SERS-based long-term mitochondrial pH monitoring during differentiation of human induced pluripotent stem cells to neural progenitor cells.

As one of the important organelles in the process of cell differentiation, mitochondria regulate the whole process of differentiation by participating in energy supply and information transmission. Mitochondrial pH value is a key indicator of mitochondrial function. Therefore, real-time monitoring of mitochondrial pH value during cell differentiation is of great significance for understanding cell biochemical processes and exploring differentiation mechanisms. In this study, Surface-enhanced Raman scattering (SERS) technology was used to achieve the real-time monitoring of mitochondrial pH during induced pluripotent stem cells (iPSCs) differentiation into neural progenitor cells (NPCs). The results showed that the variation trend of mitochondrial pH in normal and abnormal differentiated batches was different. The mitochondrial pH value of normal differentiated cells continued to decline from iPSCs to embryoid bodies (EB) day 4, and continued to rise from EB day 4 to the NPCs stage, and the mitochondrial microenvironment of iPSCs to NPCs differentiation became acidic. In contrast, the mitochondrial pH value of abnormally differentiated cells declined continuously during differentiation. This study improves the information on acid-base balance during cell differentiation and may provide a basis for further understanding of the changes and regulatory mechanisms of mitochondrial metabolism during cell differentiation. This also helps to improve more accurate and useful differentiation protocols based on the microenvironment within the mitochondria, improving the efficiency of cell differentiation.

DHM/SERS reveals cellular morphology and molecular changes during iPSCs-derived activation of astrocytes.

The activation of astrocytes derived from induced pluripotent stem cells (iPSCs) is of great significance in neuroscience research, and it is crucial to obtain both cellular morphology and biomolecular information non-destructively in situ, which is still complicated by the traditional optical microscopy and biochemical methods such as immunofluorescence and western blot. In this study, we combined digital holographic microscopy (DHM) and surface-enhanced Raman scattering (SERS) to investigate the activation characteristics of iPSCs-derived astrocytes. It was found that the projected area of activated astrocytes decreased by 67%, while the cell dry mass increased by 23%, and the cells changed from a flat polygonal shape to an elongated star-shaped morphology. SERS analysis further revealed an increase in the intensities of protein spectral peaks (phenylalanine 1001 cm-1, proline 1043 cm-1, etc.) and lipid-related peaks (phosphatidylserine 524 cm-1, triglycerides 1264 cm-1, etc.) decreased in intensity. Principal component analysis-linear discriminant analysis (PCA-LDA) modeling based on spectral data distinguished resting and reactive astrocytes with a high accuracy of 96.5%. The increase in dry mass correlated with the increase in protein content, while the decrease in projected area indicated the adjustment of lipid composition and cell membrane remodeling. Importantly, the results not only reveal the cellular morphology and molecular changes during iPSCs-derived astrocytes activation but also reflect their mapping relationship, thereby providing new insights into diagnosing and treating neurodegenerative diseases.

Prognostic significance of alterations in fibrinogen level and fibrinogen-to-lymphocyte ratio after radiotherapy on survival outcomes in glioblastoma.

Background: Fibrinogen (FIB) plays an important role in tumor initiation, progression, and metastasis, but its clinical significance in glioblastoma has not been studied. We intend to explore the prognostic value by retrospectively analyzing the changes in FIB and fibrinogen-to-lymphocyte ratio (FLR) in glioblastoma patients before and after radiotherapy, and study the impact of radiotherapy on them. Methods: This study retrospectively included 104 patients who were newly diagnosed with glioblastoma between February 2017 and February 2022 and analysed their clinical data from before to after radiotherapy. The cut-off values for FLR and FIB were calculated using a receiver operating characteristic curve. For inter-group comparisons, the Mann-Whitney U or t-test was applied. The prognostic importance of FIB and FLR was evaluated using the Kaplan-Meier curve and the Cox regression model. Spearman correlation coefficients were calculated to evaluate the association of FIB and FLR with radiotherapy-related dose-volume parameters. Results: The mean progression-free survival (PFS) and overall survival (OS) of the high FIB and high FLR groups were significantly lower than those of the low FIB and low FLR groups (P<0.05). Larger planning target volume (PTV), mean brain dose, and mean brainstem dose were independent prognostic factors for poor PFS and OS in patients with glioblastoma. Conclusions: FLR was a unique and very accurate predictor for the prognosis of glioblastoma, and FIB rise after radiation was a predictive sign of poor survival. Both PTV volume and dose volume for involved organs could significantly affect the FIB and FLR values in patients with glioblastoma.

A novel immune cell signature for predicting glioblastoma after radiotherapy prognosis and guiding therapy.

Background: Glioblastoma, a highly aggressive brain tumor, poses a significant clinical challenge, particularly in the context of radiotherapy. In this study, we aimed to explore infiltrating immune cells and identify immune-related genes associated with glioblastoma radiotherapy prognosis. Subsequently, we constructed a signature based on these genes to discern differences in molecular and tumor microenvironment immune characteristics, ultimately informing potential therapeutic strategies for patients with varying risk profiles. Methods: We leveraged UCSC Xena and CGGA gene expression profiles from post-radiotherapy glioblastoma as verification cohorts. Infiltration ratios were stratified into high and low groups based on the median value. Differential gene expression was determined through Limma differential analysis. A signature comprising four genes was constructed, guided by Gene Ontology (GO) functional enrichment results and Kaplan-Meier survival analysis. We evaluated differences in cell infiltration levels, Immune Score, Stromal Score, and ESTIMATE Score and their Pearson correlations with the signature. Spearman's correlation was computed between the signature and patient drug sensitivity (IC50), predicted using Genomics of Drug Sensitivity in Cancer (GDSC) and CCLE databases. Results: Notably, the infiltration of central memory CD8+T cells exhibited a significant correlation with glioblastoma radiotherapy prognosis. Samples were dichotomized into high- and low-risk groups based on the optimal signature threshold (2.466642). Kaplan-Meier (K-M) survival analysis revealed that the high-risk group experienced a significantly poorer prognosis (p = .0068), with AUC values exceeding 0.82 at 1, 3, and 5 years, underscoring the robust predictive potential of the signature scoring system. Independent validation sets substantiated the validity of the signature. Statistically significant differences in tumor microenvironments (p < .05) were observed between high- and low-risk groups, and these differences were significantly correlated with the signature (p < .05). Furthermore, there were significant correlations between high and low-risk groups regarding immune checkpoint expressions, Immune Prognostic Score (IPS), and Tumor Immune Dysfunction and Exclusion (TIDE) scores. Conclusion: The immune cell signature, comprising SDC-1, PLAUR, FN1, and CXCL13, holds promise as a predictive tool for assessing glioblastoma prognosis following radiotherapy. This signature also offers valuable guidance for tailoring treatment strategies, emphasizing its potential clinical relevance in improving patient outcomes.

Fresnel incoherent compressive holography toward 3D videography via dual-channel simultaneous phase-shifting interferometry.

Fresnel incoherent correlation holography (FINCH) enables high-resolution 3D imaging of objects from several 2D holograms under incoherent light and has many attractive applications in motionless 3D fluorescence imaging. However, FINCH has difficulty implementing 3D imaging of dynamic scenes since multiple phase-shifting holograms need to be recorded for removing the bias term and twin image in the reconstructed scene, which requires the object to remain static during this progress. Here, we propose a dual-channel Fresnel noncoherent compressive holography method. First, a pair of holograms with π phase shifts obtained in a single shot are used for removing the bias term noise. Then, a physic-driven compressive sensing (CS) algorithm is used to achieve twin-image-free reconstruction. In addition, we analyze the reconstruction effect and suitability of the CS algorithm and two-step phase-shift filtering algorithm for objects with different complexities. The experimental results show that the proposed method can record hologram videos of 3D dynamic objects and scenes without sacrificing the imaging field of view or resolution. Moreover, the system refocuses images at arbitrary depth positions via computation, hence providing a new method for fast high-throughput incoherent 3D imaging.

Convenient dual-wavelength digital holography based on orthogonal polarization strategy with a Wollaston prism.

Dual-wavelength digital holography effectively expands the measurement range of digital holography, but it increases the complexity of optical system due to non-common-path of two wavelengths. Here, by using orthogonal polarization strategy, we present a dual-wavelength digital holography based on a Wollaston prism (DWDH-WP) to separate the reference beams of two wavelengths and realize the common-path of two wavelengths. A Wollaston prism is inset into the reference beam path of the off-axis digital holography system, so two orthogonal-polarized reference beams of two different wavelengths separated at different directions are generated. Then a dual-wavelength multiplexed interferogram with orthogonal interference fringes is captured by using a monochrome camera, in which both the polarization orientations and the interference fringe orientations of two wavelengths are orthogonal, so the spectral crosstalk of two wavelengths with arbitrary wavelength difference can be avoided. Compared with the existing DWDH method, the proposed DWDH-WP method can conveniently realize the common-path of the reference beams of two wavelengths, so it reveals obvious advantages in spectral separation, spectral crosstalk, system simplification, and adjustment flexibility. Both effectiveness and flexibility of the proposed DWDH-WP method are demonstrated by the phase measurement of the HeLa cell and vortex phase plate.

Adaptive phase-shifting interferometry based on a phase-shifting digital holography algorithm.

Phase-shifting interferometry (PSI) requires accurate phase shifts between interferograms for realizing high-accuracy phase retrieval. This paper presents an adaptive PSI through synchronously capturing phase shifts measurement interferograms and phase measurement interferograms, in which the former is a series of spatial carrier frequency phase-shifting interferograms generated by an additional assembly and the phase shifts are calculated with the single-spectrum phase shifts measurement algorithm (SS-PSMA), the latter is employed for phase retrieval with an adaptive phase-shifting digital holography algorithm (PSDHA) based on complex amplitude recovery. In addition to exhibiting excellent reliability, high-accuracy phase retrieval (0.02 rad), and short calculation time (<25 ms), the proposed adaptive PSDHA is suitable for various interferograms with different fringe shapes and numbers. Importantly, both simulation analysis and experimental result demonstrate that this adaptive PSI based on PSDHA can effectively eliminate phase-shifting errors caused by phase shifter and external disturbance, ensuring high-accuracy phase shifts measurement and phase retrieval, meanwhile significantly reducing phase-shifting interferograms acquisition time and phase retrieval calculation time.

Polar optical flow network: extracting overlapped holograms of dynamic particles.

Digital holography with lensless in-line setup has been extensively used in particle field measurements. As particle concentration increases, the holograms of dynamic particles locating at different depths tend to superpose with each other with incoherent overlap, hampering effective measurement of individual particles with incomplete information. Drawing inspiration from suborbicular nature of the in-line holographic fringes, in this study, we propose an optical flow method in polar coordinates to mitigate the overlap issue. The approach employs a radial transformer-enhanced network that leverages both the radial and angular characteristics of the polar hologram. Through ablation tests and experimental results, we have demonstrated the effectiveness and superiority of our proposed method.

Tracking intracellular nuclear targeted-chemotherapy of chidamide-loaded Prussian blue nanocarriers by SERS mapping.

The novel histone deacetylase drug chidamide (CHI) has been proven to regulate gene expression associated with oncogenesis via epigenetic mechanisms. However, huge side effects such as non-targeting, poor intracellular accumulation and low nuclear entry efficiency severely restrict its therapeutic efficacy. Dual-targeted nanodrug delivery systems have been proposed as the solution. Herein, we developed a CHI-loaded drug delivery nanosystem based on Prussian blue (PB) nanocarrier, which combines surface-enhanced Raman scattering (SERS) tracking function with cancer cell/nuclear-targeted chemotherapy capability. With the property of background-free SERS mapping, PB nanocarriers can serve as tracking agents to localize intracellular CHI. The incorporation of targeted molecules specifically enhances the cancer cell/nuclear internalization and chemotherapeutic effects of CHI-loaded PB nanocarriers. In vitro cytotoxicity assay clearly shows that the constructed CHI-loaded PB nanocarriers have significant inhibitory on Jurkat cell proliferation. Furthermore, SERS spectral analysis of Jurkat cells incubated with the CHI-loaded PB nanocarriers reveals obvious features of cellular apoptosis: DNA skeleton fragmentation, chromatin depolymerization, histone acetylation, and nucleosome conformation change. Importantly, this CHI-loaded PB nanocarrier will provide a new insight for lymphoblastic leukemia targeted chemotherapy.

Real-time phase imaging with physics-enhanced network and equivariance.

Learning-based phase imaging balances high fidelity and speed. However, supervised training requires unmistakable and large-scale datasets, which are often hard or impossible to obtain. Here, we propose an architecture for real-time phase imaging based on physics-enhanced network and equivariance (PEPI). The measurement consistency and equivariant consistency of physical diffraction images are used to optimize the network parameters and invert the process from a single diffraction pattern. In addition, we propose a regularization method based total variation kernel (TV-K) function constraint to output more texture details and high-frequency information. The results show that PEPI can produce the object phase quickly and accurately, and the proposed learning strategy performs closely to the fully supervised method in the evaluation function. Moreover, the PEPI solution can handle high-frequency details better than the fully supervised method. The reconstruction results validate the robustness and generalization ability of the proposed method. Specially, our results show that PEPI leads to considerable performance improvement on the imaging inverse problem, thereby paving the way for high-precision unsupervised phase imaging.

Single-shot Fresnel incoherent correlation holography via deep learning based phase-shifting technology.

Fresnel incoherent correlation holography (FINCH) realizes non-scanning three-dimension (3D) images using spatial incoherent illumination, but it requires phase-shifting technology to remove the disturbance of the DC term and twin term that appears in the reconstruction field, thus increasing the complexity of the experiment and limits the real-time performance of FINCH. Here, we propose a single-shot Fresnel incoherent correlation holography via deep learning based phase-shifting (FINCH/DLPS) method to realize rapid and high-precision image reconstruction using only a collected interferogram. A phase-shifting network is designed to implement the phase-shifting operation of FINCH. The trained network can conveniently predict two interferograms with the phase shift of 2/3 π and 4/3 π from one input interferogram. Using the conventional three-step phase-shifting algorithm, we can conveniently remove the DC term and twin term of the FINCH reconstruction and obtain high-precision reconstruction through the back propagation algorithm. The Mixed National Institute of Standards and Technology (MNIST) dataset is used to verify the feasibility of the proposed method through experiments. In the test with the MNIST dataset, the reconstruction results demonstrate that in addition to high-precision reconstruction, the proposed FINCH/DLPS method also can effectively retain the 3D information by calibrating the back propagation distance in the case of reducing the complexity of the experiment, further indicating the feasibility and superiority of the proposed FINCH/DLPS method.

Clinical study on changes of peripheral blood immune function indicators in adults with newly diagnosed glioblastoma during the peri-radiotherapy period.

To analyze the changes of immune function-related indicators with newly diagnosed glioblastoma before and after radiotherapy and their clinical significance. Clinical data of 104 patients were analyzed. The independent samples t-test or chi-square test was used to compare changes in immune function indicators and to ascertain the differences between groups with different doses or volumes. The grading of the lowest lymphocyte count during radiotherapy was compared. The log-rank (Mantel - Cox) test of the Kaplan - Meier method was used to compare the survival rate, and the relationship of radiotherapy-related parameters, with the survival rate was evaluated by using the Spearman correlation coefficient. A Cox regression model was used to determine the relationship between various immune function indicators and prognosis. The percentages of total T lymphocytes and CD4+ T cells, the CD4-to-CD8 subset ratio, and the percentages of B cells and NKT cells showed an overall decreasing trend, whereas the percentages of CD8+ T cells and NK cells displayed an overall increasing trend. The lower CD4+ T cell percentage and CD4/CD8 ratio after radiotherapy were independent risk factors for OS. Short OS was observed in patients with grade 3 or 4 lymphopenia or with low levels of hemoglobin and serum albumin before radiotherapy. The percentage of CD4+ T cells and the CD4/CD8 ratio were higher in patients with the low tumor-irradiated volume and irradiated volume and dose of the OAR, than in patients from the corresponding high indicator group. Different irradiation dose or volume can differentially alter various immune function indicators.

A SERS-Based Dual-Parameter Monitoring Nanoprobe of ROS and PI3K/Akt during Ginsenoside Rg3-Induced Cell Apoptosis.

Both the reactive oxygen species (ROS) level and Phosphatidylinositol 3 Kinase (PI3K) protein content are two crucial parameters for characterizing states of cell apoptosis. Current methods measure these parameters with two different techniques, respectively, which usually lead to evaluation contingency. Ginsenoside Rg3 exhibits an excellent anticancer effect, which is enacted by the Phosphatidylinositol 3 Kinase/Protein Kinase B (PI3K/Akt) pathway involving ROS; however, the precise mechanism that induces cell apoptosis remains unknown. This is due to the lack of information on quantitative intracellular ROS and PI3K. Here, we used a surface-enhanced Raman scattering (SERS)-based boric acid nanoprobe to monitor the intracellular ROS level and phosphatidylinositol-3,4,5-triphosphate (PI(3,4,5)P3) content, which reflects the regulatory effect of the PI3K/Akt pathway. After treatment with ginsenoside Rg3, the PI3K/Akt content first increased and then decreased as the ROS level increased. Moreover, when the ROS level significantly increased, the mitochondrial membrane potential reduced, thus indicating the dynamic regulation effect of intracellular ROS level on the PI3K/Akt pathway. Importantly, in addition to avoiding evaluation contingency, which is caused by measuring the aforementioned parameters with two different techniques, this SERS-based dual-parameter monitoring nanoprobe provides an effective solution for simultaneous ROS level and PI3K content measurements during cell apoptosis. Furthermore, the intracellular ROS level was also able to have a dynamic regulatory effect on the PI3K/Akt pathway, which is essential for studying ROS/PI3K/Akt-pathway-related cell apoptosis and its activation mechanism.

SERS-based error calibration of a TMB-H2O2 colorimetric system.

3,3',5,5'-tetramethylbenzidine (TMB)-H2O2 is widely used as an effective colorimetric system, in which the color reaction is implemented with peroxidase-catalyzed TMB oxidation by H2O2 that usually measured UV-vis absorption spectra or Raman spectra. However, its low accuracy significantly limits its application. Blue charge transfer complex (CTC), which is the product of TMB and H2O2 reaction and is used as the basis for partial colorimetric methods, usually causes colorimetric error owing to changes in the UV-vis absorption and Raman spectra during TMB oxidation under various environmental conditions (catalyst type, temperature, H2O2 concentration). Herein, we propose a surface-enhanced Raman spectrum (SERS)-based error calibration method to improve the accuracy of the TMB-H2O2 colorimetric system. It is found that under 633 nm laser excitation, TMB has three Raman peaks at 1189, 1335 and 1609 cm-1 in the single-electron oxidation phase, and these peaks disappear completely in the two-electron oxidation phase. By comparing these Raman peaks, we can conveniently obtain the actual process information during TMB oxidation. Using the proposed method, the accuracy of the TMB-H2O2 colorimetric system improved by more than 15%. Importantly, this SERS-based TMB-H2O2 error calibration method will open a new horizon for enzyme-linked immunosorbent assay (ELISA) and other biomedical applications.

Accurate identification of living Bacillus spores using laser tweezers Raman spectroscopy and deep learning.

Accurately, rapidly, and noninvasively identifying Bacillus spores can greatly contribute to controlling a plenty of infectious diseases. Laser tweezers Raman spectroscopy (LTRS) has confirmed to be a powerful tool for studying Bacillus spores at a single cell level. In this study, we constructed a single-cell Raman spectra dataset of living Bacillus spores and utilized deep learning approach to accurately, nondestructively identify Bacillus spores. The trained convolutional neural network (CNN) could efficiently extract tiny Raman spectra features of five spore species, and provide a prediction accuracy of specie identification as high as 100 %. Moreover, the spectral feature differences in three Raman bands at 660, 826, and 1017 cm-1 were confirmed to mostly contribute to producing such high prediction accuracy. In addition, optimal CNN model was employed to monitor and identify sporulation process at different metabolic phases in one growth cycle. The obtained average prediction accuracy of metabolic phase identification was approximately 88 %. It can be foreseen that, LTRS combined with CNN approach have great potential for accurately identifying spore species and metabolic phases at a single cell level, and can be gradually extended to perform identification for many unculturable bacteria growing in soil, water, and food.

Diffraction-Net: a robust single-shot holography for multi-distance lensless imaging.

Digital holography based on lensless imaging is a developing method adopted in microscopy and micro-scale measurement. To retrieve complex-amplitude on the sample surface, multiple images are required for common reconstruction methods. A promising single-shot approach points to deep learning, which has been used in lensless imaging but suffering from the unsatisfied generalization ability and stability. Here, we propose and construct a diffraction network (Diff-Net) to connect diffraction images at different distances, which breaks through the limitations of physical devices. The Diff-Net based single-shot holography is robust as there is no practical errors between the multiple images. An iterative complex-amplitude retrieval approach based on light transfer function through the Diff-Net generated multiple images is used for complex-amplitude recovery. This process indicates a hybrid-driven method including both physical model and deep learning, and the experimental results demonstrate that the Diff-Net possesses qualified generalization ability for samples with significantly different morphologies.

Quantitative phase imaging based on model transfer learning.

Convolutional neural networks have been widely used in optical information processing and the generalization ability of the network depends greatly on the scale and diversity of the datasets, however, the acquisition of mass datasets and later annotation have become a common problem that hinders its further progress. In this study, a model transfer-based quantitative phase imaging (QPI) method is proposed, which fine-tunes the network parameters through loading pre-training base model and transfer learning, enable the network with good generalization ability. Most importantly, a feature fusion method based on moment reconstruction is proposed for training dataset generation, which can construct rich enough datasets that can cover most situations and accurately annotated, it fundamentally solves the problem from the scale and representational ability of the datasets. Besides, a feature distribution distance scoring (FDDS) rule is proposed to evaluate the rationality of the constructed datasets. The experimental results show that this method is suitable for different types of samples to achieve fast and high-accuracy phase imaging, which greatly relieves the pressure of data, tagging and generalization ability in the data-driven method.

Differential phase measurement based on synchronous phase shift determination.

Based on synchronous phase shift determination, we propose a differential phase measurement method for differential interference contrast (DIC) microscopy. An on-line phase shift measurement device is used to generate carrier interferograms and determine the phase shift of DIC images. Then the differential phase can be extracted with the least-squares phase-shifting algorithm. In addition to realizing on-line, dynamic, real-time, synchronous and high precision phase shift measurement, the proposed method also can reconstruct the phase of the specimen by using the phase-integral algorithm. The differential phase measurement method reveals obvious advantages in error compensation, anti-interference, and noise suppression. Both simulation analysis and experimental result demonstrate that using the proposed method, the accuracy of phase shift measurement is higher than 0.007 rad. Very accurate phase reconstructions were obtained with both polystyrene microspheres and human vascular endothelial.

Clinical characteristics, treatment and outcomes of acute postpartum inflammatory sacroiliitis: a retrospective study.

PURPOSE: We performed this research to report the clinical characteristics and clinical therapeutic strategies of acute postpartum inflammatory sacroiliitis. METHODS: We retrospectively analyzed the data of patients diagnosed with acute postpartum inflammatory sacroiliitis from 2014 to 2020. All their clinical details including clinical symptoms and signs, laboratory tests, radiologic examination, diagnosis and treatment process and clinical outcomes were obtained and analyzed in this retrospective analysis. RESULTS: Eleven patients diagnosed with acute postpartum inflammatory sacroiliitis complain of low back pain. Magnetic resonance imaging (MRI) is useful in diagnosing acute postpartum inflammatory sacroiliitis. The systemic non-steroidal anti-inflammatory drugs (NSAIDs) administration, sacroiliac joint injection, and physical therapy effectively alleviated the pain with symptoms disappearing, and the abnormal signal reduced in MRI. CONCLUSION: Acute postpartum inflammatory sacroiliitis is an uncommon disease with atypical symptoms. MRI examination may be the best diagnostic method. General NSAIDs and sacroiliac joint injections of local anesthetic plus corticosteroid under the guidance of fluoroscopy or ultrasound can achieve safe and effective treatment. This retrospective study was approved by the Committee on the Ethics of our hospital (No. 202101023). TRIAL REGISTRY: Trial registration was performed in the Chinese Clinical Trial Registry ( http://www.chictr.org.cn , No. ChiCTR2100045656).

Bovine Milk Exosomes Alleviate Cardiac Fibrosis via Enhancing Angiogenesis In Vivo and In Vitro.

Cardiac fibrosis is a difficult clinical puzzle without effective therapy. Exosomes play an important role in alleviating cardiac fibrosis via angiogenesis. This research aimed to assess the effect of bovine milk on cardiac fibrosis. The proangiogenic effect of bovine milk exosomes was analyzed both in isoproterenol (ISO)-induced cardiac fibrosis rats in vivo and in human umbilical vein endothelial cells (HUVECs) after oxygen and glucose deprivation (OGD) in vitro. Results indicated that bovine milk exosomes alleviated the extracellular matrix (ECM) deposition and enhanced the cardiac function in cardiac fibrosis rat. The proangiogenic growth factors were significantly enhanced in rats accepted bovine milk exosomes. Meanwhile, bovine milk exosomes ameliorated the motility, migration, and tube-forming ability of HUVECs after OGD in vitro. Bovine milk exosomes alleviate cardiac fibrosis and enhance cardiac function in cardiac fibrosis rats via enhancing angiogenesis. Bovine milk exosomes may represent a potential strategy for the treatment of cardiac fibrosis.