Cancer remains a major life-threatening disease worldwide, as reported by the World Health Organization (WHO). Surgery is the primary therapy for most solid tumors, with the ideal outcome relying on a balance between complete tumor removal and maximal preservation of surrounding normal tissue. Current clinical imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) lack the resolution to accurately delineate tumor boundaries. The gold standard in clinics for detecting tumor boundaries and infiltration is the histopathological analysis of surgical specimens via hematoxylin and eosin (H&E) staining. However, the H&E staining workflow requires time-consuming tissue processing, including formalin fixation, paraffin embedding, and manual staining, often taking more than a day before diagnostic results are available to surgeons. Consequently, there is an urgent demand for new real-time microscopic imaging techniques that can be used intraoperatively to provide instant feedback during tumor surgery.

Recent years have seen promising developments in label-free nonlinear imaging techniques for real-time tissue pathology in the operating room. These techniques include multiphoton fluorescence microscopy, optical coherence tomography (OCT), Raman microscopy, and harmonic microscopy, which can visualize tumor margins without exogenous labels. Among these, third harmonic generation (THG) combined with second harmonic generation (SHG) offers a unique, label-free subcellular-resolution assessment of fresh and unprocessed tissues. THG signals arise from nonlinear three-photon optical responses at cell-cell and cell-matrix interfaces (Fig. 1), effectively detecting proliferative cells and vasculatures, key hallmarks of tumor pathology. THG microscopy stands out by providing sub-cellular resolution, rich cellular and molecular information, and images of H&E quality. Additionally, using a single beam, complementary information from SHG, two-photon excited fluorescence (2PEF), and three-photon excited fluorescence (3PEF) can be simultaneously collected, visualizing extensive architectural and molecular details. These advantages position THG imaging as a highly promising technique for intraoperative determination of tumor margins.

In this review, we explore the fundamental principles of the THG nonlinear process and discuss its latest applications in intraoperative tumor imaging. We highlight recent engineering innovations enabling miniaturized, portable THG imaging systems suitable for operating room deployment. We also review pioneering efforts in developing THG-capable endoscope probes using flexible fiber-optics, potentially integrating with standard surgical equipment. Embedding THG microscopy seamlessly into clinical workflows can provide surgeons with real-time, in-situ histopathology, enhancing surgical outcomes without disrupting the surgical rhythm. This review aims to accelerate the translation and adoption of label-free nonlinear optical imaging, particularly THG microscopy, as a valuable intraoperative guidance tool.

Recent studies have demonstrated the potential of integrated THG, SHG, and multiphoton fluorescence microscopy for ex-vivo characterization of freshly resected human brain tumors (Fig. 2), ovarian tumors, breast cancer specimens, lung tumors (Fig. 3), and other tumor types. These studies reveal pathological hallmarks such as increased cellularity, nuclear pleomorphism, and vascular proliferation. The in-situ extraction of tumor pathological features underscores THG imaging's potential to improve surgical outcomes. Efforts are underway to transition THG microscopy from benchtop to clinically viable tools. Most THG microscopes are currently confined to research labs, with large volumes, complex opto-mechanical components, and limited consideration for patient safety or imaging stability. To facilitate widespread intraoperative use, miniaturized and portable THG imaging platforms are necessary. Researchers in the Netherlands and the USA have independently developed compact, multimodal THG microscopes, and these devices have been tested in clinical settings, such as operation rooms or pathological laboratories, for pilot clinical validation (Fig. 4). These devices enable on-site assessment of surgical specimens and provide rapid diagnostic feedback for tumor classification and margin determination, assisting surgeons in decision-making. However, existing miniaturized THG microscopes are limited to ex-vivo imaging. To enable real-time, in-situ guidance without tissue removal, endoscopic techniques are essential for THG imaging. The nonlinear imaging field is witnessing increasing efforts to design THG-capable endoscopes, drawing from innovations in 2PEF/3PEF, SHG, OCT, and Raman microscopy (Fig. 5). THG endoscopy is still in its early stages, presenting numerous opportunities for scientific research, technology translation, and clinical studies.

THG imaging shows promise for real-time intraoperative assessment of various cancer types. Significant progress has been made in developing compact, portable THG imaging systems for intraoperative use. Currently, only two groups have begun clinical testing with their portable THG microscopes. More systematic clinical testing is needed to further mature this technology for routine operation room use. Additionally, technical translations from other imaging modalities are required to advance THG endoscopy solutions. Despite the vast potential of THG microscopy for real-time, non-destructive assessment of fresh tissue, more efforts from both the scientific and industrial sectors are imperative to promote the translation of THG microscopes from laboratories to clinical settings.

X-ray luminescence computed tomography (XLCT) technology uses X-ray excitation to stimulate specific luminescent materials at the nanoscale, termed phosphor nanoparticles (PNPs), to produce near-infrared light. Photodetectors then capture the emitted near-infrared light signals from these excited PNPs. Through suitable algorithms, the distribution of PNPs within biological tissues can be visualized. This method allows for structural and functional insights into biological tissues, showing great potential for advancement. There are two main types of XLCT systems: narrow-beam and cone-beam. The narrow-beam XLCT system exhibits higher spatial resolution, albeit at the cost of lower X-ray utilization efficiency. This inefficiency results in extended imaging times, limiting its potential for clinical use. Conversely, the cone-beam XLCT system improves X-ray efficiency and shortens detection time. However, the quality of the reconstructed images tends to be lower due to detection angle limitations. To overcome these challenges, there is a need for an innovative XLCT system that realizes rapid and highly sensitive data collection while also maximizing the use of X-ray technology. By addressing these issues, the clinical limitations of XLCT can be reduced to pave the way for its further development, thereby unlocking a plethora of possibilities.

This study introduces a new cone-beam XLCT system based on photon-counting measurements, complemented by an associated reconstruction method. Through the synergistic collaboration between the field-programmable gate array (FPGA) based sub-sampling unit and upper-level control unit, the system realizes automated multi-channel measurements. This integration shortens data acquisition time, boosts experimental efficiency, and mitigates the risks associated with X-ray exposure. After the completion of system implementation, we conduct experimental validation of the system and methodology. Specifically, a fabricated phantom is subjected to multi-angle projection measurements using the established system, and image reconstruction and evaluation are performed using the Tikhonov reconstruction algorithm.

The results of the dual target phantom experiment indicate that under the conditions of a cylindrical phantom radius of 40 mm, target radius of 6 mm, and distance of 14 mm from the dual target phantom (Fig.2), the similarity coefficient (DICE) of the reconstructed image of the dual target phantom exceeds 50% under six-angle cone-beam X-ray irradiation. Furthermore, the system fidelity (SF) exceeds 0.7 (Table 1). In the phantom experiment of dual targets with different concentrations, the system proposed in this study effectively distinguishes dual targets with a mass concentration difference of more than 3 mg/mL. The DICE of the reconstruction image maintains over 50%, SF remains over 0.7, and reconstruction concentration error (RCE) is also over 0.7 (Table 2). These phantom experiment results confirm the good fidelity and resolution capability of the proposed system. Nevertheless, numerous factors potentially degrade the experimental outcomes, such as the attenuation and scattering of X-ray beams in the XLCT system, the physical and chemical composition of the target body, or even uneven concentration distribution. Additionally, artifacts appear in the reconstructed images. In the future, our research will focus on optimizing algorithms and reducing noise to enhance the application of cone-beam XLCT for in vivo experiments.

This study comprehensively considers the advantages and disadvantages of two imaging methods in XLCT and proposes a photon-counting-based multi-channel cone-beam XLCT system. The system automation for multi-angle measurements is realized via FPGA and host computer interaction. Specifically, multi-angle cone-beam irradiation reduces data acquisition time, while photon-counting measurement enhances the system sensitivity. Furthermore, a phantom experiment is conducted to validate the effectiveness and practicality of the proposed system and algorithm. The results demonstrate a significant reduction in data acquisition time and an improvement in the utilization of X-rays.

Cells, the basic structural and functional units, play an essential role in the development, aging, disease, and death of organisms. Since the first microscopic observation of cells by Robert Hooke in 1665, numerous advanced technical and theoretical methods have been developed over the past centuries to microscopically visualize cells, enabling a thorough analysis of life activities from the cellular to the molecular levels. Cells are composed of numerous macromolecular complexes with different sizes and diverse compositions. For example, the eukaryotic 80S ribosome is composed of large and small subunits, and each subunit contains various ribosomal RNA (rRNA) and ribosomal proteins. These complexes are usually considered as core signaling hubs to precisely control cellular structures and functions during various biological activities. Accordingly, cells can properly generate immediate responses to frequent environmental changes and distinct cellular stresses. Therefore, a mechanistic investigation of the structural assembly of these key signaling hubs and their functional regulation is necessary to improve our understanding of life activities and to identify potential therapeutic targets for disease treatment.

Currently, single-particle cryo-electron microscope (cryo-EM), which requires only a small number of samples for analysis and does not involve the use of crystals unlike traditional X-ray-based methods, is the most powerful tool in structural biology owing to its extremely high spatial resolution. However, precisely resolving a structure using cryo-EM involves purification or enrichment of the target biomolecules, which increases the risk of inconsistency between in vitro resolved structures and the native structures in cells. Notably, owing to the lack of molecular specificity, understanding the interactions among different molecules when resolving multi-component complexes is challenging. In addition, high-quality cryo-EM analyses depend on the computational averaging of thousands of images of identical particles with good homogeneity and are thus currently unsuitable for evaluating highly heterogeneous signaling hubs that determine cell fates.

Excitingly, super-resolution microscope (SRM) has emerged as an effective solution to these above-mentioned challenges. Fluorescence imaging is an indispensable technical tool for modern biological research owing to its molecular specificity, in situ visualization feature, and multiplex analysis ability. Super-resolution imaging, which overcomes the optical diffraction limit, is an efficient method for visualizing the arrangement and functions of biological hundred-nanometer signalosomes at the subcellular scale or even with single-molecule precision.

This review first introduces the basic principles and technical development of several major types of SRM, including stimulated emission depletion microscope (STED), structured illumination microscope (SIM), photoactivated localization microscope (PALM), stochastic optical reconstruction microscope (STORM), point accumulation for imaging in nanoscale topography (PAINT), DNA-PAINT, and minimal photon fluxes (MINFLUX). These tools have facilitated precise visualization of various biological activities and targets at remarkably high temporal and/or spatial resolutions, even reaching the molecular or angstrom scale in some extreme cases (Figs.1-2). More importantly, to date, several representative SRM-based applications in life science research have been demonstrated. Through rationale optimization of the key steps in STORM (including structure preservation, fluorescence labeling, signal acquisition, and image analysis), Xin Chen’s group from Xiamen University first visualized the ordered organization of necrosomes at the nanoscale and revealed their underlying mechanism to effectively initiate MLKL (a mixed lineage kinase domain-like protein)-dependent necroptosis and to precisely control the transition between apoptosis and necroptosis in cells stimulated by tumor necrosis factor (TNF). Maria Pia Cosma’s group from the Barcelona Institute of Science and Technology employed single-molecule localization microscope (SMLM) to investigate genome organization, especially the formation of chromatin ring structures. They proposed that the transcription-dependent negative superhelix primarily drives the master molecule cohesin to generate ring structures in vivo. The team led by Ana J. Garcia-Saez from the University of Tübingend quantitatively imaged Bax- and Bak-mediated pores in the mitochondrial outer membrane during intrinsic cell apoptosis; they observed the interplay of apoptosis and inflammation by controlling the dynamics of the mitochondrial content release. Ardem Patapoutian’s group from the Scripps Research utilized the iPALM and MINFLUX technologies to directly visualize the conformational stages of the mechanosensitive channel PIEZO1 in complex cellular environments (Fig.3). Finally, based on the practical experience gained from our group’s efforts, we summarized some important strategies, such as methods to minimize reconstruction artifacts, improve labeling efficiency, and strengthen quantitative analysis of super-resolved images, to obtain high-quality super-resolution images using SMLM (Fig.4).

With the groundbreaking innovation of SMLM in the past two decades, our understanding of structural organization and functional regulation in multiple types of cells undergoing various biological activities has improved. Although the classic genetic and biochemical experiments revealed the fundamental cellular mechanisms, cell imaging provides more precise and intuitive information on molecular interactions in situ. Therefore, the spatial resolution of SMLM can be further improved up to the molecular level to precisely depict an informative signaling network for a variety of critical biological processes. Thus, considering the continuous development of SMLM and other SRM technologies, we believe that in situ nanoscale functional organization of key signaling hubs will become one of the most promising research areas in cell biology in the near future. In addition, SMLM is expected to revolutionize research in science and technology and lead to outstanding discoveries in the next 5-10 years.

Because of the wave characteristics of light, conventional fluorescence microscopy is typically restricted by the diffraction limit, which is approximately 200 nm laterally and 500 nm axially. Super-resolution microscopy has overcome this barrier and improved the imaging resolution to a few nanometers, which enables the observation of biological structures at a nanoscale and revolutionizes the development of life sciences. Super-resolution microscopy can be classified into three types. The first type is scanning imaging based on point spread function (PSF) decoration, whose representative technique is stimulated emission depletion (STED). The second is wide-field imaging based on spectrum spread, whose representative technique is structured illumination microscopy (SIM). The third is single-molecule localization microscopy (SMLM), also known as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM). In super-resolution fluorescence microscopy, both instrumentation and sample-induced aberrations decrease the spatial resolution and degrade the imaging quality. Therefore, the adaptive optics (AO) technique is applied, which detects aberrations using direct or indirect methods, and performs compensation through wavefront correction elements to capture high-quality super-resolution images (Fig.1). This review introduces the origin and working principle of AO, summarizes its application in super-resolution fluorescence microscopy, and highlights its future development prospects.

In STED microscopy [see Fig.2(a)], aberrations in the excitation, depletion, and emission paths influence the image quality simultaneously, particularly in the depletion path, which need to be corrected with AO. In 2012, Gould et al. proposed the first implementation of AO in STED microscopy, which used modal sensing with the sharpness metric to examine the aberrations, and performed corrections with two spatial light modulators (SLMs) in both excitation and depletion paths [see Fig.2(b)]. They imaged fluorescence beads at a depth of 25 μm above the retina sections of a zebrafish, with an axial resolution of 250 nm. In 2014, Lenz et al. proposed an off-axis holography configuration that used one SLM to correct instrumentation and sample-induced aberrations [see Fig.2(d)]. They achieved a lateral resolution of 120 nm and an axial resolution of 173 nm when imaging tubulin at depths of 8?10 μm. In 2016, Patton et al. proposed an implementation that incorporates two AO elements to enable aberration correction in all three beam paths [see Fig.2(e)]. They used modal sensing with the Fourier ring correlation (FRC) metric and resolved glutamatergic vesicles in neural boutons in intact brains of Drosophila melanogaster at a depth of 10 μm. In 2019, Zdankowski et al. proposed an automated AO solution to correct instrumentation and sample-induced aberrations. They used modal sensing with the brightness metric and achieved super-resolution imaging of a 15 μm mitotic spindle with a resolution of 50 nm×50 nm×100 nm. On this basis, in 2020, Zdankowski et al. combined AO with image denoising algorithm by block-matching and collaborative three-dimensional (3D) filtering (BM3D) to enhance the image quality and super-resolved 3D imaging of axons in differentiated induced pluripotent stem cells growing under an 80 μm thick layer of tissue with lateral and axial resolutions of 204 and 310 nm, respectively [see Fig.3(a)]. In 2020, Antonello et al. proposed using wavelet analysis to quantify resolution loss and established a multivalued image quality metric. They achieved super-resolution imaging of CA1 pyramidal neurons in an organotypic hippocampal slice at a depth of 14 μm. In 2021, Hao et al. combined AO with 4Pi-STED. They used two deformable mirrors (DMs) in the two paths and analyzed the aberrations with modal sensing [see Fig.4]. They achieved sub 50 nm isotropic resolution of structures, such as neuronal synapses and ring canals previously inaccessible in tissues. Other indirect or direct wavefront detection techniques have been also used to measure aberrations in STED microscopy.

In SIM [see Fig.6(a)], aberrations in excitation and emission paths decrease the imaging quality and should be corrected with AO. In 2008, Débarre et al. implemented sensorless AO in SIM. They investigated how the image formation process in this type of microscopy is affected by aberrations and performed aberration correction with modal sensing. In 2015, Thomas et al. combined sensorless AO with SIM and achieved super-resolution imaging of 100 nm fluorescence beads fixed beneath a C. elegans sample with a 140 nm resolution. In 2021, Zheng et al. proposed an AO correction method based on deep learning and utilized the method to correct aberrations with SLM, realizing super-resolution imaging of phalloidin-labeled actin in cultured BHK cells. Recently, direct wavefront sensing has also been used in SIM. In 2019, Turcotte et al. applied AO in SIM in vivo by generating the guide star with two-photon excitation as the input of the Shack-Hartmann wavefront sensor and performing aberration correction with a DM. They imaged the brains of live zebrafish larvae [see Fig.5(a)] and mice and observed the dynamics of dendrites and dendritic spines at nanoscale resolution. Similarly, in 2020, Li et al. used AO in optical-sectioning SIM [see Fig.6(b)] and achieved fast, high-resolution in-vivo imaging of mouse cortical neurons at depths of 21?29 μm [see Fig.5(b)] and zebrafish larval motor neurons at depths of 10?110 μm. In 2021, Lin et al. used direct wavefront sensing in SIM with a configuration that can be switched among wide-field imaging, structured illumination, and confocal illumination [see Fig.6(c)]. They used modal sensing to correct the aberrations of fluorescence beads and then recorded the image arrays in Shack-Hartmann wavefront sensor as a reference. Subsequently, they used confocal illumination to generate the guide star, input it into the Shack-Hartmann wavefront sensor, and reconstructed the wavefront. They decreased the peak-valley values of the wavefront amplitude from 1.5 to 0.1 μm when imaging C.elegans.

In SMLM [see Fig.7(a)], aberrations in the emission path result in distorted PSFs and decreased localization precision, which should be corrected with AO. In 2015, Burke et al. proposed a technique for correcting aberrations using modal sensing with the sharpness metric [see Fig.7(c)]. They achieved a resolution of 78 nm laterally and 136 nm axially for microtubules at a depth of 6 μm. Tehrani et al. optimized aberrations using genetic algorithm [see Fig.7(d)] with the intensity-independent Fourier metric and increased the localization precision by four times at a depth of 50 μm. In 2017, Tehrani et al. proposed a real-time wavefront aberration correction approach based on particle swarm optimization [see Fig.7(e)] and the intensity-independent Fourier metric. They achieved a resolution of 146 nm for the central nervous system of Drosophila melanogaster at a depth of 100 μm. In 2018, Mlodzianoski et al. developed adaptive astigmatism using Nelder-Mead simplex algorithm to correct wavefront distortions with the weighted sharpness metric. They achieved a resolution of 20 nm laterally and 50 nm axially for mitochondria at a depth of 95 μm. In 2021, Siemons et al. proposed robust and effective adaptive optics in localization microscopy (REALM) combined with modal sensing using the weighted sharpness metric [see Fig.7(f)]. They achieved an FRC resolution of 76 nm for microtubules [see Fig.8(a)] and cytoskeletal spectrin of the axon initial segment at a depth of 50 μm. In 2023, Zhang et al. proposed deep-learning-driven adaptive optics (DL-AO) that examined aberrations from detected PSFs using deep neuron network [see Fig.7(g)]. They achieved a resolution of 14?31 nm laterally and 41?81 nm axially for mitochondria [see Fig.8(b)] and dendrites at a depth of 133 μm. In 2023, Park et al. developed closed-loop accumulation of single-scattering (CLASS), which measured complex tissue aberrations from intrinsic reflectance and performed compensation [see Fig.7(h)], and resolved subdiffraction morphologies of cilia and oligodendrocytes in entire zebrafish at a depth of 102 μm, improving the localization precision from 67 nm to 34 nm.

This review summarizes the application of adaptive optics in super-resolution microscopy, including indirect and direct wavefront detection. Indirect wavefront sensing requires no setup modifications, except for inserting the wavefront correction elements, which is economical and practical. However, the low response speed and narrow dynamic range limit its effectiveness for severe distortions. Direct wavefront sensing can provide increased response speed and dynamic range, despite its increasing complexity in instrumentation. The future prospects of AO methods in super-resolution microscopy include increasing the field-of-view, response speed, and imaging depth. We expect that the AO method will be a general option in future super-resolution fluorescence microscopy.

In recent years, the rapid development of bioimaging technology has provided powerful tools for life science research. Among them, fluorescence imaging, as an important imaging technique, enables real-time and non-invasive visualization of physiological activities in biological systems. Since biological tissues have lower absorption and scattering of photons in the near-infrared region Ⅱ (NIR-Ⅱ), combined with the weaker autofluorescence of tissues in this region, the signal-to-background ratio is greatly improved. Therefore, NIR-Ⅱ fluorescence imaging can achieve deeper and higher-resolution biological imaging, and is expected to be widely used as an ideal precision imaging technique in basic research and clinical practice in the future.

NIR-Ⅱ fluorescence probes can be mainly categorized into inorganic and organic probes. Organic probes have advantages such as strong near-infrared absorbance, good biocompatibility, and easy metabolism, making them the preferred choice for in vivo imaging. Currently, there are two major classes of organic probes used in NIR?Ⅱ fluorescence imaging. One class is dyes with a donor-acceptor-donor structure, and the other class is cyanine dyes connected by conjugated polymethyl chains with a certain length of carbon atoms. Compared with donor-acceptor-donor dyes, the synthesis process of NIR-Ⅱ cyanine dyes is relatively simple, and they have higher brightness, thus possessing significant advantages in NIR-Ⅱ imaging. Cyanine dyes, as a highly valuable class of molecular probes, exhibit excellent fluorescence characteristics in the NIR-Ⅱ region, so that they have attracted extensive research interests and continue to develop in the field of disease diagnosis and treatment. Due to the high tissue penetration depth and low interference from biological background signals, NIR‐Ⅱ cyanine dyes can overcome the drawbacks of traditional fluorescence probes and be applied in the diagnosis of diseases.

Cancer is one of the leading causes of death of the global population, characterized by high mortality and recurrence rates. NIR-Ⅱ cyanine dyes can be used for tumor detection and visualization in the NIR-Ⅱ region. Their high sensitivity and high-resolution imaging make them important tools for early tumor diagnosis. Additionally, cyanine dyes also have significant advantages in real-time dynamic display of tumor boundaries, providing critical information for tumor resection surgery. Inflammation is a protective response to stimuli. However, if inflammation persists without timely diagnosis and effective control, the detrimental effects will outweigh its biological benefits. NIR-Ⅱ cyanine dyes also have important value in the application of inflammatory diseases. On the one hand, they can precisely locate the inflammatory area, and on the other hand, by monitoring the distribution and concentration changes of the dye in the body, the activity of inflammation can be evaluated, providing guidance for treatment. NIR-Ⅱ cyanine dyes can also effectively differentiate and locate the sites of injury, visualize injuries, and help assess the extent of tissue injuries. Furthermore, the combination of NIR-Ⅱ cyanine dyes with drugs enables targeted drug delivery to tumors, inflammatory areas, or injured sites. By monitoring the distribution of the drug-dye complexes in the body, the therapeutic effect can be assessed in real time. These advanced applications demonstrate the tremendous potential of NIR-Ⅱ cyanine dyes in the field of modern medicine and their broad application prospects in diseases.

The latest advancements in the applications of NIR‐Ⅱ cyanine dyes in various diseases are summarized. First, the structural characteristics, classifications, and applications of cyanine dyes are introduced. Then, the utilization of NIR-Ⅱ cyanine dyes in various tumors such as brain tumors, breast cancer, pancreatic cancer, liver cancer, bladder cancer, colorectal cancer, gastric cancer and other tumors is comprehensively reviewed, referencing prior researches. Tian’s research group from University of Chinese Academy of Sciences and Gambhir et al. from Stanford University have developed an integrated visible and NIR-Ⅰ/Ⅱ multispectral imaging instrument to perform the first human liver tumor surgery. They have taken relatively pioneering studies on treatment of tumors. Additionally, the research group from Fudan University, led by Zhang, has developed a tumor-microenvironment-responsive lanthanide-cyanine fluorescence resonance energy transfer (FRET) sensor for NIR-Ⅱ luminescence-lifetime in situ imaging of hepatocellular carcinoma [Fig. 5(a)]. The applications of NIR-Ⅱ cyanine dyes in various inflammatory diseases like acute vascular inflammation, rheumatoid arthritis, gastritis, and in injuries related to liver, kidney, and biliary tract are further discussed. Liu et al. collaborated on cyanine-doped lanthanide metal-organic frameworks for NIR-Ⅱ bioimaging [Fig. 6(a)]. It is noted that the application research of NIR-Ⅱ cyanine dyes is still limited and not comprehensive. Finally, the challenges and research trends in this field are discussed.

NIR?Ⅱ cyanine dyes have tremendous potential in the imaging and treatment of tumors, inflammatory diseases, and injuries. In summary, further in-depth exploration is needed for the development of NIR-Ⅱ cyanine dyes to promote their wider clinical applications, and bring new breakthroughs and developments to the fields of medical imaging and clinical diagnosis.

The nuclear pore complex (NPC) is an intricate structure comprising multiple distinct nuclear pore proteins known as nucleoporins (Nups). It plays a crucial role in the transformation of matter and information between the nucleus and cytoplasm. With a total molecular weight of 110‒125 MDa, the NPC is hailed as the "holy grail" of structural biology. Scientists have used such techniques as electron microscopy, atomic force microscopy, and cryoelectron microscopy to collectively reveal the composition, assembly, and ultrastructure of the NPC, providing a solid structural foundation for further exploration of its functions. The diameter of the NPC is approximately 130 nm. Therefore, single-molecule localization microscopy (SMLM) with an imaging resolution of 20 nm is an ideal tool for studying the ultrastructure of NPC. However, during long-term imaging, data loss may occur because of sparse blinking, and the dynamic activities of life also lead to heterogeneity in imaging results, posing challenges for data analysis. To address these issues, corresponding image reconstruction methods must be developed. Clustering algorithms are powerful tools for quantitative extraction, classification, and analysis of SMLM data. The unique clustered distribution structure of the NPC makes clustering methods highly suitable for structural analysis of the NPC. Therefore, to compensate for the limitations of SMLM data and obtain more detailed structural information about the NPC, a processing procedure for SMLM images of the NPC was developed in this study based on clustering algorithms. It involves screening out NPC structures with a more uniform morphology, followed by subjecting these structures to high-throughput statistical analysis and reconstruction.

After PFA fixation, permeabilization with a blocking buffer, and labeling with antibodies (Nup133 and Nup98), U2OS cells were imaged by a self-built SMLM imaging system. A total of 50000 frames were captured after appropriate fields of view were selected. Through localization and drift correction processes, corresponding SMLM images were obtained. After the regions of interest were selected, the coordinate data with high localization accuracy were preserved for further analysis. First, a first round of density-based spatial clustering of applications with noise clustering (DBSCAN) analysis was used to remove background noise, identify individual NPCs, and determine the centroids of the NPCs (Fig. 3). To achieve a more accurate delineation of each Nup within every NPC in the case of retaining all signal points, a combination of the DBSCAN algorithm and hierarchical clustering was employed in the second round of delineation. In the second round of DBSCAN analysis, the algorithm was applied to identify the number of individual Nups within each NPC, and the data were further input into a hierarchical clustering algorithm for refinement of Nup localization. Subsequently, NPCs containing four to eight Nups were retained, and a second screening based on shape factors was performed to preserve NPCs with more uniform morphologies. Finally, the centroids of all remaining NPCs were aligned to obtain the complete distribution of labeled Nups in the NPCs. Using the least-squares method with NPC centroids as the center, a reconstruction of the Nup distribution with octagonal symmetry was achieved (Fig. 4). The reconstructed structure can be used to analyze the spatial characteristics of the Nup.

Nup133, as a characteristic "Y"-scaffold-shaped component protein, has received extensive attention in recent research. Through statistical analysis of multiple datasets, the first round of the DBSCAN algorithm identified 10329 NPCs (Fig. 5). Among them, 3076 NPCs containing four to eight Nup133 were present, accounting for approximately 30% of the total. By selecting based on shape factors, a final set of 558 NPCs with relatively regular shape was obtained, accounting for approximately 5% of the total (Table 1). The retained NPCs were aligned by their centroids, resulting in an overlapped NPC image. Gaussian fitting was applied to calculate the radii of all Nup133, with the peak corresponding to a horizontal coordinate of (58.4±0.1) nm. This value is very close to the Nup133 radius of (59.4±0.2) nm calculated using the particle averaging method with antibody labeling. This further demonstrates the high-precision performance of the screening and reconstruction methods used in this study. In addition, the same analysis process was applied to analyze NPCs labeled with Nup98. Compared with that of Nup133, the distribution of Nup98 located in the inner ring of the NPC is more condensed (Fig. 6). A total of 10668 NPCs were analyzed, and 1126 NPCs were ultimately retained, accounting for approximately 10% of the total (Table 1). Similarly, the remaining NPCs labeled with Nup98 were aligned by the centroids, and Gaussian fitting was applied to the overlapped Nup98, resulting in a peak corresponding to a horizontal coordinate of (39.7±0.2) nm (Fig. 6). Compared with that of Nup133, the radius of Nup98 is smaller by 18.7 nm, indicating that Nup98 is closer to the center position of the NPC than Nup133. Finally, the eightfold symmetric structure of Nup133 and Nup98 was successfully reconstructed using the rotation alignment method, which is consistent with the acknowledged model.

The present study proposes a processing workflow based on clustering methods for screening and reconstruction of SMLM images of the NPC. The workflow has three main parts: classification, screening, and reconstruction. By performing two rounds of clustering to identify the NPC and Nup components, NPCs with a uniform shape containing four to eight Nups are selected and subjected to reconstruction analysis. The NPC with an eightfold symmetric structure is successfully reconstructed using the proposed workflow. Experimental results on Nup133 and Nup98 show that the radius of Nup133 is (58.4±0.1) nm, which closely aligns with the radius determined by the particle averaging method. The radius of Nup98 is (39.7±0.2) nm, indicating that Nup98 is situated in closer proximity to the central region of the nuclear pore. The proposed method reproduces the eightfold symmetric structure of the NPC, providing accurate localization information and aiding in a deeper understanding of the composition of this important structure. This clustering-based reconstruction method can also be extended to other nuclear pore-like structures, such as centrioles and basal bodies, or other structures with isotropic symmetric features, offering important strategies and methods for deciphering complex biological structures.

The accurate classification of white blood cells (WBCs) is crucial in the examination of blood and the diagnosis and treatment of clinical conditions. Manual examination under a bright-field microscope, the gold standard for blood cell analysis, is time-consuming and inspector-dependent. Currently, blood cell analyzers based on the impedance method or flow cytometry are extensively employed. However, some false positives may occur because of the structural variability of WBCs, which requires a manual microscopic review. In addition, these instruments are expensive. Deep learning, which can reduce the technical requirements of inspectors, is widely used for WBC classification. However, this analysis continues to rely on the morphology and color characteristics of the stained cells. To achieve high accuracy in the classification of WBCs, the process usually requires image acquisition and processing under a 100× objective lens, which can be time-consuming and data-intensive. Quantitative-phase imaging (QPI) is an effective method for studying cell morphology and biochemistry. However, identifying WBCs solely based on their phase characteristics is challenging, particularly when these phase characteristics are not prominent. Research on stained cells using QPI has shown that the inclusion of phase information, alongside bright-field pictures, might provide useful insights for WBC classification. In this study, the phase distributions of five different types of WBCs were quantitatively analyzed, and the substructure phase information was effectively divided using a co-localization imaging system based on digital holographic microscopy (DHM) and bright-field microscopy. A series of feature parameters were extracted to assist with the WBC classification. The accuracies of the classification of the three types of granulocytes based on the extracted phase feature parameters were 94%. Additionally, atypical lymphocytes were studied, and a recognition accuracy of 84.5% was achieved. The proposed method utilizes routine blood smear samples stained for clinical microscopy, making it easy to integrate into a commercial microscopic system and providing a wide range of practical applications.

A benchtop co-localization imaging system was used to obtain bright-field images and quantitative phase images of WBCs from peripheral blood smears of healthy individuals. Quantitative phase images of the WBCs were reconstructed from off-axis holograms obtained from DHM. To segment the phase information, WBCs were first extracted and divided into two parts, the nucleus and the cytoplasm, based on bright-field images. Then, the position information of the nucleus and cytoplasm of the WBCs in the bright-field images was transposed onto the corresponding phase images. Finally, the quantitative phase distributions of WBCs and their corresponding nuclei and cytoplasm were successfully acquired. A substantial number of WBC samples consisting of 100 neutrophils, eosinophils, basophils, monocytes, large lymphocytes, and small lymphocytes were selected for co-localization imaging and statistical analysis. Various feature parameters were extracted to quantitatively describe and analyze the morphological and substructural features of the different WBCs.

The feature parameters of the five types of WBCs were subjected to analysis and comparison, revealing distinct phase characteristics for each type. Neutrophils had a substantially higher nuclear phase value than the cytoplasmic phase value [Fig. 4(a)], whereas eosinophils had comparable nuclear and cytoplasmic phase values (Fig. 4). The cytoplasmic phase values in basophils fluctuated substantially [Fig. 5(c)], and monocytes showed a smaller phase difference between the nucleus and cytoplasm than lymphocytes [Fig. 4(b)]. Using the extracted feature parameters, three types of granulocytes were successfully classified with 94% accuracy. The efficiency of classifying phase features was evaluated by analyzing a total of 1200 neutrophils and eosinophils. This analysis was conducted using a phase feature method based on a 40× co-localization microscope, deep learning classification based on a 40× brightfield microscope, and a commercial system called Morphogo with a 100× microscope. The results showed that the phase feature accurately identified easily confused cells in deep learning classification or the Morphogo system (Fig. 7). Furthermore, an examination of atypical cells was conducted, revealing that the use of phase characteristics resulted in a classification accuracy of 84.5%. These results demonstrate that the phase feature parameters are effective in aiding WBC classification.

This study proposes a method for classifying WBCs using QPI. The approach involved analyzing different types of WBCs using a co-localization imaging system that combines DHM and bright-field microscopy. The position and structural information of WBCs were obtained from bright-field images, and the phase information of WBCs and their nuclei and cytoplasm were extracted accordingly. Statistical analysis was then used to extract feature parameters that effectively aided in the classification of WBCs. This method achieved an accuracy rate of 94% for classifying the three types of granulocytes based on the substructure phase characteristic parameters. Further analysis showed an accuracy rate of 84.5% for identifying atypical lymphocytes, which are often misinterpreted during microscopic examinations. Compared with using only phase information to classify WBCs, the proposed method incorporates high contrast between the nucleus and cytoplasm in bright-field images to effectively compare the characteristics of different WBC substructures, leading to an improved classification scope and accuracy. In addition, compared to conventional microscopic classification, the proposed method provides additional phase information that can assist in WBC classification. This method is easy to integrate with microscope and does not require the special treatment of conventionally stained blood smear samples. It is expected to be widely used for the leukocyte classification and diagnosis and treatment of various blood diseases.

Cervical cancer is one of the most common malignant tumors and poses a serious threat to human health. However, because the onset of cervical cancer is gradual, early and effective screening is crucial. Traditional screening methods rely on manual examinations by pathologists, a process that is time-consuming, labor-intensive, error-prone, and often lacks an adequate number of pathologists for cervical cytology screening, making it challenging to meet the current demands for cervical cancer screening. In recent years, several deep-learning-based methods have been developed for screening abnormal cervical cells. However, because abnormal cervical cells develop from normal cells, they exhibit morphological similarities, making differentiation challenging. Pathologists typically need to reference normal cells in images to accurately distinguish them from abnormal cells. These factors limit the accuracy of abnormal cervical cell screening. This study proposes a Transformer-based approach for abnormal cervical cell screening that leverages the powerful global feature extraction and long-range dependency capabilities of Transformer. This method effectively enhances the detection accuracy of abnormal cervical cells, improving screening efficiency and alleviating the burden on medical professionals.

This study introduces a novel Transformer-based method for abnormal cervical cell detection that leverages the powerful global information extraction capabilities of Transformer to mimic the screening process of pathologists. The proposed method incorporates two innovative structures. The first is an improved Transformer encoder, which consists of multiple blocks stacked together. Each block comprises two parts: a multi-head self-attention layer and a feedforward neural network layer. The multi-head self-attention layer captures the correlation of the input data at different levels and scales, enabling the model to better understand the structure of the input sequence. The feedforward neural network layer includes multiple fully connected layers and activation functions and introduces nonlinear transformations to help the model adapt to complex data distributions. We also introduce Depthwise (DW)convolution and Dropout layers to the encoder. DW convolution layer performs convolution operations with separate kernels for each input channel, capturing features within the channels without introducing inter-channel dependencies. Dropout layer reduces the tendency of neural networks to overfit the training data, thereby enhancing the generalization of the model to unseen data. Additionally, we design a dynamic intersection-over-union (IOU) threshold method that adaptively adjusts the IOU threshold. In the initial stages of training, the model can obtain as many effective detections as possible, whereas in later stages, it can filter out most false positive predictions, thereby improving the detection accuracy of the model. Using the proposed method, the model can obtain precise information regarding the location of abnormal cells.

To validate the effectiveness of our proposed method, we compare it with common general-purpose object detection methods. The average accuracy (AP) and AP₅₀ of our method are 26.1% and 46.8%, respectively, surpassing those of all general object detection models (Table 1). In particular, our method outperforms other comparative models by a significant margin in AP metrics, demonstrating that our model not only detects normal-sized targets but can also detect extremely small targets. Additionally, in a comparison with attFPN, a network specifically designed for abnormal cervical cell detection, our method surpasses attFPN in terms of AP by 1.1% (Table 2). Visual inspection of the detection results reveals that our method more accurately identifies target regions with lower false-positive and false-negative rates (Fig.5). Ablation experiments indicate that adopting the improved Transformer encoder method increases AP and AP₅₀ by 1.8% and 2.3%, respectively, compared with the original model. The use of dynamic IOU thresholds results in a 0.6% increase in AP and a 0.9% increase in AP₅₀ compared with the original model (Table 4). Furthermore, a comparison between the dynamic and fixed IOU thresholds in terms of loss and AP during the training process shows that the model with dynamic IOU thresholds experiences a faster loss reduction and achieves a higher AP in the later stages of training (Fig.6).

This study introduces an automatic identification method for abnormal cervical cells utilizing Transformer as the backbone. We further propose an enhanced Transformer encoder structure and a dynamically adjustable IOU threshold. Various comparative experiments on datasets demonstrate that the proposed method outperforms existing approaches in terms of accuracy and other metrics, thereby achieving precise identification of abnormal cervical cells. Through ablation experiments, it is proven that both proposed modules enhance the accuracy of the model in identifying abnormal cervical cells. Overall, the proposed method significantly improves the efficiency of medical image screening, saving medical time and resources, facilitating timely detection of cancerous lesions, and presenting considerable clinical and practical value. Future research may focus on the application of semi-supervised and unsupervised learning in the field of medical imaging to enhance image utilization, improve model detection performance, and better meet clinical requirements.

Quality testing of tomatoes is critical in many aspects of their growth, storage, and transportation. Sugar content (Brix) is a necessary criterion for evaluating whether a fruit is tasty. The timely and accurate mastery of quality parameters, such as the Brix distribution during the ripening process, is crucial for the scientific and efficient cultivation of tomatoes. Among the widely used detection methods, the Brix meter detection, which is based on the principle of light refraction, is a mean value measurement method based on the fruit juice, which cannot satisfactorily assess the fine distribution of different parts of a sample. The hyperspectral imaging technology leads to a significant amount of redundancy in the amount of data and is easily affected by the depth of light penetration and the water content of the sample, which is insufficient to detect and characterize the full range of details of the sample. Mass spectrometry is complex and cumbersome for sample preparation and does not support rapid detection. This study proposes a method for detecting and characterizing the sugar content of tomato fruits from the perspective of cellular phase information based on phase imaging technology.

The physiological properties of the samples were analyzed and characterized in this study from a cellular perspective, starting from the microscopic material basis of plant growth. Based on the characteristics of the quantitative phase microscopy, which uses the inherent contrast source of different refractive indices between different components in the cell, we performed phase imaging experiments on tomato pulp cells and extracted the cellular phase parameters, called "phase envelope volume" and "phase peak." The correlation between the phase parameters and Brix was analyzed by comparing them with the measurement results of the Brix meter. Based on the experimental data, a data cube of the two-phase parameters and Brix was constituted, and positive correlations between the phase parameters and Brix were obtained. This provides a basis for characterizing local Brix using phase parameters.

The proposed detection and characterization method can be applied to any part of a tomato plant and requires only a single frame of the phase map at any incidence angle. The extraction of phase parameters eliminates the tedious operation of decoupling the physical thickness and refractive index of the cells, and the entire analysis process only takes approximately 0.5 s. Based on the sensitivity of the phase information to the internal chemical composition of the cell, the phase parameter characterization method can also be applied to detect the physiological state of other fruits and vegetables in addition to sugar (Fig. 10). This study provides a reference for the refinement and precision in detecting the quality of agricultural products.

This paper focuses on the demand for rapid and accurate quality inspection of fruits and vegetables in modern agriculture. A detection method based on phase imaging is proposed. The inspection of tomato fruit sugar is used as an example to explain the related principles and procedures. In this method, only a single frame of the phase map from any angle of incidence is required. Two phase parameters, that is, "phase envelope volume" and "phase peak," are extracted from the phase map to quantitatively investigate the sugar content characteristic of a cell. The experimental results of the comparison with the detection based on the Brix meter indicate that the sugar content and the above phase parameters show a significant positive correlation. This provides a basis for characterizing the sugar content using the phase parameters. The local sugar content distribution of a tomato fruit was detected experimentally, and the results show good consistency with those of hyperspectral detection. The feasibility and effectiveness of this method have been demonstrated to a certain extent. This phase detection and characterization method requires only one frame of the phase image, and the related analysis process eliminates the cumbersome operation of decoupling the physical thickness and refractive index of the cell. This means that the hardware and time costs can be reduced. Based on the sensitivity of the phase information to the internal chemical composition of the cell, the phase parameter characterization method can also be applied to detect the physiological state of other fruits and vegetables, which may be used as a workable solution for the rapid and accurate detection of agricultural product quality.

Burns are a common type of skin injury. Diagnosing the degree of the burn is very important for proper treatment. Optical coherence tomography is a non-invasive, non-destructive, and high-resolution optical detection technology. Polarization-sensitive optical coherence tomography (PS-OCT) provides a comparison of birefringence information compared to the conventional structural OCT modality. It can be used for the high-resolution, high-contrast, real-time three-dimensional imaging of damaged skin. In this work, a simple, compact, flexible, and efficient PS-OCT system is developed based on single-mode fiber optics with a circularly polarized single-input state as the swept source. The high-performance swept source enables a high imaging speed and long coherence length for the OCT imaging. The PS-OCT system is based on single-mode fiber optics and features low polarization crosstalk, low polarization mode dispersion, and a compact size. A multiple-parameter analysis shows that the PS-OCT system has the potential to provide accurate clinical assessments of skin burns.

We construct a swept-source PS-OCT system with single-mode fiber optics. By tuning the polarization controllers step by step, a single circular polarization input in the sample arm and OCT signal detection with orthogonal polarization channels are achieved. Using straightforward data processing algorithms, the PS-OCT system has the capability to acquire various parameters, including the structural intensity, degree of polarization uniformity (DOPU), cumulative phase retardation (CPR), and Stokes state. Given the anatomical and physiological resemblance between pig skin and human skin, ex vivo pig skin is selected as the imaging subject for the skin burn model in this study. To simulate the burns, eight groups of pig skin samples are subjected to a circular thermal injury with a diameter of 10 mm using a temperature-controlled wound burning device at 90 °C for a duration of 30 s. We compare the multi-parameter PS-OCT images of the normal and burned pig skin samples. According to the image histogram, the Bhattacharyya distance is calculated to demonstrate the capability of the PS-OCT system for skin burn evaluation.

In the structural OCT images, the difference between the normal and burned pig skin samples is not obvious (Fig.3). As shown in the cross-sectional structural OCT images, the total scattering intensity has similar values in the regions of the normal and burned skin samples. In the en-face structural images, the boundary of the burned skin region is clear, and the pattern of the skin texture is different. Compared to the structural images, the polarized images show obvious differences between the normal and burned pig skin samples in terms of the Stokes state, DOPU, and cumulative phase retardation (Fig.4). In the region of the burned skin, the color of the Stokes state image becomes relatively uniform, the value of the DOPU image is relatively large, and the CPR value is relatively low. The en-face images demonstrate that the structural intensity values of the normal and burned pig-skin regions are very similar, whereas the DOPU, CPR, and Stokes values have relatively large differences. The histograms of these en-face images further verify that polarized images are more useful in distinguishing normal and burned skin (Fig.5 and Fig.6). Using to the histograms, we calculate the Bhattacharyya distance to quantify the difference in the images between normal and burned pig skin (Fig.7). If the images are very similar, the Bhattacharyya distance is close to 0. If the images are very different, the Bhattacharyya distance is close to 1. For the 8 groups of skin burn experiments, the average Bhattacharyya distance of the structural images is 0.184, while the values for the DOPU images, CPR images, and Stokes images are 0.917, 0.744, and 0.839, respectively. A quantification analysis demonstrates that the difference between normal and burned skin in the traditional OCT structural images is small, while the polarized images show a significant difference in the burned skin. The PS-OCT system used in this study adopts a design based on single-mode fiber optics. However, the birefringence characteristics of single-mode fiber optics are easily affected by environmental factors such as bending stress and temperature changes. Therefore, once we have completed the steps to calibrate the polarization state of the PS-OCT system, the optical fibers in the system must not be touched. In an actual work environment, the polarization state of the imaging system can be maintained for several days without significant changes, thus meeting the needs of most clinical and life science applications. In the future, we will further optimize the optical design of the PS-OCT system to improve its polarization stability. In addition, the PS-OCT imaging system shows that a polarized image of pig skin tissue exhibits an obvious change after being burned. The mechanism of the change in the polarization state mainly comes from the irreversible denaturation of the collagen and elastic fibers in the skin tissue after heating. However, in this study, only a small amount of ex vivo pig skin is used as the model for a skin burn. The number and type of experimental samples are insufficient. In addition, the ex vivo skin samples have lost their biological tissue activity characteristics. In the future, we will increase the number and type of skin burn models. Furthermore, we also need to investigate living animal samples and skin burn patients to promote the application of PS-OCT imaging in the diagnosis and treatment of skin burns.

A flexible and efficient PS-OCT system based on single-mode fiber optics and a single-state input is built to image ex vivo pig skin for skin-burn investigations. The system can provide structural images and three polarized images (DOPU, CPR, and Stokes state) of skin tissue. We compare images of normal and burned skin, and perform histogram statistical analysis to illustrate the distribution of these parameters. Moreover, we calculate the Bhattacharyya distance as a histogram similarity coefficient to further quantify the imaging performance. The results show that there are significant birefringence changes in the burned skin tissue compared to the normal skin tissue, which are mainly due to the denaturation of the collagen and elastic fibers after heating. The changes in burned skin can be clearly observed using the polarization parameters (DOPU, CPR, and Stokes state). These polarized OCT images exhibit enhanced contrast and more pronounced distinctions for burned skin compared to conventional structural OCT images. This research demonstrates the promising potential of PS-OCT technology for skin-burn diagnosis.

China currently has the highest myopia rate among youth in the world, with myopia in children and adolescents becoming the leading cause of visual impairment in the country. Myopia is a progressive condition, but early detection and treatment during the pre-myopia stage can help restore vision. Currently, most children and adolescents rely on traditional computerized optometry in hospitals and ophthalmology institutions for vision screening. However, the monitoring density is insufficient to keep up with the rapid progression of myopia, and if parents notice abnormal vision in their children, they may have missed the optimal intervention period. The objective of this study is to address the issues of bulky and expensive existing computerized optometry and vision-screening instruments. We aim to provide an experimental reference for the miniaturization and instrumentation of refractive measurement systems, enabling their application in scenarios that require portability and miniaturization.

In this paper, we first provide a detailed introduction to the measurement principles of Shack-Hartmann wavefront sensing technology, followed by the derivation of the wavefront reconstruction algorithm principles. Human eyes with different diopters were modeled using Zemax software, and a Shack-Hartmann wavefront sensor was used to simulate the diffuse reflection phenomenon of a laser spot used as a point light source at the fovea centralis of the human eye, which is located at the center of the retina. The human eye and Shack-Hartmann wavefront sensor were placed at different distances, capturing the outgoing wavefront of the human eye at the corresponding location and imaging it on the detector. This simulated the image acquisition optical path in the refractive measurement system. The collected refractive power images were fed into the algorithm to calculate and then analyze the relationship between the actual measured refractive power and true refractive power at different distances between the human eye and Shack-Hartmann wavefront sensor. Finally, we designed the optical-mechanical structure of an experimental prototype and constructed the system. Model eyes with different diopters were placed at different distances (55, 60, and 65 mm) from the Shack-Hartmann wavefront sensor and measurements were repeated ten times. The actual measurement values were compared with the true values of the model eye to validate the accuracy of the measurements, and the coefficient of variation was used to assess the repeatability of the measurement results.

Measurements on model eyes with different diopters show that the stability of the measurement results is better for myopic eyes than for hyperopic eyes. Additionally, the maximum deviation between the measurement results of myopic eyes and the true values of the model eye is generally smaller than that of hyperopic eyes. This is because the wavefront of hyperopic eyes expands outward after exiting the eyeball, leading to fragmentation of the spot formed on the CMOS sensor by the received wavefront in the Shack-Hartmann wavefront sensor, thereby affecting the centroid-localization accuracy in the diopter calculation algorithm. A certain amount of astigmatism is observed in the measurement results for the diopter of cylinder on model eyes without astigmatism. This is due to the inability to strictly align the main optical axes of the human eye, Shack-Hartmann wavefront sensor, and central area of the CMOS during the device adjustment process, which subsequently affects the calculation of astigmatism values. However, overall, the coefficient of variation for repeated measurements of the diopter of sphere in the diopter measurement results remains below 3%, with a maximum error of 0.2 D. The coefficient of variation for repeated measurements of the diopter of cylinder is below 9%, with a maximum error not exceeding 0.25 D. The measurement accuracy meets the requirements of the “Verification Procedures for Ophthalmic Instruments” (JJG892—2022) of the People’s Republic of China, which stipulates a maximum allowable error for the diopter of sphere within a range of -10 to +10 D with error of ±0.25D, and a maximum allowable error for the diopter of cylinder within a range of 0 to 6 D with error of ±0.25 D.

In this study, we design a compact diopter measurement system based on Shack-Hartmann wavefront sensing technology. The system is calibrated using a model eye provided by the National Institute of Metrology of China to observe the diopter measurement results. An analysis of the results shows that the system’s measurement results are highly consistent with the true values of the model eye, with no significant differences and good repeatability. The system is capable of effectively measuring the diopter within a range of -10‒+10 D, even at non-fixed distances along the z-axis. Furthermore, the system has a simple structure and low cost. It is expected that the size of the device can be further reduced with the future customization of key components, making it more suitable for scenarios requiring miniaturized instruments. Therefore, this system has broad prospects for applications.

Photoacoustic imaging is a non-invasive, functional optical imaging technique that uses the photoacoustic effect with ultrasound as a mediator. Despite its potential for various medical applications, traditional contact-based signal detection methods have hindered its progress in clinical practice. To overcome these limitations, non-contact detection of photoacoustic signals has emerged as a solution. This approach uses air-coupled or all-optical detection methods and achieves a wide bandwidth and high sensitivity for ultrasound signal reception, aligning with the demands of modern medical technology. Current contact-based photoacoustic imaging still faces challenges, such as signal attenuation, surface scattering, system sensitivity, and environmental interference. Therefore, in this study, a noncontact, noninvasive, and cost-effective photoacoustic signal detection device, based on the optical heterodyne technology, is proposed. We aim to address the challenges in photoacoustic signal detection, reduce system costs and complexity, and promote the practical application of non-contact photoacoustic imaging in clinical settings.

The photoacoustic signals are detected using heterodyne interferometry. First, based on the characteristic parameters of tissue surface vibration signals and the propagation properties of ultrasound waves in a medium, the relationship between the vibration displacement and pressure causing the vibrations is established. Subsequently, by employing the dual-frequency optical heterodyne interferometric theory, the relationship between the photoacoustic signal-induced tissue surface vibration displacement and phase changes is established. Furthermore, I/Q quadrature demodulation is applied to process the photoacoustic signals; this ensures system stability and high demodulation accuracy in complex environments. To achieve all-optical detection of photoacoustic signals, an photoacoustic signal detection system is designed using a He-Ne laser as the detection light source. The optical components are configured to construct an optical-path system for precise detection of photoacoustic signals. In the experiments, an electro-optic Q-switched dual-wavelength Nd∶YAG laser is selected as the excitation light source. This laser allows for flexible control of the excitation light conditions by adjusting the beam diameter and intensity. Finally, the acoustic vibration characteristics induced in the sample under stimulation are evaluated by observing the phase changes and vibration displacement of the photoacoustic signals.

In this study, we investigate the detection of ultrasound vibrations generated by an ultrasound transducer (UST) using a photoacoustic signal full-optical detection system and an immersion probe. A comparative analysis of the measurement results reveals that the heterodyne interference system effectively reconstructs the ultrasound vibrations. The demodulated ultrasound displacement pulse envelope is closely aligned with the measurement result obtained using the immersion probe (Figs.3 and 4). Under constant input parameters, varying the amplitude of the power supply voltage results in a linear increase in the ultrasound signal intensity, which is measured by both the heterodyne system and immersion probe (Fig.5). Furthermore, different driving frequencies are set with constant input signal parameters. The ultrasound vibration frequencies measured by our system and the immersion probe are comparatively analyzed. According to the analysis results, the I/Q quadrature demodulation method accurately extracts ultrasound vibration frequencies with minimal relative measurement error, exhibiting an absolute difference of 0.2 kHz (Table 1). In the absence of excitation pulses, the demodulated baseline interference signal displays subtle displacement deviations with displacement offset control at the nanometer level (Fig.8). The detection of ultrasound vibrations on the surface of a carbon rod demonstrates a close agreement between the ultrasound vibration frequencies demodulated by our system and those measured by the immersion probe (Figs.6 and 7). However, in the case of ultrasound detection on the surface of the porcine liver, the rigidity of measurement mirror M2 leads to higher-frequency vibrations demodulated by our system compared to those measured by the immersion probe (Figs.9 and 10).

In this study, optical heterodyne interferometry and digital Doppler signal demodulation methods are used to experimentally investigate non-contact photoacoustic signal detection. The acoustic vibration characteristics of the target are extracted through the demodulation of the dual-frequency optical heterodyne interference signals. Subsequently, an ultrasonic transducer is employed to simulate the high-frequency vibration signals, and a performance test is conducted. The experimental results demonstrate that the heterodyne system effectively reconstructs photoacoustic vibration signals with minimal relative frequency deviation compared to the immersion probe. In addition, experiments involving a carbon rod and excised biological tissue reveal that the heterodyne system based on the I/Q orthogonal method exhibits superior performance in demodulating photoacoustic signals owing to its insensitivity to changes in the interference signal amplitude. Moreover, the designed photoacoustic signal detection system incorporates linearly polarized light and heterodyne interferometry and the detection sensitivity and precision are enhanced. The heterodyne optical path structure, which is easily adjustable and effective in suppressing interference noise, contributes to the robust performance of the system. By utilizing high-speed data acquisition cards and digital signal processing techniques for interference signal processing, the demodulation algorithm proves to be simple and flexible in design, offering potential cost savings in hardware implementation. The research findings suggest that the proposed system holds a certain reference value for clinical applications in noncontact photoacoustic signal detection.

Research on quantum dots has attracted significant attention since the Nobel Prize in Chemistry was awarded to scientists in this field. As a special type of quantum dots, fluorescent carbon quantum dots (CDs) have excellent fluorescence and controllable surface chemical properties, which can be applied in biological medicine fields such as bioimaging and diagnosis and treatment of diseases. CDs are fluorescent nanomaterials with a size of less than 10 nm. Their preparation methods are diverse and simple, precursors are widely available, optical properties are stable, and photobleaching resistance is strong. Compared with inorganic quantum dots, they do not contain heavy metals, so they have lower biotoxicity and higher biocompatibility, and have great application potential in the biomedical field. The surface of CDs is rich in functional groups, which determine their physical, chemical, and fluorescent properties, including quantum yield, emission wavelength, aggregation-induced emission/quenching, fluorescence lifetime, biocompatibility, and special material response. One of their most important properties is luminescence, which comprises a variety of mechanisms, including surface-controlled luminescence, cross-linked enhanced emission effect, quantum size effect, and carbon core-controlled luminescence. These mechanisms interact with each other to influence the CD fluorescence effect. Reasonable regulation of the CD luminescence properties, such as fluorescence wavelength and intensity, is of great significance in disease diagnosis. At the same time, through regulation of the surface functional groups of CDs, the scavenging ability of ROS free radicals can be adjusted. Therefore, CDs have great application potential in the diagnosis and treatment of tumors and inflammation.

Based on recent literature reports, this study introduces and summarizes in detail the application of CDs in the field of biomedicine and their related mechanisms and characteristics. First, in terms of biological imaging, CD nanostructures enter cells through endocytosis and exocytosis and disperse in the cytoplasm or specifically in some organelles. As a result, we can clearly observe the physiological activities of body structures such as micro vessels and brain tissue with the help of confocal microscopy or other instruments [Figs. 2(a) and (b)]. The design and preparation of CDs with near-infrared fluorescence wavelength and high quantum yield result in higher resolution and tissue penetration ability, which is advantageous for in vivo imaging [Figs. 2(c) and (d)]. On this basis, we introduce the application of CDs in disease diagnosis. Compared with other diagnosis methods, the application of CDs is less traumatic, which opens up broad prospects in disease diagnosis. CDs with pH-sensitive luminescence characteristics can be used as potential imaging reagents for pH monitoring [Fig. 3(a)]. Fluorescence enhancement strategies based on nitrogen-doped CDs induced by nicotinamide adenine dinucleotide can be used to monitor tumor occurrence and provide early warning of tumor formation [Fig. 3(b)]. CDs can also produce selective responses to some biomarkers, resulting in changes in fluorescence signals, which can play a role in monitoring the occurrence and development of diseases through the detection of cytochrome C in human serum samples [Fig. 3(c)] and creatine kinase (CK), an important biochemical indicator of heart injury [Fig. 3(d)]. Finally, CDs with rich surface states can interact with the body in a variety of chemical reactions. CDs designed and prepared with specific structures can be effective in disease treatment, mainly in the following three areas: 1) tumor treatment, 2) antibacterial and antiviral treatment, and 3) anti-inflammatory treatment. A novel CD for the treatment of glioblastoma was synthesized using metformin and gallic acid precursors [Fig. 4(a)], whereas Fe single-atom nano cases with high pyrrole nitrogen content and ultra-small CD support were prepared using a phenazoline mediated ligand-assist strategy [Fig. 4(b)]. CDs effectively inhibit the growth of tumor cells through synergistic chemical kinetics and photothermal effects. The synthesized quaternary ammonium CDs have positive charge properties and can retain antibiotic precursor active groups [Figs. 4(c) and (d)], leading to effective antimicrobial activity. The surface of CDs has many oxidized chemically active groups, such as phenolic hydroxyl, which react easily with oxidizing substances, thus playing antioxidant and anti-inflammatory roles. Anti-inflammatory and antioxidant CDs are prepared through precursor optimization, solvent extraction, and use of broccoli as a biological feedstock [Fig. 4(e)]. CDs can also be designed as nano-enzymes to perform anti-inflammatory and antioxidant functions [Fig. 4(f)]. At the end of the paper, we outline the challenges faced by CDs in biomedical applications. First, for efficient application of CDs in biomedical fields, various preparation conditions need to be considered comprehensively to achieve accurate control of their key properties. Second, the conversion of CDs into actual products still faces challenges, and further solutions are needed to promote their production and commercialization. Finally, the regulation and standardization of CDs are becoming increasingly important. To solve the above problems, the development and application of CD preparation technology should be promoted.

CDs are being widely used in the field of biomedicine, including bioimaging and diagnosis and treatment of diseases (Table 1). Their excellent optical, physical, and chemical properties provide them with obvious advantages in the field of biomedicine, including safety, light stability, easy access, and performance tunability. In the future, the large-scale and diversified development of CDs can be further enhanced to promote their industrial production, commercialization, and application in real life.

In recent years, laser and infrared detection technology has been rapidly developed. The material preparation, generation method, extinction performance test, and effect evaluation of multi-band smoke screens have garnered widespread attention. Traditional inorganic extinction materials, such as metal powder, red phosphorus, and expanded graphite, often possess drawbacks such as a narrow extinction band, high costs, combustibility, difficulty in degradation, a single release method, and environmental harm. Consequently, environmentally friendly extinction materials characterized by a broad extinction band, long duration, low preparation cost, pollution-free, and non-combustibility emerge as research hotspots both domestically and internationally.

Artificially controlled biomaterials, such as spores or hyphae, represent a new type of smoke screens medium, distinct from traditional inorganic extinction materials. Once released into the air, these biomaterials form smoke screens, altering light transmission properties through absorption and scattering. Hence, biomaterials can diminish the detection capabilities of visible, laser, and infrared detection systems and equipment, making them suitable for the photoelectric protection of critical targets or facilities. Biomaterials aggregated particles systems formed from tiny biological particles due to static electricity, collision, or adhesion, possess complex spatial structures and random orientations.

There is a significant progress in researching the extinction properties of biomaterials. Biomaterials can be prepared with attributes such as controllable morphology, cost-efficiency, ease of batch preparation, high impedance, environmental friendliness, and non-toxicity. Researchers have constructed structure models of spherical particles, typical non-spherical particles, monodisperse aggregated particles, and polydisperse aggregated particles and have analyzed their static extinction properties. Additionally, the dynamic extinction properties of biomaterials have been examined under varying wind speeds, surface roughnesses, and relative humidities. Regarding the differential extinction properties of viable and dead biomaterials, the activity ratio of biomaterials can be qualitatively determined. Although many advances have occurred, challenges persist in the simulation, testing, and enhancement of biomaterials' extinction characteristics. Thus, outlining current research on the extinction characteristics of biomaterials becomes essential, paving the way for future developments in safer and more eco-friendly broadband smoke screen materials.

First, the extinction characteristics of biomaterials are introduced, with absorption and scattering attributes based on the characteristics of complex refractive index. The calculation flowchart for the extinction characteristics of biomaterials is presented (Fig. 5), and characterization methods for different biomaterial structures are summarized. These structures include spherical single particles, typical non-spherical single particles, monodisperse aggregated particles, and polydisperse aggregated particles. Although the extinction properties are primarily determined by the composition and structural parameters of biomaterials (as shown in Fig. 6 and Fig. 9), other influential factors are examined. These factors are represented by biomaterial activity (Fig. 10), wind speed (Fig. 12), ground roughness (Fig. 13), and relative humidity (Fig. 14). Subsequently, static and dynamic testing methods for biomaterials are listed. In the static methods, the scanning electron microscope (SEM) test (Fig. 15) and infrared spectroscopy test (Fig. 16) are featured, while in the dynamic methods, the smoke box test (Fig. 17) and field test (Fig. 19) are included. In conclusion, emerging trends such as precise simulations of intricate spatial structures, analyses of factors influencing extinction characteristics, and standardization of extinction characteristics testing are emphasized.

In recent years, significant advancements have been observed in the study of extinction characteristics and test techniques of biomaterials. However, certain challenges persist that require attention in the forthcoming research, including the simulation of randomly oriented aggregation for biological particles, the multivariate analysis of dynamic extinction properties of biomaterials, and the standardization of extinction performance testing. Initially, given that biological particles generally possess irregular shapes and biological particle aggregations exhibit complex and variable structures, only a model accounting for the randomly oriented aggregation of these irregular particles can accurately represent the spatial structure of aggregated biological particles, ensuring precise calculations of the biomaterials' extinction properties. At this juncture, due to the absence of an established model for randomly oriented aggregation of irregular particles, simulations are restricted to particles with regular shapes. Furthermore, a comprehensive consideration of factors, such as wind speed, temperature, and atmospheric stability, becomes imperative, surpassing the simplicity of previous analyses affecting the extinction properties of biomaterials. Additionally, addressing issues of a low effectiveness-cost ratio and limited repeatability by standardizing the collection and analysis of experimental data emerges as a crucial research direction. Anticipated improvements for the near future include the development of a randomly oriented aggregation model for diverse irregular biological particles, enabling the study of extinction characteristics for non-spherical biological materials. There is also the need for accurate simulations and predictions of sedimentation diffusion of aggregated particles under varied meteorological conditions. This would involve the consideration of multiple influencing factors, the enhancement of specific organic groups performance and the integration of other material components to bolster biomaterial performance. Lastly, the establishment of clear evaluation tests and criteria for the extinction performance of biomaterials is crucial, ensuring experimental data are gathered and analyzed following a relatively consistent standard.

Since Arthur Ashkin first demonstrated the ability to optically levitate and trap particles, optical tweezers and optical trapping have been applied in the physical, chemical, biological, material, and atmospheric sciences. Optically trapped microparticles in air are more likely to be affected by external disturbances, such as vibration or airflow, than those in liquid, which makes them difficult to trap in air. Recently, technology for optical trapping in air was developed. The gradient force generated by a high-focus laser and the photophoretic force resulting from thermal processes play dominant roles in the optical trapping of particles in air. When the particles are trapped, their physical and chemical properties can be studied using spectroscopic techniques. In this paper, the principles and experimental devices of the optical trapping of airborne particles are introduced, and the applications, progress, and challenges of optical trapping and laser spectroscopy are reviewed.

When a photon interacts with a particle, the partial momentum of the photon is transferred to the particle, which forms the scattering and gradient forces, where the gradient force is used to trap the particle. For r?λ (particle radius, r; laser wavelength, λ), the ray optics model can be used to calculate the two forces (Fig.1). For r?λ, the Rayleigh scattering model is often used. In addition, the absorbing particles will also be trapped by the photophoretic force, which results from thermal processes.

A single-Gaussian-beam trap using a tightly focused single beam can trap a particle in three dimensions. It employs a high numerical aperture (NA) objective, which provides a strong gradient force at low laser power. However, the single-Gaussian-beam trap has a very short working distance, which limits its compatibility with other measuring techniques. The two counter-propagating beams can balance the scattering force and retain the gradient force so that the dual-Gaussian-beam trap can obtain a longer working distance (Fig.2). A single-beam photophoretic trap uses only a single laser beam that contains low intensity regions to trap absorbing particles. For instance, a hollow beam, usually formed using axicons, has the advantages of a simple configuration and long working distance (Fig.3). A dual-hollow-beam trap has stronger trapping robustness than a single-hollow-beam trap, and the number and size of trapping particles can be controlled by adjusting the distance between the two focal points (Fig.4). However, the two foci must be aligned with each other at a precision of sub-micrometers. Fortunately, confocal-beam traps integrate the simplicity of single-beam traps and the robustness of dual-beam traps (Fig.5). Among the above optical traps, none were able to trap both transparent and absorbing particles until the universal optical trap was developed (Fig.6). In our experiments, particles were trapped with different arrangements using different shape laser beams (Fig.7), and we realized a variety of particles trapped by dual-hollow-beam and dual-Gaussian-beam traps (Fig.8).

The combination of optical trapping and spectroscopic measurements can be used to investigate the physical and chemical properties of airborne particles. Optical trapping Raman spectroscopy (OT-RS) is mainly used to study droplets; therein, the size and refractive index of aerosol droplets can be obtained from the stimulated Raman spectroscopy (Fig.9). Because the spontaneous Raman scattering intensity is weak, a higher power laser is required (Fig.10). By optimizing the slit setting, the problem of signal superposition from different positions of the droplets can be eliminated, and a high spatial resolution can be obtained (Fig.11).

Compared to OT-RS of droplets, fewer studies have been reported on OT-RS of solid particles. Most solid airborne particles have arbitrary size, composition, and morphology, which introduce challenges in the repeatability of experiments. In 2012, OT-RS of carbon nanotubes was investigated for the first time using a dual-hollow-beam trap (Fig.12). Researchers have improved the trapping robustness of solid airborne particles using a variety of means and have realized OT-RS detection and rapid identification of various oxides and bioaerosols. Combined with an imaging system, it can also monitor changes in particle size and morphology .

Stable trapping enables us to measure the temporal evolution processes of airborne particles in situ for a sufficiently long time. For example, the hydration and dehydration of trapped particles, the reactions of particles with the ambient atmosphere, and photochemical reactions can be investigated with OT-RS. In addition to Raman spectroscopy, optical trapping can also be combined with other laser spectroscopic techniques, such as cavity ringdown spectroscopy (Fig.14) and laser-induced breakdown spectroscopy (Fig.15).

At present, research on optically trapped airborne particles is still in its infancy. Although a variety of methods, such as OT-RS, have been developed to retrieve fundamental information from airborne particles in their native states, there are still many problems in practical applications, such as weak spectral signals, complex trapping forces, and inappropriate particle introduction methods.

In recent years, the optical trapping and spectroscopic measurement of airborne particles have been improved. In this review, optical trapping forces are briefly introduced. Diverse optical configurations used in the optical trapping of airborne particles are discussed, and the configuration simplicity and trapping robustness are evaluated. Optical trapping combined with spectroscopic techniques can characterize the physicochemical properties of a single airborne particle in its native state, and the study of heterogeneous chemical reactions under controlled environments can be realized with high temporal and spatial resolution ability. However, owing to the limitation of the trapping force, most particles reported to date are approximately 1?50 μm. It is hoped that with the development of optical trapping, there will be more research involving single nanoparticles, and the on-site monitoring of environmental particles can be realized in combination with real-time sampling apparatus.

Recently, fluorescence imaging in the second near-infrared window (NIR-Ⅱ, 1000?1700 nm) has attracted widespread attention from researchers. Compared with visible light window (300?550 nm) and first near-infrared window (NIR-I, 600?950 nm) imaging, NIR-Ⅱ fluorescence imaging exhibits unique advantages such as high tissue penetration (on the order of centimeters), high resolution (on the order of nanometers), and low background. NIR?Ⅱ fluorescent gold nanoclusters (NIR?Ⅱ Au NCs) represent a category of nano-materials with exceptional clinical translational potential. NIR?Ⅱ Au NCs possess singular advantages of monomeric composition, stable performance, small size (<3 nm), and renal clearance capability. They have been applied in various fields, including tumors, cardiovascular diseases, bacterial infections, neurosciences, and implantable medical devices, demonstrating significant potential applications and promising clinical translation prospects in the realm of high-sensitivity, high-resolution, and deep-tissue molecular imaging of major disease biomarkers.

In this review, we initially introduce the synthesis methods of NIR-Ⅱ Au NCs, discussing the challenges of low yield and scalable production. Subsequently, we delve into the surface modulation techniques for NIR-Ⅱ Au NCs, and methods to regulate the cluster surface structure, composition, and morphology for enhancing their emission wavelengths and fluorescence quantum yields. We then summarize the latest research advancements of NIR?Ⅱ Au NCs in vascular imaging, lymphatic vessel and lymph node imaging, tumor imaging, and imaging-guided therapy. Finally, we discuss the opportunities and challenges faced by NIR-Ⅱ Au NCs in the field of biomedical photonics.

NIR?Ⅱ Au NCs stand as potent candidates in the realm of biomedical photonics research, showcasing advantages of convenient synthesis, singular composition, tunable emission wavelength, good biocompatibility, in vivo clearance, and ease of targeted modification. They have demonstrated promising applications in tumor diagnosis, drug delivery, and multimodal imaging. However, further application and clinical translation of NIR?Ⅱ Au NCs encounter numerous challenges: 1) Existing synthesis methods of NIR?Ⅱ Au NCs suffer from low yield and lack of large-scale macro production processes, necessitating the development of more efficient preparation methods and processes. 2) The central emission wavelengths of existing NIR?Ⅱ Au NCs are less than 1300 nm, with a fluorescence quantum yield below 10%, urgently requiring improved synthesis methods to increase their emission wavelengths and enhance their NIR?Ⅱ fluorescence quantum yields. 3) The clinical use scenarios of NIR?Ⅱ Au NCs require further investigation to elucidate their precise clinical value and better serve disease diagnosis and treatment. Future research can expand into other application areas, including cardiovascular diseases, inflammation imaging, and intraoperative tumor boundary visualization, to better meet clinical translation needs and play a crucial role in safeguarding public health.

Colon cancer is a solid tumor with strong immunogenicity that is prone to metastasis in its early stages. Traditional single-treatment methods have limited efficacy; therefore, the development of new, safe, effective treatment strategies has become urgent. Natural killer (NK) cell-mediated immunotherapy can kill tumor cells in a nonspecific antigen manner and has good prospects for the treatment of malignant tumors. However, because of the common immune escape mechanism in malignant tumor tissues, the activity and infiltration of NK cells in tumor tissues are insufficient, making it difficult to effectively eliminate tumor cells. Recently, it was found that photothermal therapy (PTT) and photodynamic therapy (PDT), which induce local hyperthermia or reactive oxygen species in tumor tissues via laser-induced phototherapy, not only directly induce apoptosis and necrosis of tumor cells but also improve the immunosuppressive environment in tumor tissues by inducing immunogenic death of tumor cells. This promotes the infiltration and activity of immune cells, including NK cells, in tumor tissues. As a pure natural edible substance and a potential anticancer molecule in plants, lupeol directly promotes tumor cell apoptosis and NK cell activity, making it easier for NK cells to recognize and eliminate tumor cells. In this study, we investigated the synergistic effect and mechanism of a nanoliposome carrier combined with FDA-approved indocyanine green (ICG)-mediated optical therapy and the natural molecule, lupeol, in enhancing NK cell activity for colon cancer cell inactivation. The results show that Lip-Lupeol & ICG reduced colon cancer cell activity to 59.6% after 20 min of irradiation and 43.4% after 20 min+10 min of irradiation. When NK cells are added after 20 min+10 min of irradiation, the activity decreased to 16.7%, providing a new approach for colon cancer treatment.

The use of nanoliposomes as carriers to encapsulate the photosensitizer, ICG, and the natural anticancer product, lupeol, in fruits and vegetables to prepare nanoliposome drugs with uniform particle size and good stability (Lip-Lupeol & ICG) was used to achieve the synergistic amplification of PTT and PDT with lupeol-mediated NK cell immunotherapy. Lip-Lupeol & ICG can induce apoptosis of colon cancer cells and trigger immune responses through ICG-PDT under 808 nm laser radiation. In addition, it can release encapsulated lupeol to activate NK cells, thereby facilitating the accurate identification of colon cancer cells. Lip-Lupeol & ICG exhibits excellent tumor-killing effects and stimulates NK cell immune responses, achieving a synergistic therapeutic effect of NK cell immune enhancement and photodynamic therapy mediated by lupeol.

The prepared Lip-Lupeol & ICG has a typical phospholipid bilayer liposome structure, with bilayer vesicles for drug encapsulation and intracellular delivery. The particle size is approximately 144?153 nm, and the stability is good for 14 d. Lupeol and ICG were successfully encapsulated. Next, under the irradiation of an 808 nm laser on the liposome causing structural rupture, the encapsulated Lip-Lupeol & ICG were released rapidly. After 18 min, the accumulation of ICG reached 82.1%, indicating the photothermal response of Lip-Lupeol & ICG to laser irradiation. ICG-encapsulated liposomes enter tumor cells through endocytosis and induce severe cytotoxicity through PTT and PDT under a laser irradiation of 808 nm. In addition, lupeol synergistically enhances NK cell activity-mediated immunotherapy to achieve synergistic photodynamic immune antitumor effects.

In this study, a lipid nanocarrier system was designed to synergistically integrate the NK immune enhancement of lupeol-and ICG-mediated optical therapy and achieve controlled release. Both were effectively integrated to achieve precise targeting of lupeol and ICG to colon cancer cells, thereby enhancing the indirect immune response and anticancer effects of lupeol by promoting NK cell activity.

Changes in optical parameters can reflect the physiological status of biological tissue and constitute a fundamental and important topic in the field of near-infrared spectroscopy. Compared with the continuous-wave and frequency-domain measurement methods, the time-domain measurement method has the best performance in distinguishing and separating absorption and scattering coefficients, particularly in single-point measurement scenarios. Consequently, the time-domain measurement method is more commonly used to measure changes in optical parameters, also known as time-resolved spectroscopy. Currently, the biological tissue model used for time-resolved spectroscopy inversion schemes often assumes that the biological tissue is a single-layer biological tissue model, which hypothesizes that the optical properties are identical throughout the tissue. Although the single-layer biological tissue model simplifies the complexity of light propagation models and inversion algorithms, it is not very suitable for representing the structure of most human biological tissues; biological tissues at different depths exhibit a layered structure owing to variations in structure and function. Considering the high computational complexity and marginal improvement in accuracy associated with multilayer models, recent research has increasingly focused on the double-layer biological tissue model.

Currently, the commonly used double-layer biological tissue model parameter inversion methods face several challenges. First, they require a substantial amount of experimental data from multiple sources and detector separation, resulting in extended overall measurement times. Second, considerable time and effort are required to construct precise databases. Third, the need for iterative differentiation leads to prolonged computation time and lower accuracy. Finally, these methods struggle to handle complex scenarios, such as those in which both layers of tissue parameters are entirely unknown. To address these issues, this study introduces the Nelder-Mead simplex algorithm for the first time into the framework of Monte Carlo model-based tissue optical parameter inversion, developing a time-domain Monte Carlo supported Nelder–Mead simplex (MC-NMS) inversion algorithm.

The Monte Carlo model can use simulations to customize the optical parameters based on the structural characteristics of layered tissues, which are often employed as transport models for double-layer biological tissue model parameter inversion. This study introduces the Nelder–Mead simplex algorithm into Monte Carlo-based tissue optical parameter inversion for the first time. By utilizing only two source and detector separation time-domain diffuse reflectance data, the need to construct extensive databases in advance is eliminated. Initially, we empirically set the parameter values to find a feasible solution within the feasible region. The variables were incrementally adjusted through a cyclic iterative approach involving the establishment of different base vectors. Through matrix linear transformations, the optimal value of the objective function was determined using a heuristic search method that obviated the need for differentiation. Ultimately, this approach achieves a high-fidelity inversion of the optical parameters in layered tissues under complex conditions.

The numerical simulation experiments demonstrate that in the single-layer tissue optical parameter inversion application scenario, the proposed MC-NMS method yields significantly superior results compared to the TDIA and SDIA methods (Fig.3). Additionally, when the source-detector separation is set to 3 mm, the MC-NMS method yields the best results. (Fig.4). For double-layer biological tissue model optical parameter inversion, the results reveal that changing the upper-layer tissue thickness also requires different optimal source–detector separations (Fig.5, Fig.6). Moreover, the inversion errors obtained using the MC-NMS method are lower than those obtained using the TDIA and SDIA methods. Experimental validation was conducted using a multi-wavelength and multi-source-detector separation time-resolved measurement system based on time-correlated single-photon counting technology developed by our research group. Data were computed using the 25% rising edge to 20% falling edge time channels of the measured time-point spread function curves. The results indicate that the MC-NMS method achieves inversion errors of 11.64% and 0.89% in the single-layer biological tissue model for μa and μs', respectively. In the double-layer biological tissue model, the inversion errors for μa1, μa2, and μs' are 28%, 20%, and 14%, respectively, representing an overall improvement in the parameter inversion accuracy of approximately 17% compared to the TDIA method.

The results of the liquid phantom experiments for the single-layer biological tissue and double-layer biological tissue models consistently demonstrate that the MC-NMS method outperforms other approaches. Notably, when the μa is relatively larger, the inversion errors are smaller. The results indicate that the MC-NMS can not only maintain high inversion accuracy in the straightforward application scenario of the single-layer biological tissue model but also ensure the accuracy of complex scenarios, such as those in which all optical parameters of the double-layer biological tissue model layers are unknown. The MC-NMS can be an effective method for clinical applications of time-resolved tissue oxygen measurement and imaging instruments, providing a pragmatic tool for enhancing accuracy in clinical applications.

Optical fiber is an efficient propagation carrier of laser energy. A short-pulse laser can be focused on the end of a fiber to realize the directional propagation of energy along the carrier path. Therefore, the efficient and high-energy transmission of laser energy can be realized by inducing a plasma detonation wave with an underwater fiber laser. The integration of underwater fiber laser propulsion technology with various scientific and technological advancements holds significant promise in fields such as green ship manufacturing, submarine stealth propulsion, detonation engine performance, and supercavitation weapon systems. In the medical field, vascular embolism and thrombotic disease caused by endovascular thrombus flaking are still intractable diseases. Traditional thrombectomy and interventional hemolysis can cause harmful complications. For example, a thrombectomy can easily cause large-scale bleeding and the embolization of blood vessels. In view of the prominent problems with traditional thrombus removal, the technique of underwater fiber laser propulsion has been applied to the targeted removal of blood vessel thrombi. Based on fiber conduction, a short-pulse laser-induced plasma detonation wave propulsion scheme is proposed as part of the technical research on the noninvasive comprehensive treatment of thrombi. To explore the propagation characteristics of laser-induced plasma detonation waves, the feasibility of the fixed-point and directional noninvasive removal of thrombi using fiber laser-induced plasma detonation waves is verified by combining experiments and simulations.

This study analyzed the mechanism of underwater fiber laser-induced plasma shock wave propulsion. It modeled a thrombus in a human blood vessel, creating two environments for underwater fiber-optic laser propulsion. The study employed numerical simulations to observe the propagation process of plasma shockwaves generated by laser energy. First, the model, propagation mechanism, and absorption mechanism of laser plasma detonation waves were determined. Second, using a numerical simulation method for the energy source term and plasma equation of state, the thrombus propulsion in two blood environments was numerically simulated, and the pressure cloud image and thrust curve of the detonation waves acting on the thrombus were obtained. Then, we analyzed the factors influencing the thrombus progression. These influence factors were determined to be the amount of laser energy and the size and shape of the thrombus, and a corresponding numerical simulation was carried out to obtain the thrust curve conforming to certain rules. Finally, based on the characteristics of the thrombus, experiments that used an underwater fiber laser to push a single microsphere and microsphere cluster were carried out to verify the feasibility of thrombus removal.

The numerical simulation results show that the pressure variation of a plasma detonation wave with 9 mJ of laser energy decreases rapidly with distance and time, and the detonation wave pressure exceeds 10⁸ Pa within 100 μm from the center (Fig. 6). The peak thrust force of a detonation wave on the thrombus first increases and then decreases. In arterial and venous blood environments, the peak thrust forces produced with 20 μJ of laser energy on 2 mm thrombi can reach 1.2 and 1.0 N, respectively (Fig. 10), which can be used for thrombus clearance. The peak thrust on the thrombus is affected by the laser energy and the size and shape of the thrombus. As the laser energy increases from 5 to 25 μJ, the peak thrust on the thrombus increases continuously (Fig. 11). As the size of the thrombus increases from 1 to 3 mm, the peak thrust on the thrombus gradually increases, and the shape of the thrombus also has a significant impact on the peak thrust. A 3 mm square thrombus shows a larger peak thrust than a 3 mm spherical thrombus (Fig. 12). The experimental results show that a laser with an energy of 25 μJ can be used to propel a microsphere particle with a diameter of 50 μm, which has an obvious movement of approximately 300 μm in 4 ms (Fig. 15). A laser with an energy of 36 μJ can be used to break up microsphere clusters of 50 μm microsphere particles into discrete particles that can then be removed (Fig. 16).

With the goal of treating human vascular embolism, this paper discusses the construction of two different human vascular models and numerical simulations of human blood environments. The research shows that when using laser propulsion, the peak thrust on a human thrombus can exceed 1.0 N, and the thrust attenuation is a rapid process. The whole process will cause no harm to human blood vessels, and a human thrombus can be cleared by laser plasma detonation wave propulsion. At the same time, experimental data on how underwater fiber laser plasma detonation waves push microspheres and clusters are collected, and the experimental results are extended to the vascular environment to verify the feasibility of using a fiber laser to move a thrombus. Therefore, fiber laser plasma detonation waves can be used to push and clear a micro-thrombus and break up the thrombus clusters formed by the agglomeration of micro-thrombi.

Photoacoustic imaging is a multimodal imaging technique that integrates principles of optics and acoustics, enabling the observation and acquisition of structural and functional information within tissues. Blood flow velocity serves as a crucial indicator for evaluating vascular function and is closely associated with the occurrence and development of diseases. Accurate measurement of blood flow is particularly crucial for the diagnosis of various conditions, such as burns, stroke, atherosclerosis, diabetes, and cancer. Furthermore, the dynamics of blood flow have a significant impact on the effectiveness of pharmaceutical interventions in the human body, which emphasizes the importance of precise quantitative measurement of blood flow in clinical medicine. Photoacoustic measurement technology is a non-contact measurement approach based on the photoacoustic effect. It involves the application of pulsed laser energy to the target object, inducing thermal expansion and pressure waves that generate acoustic signals. The resulting acoustic signals are detected by an ultrasound transducer, and relevant algorithms are applied to measure fluid flow information (Fig. 1). Compared with traditional flow velocity measurement techniques, photoacoustic measurement technology offers higher resolution, greater imaging depth, increased contrast, and does not involve ionizing radiation.

This study employs the photoacoustic thermal measurement method to measure blood flow velocity. The principle of the photoacoustic thermal measurement method is rooted in the dependence of the photoacoustic signal amplitude on the temperature of the flowing medium. This dependence can be modulated through external heating and is influenced by the flow velocity. In the photoacoustic thermal measurement method, a pulsed laser beam is directed onto the fluid (blood). The absorbed optical energy induces a transient increase in local fluid temperature, creating a "thermal marker" and generating a corresponding ultrasound signal. Due to the acceleration of thermal transfer caused by fluid motion, the equilibrium temperature of the "thermal marker" varies at different flow velocities under the same laser irradiation, and it is correlated with the flow velocity. In this study, the fundamental theory for measuring blood flow velocity is deduced based on the thermal measurement method, establishing the relationship between velocity and the average photoacoustic signal amplitude. Furthermore, an experimental system for photoacoustic velocity measurement and imaging is constructed (Fig. 2). Utilizing LabVIEW for centralized control of the mechanical displacement stage and the signal acquisition system, experiments on photoacoustic velocity measurement and imaging are being conducted.

Through experimental investigation, quantitative relationships between photoacoustic pressure and fluid velocity are obtained. The study includes uncertainty analysis, and the experimental validation reveals an average measurement error of 8.2% for flow velocity within a relatively large range (0-200 mm/s) (Figs. 7 and 8), ascertaining the accuracy of the measurement. The lateral resolution of the imaging system is determined to be 10 μm (Fig. 9). Subsequent experiments involve two-dimensional scanning imaging, confirming the structural imaging capability of the system (Fig. 10). Finally, morphological and velocity photoacoustic co-measurements are conducted, demonstrating the system multimodal imaging functionality (Fig. 11). While the study does not consider the potential impact of vascular viscoelasticity on results, its underlying principle is based on the thermal equilibrium of laser heating, conduction, and blood convection within the heated volume, mitigating the effects of blood being a non-Newtonian fluid with shear forces and viscosity. Challenges in photoacoustic blood flow measurement, including measurement depth and signal interference, will be the focus of future research. Additionally, further experiments under different conditions, such as phantom and animal blood flow measurements, will be conducted to validate the feasibility of this method.

This study develops a thermal measurement-based photoacoustic experimental system for concurrent measurement of vascular morphology and blood flow velocity. The system utilizes a single light source to achieve synchronized measurements of vascular morphology and flow velocity. The experimental setup comprises optical excitation and laser shaping modules, photoacoustic detection module, sample pool, scanning motion module, and data acquisition module. The LabVIEW platform is employed for the control and storage of photoacoustic data. Through in vitro single-point velocity experiments, quantitative relationships between the photoacoustic pressure and fluid velocity are established. The system velocity measurement average error is validated to be 8.2%, with a maximum measurable velocity range of up to 200 mm/s. Building upon this foundation, a two-dimensional mechanical scanning approach is implemented to achieve concurrent photoacoustic morphology and flow velocity measurements with a resolution of 10 μm. Subsequent work will involve in vivo measurements of blood flow velocity and vascular morphology using this experimental system, aiming to further enhance the system imaging resolution and velocity measurement accuracy.

Warfarin sodium stands out as the primary oral anticoagulant for treating pulmonary embolism, necessitating individualized dosage adjustments guided by post-administration blood concentration, typically maintained in the range of 2.23?2.30 nmol/mL. Common quantitative methods such as mass spectrometry (MS), liquid chromatography-mass spectrometry (LC-MS), and high-performance liquid chromatography-fluorescence detection (HPLC-FLD) suffer from the problems of expensive equipment, high consumable costs, and long analysis time (>30 min). In contrast, terahertz (THz) spectroscopy offers a solution by acquiring molecular fingerprinting properties. When combined with density functional theory (DFT) simulation, it is capable of predicting molecular spectral properties and analyzing vibrational modes. This combination has been widely used in drug studies. This study aims to establish a new method using THz spectroscopy for rapid qualitative and quantitative analysis in the clinical detection of warfarin sodium. The proposed method achieves high-sensitivity quantitative analysis of warfarin sodium with two indexes, and the minimum detection limit reaches 0.01 nmol/mL, which is lower than the clinical blood concentration.

This study employs the quantum chemistry software Gaussian 09 to theoretically analyze the molecular vibrational properties of warfarin sodium. Specifically, the DFT/B3LYP/3-21G basis set is used to predict the vibrational properties in the range of 10?16 THz. Concurrently, a Fourier transform infrared spectrometer is employed to perform qualitative and quantitative analysis on warfarin sodium. The samples for analysis are prepared by doping 20 μL warfarin sodium solutions on high-resistance silicon surface, followed by drying under vacuum conditions at 20 ℃. THz absorption spectra of warfarin sodium solutions, with concentrations in the range of 2?100 nmol/mL, are obtained at a resolution of 4 cm^-1.

In this study, qualitative experimental tests on 2 mg warfarin sodium are performed to obtain the THz characteristic absorption spectrum. The results reveal clear absorption peaks at 11.10, 11.94, 13.05, 13.74, and 15.43 THz, along with a shoulder peak at 14.01 THz (Fig. 1). Meanwhile, the molecular theoretical spectrum of warfarin, obtained by DFT calculation, demonstrates six characteristic absorption peaks within the frequency range of 10?16 THz. These theoretical peaks are located at 11.07, 11.70, 13.28, 13.82, 14.27, and 15.71 THz (Fig. 2). Comparison of the theoretical spectra with the experimental spectra exhibits consistency (Table 1), and different experimental peaks arise from different molecular vibrational modes (Fig. 3). For quantitative analysis, experimental peaks at 12.05, 13.79, and 15.58 THz are selected owing to their distinct vibration modes and strong absorbance. The peak area and intensity of these peaks exhibit linear relationships with the concentration of warfarin sodium solutions (Fig. 4 and Fig. 5), with correlation coefficients exceeding 0.96, conforming to Beer-Lambert law. Based on these results, the detection sensitivity and limit of detection (LOD) are further determined (Table 2). The lowest LOD reaches 0.01 nmol/mL, which is lower than the clinical blood concentration. Therefore, a rapid and reliable quantitative analysis method for warfarin sodium is established based on its multiple THz characteristic peaks.

In this study, a rapid qualitative and quantitative analysis method for the anticoagulant drug warfarin sodium is developed based on THz spectroscopy. Through THz spectral experiments and DFT calculations, it is clarified that six characteristic peaks of warfarin sodium exist in the range of 10?16 THz, corresponding to the frequencies of 11.10, 11.94, 13.05, 13.74, 14.01, and 15.43 THz, respectively. The attribution of these peaks is analyzed, and a qualitative identification method for warfarin sodium is established. Subsequently, the THz spectra of warfarin sodium solutions with different concentrations are analyzed. The correlation between drug concentration and the peak intensity, along with the peak area is analyzed, and the quantitative detection curve of warfarin sodium is given. The sensitivity and detection limit are calculated. The results demonstrate that the peak intensity and peak area increase linearly with the increase in warfarin sodium concentration (the correlation coefficient is >0.96). Based on the peak area at 15.58 THz, the detection limit reaches 0.01 nmol/mL, which is lower than the clinical blood concentration (2.23?2.30 nmol/mL). This study proposes a rapid quantitative detection method of warfarin sodium and contributes to the development of blood drug concentration monitoring technology.