Roadmap on Label-Free Super-Resolution Imaging

Molecular Fingerprinting of Mouse Brain Using Ultrabroadband Coherent Anti-Stokes Raman Scattering (CARS) Microspectroscopy Empowered by Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS)

The Raman fingerprint spectral region provides abundant structural information on molecules. However, analyzing vibrational images within this region using coherent Raman imaging remains challenging due to the small Raman cross section and congested spectral features. In this study, we combined ultrabroadband coherent anti-Stokes Raman scattering (CARS) microspectroscopy across the spectral range of 500-4000 cm-1 with multivariate curve resolution-alternating least-squares (MCR-ALS) to reveal hidden Raman bands in the fingerprint region. Applying this method to mouse brain tissue, we extracted information on cholesterol and collagen, leveraging their distinctive molecular signatures, as well as on key molecules such as lipids, proteins, water, and nucleic acids. Moreover, the simultaneous detection of second harmonic generation facilitated label-free visualization of organelles, including arachnoid membrane and Rootletin filaments.

Surpassing the Diffraction Limit in Label-Free Optical Microscopy

Super-resolution optical microscopy has enhanced our ability to visualize biological structures on the nanoscale. Fluorescence-based techniques are today irreplaceable in exploring the structure and dynamics of biological matter with high specificity and resolution. However, the fluorescence labeling concept narrows the range of observed interactions and fundamentally limits the spatiotemporal resolution. In contrast, emerging label-free imaging methods are not inherently limited by speed and have the potential to capture the entirety of complex biological processes and dynamics. While pushing a complex unlabeled microscopy image beyond the diffraction limit to single-molecule resolution and capturing dynamic processes at biomolecular time scales is widely regarded as unachievable, recent experimental strides suggest that elements of this vision might be already in place. These techniques derive signals directly from the sample using inherent optical phenomena, such as elastic and inelastic scattering, thereby enabling the measurement of additional properties, such as molecular mass, orientation, or chemical composition. This perspective aims to identify the cornerstones of future label-free super-resolution imaging techniques, discuss their practical applications and theoretical challenges, and explore directions that promise to enhance our understanding of complex biological systems through innovative optical advancements. Drawing on both traditional and emerging techniques, label-free super-resolution microscopy is evolving to offer detailed and dynamic imaging of living cells, surpassing the capabilities of conventional methods for visualizing biological complexities without the use of labels.

Neural network-based processing and reconstruction of compromised biophotonic image data

In recent years, the integration of deep learning techniques with biophotonic setups has opened new horizons in bioimaging. A compelling trend in this field involves deliberately compromising certain measurement metrics to engineer better bioimaging tools in terms of e.g., cost, speed, and form-factor, followed by compensating for the resulting defects through the utilization of deep learning models trained on a large amount of ideal, superior or alternative data. This strategic approach has found increasing popularity due to its potential to enhance various aspects of biophotonic imaging. One of the primary motivations for employing this strategy is the pursuit of higher temporal resolution or increased imaging speed, critical for capturing fine dynamic biological processes. Additionally, this approach offers the prospect of simplifying hardware requirements and complexities, thereby making advanced imaging standards more accessible in terms of cost and/or size. This article provides an in-depth review of the diverse measurement aspects that researchers intentionally impair in their biophotonic setups, including the point spread function (PSF), signal-to-noise ratio (SNR), sampling density, and pixel resolution. By deliberately compromising these metrics, researchers aim to not only recuperate them through the application of deep learning networks, but also bolster in return other crucial parameters, such as the field of view (FOV), depth of field (DOF), and space-bandwidth product (SBP). Throughout this article, we discuss various biophotonic methods that have successfully employed this strategic approach. These techniques span a wide range of applications and showcase the versatility and effectiveness of deep learning in the context of compromised biophotonic data. Finally, by offering our perspectives on the exciting future possibilities of this rapidly evolving concept, we hope to motivate our readers from various disciplines to explore novel ways of balancing hardware compromises with compensation via artificial intelligence (AI).

Fundamental precision limits of fluorescence microscopy: a perspective on MINFLUX

Over the past years, fluorescence microscopy (FM) has steadily progressed in increasing the localization precision of fluorescent emitters in biological samples and led to new claims, whose rigorous validation remains an outstanding problem. We present a novel, to the best of our knowledge, multi-parameter estimation framework that captures the full complexity of a single-emitter FM localization experiment. We showcase our method with Minimum Flux (MINFLUX) microscopy, among the highest-resolution approaches, demonstrating that (i) the localization precision can be increased only by turning the illumination intensity up, thus increasing the risk of photo-bleaching, and it is independent from the beams' separation, and (ii) in presence of background noise, the localization precision decreases with the beams' separation. Finally, we apply our method to Minimum Flux Stimulated Emission Depletion (MINSTED) microscopy, showing that a reduction of the beam width can provide similar performance to MINFLUX.

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part II

Significance

Quantitative phase imaging (QPI) is a non-invasive, label-free technique that provides intrinsic information about the sample under study. Such information includes the structure, function, and dynamics of the sample. QPI overcomes the limitations of conventional fluorescence microscopy in terms of phototoxicity to the sample and photobleaching of the fluorophore. As such, the application of QPI in estimating the three-dimensional (3D) structure and dynamics is well-suited for a range of samples from intracellular organelles to highly scattering multicellular samples while allowing for longer observation windows.

Aim

We aim to provide a comprehensive review of 3D QPI and related phase-based measurement techniques along with a discussion of methods for the estimation of sample dynamics.

Approach

We present information collected from 106 publications that cover the theoretical description of 3D light scattering and the implementation of related measurement techniques for the study of the structure and dynamics of the sample. We conclude with a discussion of the applications of the reviewed techniques in the biomedical field.

Results

QPI has been successfully applied to 3D sample imaging. The scattering-based contrast provides measurements of intrinsic quantities of the sample that are indicative of disease state, stage of growth, or overall dynamics.

Conclusions

We reviewed state-of-the-art QPI techniques for 3D imaging and dynamics estimation of biological samples. Both theoretical and experimental aspects of various techniques were discussed. We also presented the applications of the discussed techniques as applied to biomedicine and biology research.

Effect of boundary conditions in modeling of microsphere-assisted imaging

Exploring the performance of label-free imaging relies heavily on adequate physical models and accurate numerical simulations. A particularly challenging situation is imaging through contact microspheres, which have demonstrated resolution values exceeding the diffraction limit. Here an ab initio modeling of microsphere-assisted imaging is reported and its results are analyzed. The key part of modeling is solving the light scattering problem, which requires handling a rather large computational domain and broad angle illumination made up of multiple mutually incoherent plane waves. To account for plane wave incidence, two simulation approaches are developed that differ only by boundary conditions-quasiperiodic and absorbing. The algorithms to find images in both approaches are discussed and the simulation results are compared for free space and microsphere-assisted imaging. It is shown that while the super-resolution in microsphere-assisted imaging can be demonstrated using both approaches, the latter allows a large reduction in the computational resources. This significantly extends the capability of the simulations, enabling a rigorous exploration of novel imaging regimes.

High-resolution cell imaging using white light phase shifting interferometry and iterative phase deconvolution

An optimization algorithm is presented for the deconvolution of a complex field to improve the resolution and accuracy of quantitative phase imaging (QPI). A high-resolution phase map can be recovered by solving a constrained optimization problem of deconvolution using a complex gradient operator. The method is demonstrated on phase measurements of samples using a white light based phase shifting interferometry (WLPSI) method. The application of the algorithm on real and simulated objects shows a significant resolution and contrast improvement. Experiments performed on Escherichia coli bacterium have revealed its sub-cellular structures that were not visible in the raw WLPSI images obtained using a five phase shifting method. These features can give valuable insights into the structures and functioning of biological cells. The algorithm is simple in implementation and can be incorporated into other QPI modalities .

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part I

Significance

Quantitative phase imaging (QPI) techniques offer intrinsic information about the sample of interest in a label-free, noninvasive manner and have an enormous potential for wide biomedical applications with negligible perturbations to the natural state of the sample in vitro.

Aim

We aim to present an in-depth review of the scattering formulation of light-matter interactions as applied to biological samples such as cells and tissues, discuss the relevant quantitative phase measurement techniques, and present a summary of various reported applications.

Approach

We start with scattering theory and scattering properties of biological samples followed by an exploration of various microscopy configurations for 2D QPI for measurement of structure and dynamics.

Results

We reviewed 157 publications and presented a range of QPI techniques and discussed suitable applications for each. We also presented the theoretical frameworks for phase reconstruction associated with the discussed techniques and highlighted their domains of validity.

Conclusions

We provide detailed theoretical as well as system-level information for a wide range of QPI techniques. Our study can serve as a guideline for new researchers looking for an exhaustive literature review of QPI methods and relevant applications.

Numerical study of transient absorption saturation in single-layer graphene for optical nanoscopy applications

Transient absorption, or pump-probe microscopy is an absorption-based technique that can explore samples ultrafast dynamic properties and provide fluorescence-free contrast mechanisms. When applied to graphene and its derivatives, this technique exploits the graphene transient response caused by the ultrafast interband transition as the imaging contrast mechanism. The saturation of this transition is fundamental to allow for super-resolution optical far-field imaging, following the reversible saturable optical fluorescence transitions (RESOLFT) concept, although not involving fluorescence. With this aim, we propose a model to numerically compute the temporal evolution under saturation conditions of the single-layer graphene molecular states, which are involved in the transient absorption. Exploiting an algorithm based on the fourth order Runge-Kutta (RK4) method, and the density matrix approach, we numerically demonstrate that the transient absorption signal of single-layer graphene varies linearly as a function of excitation intensity until it reaches saturation. We experimentally verify this model using a custom pump-probe super-resolution microscope. The results define the intensities necessary to achieve super-resolution in a pump-probe nanoscope while studying graphene-based materials and open the possibility of predicting such a saturation process in other light-matter interactions that undergo the same transition.

Recent Advances and Current Trends in Transmission Tomographic Diffraction Microscopy

Optical microscopy techniques are among the most used methods in biomedical sample characterization. In their more advanced realization, optical microscopes demonstrate resolution down to the nanometric scale. These methods rely on the use of fluorescent sample labeling in order to break the diffraction limit. However, fluorescent molecules' phototoxicity or photobleaching is not always compatible with the investigated samples. To overcome this limitation, quantitative phase imaging techniques have been proposed. Among these, holographic imaging has demonstrated its ability to image living microscopic samples without staining. However, for a 3D assessment of samples, tomographic acquisitions are needed. Tomographic Diffraction Microscopy (TDM) combines holographic acquisitions with tomographic reconstructions. Relying on a 3D synthetic aperture process, TDM allows for 3D quantitative measurements of the complex refractive index of the investigated sample. Since its initial proposition by Emil Wolf in 1969, the concept of TDM has found a lot of applications and has become one of the hot topics in biomedical imaging. This review focuses on recent achievements in TDM development. Current trends and perspectives of the technique are also discussed.

Ab initio simulation of imaging of wavelength-sized objects and estimation of resolution

Image characterization in microscopy, in particular, the estimation of its resolution, requires detailed knowledge of its relation to the object. For objects with sizes comparable to or smaller than the operating wavelength, such a relation can be obtained only by considering electromagnetic scattering described by the Maxwell equations. Here we follow precisely the steps involved in the image formation in microscopy with broad angle illumination-starting from the Maxwell equations to find the scattered far fields for each plane wave, projecting them into a sensor array, and finally assembling the incoherent image by adding all coherent contributions. We consider a classical object-a narrow slit in an absorbing screen, which is taken as a very thin chromium film deposited on a glass substrate. The inapplicability of the Kirchhoff approximation for such a slit is addressed, and the calculated image is subsequently analyzed to evaluate its intrinsic resolution using a point spread function. The difference in image intensities defined using the Poynting vector and the electric field intensity is also discussed.

Expanding the microbiologist toolbox via new far-red-emitting dyes suitable for bacterial imaging

IMPORTANCE

By harnessing the versatility of fluorescence microscopy and super-resolution imaging, bacteriologists explore critical aspects of bacterial physiology and resolve bacterial structures sized beyond the light diffraction limit. These techniques are based on fluorophores with profitable photochemical and tagging properties. The paucity of available far-red (FR)-emitting dyes for bacterial imaging strongly limits the multicolor choice of bacteriologists, hindering the possibility of labeling multiple structures in a single experiment. The set of FR fluorophores characterized in this study expands the palette of dyes useful for microbiologists, as they can be used for bacterial LIVE/DEAD staining and for tagging the membranes of viable Escherichia coli and Bacillus subtilis cells. The absence of toxicity makes these dyes suitable for live-cell imaging and allows monitoring of bacterial membrane biogenesis. Moreover, a newly synthesized FR-fluorophore can be employed for imaging bacterial membranes with stimulated emission depletion microscopy, a super-resolution technique capable of increasing the resolving power of conventional microscopes.