Piezoelectric materials provide a unique platform for bioelectronic interfaces, enabling dynamic sensing and electroactive therapies through bidirectional transduction between biomechanical and bioelectrical signals. However, the development of bioresorbable piezoelectric materials that combine high functional performance with mechanical compliance remains a critical challenge for seamless integration with soft biological tissues, while eliminating the need for retrieval surgeries and long-term material retention. Here, we report a bioresorbable, flexible piezoelectric composite composed of Rochelle salt (RS) crystals embedded within poly(L-lactic acid) (PLLA) nanofibers. Fabricated via electrospinning and uniaxial compression, centimeter-scale biodegradable nanofiber films are achieved, exhibiting excellent effective piezoelectric coefficient of 43.1 pC N−1 and piezoelectric voltage coefficient of 1909.2 mV m N−1, surpassing the piezoelectric performance of previously reported biodegradable flexible materials. Ultrasound-driven scaffold devices derived from these bioresorbable piezoelectric materials markedly enhance sciatic nerve regeneration in rodents. Additionally, a biodegradable piezoelectric strain sensor enables wireless, real-time monitoring of intestinal motility, facilitating diagnosis of colonic dysfunction. Together, these findings establish a prominent materials paradigm for biodegradable piezoelectric electronics, offering a versatile platform for bioelectronic applications in regenerative medicine, neuromodulation, and physiological monitoring. Bioresorbable piezoelectric materials are key for bioelectronic–tissue integration but remain challenging to realize. Here, the authors develop flexible Rochelle salt/PLLA nanofibers that enable effective nerve regeneration and wireless monitoring of intestinal motility.

Electrocatalytic nitrate reduction (NO3RR) provides a sustainable approach for removing nitrate pollutants and producing valuable nitrogen chemicals. However, understanding catalytic behavior under realistic dilute conditions remains challenging, as conventional electrochemical measurements rely on ensemble-averaged signals that obscure dynamic interfacial processes at individual particles. Here we show an operando electrochemiluminescence (ECL) microscopy strategy that visualizes and evaluates apparent NO3RR kinetics at the single-particle level. Using Cu(111) nanosheets as a model catalyst, we convert reaction-induced optical responses into spatially resolved descriptors of nitrate adsorption and intermediate evolution. The time-dependent ECL response reveals the generation and diffusion of nitrite, a key intermediate in nitrate reduction. These descriptors provide apparent kinetic mapping, uncovering substantial kinetic heterogeneity of individual particles. Correlative imaging of intermediate diffusion demonstrates that interparticle coupling influences apparent catalytic performance by modulating intermediate accumulation and interfacial mass transport under dilute nitrate conditions. This approach provides an operando optical microscopy platform for visualizing dynamic catalytic interfaces and linking interfacial processes with apparent catalytic performance. Understanding catalytic dynamics at electrochemical interfaces is important, while reactions at individual particles remain difficult to observe. Here, the authors report an operando electrochemiluminescence microscopy approach to visualize nitrate reduction processes and monitor apparent kinetics.

Slice-based volumetric imaging is widely applied and it demands representations that compress aggressively while preserving internal structure for analysis. We introduce GaussianPile, unifying 3D Gaussian splatting with an imaging system-aware focus model to address this challenge. Our proposed method introduces three key innovations: (i) a slice-aware piling strategy that positions anisotropic 3D Gaussians to model through-slice contributions, (ii) a differentiable projection operator that encodes the finite-thickness point spread function of the imaging acquisition system, and (iii) a compact encoding and joint optimization pipeline that simultaneously reconstructs and compresses the Gaussian sets. Our CUDA-based design retains the compression and real-time rendering efficiency of Gaussian primitives while preserving high-frequency internal volumetric detail. Experiments on microscopy and ultrasound datasets demonstrate that our method reduces storage and reconstruction cost, sustains diagnostic fidelity, and enables fast 2D visualization, along with 3D voxelization. In practice, it delivers high-quality results in as few as 3 minutes, up to 11x faster than NeRF-based approaches, and achieves consistent 16x compression over voxel grids, offering a practical path to deployable compression and exploration of slice-based volumetric datasets.

Modern data centers face unprecedented challenges from complex communication patterns generated by large-scale AI training and novel heterogeneous accelerators. To address these issues, we present a co-designed data center network (DCN) architecture that holistically integrates topology, routing, and scheduling around a unified spectral principle. The core of our design is a hierarchical network built from Ramanujan subclusters, which leverages their near-optimal expansion properties for practical deployment. At the topology level, we propose an heuristic construction for Ramanujan graphs that supports arbitrary degrees for an arbitrary number of nodes and a scalable subcluster-merging procedure. At the routing level, we introduce a spectral-health-aware routing scheme that combines offline precomputation with lightweight online eigenvalue estimation to maintain performance under congestion and failures. At the scheduling level, we develop a topology-aware scheduling framework that uses spectral-affinity clustering to align distributed training workloads with the underlying network structure. Extensive simulations across diverse network topologies, traffic patterns, and large-scale training scenarios demonstrate that our co-designed system consistently achieves lower latency, more balanced link utilization, and improved robustness under challenging conditions including hotspot traffic and link failures.

Understanding how applied voltage regulates metabolism in microbial electrochemical systems is challenging due to the lack of adequate electrophysiological tools for microorganisms. Here, we present an imaging platform based on electrochemiluminescence (ECL) that allows real-time, femtocoulomb-scale quantification of surface charge in single bacterial cells. The method exploits the electrostatic enrichment of cationic luminophores at bacterial membranes to amplify ECL signals, thereby linking surface charge dynamics to intracellular electron metabolism and interfacial electron flow. Using Shewanella oneidensis MR-1 as a model, we show voltage-activated metabolic enhancement mediated by outer-membrane cytochromes. By modulating direct and indirect electron-transfer pathways, we reveal that cytochrome-dependent direct electron transfer initiates activation, while mediator-enabled indirect electron transfer prevents charge saturation and sustains elevated metabolic turnover. Furthermore, dual-parameter screening enables identification of bacterial subpopulations with high metabolic activity and efficient electron transfer capability. Thus, our work provides a framework for microbial electrophysiology at the single-cell level and opens potential avenues for engineering high-performance electroactive strains for bio-electrochemical applications.

Peripheral artery disease (PAD) spans a continuum from large-vessel obstruction to distal microvascular dysfunction, yet routine non-invasive tests, including the ankle-brachial index (ABI), do not provide structurally resolved assessment of the foot microvascular bed and may be unreliable in the setting of medial arterial calcification or perioperative follow-up. Here we developed a clinic-oriented multispectral compound-scanning photoacoustic tomography system (MCPATS) for compression-free distal toe imaging, and an interpretable photoacoustic tomography distal microcirculation score, termed PACT-DMS, for phenotyping PAD-related distal vascular abnormalities. PACT-DMS was derived from anatomically standardized distal toe sections and integrated seven prespecified vascular features spanning trunk-vessel morphology, microvascular distribution and pulsation-related dynamics through a traceable linear support vector machine. In a prospective single-centre cohort of 45 participants, the bilateral fusion PACT-DMS model distinguished patients with PAD from healthy controls with an area under the receiver operating characteristic curve of 0.964 (95% CI, 0.907-1.000) and an accuracy of 91.1% (95% CI, 82.2%-97.8%) under subject-level leave-one-out cross-validation, supported by complementary robustness analyses. Exploratory analyses further showed that PACT-DMS identified abnormal distal vascular phenotypes in 6 of 9 clinically diagnosed PAD limbs with non-abnormal ABI and visualized distal vascular-bed changes before and after revascularization. These findings support MCPATS-enabled interpretable photoacoustic vascular phenotyping as a candidate adjunctive approach for distal microcirculatory assessment in PAD; larger multicentre studies with external validation and prespecified analysis protocols will be required to define its clinical role. ### Competing Interest Statement J.X., N.Z., W.F. and X.W. are employees of Beijing Tsingpai Technology Co., Ltd., a company involved in the development and manufacture of photoacoustic/ultrasound imaging systems. C.M. holds equity interest in Beijing Tsingpai Technology Co., Ltd. The imaging equipment used in this study was produced and maintained by Beijing Tsingpai Technology Co., Ltd., and company-affiliated authors assisted with equipment operation and data acquisition. Clinical diagnosis, patient management, reference-standard assessment, statistical analysis and interpretation of the clinical findings were performed independently by the academic and clinical investigators. The remaining authors declare no competing interests. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Ethics Committee of Beijing Friendship Hospital, Capital Medical University gave ethical approval for this work (approval number 2024-P2-080-01). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes De-identified individual-level data, model outputs and reporting checklists are provided with the article as Supplementary Data. Supplementary Data 1 contains participant baseline characteristics; Supplementary Data 2 contains de-identified clinical presentations and vascular imaging summaries; Supplementary Data 3 contains limb-level subject-level leave-one-out cross-validation results, PACT-DMS decision scores and F1-F7 feature values; Supplementary Data 4 contains participant-level bilateral fusion scores and classification results; Supplementary Data 5 contains vessel pulsation scores, binary decisions, adjudication results and final pulsation labels; Supplementary Data 6 contains the STARD 2015 reporting checklist; and Supplementary Data 7 contains the TRIPOD+AI reporting checklist. Because raw PACT images and clinical imaging data may contain identifiable anatomical information or be subject to hospital ethics and data-management restrictions, complete raw imaging data are available from the corresponding authors upon reasonable request and after ethics and data-use approval. National Key Research and Development Program of China, 2024YFC2421800, 2025YFC2422600 Chinese Institutes for Medical Research, Beijing (CIMR), CX23YQ07 National Natural Science Foundation of China, 82570574 Beijing High-Level Innovation and Entrepreneurship Talent Support Program, 2025-04841037 Beijing Hospitals Authority, YGLX202503

Photoacoustic imaging critically depends on the sensitivity of its acoustic readout chain, yet system-level optimization beyond the transducer remains insufficiently understood. Here, we present an end-to-end hardware model for photoacoustic signal readout chains by analytically rederiving the Krimholtz, Leedom, and Matthaei (KLM) model and extending it to include cable parasitics and complex receiver impedance. The model reveals how element area (EA), cable length (CL), and receiver impedance (RI) jointly govern detection sensitivity, bandwidth, and signal-to-noise ratio, which is validated experimentally with errors below 5%. Beyond sensitivity optimization, the model also provides insight into waveform distortion mechanisms in practical systems, identifying radial resonance as the source of low-frequency ringing artifacts. This work provides a practical theoretical framework for sensitivity optimization and artifact-aware design in photoacoustic systems.

Photoacoustic computed tomography (PACT) is an emerging biomedical imaging modality that uniquely combines high spatial resolution with deep penetration, holding great promise for noninvasive mapping of tissue oxygen saturation (sO2) — a critical biomarker in metabolism and pathophysiology. However, achieving accurate quantitative sO2 mapping is fundamentally challenged by the spatiotemporal heterogeneity of optical fluence, which leads to the spectral coloring effect and severely distorts measurements in deep tissue. This review systematically summarizes the evolution of quantitative PACT oximetry, critically analyzing techniques devised to overcome this bottleneck. We explore the limitations of linear unmixing and provide a focused analysis of advanced correction strategies, including photon transport modeling, acoustic-spectrum-based self-calibration, multimodality fusion, statistical inference, and learning-based approaches. By synthesizing and contrasting the strengths and weaknesses of these diverse approaches, this review aims to serve as a comprehensive reference for researchers, supporting the development of robust oximetry techniques and facilitating the clinical translation of PACT.

Combining tumor-associated macrophage (TAM)-targeted immunotherapy with starvation therapy represents a promising strategy for enhancing antitumor efficacy. Energy metabolism and nitrosative stress represent two key metabolic pathways that can effectively guide the efficacy of the combination of TAM-targeted immunotherapy and starvation therapy. However, methods capable of simultaneously profiling of the dynamic interplay between energy metabolism and nitrosative stress during cancer starvation-immunotherapy (CSI) remains challenging. Here, we report a TAM-targeted dual-mode nanoprobe, NNDA, for real-time imaging of energy metabolism and M1-like TAM-mediated nitrosative stress during CSI. The nanoprobe was designed to comprise NAD(P)H-sensitive dye Glu-RB and NO-responsive dye CY-NO assembled on the surface of upconversion nanoparticles, showing excellent selectivity and sensitivity to energy metabolism-associated NAD(P)H and nitrosative stress-associated NO with two independent NIR photoacoustic (PA, 710/1064 nm) and upconversion luminescence (UCL, 660/800 nm) channels. In vitro and in vivo studies confirmed that NNDA accurately tracked metabolic reprogramming and TAM repolarization, revealing that CSI regimens sustain nitrosative stress under energy suppression. Importantly, the ratio R-PA1064/PA710 serves as an early prognostic indicator of treatment outcome, displaying strong correlation with tumor growth inhibition. This work provides a cross-referencing imaging tool for dynamically deciphering metabolic-immune crosstalk, facilitating the screening and optimization of synergistic anticancer therapies.

Abstract Acute myocardial infarction is a life-threatening cardiovascular event, and point-of-care determination of cardiac troponin I (cTnI) is crucial for early diagnosis and timely intervention. Herein, a self-powered point-of-care sensing platform based on a light-driven bipolar electrode (BPE) for synchronous electrochromic and photoelectrochemical dual-readout detection of cTnI was reported. The BPE integrates a photocathodic sensing pole and an electrochromic reporting pole, enabling simultaneous generation of photocurrent and visual color change through a single photoinduced electron-transfer pathway. Magnetic molecularly imprinted microspheres (MMIPs) were employed as robust capture elements to selectively extract cTnI from biophysical samples. Subsequently, cTnI quantitatively bridges MMIPs with Cu-MOF@TiO2 nanoprobes to form a sandwich complex, which is immobilized onto the sensing pole. Upon light irradiation, the Cu-MOF@TiO2 composite generates photogenerated charge carriers, producing a photocurrent at the sensing pole while synchronously driving the reduction of Prussian blue (PB) to Prussian white (PW) at the reporting pole through the BPE circuit. The electrochromic response can be quantitatively analyzed by smartphone RGB imaging, providing visual detection of cTnI from 10–9 to 10–4 mg/mL, while the photoelectrochemical mode exhibits a wider linear range from 10–11 to 10–4 mg/mL. This work offers a portable, instrument-minimized, and self-powered dual-readout strategy for onsite cardiac biomarker analysis, and provides a versatile framework for future multiplexed biosensing applications.

Accurately assessing how individual cells respond to anticancer agents remains challenging because most assays provide bulk or binary readouts and cannot translate single-cell imaging into scalable, mechanism-relevant quantification. Here, we develop a nuclear DNA-gated electrochemiluminescence (ECL) microscopy assay in which genomic DNA acts as an intrinsic coreactant for Ru(bpy)32+, converting apoptosis-associated chromatin condensation and fragmentation into spatially resolved decreases in nuclear ECL intensity. The resulting signal provides a dose- and time-dependent measure of the apoptotic progression. For drug-treated cells, a deep learning model trained on ECL images enables high-throughput classification of apoptotic and nonapoptotic cells, allowing quantitative apoptosis profiling across large datasets. Using this framework, we compare the apoptotic potency of three natural anticancer compounds and reveal distinct spatial damage signatures for two photosensitizers, reflecting their different ROS-mediated pathways. This integrated approach offers a quantitative and scalable strategy for single-cell apoptosis profiling.

Photoacoustic tomography (PAT) and thermoacoustic tomography (TAT) both leverage acoustic signals generated by electromagnetic absorption to noninvasively image deep tissues. PAT operates by detecting optical absorption, whereas TAT targets radiofrequency (RF) absorption, providing complementary information on tissue composition and structure. Combining these modalities into a single system promises richer contrast but remains difficult due to the expense and complexity of the RF source. Here, we show that PAT can be integrated with a low-cost RF heater and used to image both optical and RF absorption in tissue phantoms. RF Heating-Enhanced Photoacoustic Tomography (HEPAT) maps RF absorption via temperature-dependent changes in thermomechanical properties, which enables the use of slow, inexpensive RF subsystems and provides an additional layer of contrast. HEPAT therefore provides distinct, complementary contrast relative to existing photoacoustic imaging systems, expanding specificity and diagnostic power while opening new avenues for studying temperature-related tissue phenomena.

Photoacoustic tomography combines high optical absorption contrast with deep ultrasonic penetration, providing powerful capabilities for high resolution biomedical imaging. It often demands wide field and large data acquisition, posing significant challenges to imaging speed. Sparse sampling effectively reduces data volume and accelerates imaging, but the resulting artifacts and detail loss limit its applications. Therefore, we construct a sparse-view photoacoustic tomography system and propose generative adversarial network with multiscale structural features, to achieve high speed and quality three-dimensional imaging. The generator incorporates pyramid squeeze attention block to extract multiscale structural information, while skip connection with a channel attention module in the discriminator enhances organ structural consistency. In addition, dual gradient regularized adversarial loss is designed to improve stability in detail enhancement and artifact suppression. Experiments with 128 and 64 views sampling verify that the proposed system achieves superior artifact suppression and detail recovery, preserving structural features consistent with full-view reconstruction. Furthermore, compared with the strongest baseline diffusion model and MambaIR, MSF-GAN improved the peak signal-to-noise ratio and structural similarity index by 1.128% and 1.176% under 128 views sampling, and by 2.442% and 0.536% under 64 views. These demonstrate that the proposed system and method effectively leverage photoacoustic structural information to improve fidelity and contrast. This work achieves a desirable balance between high speed and quality reconstruction, providing a promising pathway for translating photoacoustic tomography into practical clinical applications

Optical-resolution photoacoustic microscopy is a novel imaging technique that combines the advantages of optical and ultrasound imaging, enabling high-resolution visualization of biological tissues at the micrometer scale. However, the divergence of the excited Gaussian beam limits the depth-of-field of the system to less than 100[Formula: see text] [Formula: see text]m, which hinders accurate three-dimensional imaging of living tissues and restricts its applicability in biological research. Therefore, there is an urgent need for an effective method to enhance the depth-of-field without altering the hardware configuration. This paper presents a photoacoustic microscopy depth-of-field extension method and system based on three-dimensional continuity and sparsity deconvolution. This method utilizes a depth-varying point spread function and incorporates continuity and sparsity constraints into the deconvolution process to mitigate the effect of background noise, enhancing the stability and accuracy of the depth-of-field extension. Experimental results using tungsten wire phantoms suggest that the depth-of-field of system can be extended to 650[Formula: see text] [Formula: see text]m, which is 7.2 times greater than conventional system, while improving the resolution of the defocused region by an average factor of 3.5. Furthermore, experiments on zebrafish and nude mouse ears with irregular topologies demonstrate that the proposed method successfully overcomes image blurring and the loss of structural information due to limited depth-of-field. All the results suggest that the system with higher lateral resolution and enhanced depth-of-field has significant potential for a wide range of practical biomedical applications.

Fibroblast activating protein (FAP) is up-regulated in cancer-associated fibroblasts (CAFs) of more than 90% of tumor microenvironment and also highly expressed on the surface of multiple tumor cells like glioblastoma, which can be used as a specific target for tumor diagnosis and treatment. At present, small-molecule radiotracer targeting FAP with high specificity exhibit limited functionality, which hinders the integration of theranostics as well as multifunctionality. In this work, we have engineered a multifunctional nanoplatform utilizing organic melanin nanoparticles that specifically targets FAP, facilitating both multimodal imaging and synergistic therapeutic applications. This nanoplatform can perform positron emission tomography (PET), magnetic resonance imaging (MRI) and photoacoustic imaging (PAI) with strong near infrared absorption and metal chelating ability, achieving efficiently targeting accumulation and display long retention in the tumor region. Meanwhile, 131I-labeled nanoplatform for targeted radioisotope therapy (TRT) and photothermal therapy (PTT) were significantly suppressed tumor growth in glioblastoma xenograft models without obvious side effects. These results demonstrated that this novel nanoparticles-based theranostics nanoplatform can effectively enhance multimodal imaging and targeted radionuclide-photothermal synergistic therapy for solid tumors with FAP expression.

The integration of near-infrared genetically encoded reporters (NIR-GERs) with photoacoustic (PA) imaging enables visualizing deep-seated functions of specific cell populations at high resolution, though the imaging depth is primarily constrained by reporters' PA response intensity. Directed evolution can optimize NIR-GERs' performance for PA imaging, yet precise quantifying of PA responses in mutant proteins expressed in E. coli colonies across iterative rounds poses challenges to the imaging speed and quantification capabilities of the screening platforms. Here, we present self-calibrated photoacoustic screening (SCAPAS), an imaging-based platform that can detect samples in parallel within 5 s (equivalent to 50 ms per colony), achieving a considerable quantification accuracy of approximately 2.8% and a quantification precision of about 6.47%. SCAPAS incorporates co-expressed reference proteins in sample preparation and employs a ring transducer array with switchable illumination for rapid, wide-field dual-wavelength PA imaging, enabling precisely calculating the PA response using the self-calibration method. Numerical simulations validated the image optimization strategy, quantification process, and noise robustness. Tests with co-expression samples confirmed SCAPAS's superior screening speed and quantification capabilities. We believe that SCAPAS will facilitate the development of novel NIR-GERs suitable for PA imaging and has the potential to significantly impact the advancement of PA probes and molecular imaging. (c) 2025 Chinese Laser Press

This article reviews the latest developments in electrochemiluminescence microscopy (ECLM) technology, which combines electrochemical input and optical output, and features low background noise, high controllability, as well as high spatial resolution. Through various adjustment strategies such as temperature regulation, ultrasonic enhancement, electro field regulation, and optical regulation, researchers have achieved precise control of ECL signals, thus improving the measurement sensitivity of ECLM. These technologies provide new strategies and tools for biological imaging, clinical testing, and nanomaterial analysis. For example, efficient ECL emission and direct modulation of ECL intensity at low potentials were achieved through a metal-insulator-semiconductor structure or an external magnetic field. In addition, the application of aggregation-induced luminescence effect demonstrates the potential of ECLM in improving the specificity of sensors and solving aggregation quenching problems. Despite the challenges, continuous innovation of ECLM technology is expected to bring wider applications in the biomedical field.

Anisotropy in imaging systems often results in directional degradation, impairing image quality and complicating subsequent analyses. While multiangle imaging has proven effective in mitigating these effects, it introduces challenges such as extended imaging times and increased excitation doses. To address these limitations in Photoacoustic Tomography (PAT), we propose a novel approach—Diffusion-based Sparse Tomographic Angular Recovery (D-STAR). D-STAR significantly reduces the number of required angles for high-resolution PAT while maintaining image quality comparable to full tomographic angular imaging. By training a diffusion model on a custom 3D PAT dataset, we optimize the balance between spatial and temporal resolutions, signal-to-noise ratio (SNR), and laser exposure. Our experiments with excised brain and vessel phantoms demonstrate that D-STAR produces high-fidelity images suitable for both structural and molecular imaging. This method outperforms existing approaches in static structural recovery and quantitative data extraction, offering substantial improvements in imaging quality, particularly in resolution and contrast. Furthermore, D-STAR enhances flexibility in imaging system design, reducing the need for hardware upgrades while improving temporal resolution and minimizing laser exposure.

Significance:Myocardial oxygen metabolism is a key focus of cardiac surgery. It serves as important evidence for surgeons to evaluate surgical quality and surgical plans. However, current clinical methods lack the capability to directly monitor dynamic changes in myocardial metabolism during surgery. Photoacoustic imaging (PAI), a biomedical optical imaging modality, offers real-time assessment of blood oxygen saturation. By visualizing oxygen saturation levels in both blood and muscle tissue, PAI provides a means to infer myocardial metabolic status intraoperatively. Aim:We use PAI to observe the differences between infarcted myocardium and normal cardiac muscle and to explore the feasibility of using PAI to monitor myocardial metabolism levels during cardiac surgery. Approach:Ten rabbits were randomly divided into experimental and control groups. The animals in the experimental group underwent thoracotomy followed by left anterior descending coronary artery ligation, whereas those in the control group received thoracotomy only. PAI was performed both at the beginning and before the end of the surgical procedure. The PAI results were compared between the two groups to analyze the relationship between myocardial PAI signal changes and oxygen metabolism levels. Results:Following coronary ligation, the experimental group exhibited significant ST-segment elevation on electrocardiography, whereas no notable changes were observed in controls. PAI demonstrated: baseline myocardial oxygen saturation ( SmO 2 ) ranged from 45% to 72% across all rabbits. Ligation-induced ischemia sharply reduced SmO 2 to 1% to 19% in experimental animals. Control animals maintained stable SmO 2 levels throughout the procedure. Histopathological examination confirmed extensive myocardial necrosis in the apical region of ligated rabbits, consistent with the observed functional and metabolic alterations. Conclusions:PAI can detect myocardial oxygen saturation in real-time during surgery and determine the occurrence of myocardial ischemia and changes in oxygen metabolism levels based on differences in oxygen saturation.