Accurate and early detection of atherosclerosis (AS) is imperative for their effective treatment. However, fluorescence probes for efficient diagnosis of AS often encounter insufficient deep tissue penetration, which hinders the reliable assessment of plaque vulnerability. In this work, a reactive oxygen species (ROS) activated near-infrared (NIR) fluorescence and photoacoustic (FL/PA) dual model probe TPA-QO-B is developed by conjugating two chromophores (TPA-QI and O-OH) and ROS-specific group phenylboronic acid ester. The incorporation of ROS-specific group not only induces blue shift in absorbance, but also inhibits the ICT process of TPA-QO-OH, resulting an ignorable initial FL/PA signal. ROS triggers the convertion of TPA-QO-B to TPA-QO-OH, resulting in the concurrent amplification of FL/PA signal. The exceptional selectivity of TPA-QO-B towards ROS makes it effectively distinguish AS mice from the healthy. The NIR emission can achieve a tissue penetration imaging depth of 0.3 cm. Moreover, its PA775 signal possesses the capability to penetrate tissues up to a thickness of 0.8 cm, ensuring deep in vivo imaging of AS model mice in early stage. The ROS-triggered FL/PA dual signal amplification strategy improves the accuracy and addresses the deep tissue penetration problem simultaneously, providing a promising tool for in vivo tracking biomarkers in life science and preclinical applications.

Breast cancer is a major challenge in the field of oncology, with around 2.3 million cases and around 670,000 deaths globally based on the GLOBOCAN 2022 data. Despite having advanced technologies, breast cancer remains the major type of cancer among women. This review highlights various collagen signatures and the role of different collagen types in breast tumor development, progression, and metastasis, along with the use of photoacoustic spectroscopy to offer insights into future cancer diagnostic applications without the need for surgery or other invasive techniques. Through mapping of the tumor microenvironment and spotlighting key components and their absorption wavelengths, we emphasize the need for extensive preclinical and clinical investigations.

Osteoporosis is a systemic disease with a high incidence in the elderly and seriously affects the quality of life of patients. Photoacoustic (PA) technology, which combines the advantages of light and ultrasound, can provide information about the physiological structure and chemical information of biological tissues in a non-invasive and non-radiative way. Due to the complex structural characteristics of bone tissue, PA signals generated by bone tissue are non-stationary and nonlinear. However, conventional PA signal processing methods are not effective for non-stationary signal processing. In this study, an empirical mode decomposition (EMD)-based Hilbert-Huang transform (HHT) PA signal analysis method, called HHT PA signal analysis (HPSA), was developed to assess the microstructure information of bone tissue, which is closely related to bone health. The feasibility of the HPSA method in bone health assessment was proven by numerical simulation and experimental studies on animal samples with different bone volume/total volume (BV/TV) and bone mineral densities. First, based on adaptive EMD, the different modes correlated with multi-scale information were mined from the PA signal, the correlations between different intrinsic mode function (IMF) modes and BV/TVs were analyzed, and the optimal mode for more efficient PA time-frequency analysis was selected. Second, multi-wavelength HPSA was used to assess the changes in the chemical components of the bone tissue. The results demonstrate that the HPSA method can distinguish bones with different BV/TVs and microstructure conditions adaptively with high efficiency. They further emphasize the potential of PA techniques in characterizing biological tissues in bones for early and rapid detection of bone diseases.

Bioanalysis based on optical imaging has gained significant progress in the last few decades. Luminescence probes are capable of detecting, monitoring, and tracing particular biomolecules in complex biological systems to figure out the roles of these molecules in organisms. Considering the rapid development of luminescence probes for bio-applications and their promising future, we have attempted to explore the working principles and recent advances in bio-applications of luminescence probes, in the hope of helping readers gain a detailed understanding of luminescence probes developed in recent years. In this review, we first focus on the current widely used luminescence probes, including fluorescence probes, bioluminescence probes, chemiluminescence probes, afterglow probes, photoacoustic probes, and Cerenkov luminescence probes. The working principles for each type of luminescence probe are concisely described and the bio-application of the luminescence probes is summarized by category, including metal ions detection, secretion detection, imaging, and therapy.

Accurate image reconstruction is crucial for photoacoustic (PA) computed tomography (PACT). Recently, deep learning has been used to reconstruct PA images with a supervised scheme, which requires high-quality images as ground truth labels. However, practical implementations encounter inevitable trade-offs between cost and performance due to the expensive nature of employing additional channels for accessing more measurements. Here, we propose a masked cross-domain self-supervised (CDSS) reconstruction strategy to overcome the lack of ground truth labels from limited PA measurements. We implement the self-supervised reconstruction in a model-based form. Simultaneously, we take advantage of self-supervision to enforce the consistency of measurements and images across three partitions of the measured PA data, achieved by randomly masking different channels. Our findings indicate that dynamically masking a substantial proportion of channels, such as 80%, yields meaningful self-supervisors in both the image and signal domains. Consequently, this approach reduces the multiplicity of pseudo solutions and enables efficient image reconstruction using fewer PA measurements, ultimately minimizing reconstruction error. Experimental results on in-vivo PACT dataset of mice demonstrate the potential of our self-supervised framework. Moreover, our method exhibits impressive performance, achieving a structural similarity index (SSIM) of 0.87 in an extreme sparse case utilizing only 13 channels, which outperforms the performance of the supervised scheme with 16 channels (0.77 SSIM). Adding to its advantages, our method can be deployed on different trainable models in an end-to-end manner, further enhancing its versatility and applicability.

Photoacoustic (PA) emitters are emerging ultrasound sources offering high spatial resolution and ease of miniaturization. Thus far, PA emitters rely on electronic transitions of absorbers embedded in an expansion matrix such as polydimethylsiloxane (PDMS). Here, it is shown that mid-infrared vibrational excitation of C─H bonds in a transparent PDMS film can lead to efficient mid-infrared photoacoustic conversion (MIPA). MIPA shows 37.5 times more efficient than the commonly used PA emitters based on carbon nanotubes embedded in PDMS. Successful neural stimulation through MIPA both in a wide field with a size up to a 100 µm radius and in single-cell precision is achieved. Owing to the low heat conductivity of PDMS, less than a 0.5 °C temperature increase is found on the surface of a PDMS film during successful neural stimulation, suggesting a non-thermal mechanism. MIPA emitters allow repetitive wide-field neural stimulation, opening up opportunities for high-throughput screening of mechano-sensitive ion channels and regulators.

Neuromodulation is a powerful tool for fundamental studies in neuroscience and potential treatments of neurological disorders. Both photoacoustic (PA) and photothermal (PT) effects are harnessed for non-genetic high-precision neural stimulation. Using a fiber-based device excitable by a nanosecond pulsed laser and a continuous wave laser for PA and PT stimulation, respectively, PA and PT neuromodulation is systematically investigated at the single neuron level. These results show that to achieve the same level of neuron activation recorded by Ca2+ imaging, the laser energy needed for PA stimulation is 1/40 of that needed for PT stimulation. The threshold energy for PA stimulation is found to be further reduced in neurons overexpressing mechano-sensitive channels, indicating direct involvement of mechano-sensitive channels in PA stimulation. Electrophysiology study of single neurons upon PA and PT stimulation is performed by patch clamp recordings. Electrophysiological features induced by PA are distinct from those by PT, confirming that PA and PT stimulation operate through different mechanisms. These insights offer a foundation for the rational design of more efficient and safer non-genetic neural modulation approaches.

The accuracy and efficacy of laser ablation procedures depend on the accurate placement of the laser applicator within the diseased tissue, monitoring the real-time temperature during the ablation procedure, and mapping the extent of the ablated region. Ultrasound (US) imaging has been widely used to guide ablation procedures. While US imaging offers significant advantages for guiding ablation procedures, its limitations include low imaging contrast, angular dependency, and limited ability to monitor the temperature. Photoacoustic (PA) imaging is a relatively new imaging modality that inherits the advantages of US imaging and offers enhanced capabilities for laser-guided ablations, such as accurate, angle-independent tracking of ablation catheters, the potential for quantitative thermometry, and monitoring thermal lesion formation. This work provides an overview of ultrasound-guided procedures and how different US-related artifacts limit their utility, followed by introducing PA as complementary to US as a solution to address the existing limitations and improve ablation outcomes. Furthermore, we highlight the integration of PA-driven features into existing US-guided laser ablation systems, along with their limitations and future outlooks. Integrated US/PA-guided laser ablation procedures can lead to safer and more precise treatment outcomes.

Microscopic defects in flip chips, originating from manufacturing, significantly affect performance and longevity. Post-fabrication sampling methods ensure product functionality but lack in-line defect monitoring to enhance chip yield and lifespan in real-time. This study introduces a photoacoustic remote sensing (PARS) system for in-line imaging and defect recognition during flip-chip fabrication. We first propose a real-time PARS imaging method based on continuous acquisition combined with parallel processing image reconstruction to achieve real-time imaging during the scanning of flip-chip samples, reducing reconstruction time from an average of approximately 1134 ms to 38 ms. Subsequently, we propose improved YOLOv7 with space-to-depth block (IYOLOv7-SPD), an enhanced deep learning defect recognition method, for accurate in-line recognition and localization of microscopic defects during the PARS real-time imaging process. The experimental results validate the viability of the proposed system for enhancing the lifespan and yield of flip-chip products in chip manufacturing facilities.

Skin architecture and its underlying vascular structure could be used to assess the health status of skin. A non-invasive, high resolution and deep imaging modality able to visualize skin subcutaneous layers and vasculature structures could be useful for determining and characterizing skin disease and trauma. In this study, a multispectral high-frequency, linear array-based photoacoustic/ultrasound (PAUS) probe is developed and implemented for the imaging of rat skin in vivo. The study seeks to demonstrate the probe capabilities for visualizing the skin and its underlying structures, and for monitoring changes in skin structure and composition during a 5-day course of a chemical burn. We analayze composition of lipids, water, oxy-hemoglobin, and deoxy-hemoglobin (for determination of oxygen saturation) in the skin tissue. The study successfully demonstrated the high-frequency PAUS imaging probe was able to provide 3D images of the rat skin architecture, underlying vasculature structures, and oxygen saturation, water, lipids and total hemoglobin.