGNED: To achieve this goal, we introduce a comprehensive unified framework for evaluating the bounds for signal detection with label-free microscopy methods, including second-harmonic generation, third-harmonic generation, coherent anti-Stokes Raman scattering, coherent Stokes Raman scattering, stimulated Raman loss, stimulated Raman gain, stimulated emission, impulsive stimulated Raman scattering, transient absorption, and photothermal effect. A general model for signal generation induced by optical scattering is developed.
UNASSIGNED: Based on this model, the information obtained is quantitatively analyzed using Fisher information, and the fundamental constraints on estimation precision are evaluated through the Cramér-Rao lower bound, offering guidance for optimal experimental design and interpretation.
UNASSIGNED: We provide valuable insights for researchers seeking to leverage label-free techniques for non-invasive imaging applications for biomedical research and clinical practice.

The article elucidates the physical mechanism behind the generation of superior-contrast and high-resolution label-free images using an optical waveguide. Imaging is realized by employing a high index contrast multi-moded waveguide as a partially coherent light source. The modes provide near-field illumination of unlabeled samples, thereby repositioning the higher spatial frequencies of the sample into the far-field. These modes coherently scatter off the sample with different phases and are engineered to have random spatial distributions within the integration time of the camera. This mitigates the coherent speckle noise and enhances the contrast (2-10) × as opposed to other imaging techniques. Besides, the coherent scattering of the different modes gives rise to fluctuations in intensity. The technique demonstrated here is named chip-based Evanescent Light Scattering (cELS). The concepts introduced through this work are described mathematically and the high-contrast image generation process using a multi-moded waveguide as the light source is explained. The article then explores the feasibility of utilizing fluctuations in the captured images along with fluorescence-based techniques, like intensity-fluctuation algorithms, to mitigate poor-contrast and diffraction-limited resolution in the coherent imaging regime. Furthermore, a straight waveguide is demonstrated to have limited angular diversity between its multiple modes and therefore, for isotropic sample illumination, a multiple-arms waveguide geometry is used. The concepts introduced are validated experimentally via high-contrast label-free imaging of weakly scattering nanosized specimens such as extra-cellular vesicles (EVs), liposomes, nanobeads and biological cells such as fixed and live HeLa cells.

During the last century, fluorescence microscopy has played a pivotal role in a range of scientific discoveries. The success of fluorescence microscopy has prevailed despite several shortcomings like measurement time, photobleaching, temporal resolution, and specific sample preparation. To bypass these obstacles, label-free interferometric methods have been developed. Interferometry exploits the full wavefront information of laser light after interaction with biological material to yield interference patterns that contain information about structure and activity. Here, we review recent studies in interferometric imaging of plant cells and tissues, using techniques such as biospeckle imaging, optical coherence tomography, and digital holography. These methods enable quantification of cell morphology and dynamic intracellular measurements over extended periods of time. Recent investigations have showcased the potential of interferometric techniques for precise identification of seed viability and germination, plant diseases, plant growth and cell texture, intracellular activity and cytoplasmic transport. We envision that further developments of these label-free approaches, will allow for high-resolution, dynamic imaging of plants and their organelles, ranging in scales from sub-cellular to tissue and from milliseconds to hours.

Conventional histopathology has relied on chemical staining for over a century. The staining process makes tissue sections visible to the human eye through a tedious and labor-intensive procedure that alters the tissue irreversibly, preventing repeated use of the sample. Deep learning-based virtual staining can potentially alleviate these shortcomings. Here, we used standard brightfield microscopy on unstained tissue sections and studied the impact of increased network capacity on the resulting virtually stained H&E images. Using the generative adversarial neural network model pix2pix as a baseline, we observed that replacing simple convolutions with dense convolution units increased the structural similarity score, peak signal-to-noise ratio, and nuclei reproduction accuracy. We also demonstrated highly accurate reproduction of histology, especially with increased network capacity, and demonstrated applicability to several tissues. We show that network architecture optimization can improve the image translation accuracy of virtual H&E staining, highlighting the potential of virtual staining in streamlining histopathological analysis.

Hematoxylin and eosin (H&E) staining, the century-old technique, has been the gold standard tool for pathologists to detect anomalies in tissues and diseases such as cancer. H&E staining is a cumbersome, time-consuming process that delays and wastes precious minutes during an intraoperative diagnosis. However, even in the modern era, real-time label-free imaging techniques such as simultaneous label-free autofluorescence multiharmonic (SLAM) microscopy have delivered several more layers of information to characterize a tissue with high precision. Still, they have yet to translate to the clinic. The slow translation rate can be attributed to the lack of direct comparisons between the old and new techniques. Our approach to solving this problem is to: 1) reduce dimensions by pre-sectioning the tissue in 500 μm slices, and 2) produce fiducial laser markings which appear in both SLAM and histological imaging. High peak-power femtosecond laser pulses enable ablation in a controlled and contained manner. We perform laser marking on a grid of points encompassing the SLAM region of interest. We optimize laser power, numerical aperture, and timing to produce axially extended marking, hence multilayered fiducial markers, with minimal damage to the surrounding tissues. We performed this co-registration over an area of 3 × 3 mm2 of freshly excised mouse kidney and intestine, followed by standard H&E staining. Reduced dimensionality and the use of laser markings provided a comparison of the old and new techniques, giving a wealth of correlative information and elevating the potential of translating nonlinear microscopy to the clinic for rapid pathological assessment.

Microscopy has been essential to elucidate micro- and nano-scale processes in space and time and has provided insights into cell and organismic functions. It is widely employed in cell biology, microbiology, physiology, clinical sciences and virology. While label-dependent microscopy, such as fluorescence microscopy, provides molecular specificity, it has remained difficult to multiplex in live samples. In contrast, label-free microscopy reports on overall features of the specimen at minimal perturbation. Here, we discuss modalities of label-free imaging at the molecular, cellular and tissue levels, including transmitted light microscopy, quantitative phase imaging, cryogenic electron microscopy or tomography and atomic force microscopy. We highlight how label-free microscopy is used to probe the structural organization and mechanical properties of viruses, including virus particles and infected cells across a wide range of spatial scales. We discuss the working principles of imaging procedures and analyses and showcase how they open new avenues in virology. Finally, we discuss orthogonal approaches that enhance and complement label-free microscopy techniques.

The lack of equipped healthcare infrastructure in isolated hard-to-reach zones exposes their population to a higher risk of complications in common diseases. With a timely diagnosis setting a life-altering difference, worldwide efforts have been conducted for the development of point-of-care testing (PoCT) with cost-effective devices. Among the most common interests in PoCT is the analysis of blood smear samples, as they can help to detect, diagnose, and monitor a wide range of diseases and disorders. With microscopy being the traditional tool for these analyses, a significative advance has been the development of cost-effective digital holographic microscopy systems, driven in part by its label-free imaging capabilities that waive the need for any sample preprocessing. Here, a robust and portable digital lensless holographic microscope, functionalized for the analysis of non-preprocessed blood smear samples in PoCT environments, is presented, and its viability is tested in the observation of red blood cells. The device uses an optical fiber with a cone-shaped tip instead of a pinhole, which ensures the sturdiness of the system and eliminates the need for challenging alignment. While the distances of the microscope can be tuned before fabrication, the herein-reported operational parameters are functionalized for the specific analysis of blood samples.

Biological research is in constant need of new methodological developments to assess organization and functions at various scales ranging from whole organisms to interactions between proteins. One of the main ways to evidence and quantify biological phenomena is imaging. Fluorescence microscopy and label-free microscopy are in particular highly active fields of research due to their compatibility with living samples as well as their versatility. The Imabio Young Scientists Network (YSN) is a group of young scientists (PhD students, postdocs and engineers) who are excited about bioimaging and aim to create a proactive network of researchers with the same interest. YSN is endorsed by the bioimaging network GDR Imabio in France, where the initiative was started in 2019. Since then, we aim to organize the Imabio YSN conference every year to expand the network to other European countries, establish new collaborations and ignite new scientific ideas. From 6-8 July 2022, the YSN including researchers from the domains of life sciences, chemistry, physics and computational sciences met at the Third Imabio YSN Conference 2022 in Lyon to discuss the latest bioimaging technologies and biological discoveries. In this Meeting Review, we describe the essence of the scientific debates, highlight remarkable talks, and focus on the Career Development session, which is unique to the YSN conference, providing a career perspective to young scientists and help to answer all their questions at this career stage. This conference was a truly interdisciplinary reunion of scientists who are eager to push the frontiers of bioimaging in order to understand the complexity of biological systems.

[This corrects the article DOI: 10.3389/fcell.2021.675636.].

Cancer cells often adapt their lipid metabolism to accommodate the increased fatty acid demand for membrane biogenesis and energy production. Upregulation of fatty acid uptake from the environment of cancer cells has also been reported as an alternative mechanism. To investigate the role of lipids in tumor onset and progression and to identify potential diagnostic biomarkers, lipids are ideally imaged directly within the intact tumor tissue in a label-free way. In this study, we investigated lipid accumulation and distribution in living zebrafish larvae developing a tumor by means of coherent anti-Stokes Raman scattering microscopy. Quantitative textural features based on radiomics revealed higher lipid accumulation in oncogene-expressing larvae compared to healthy ones. This high lipid accumulation could reflect an altered lipid metabolism in the hyperproliferating oncogene-expressing cells.