Single-shot spatial light interference microscopy for dynamic monitoring of membrane fluctuations.

Single-shot spatial light interference microscopy (SS-SLIM) with a pair of non-polarizing beam splitters is proposed for substantially enhancing the speed and efficiency of conventional SLIM systems. Traditional methods are limited by the need for multiple-frame serial modulation and acquisition by spatial light modulators and detectors. Our approach integrates non-polarizing beam splitters to simultaneously capture four phase-shifted intensity images, increasing the imaging speed by at least fourfold while maintaining high quality. This capability is crucial for effectively monitoring the dynamic fluctuations of red blood cell membranes. Furthermore, the potential applications of the SS-SLIM system in biomedical research are demonstrated, particularly in scenarios requiring high temporal resolution and label-free imaging.

Piezoelectric Materials and Sensors for Structural Health Monitoring: Fundamental Aspects, Current Status, and Future Perspectives.

Structural health monitoring technology can assess the status and integrity of structures in real time by advanced sensors, evaluate the remaining life of structure, and make the maintenance decisions on the structures. Piezoelectric materials, which can yield electrical output in response to mechanical strain/stress, are at the heart of structural health monitoring. Here, we present an overview of the recent progress in piezoelectric materials and sensors for structural health monitoring. The article commences with a brief introduction of the fundamental physical science of piezoelectric effect. Emphases are placed on the piezoelectric materials engineered by various strategies and the applications of piezoelectric sensors for structural health monitoring. Finally, challenges along with opportunities for future research and development of high-performance piezoelectric materials and sensors for structural health monitoring are highlighted.

Surface-enhanced Raman scattering from an electromagnetic induced transparency substrate for the determination of hepatocellular carcinoma.

Surface-enhanced Raman scattering (SERS) is a powerful analytical method that is especially suitable for the detection of protein molecules. Detection sensitivity of SERS is directly related to the enhancement factor of the substrate, which is dependent on the strength of a local surface electric field generated by surface plasmonic resonance from substrate. In this study, an electromagnetic induced transparency like (EIT-like) metamaterial was used as the SERS substrate. The corresponding plasmonic resonance structure not only produces stronger optical near field but also reduces the spectral line broadening due to radiation damping. This is very beneficial for SERS process, which is strongly dependent on electric field intensity, to improve the sensitivity of SERS detection. Compared with the single resonance mode substrate, the enhancement factor for SERS with the double-mode substrate was increased by an order of magnitude. The obtained EIT-like substrate was used as a SERS-active substrate to detect Lens culinaris agglutinin (LCA)-reactive fraction of AFP (AFP-L3), a hepatocellular carcinoma (HCC)-specific maker. Experimental results are in good agreement with the clinical diagnosis, which demonstrates the potential application of metamaterials in the SERS-based diagnosis and biosensing.

In vivo two-photon fluorescence lifetime imaging microendoscopy based on fiber-bundle.

Fluorescence lifetime imaging microendoscopy (FLIME) has been reported to investigate the physicochemical microenvironment in biological tissue. In this work, we designed a two-photon (TP) FLIME system based on a fiber-bundle glued with an achromatic mini-objective with 1.4-mm diameter, which was coupled to a standard TP microscope containing a dispersion precompensation module in the laser source. With 840 nm excitation, the field of view and lateral resolution of our system are 390 µm and 1.55 µm, respectively. To examine the capability of imaging in vivo, we obtained Z-stack (0-130 µm) TP-FLIME images from the intestine's surface of a mouse injected with squaraine dye. Further, we utilized the TP-FLIME system to image the kidney, liver, and xenografted tumor at 100-µm depth in vivo with cellular resolution, which features the distribution of cells and tissue structures with better contrast than intensity images. These results demonstrated that the proposed system is capable of measuring fluorescence lifetime in situ and provides a powerful tool to research the deep tissue microenvironment naturally.

Rapid and Targeted Photoactivation of Ca2+ Channels Mediated by Squaraine To Regulate Intracellular and Intercellular Signaling Processes.

As an important cellular signal transduction messenger, Ca2+ has the capability to regulate cell function and control many biochemical processes, including metabolism, gene expression, and cell survival and death. Here, we introduce an accessible method for the photoactivation of Ca2+ channels mediated by squaraine (SQ) to rapidly induce cellular Ca2+ release and activate signal transduction. With a short preparation time, the maximum Ca2+ concentration increase could reach approximately 450% in 30 s, resulting from marked Ca2+ release channel opening in the endoplasmic reticulum (ER). This release was enhanced by another target location of SQ, that is, the outer mitochondrial-associated membrane where Ca2+ channels accumulate, and by the consequent large amounts of reactive oxygen species resulting from the respiratory chain activity stimulated by Ca2+ load. We used this method to investigate cellular signal transduction in different cancer cells and revealed rapid intracellular Ca2+ flow, unidirectional intercellular signaling processes, and neuronal signaling activity, which demonstrated the potential and convenience of the method for routine Ca2+ research.

Picosecond evolution of pulsed and CW alkali vapor lasers: laser oscillation buildup.

Investigation of the kinetic principle of a diode-pumped alkali vapor laser (DPAL) is key to achieve multifunctional DPALs. In this work, we propose a spatiotemporal model, which combines the time-dependent rate equations of population densities and propagation equations of energies to study the dynamic processes from turn-on to steady-state in DPALs. Time evolution of population densities and pump and laser intensity are resolved on a picosecond time scale to study the build-up process of laser oscillations. For nanosecond-pulse pumping, we obtain a laser pulse of 1.6 ns and a delay time of 2.6 ns at an incident pulse width of 2 ns. This pulse can be stretched by increasing the pump pulse width and delayed by applying a more extended cavity. For CW operation, spiking and relaxation oscillations resulting from a dynamic balance of gain and losses are demonstrated to be much faster than other types of lasers.

Fluorescence enhancement of small squaraine dye and its two-photon excited fluorescence in long-term near-infrared I&II bioimaging.

Two-photon excited fluorescence (TPEF) plays an important role in bioimaging, the longer excitation wavelength improves its imaging depths, which gives us deeper biological information. Here, we reported the two-photon absorption of a small squaraine dye (SD), and we found that the TPEF of the small SD can be enhanced significantly using albumin, the TPEF of SD in water was enhanced 17.7 times by adding bull serum albumin (BSA) in the solution. Meanwhile, the cell imaging results indicated that the SD can enter cell effectively in less than 30 min and emit bright TPEF. Furthermore, the SD showed excellent stability against photobleaching in near-infrared II (1200 nm). The cytotoxicity experiment showed that the cytotoxicity of SD is relatively low. Our work demonstrates the excellent two-photon effect of SD in cells, potential application value of SD in two-photon bioimaging, protein detection and near infrared sensing.

Modeling of time evolution of power and temperature in single-pulse and multi-pulses diode-pumped alkali vapor lasers.

A physical model combining rate, power propagation, and transient heat conduction equations for diode-pumped alkali vapor lasers (DPAL) is applied to a pulsed Rb-CH4 DPAL, which agrees well with the time evolution of laser power and temperature measured by K absorption spectroscopy. The output feature and temperature rise of a multi-pulse DPAL are also calculated in the time domain, showing that if we energize the pump light when the temperature rise decays to 1/2, rather than 1/e of its maximum, we can increase the duty cycle and obtain more output energy. The repetition rate of >100Hz is high enough to achieve QCW (quasi-continuous-wave) laser pulses.

Kinetic and fluid dynamic modeling, numerical approaches of flowing-gas diode-pumped alkali vapor amplifiers.

Comprehensive analysis of kinetic and fluid dynamic processes in flowing-gas diode-pumped alkali vapor amplifiers is reported. Taking into account effects of the temperature, the amplified spontaneous emission, the saturation power, the excitation of the alkali atoms to high electronic levels and the ionization, a detailed physical model is established to simulate the output performance of flowing-gas diode-pumped alkali vapor amplifiers. Influences of the flow velocity and the pump power on the amplified power are calculated and analyzed. Comparisons between single and double amplifier, longitudinal and transverse flow are made. Results show that end-pumped cascaded amplifier can provide higher output power under the same total pump power and the cell length, while output powers achieved by single- and double-end pumped, double-side pumped amplifiers with longitudinal or transverse flow have a complicated but valuable relation. Thus the model is extremely helpful for designing high-power flowing-gas diode-pumped alkali vapor amplifiers.

Modeling of a diode four-side symmetrically pumped alkali vapor amplifier.

Considering the amplified spontaneous emission, the saturation effect and the energy distributions of the incident pump and seed lasers, a physical model is established to describe the kinetic process and the output performance of a four sided diode pumped alkali vapor laser amplifier. According to the experimental parameters of a single-side pumped configuration with a diffuse type hollow cylinder cavity, energy distributions in the cell and influences of several important factors are simulated and analyzed. The model is validated by comparing the simulation result with the experimental data, which shows the model can provide an effective way for designing an efficient diode four-side symmetrically pumped alkali vapor laser amplifier.

Noninvasive Nonlinear Optical Computational Histology.

Cancer remains a global health challenge, demanding early detection and accurate diagnosis for improved patient outcomes. An intelligent paradigm is introduced that elevates label-free nonlinear optical imaging with contrastive patch-wise learning, yielding stain-free nonlinear optical computational histology (NOCH). NOCH enables swift, precise diagnostic analysis of fresh tissues, reducing patient anxiety and healthcare costs. Nonlinear modalities are evaluated, including stimulated Raman scattering and multiphoton imaging, for their ability to enhance tumor microenvironment sensitivity, pathological analysis, and cancer examination. Quantitative analysis confirmed that NOCH images accurately reproduce nuclear morphometric features across different cancer stages. Key diagnostic features, such as nuclear morphology, size, and nuclear-cytoplasmic contrast, are well preserved. NOCH models also demonstrate promising generalization when applied to other pathological tissues. The study unites label-free nonlinear optical imaging with histopathology using contrastive learning to establish stain-free computational histology. NOCH provides a rapid, non-invasive, and precise approach to surgical pathology, holding immense potential for revolutionizing cancer diagnosis and surgical interventions.

Rapid, high-contrast, and steady volumetric imaging with Bessel-beam-based two-photon fluorescence microscopy.

Significance: Two-photon fluorescence microscopy (TPFM) excited by Gaussian beams requires axial tomographic scanning for three-dimensional (3D) volumetric imaging, which is a time-consuming process, and the slow imaging speed hinders its application for in vivo brain imaging. The Bessel focus, characterized by an extended depth of focus and constant resolution, facilitates the projection of a 3D volume onto a two-dimensional image, which significantly enhances the speed of volumetric imaging. Aim: We aimed to demonstrate the ability of a TPFM with a sidelobe-free Bessel beam to provide a promising tool for research in live biological specimens. Approach: Comparative in vivo imaging was conducted in live mouse brains and transgenic zebrafish to evaluate the performance of TPFM and Bessel-beam-based TPFM. Additionally, an image-difference method utilizing zeroth-order and third-order Bessel beams was introduced to effectively suppress background interference introduced by sidelobes. Results: In comparison with traditional TPFM, the Bessel-beams-based TPFM demonstrated a 30-fold increase in imaging throughput and speed. Furthermore, the effectiveness of the image-difference method was validated in live biological specimens, resulting in a substantial enhancement of image contrast. Importantly, our TPFM with a sidelobe-free Bessel beam exhibited robustness against axial displacements, a feature of considerable value for in vivo experiments. Conclusions: We achieved rapid, high-contrast, and robust volumetric imaging of the vasculature in live mouse brains and transgenic zebrafish using our TPFM with a sidelobe-free Bessel beam.

Composition Regulation of Potassium Sodium Niobate Thin Films through Post-Annealing under Alkali Element Atmospheres.

Amorphous potassium sodium niobate (KNN) films were synthesized at 300 °C through the radio frequency magnetron sputtering method and subsequently crystallized by post-annealing at 700 °C in various alkali element atmospheres (Na and K). The as-deposited film is notably deficient in alkali metal elements, particularly K, whereas the loss of alkali elements in the films can be replenished through annealing in an alkali element atmosphere. By adjusting the molar ratio of Na and K in the annealing atmosphere, the ratio of Na/K in the resultant film varied, consequently suggesting the efficiency of this method on composition regulation of KNN films. Meanwhile, we also found that the physical characteristics of the films also underwent differences with the change of an annealing atmosphere. The films annealed in a high Na atmosphere exhibit large dielectric losses with limited piezoelectric vibration behavior, while annealing in a high K atmosphere reduces the dielectric losses and enhances the piezoelectric behavior. Furthermore, the results of vibration measurement demonstrated that the film annealed in a mixed powder of 25% Na2CO3 and 75% K2CO3 exhibits an optimal vibration displacement of ~400 pm under the sinusoidal excitation voltage of 8 V. This approach of altering the composition of KNN films through post-annealing may introduce the new concept of property design of KNN as well as other similar films.

Data-driven coordinated attention deep learning for high-fidelity brain imaging denoising and inpainting.

Deep learning offers promise in enhancing low-quality images by addressing weak fluorescence signals, especially in deep in vivo mouse brain imaging. However, current methods struggle with photon scarcity and noise within in vivo deep mouse brains, and often neglecting tissue preservation. In this study, we propose an innovative in vivo cortical fluorescence image restoration approach, combining signal enhancement, denoising, and inpainting. We curated a deep brain cortical image dataset and developed a novel deep brain coordinate attention restoration network (DeepCAR), integrating coordinate attention with optimized residual networks. Our method swiftly and accurately restores deep cortex images exceeding 800 µm, preserving small-scale tissue structures. It boosts the peak signal-to-noise ratio (PSNR) by 6.94 dB for weak signals and 11.22 dB for large noisy images. Crucially, we validate the effectiveness on external datasets with diverse noise distributions, structural features compared to those in our training data, showcasing real-time high-performance image restoration capabilities.

Multiscale Structural Engineering Boosts Piezoelectricity in Na0.5Bi2.5Nb2O9-Based High-Temperature Piezoceramics.

High-temperature piezoelectric materials, which enable the accurate and reliable sensing of physical parameters to guarantee the functional operation of various systems under harsh conditions, are highly demanded. To this end, both large piezoelectricity and high Curie temperature are pivotal figures of merit (FOMs) for high-temperature piezoceramics. Unfortunately, despite intensive pursuits, it remains a formidable challenge to unravel the inverse correlation between these FOMs. Herein, a conceptual material paradigm of multiscale structural engineering was proposed to address this dilemma. The synergistic effects of phase structure reminiscent of a polymorphic phase boundary and refined domain morphology simultaneously contribute to a large piezoelectric coefficient d33 of 30.3 pC/N and a high Curie temperature TC of 740 °C in (LiCeNd) codoped Na0.5Bi2.5Nb2O9 (NBN-LCN) ceramics. More encouragingly, the system has exceptional thermal stability and is nonsusceptible to mechanical loading. This study not only demonstrates that the high-performance and robust NBN-LCN high-temperature piezoceramics hold great potential for implements under harsh conditions but also opens an avenue for integrating antagonistic properties for the enhancement of the collective performance in functional materials.

Deep learning-based high-speed, large-field, and high-resolution multiphoton imaging.

Multiphoton microscopy is a formidable tool for the pathological analysis of tumors. The physical limitations of imaging systems and the low efficiencies inherent in nonlinear processes have prevented the simultaneous achievement of high imaging speed and high resolution. We demonstrate a self-alignment dual-attention-guided residual-in-residual generative adversarial network trained with various multiphoton images. The network enhances image contrast and spatial resolution, suppresses noise, and scanning fringe artifacts, and eliminates the mutual exclusion between field of view, image quality, and imaging speed. The network may be integrated into commercial microscopes for large-scale, high-resolution, and low photobleaching studies of tumor environments.

Super-Multiplex Nonlinear Optical Imaging Unscrambles the Statistical Complexity of Cancer Subtypes and Tumor Microenvironment.

Label-free nonlinear optical imaging (NLOI) has made tremendous inroads toward unscrambling the microcosmic complexity of cancers. However, harmonic and Raman microscopy offers throughput without redox information to reveal metabolic differentiation, and fluorescence lifetime microscopy lacks the vibrational response of molecules to visualize specific molecular constituents such as lipid. Here, a flexible, robust simultaneous multi-nonlinear imaging and cross-modality system that combines complementary imaging contrast mechanisms is demonstrated. This system, utilizing multiplexed ultrashort pulses, ingeniously integrates typical nonlinear processes, and high-dimension lifetime extension in a single setup to enhance the imaging dimensions and quality. Using this system, the authors perform label-free comprehensive evaluation of clinicopathological tissues of ovarian carcinoma due to its statistical complexity. The results show that the technology provides statistically rich, insightful information with high accuracy, sensitivity, and specificity, in contrast to standard histopathology, and can potentially be a powerful tool for fundamental cancer research and clinical applications.

Deep learning autofluorescence-harmonic microscopy.

Laser scanning microscopy has inherent tradeoffs between imaging speed, field of view (FOV), and spatial resolution due to the limitations of sophisticated mechanical and optical setups, and deep learning networks have emerged to overcome these limitations without changing the system. Here, we demonstrate deep learning autofluorescence-harmonic microscopy (DLAM) based on self-alignment attention-guided residual-in-residual dense generative adversarial networks to close the gap between speed, FOV, and quality. Using the framework, we demonstrate label-free large-field multimodal imaging of clinicopathological tissues with enhanced spatial resolution and running time advantages. Statistical quality assessments show that the attention-guided residual dense connections minimize the persistent noise, distortions, and scanning fringes that degrade the autofluorescence-harmonic images and avoid reconstruction artifacts in the output images. With the advantages of high contrast, high fidelity, and high speed in image reconstruction, DLAM can act as a powerful tool for the noninvasive evaluation of diseases, neural activity, and embryogenesis.

Multidimensional quantitative characterization of the tumor microenvironment by multicontrast nonlinear microscopy.

Characterization of the microenvironment features of tumors, such as its microstructures, biomolecular metabolism, and functional dynamics, may provide essential pathologic information about the tumor, tumor margin, and adjacent normal tissue for early and intraoperative diagnosis. However, it can be particularly challenging to obtain faithful and comprehensive pathological information simultaneously from unperturbed tissues due to the complexity of the microenvironment in organisms. Super-multiplex nonlinear optical imaging system emerged and matured as an attractive tool for acquisition and elucidation of the nonlinear properties correlated with tumor microenvironment. Here, we introduced a nonlinear effects-based multidimensional optical imaging platform and methodology to simultaneously and efficiently capture contrasting and complementary nonlinear optical signatures of freshly excised human skin tissues. The qualitative and quantitative analysis of autofluorescence (FAD), collagen fiber, and intracellular components (lipids and proteins) illustrated the differences about morphological changes and biomolecular metabolic processes of the epidermis and dermis in different skin carcinogenic types. Interpretation of multi-parameter stain-free histological findings complements conventional H&E-stained slides for investigating basal cell carcinoma and pigmented nevus, validates the platform's versatility and efficiency for classifying subtypes of skin carcinoma, and provides the potential to translate endogenous molecule into biomarker for assisting in rapid cancer screening and diagnosis.

Ultrafast and hypersensitive phase imaging of propagating internodal current flows in myelinated axons and electromagnetic pulses in dielectrics.

Many ultrafast phenomena in biology and physics are fundamental to our scientific understanding but have not yet been visualized owing to the extreme speed and sensitivity requirements in imaging modalities. Two examples are the propagation of passive current flows through myelinated axons and electromagnetic pulses through dielectrics, which are both key to information processing in living organisms and electronic devices. Here, we demonstrate differentially enhanced compressed ultrafast photography (Diff-CUP) to directly visualize propagations of passive current flows at approximately 100 m/s along internodes, i.e., continuous myelinated axons between nodes of Ranvier, from Xenopus laevis sciatic nerves and of electromagnetic pulses at approximately 5 × 107 m/s through lithium niobate. The spatiotemporal dynamics of both propagation processes are consistent with the results from computational models, demonstrating that Diff-CUP can span these two extreme timescales while maintaining high phase sensitivity. With its ultrahigh speed (picosecond resolution), high sensitivity, and noninvasiveness, Diff-CUP provides a powerful tool for investigating ultrafast biological and physical phenomena.