Hygroscopic cooling (h-cool) fabric with highly efficient sweat evaporation and heat dissipation for personal thermo-moisture management.

Moisture evaporation plays a crucial role in thermal management of human body, particularly in perspiration process. However, current fabrics aim for sweat removal and takes little account of basic thermo-regulation of sweat, resulted in their limited evaporation capacity and heat dissipation at moderate/intense scenarios. In this study, a hygroscopic cooling (h-cool) fabric based on multi-functional design, for personal perspiration management, was described. By using economic and effective weaving technology, directional moisture transport routes and heat conductive pathways were incorporated in the construct. The resultant fabric showed 10 times greater one-way transport index higher than cotton, Dri-FIT and Coolswitch fabrics, which contributed to highly enhanced evaporation ability (∼4.5 times than cotton), not merely liquid diffusion. As a result, h-cool fabric performed 2.1-4.2 °C cooling efficacy with significantly reduced sweat consuming than cotton, Dri-FIT and Coolswitch fabrics in the artificial sweating skin. Finally, the practical applications by actually wearing h-cool fabric showed great evaporative-cooling efficacy during different physical activities. Owing to the excellent thermo-moisture management ability, we expect the novel concept and construct of h-cool fabric can provide promising strategy for developing functional textiles with great "cool" and comfortable "dry" tactile sensation at various daily scenarios.

Serum alpha 1 antitrypsin potent act as an early diagnostic biomarker for cardiac amyloidosis.

Cardiac amyloidosis is a refractory cardiomyopathy with a poor prognosis and lacks effective treatments. N-terminal pro-brain natriuretic peptide (NT-proBNP) and troponin T are poor prognostic factors for myocardial amyloidosis. However, NT-proBNP and troponin also serve as markers of heart failure and myocardial infarction, lacking specificity. Whether abnormal elevation of alpha-1 antitrypsin in myocardial amyloidosis also predicts the poor prognosis of patients remains unknown. We conducted a retrospective single-center case-control study to analyze the serological and physical examination data of 83 cardiac amyloidosis patients and 68 healthy controls matched by gender and age. We aimed to explore the onset and prognostic factors of cardiac amyloidosis. The serum alpha-1 antitrypsin level (169.78 ± 39.59 mg/dl) in patients with cardiac amyloidosis was significantly higher than that in the normal control (125.92 ± 18.26 mg/dl). Logistic regression results showed that alpha-1 antitrypsin, free sialic acid, high-density lipoprotein cholesterol, apolipoprotein A/B ratio, and homocysteine were predictors of cardiac amyloidosis. Multivariable logistic regression showed that only alpha 1 antitrypsin was an independent risk factor for cardiac amyloidosis. Receiver operating characteristic curve analysis based on the Mayo stage and troponin level showed the cut-off value of 140.55 mg/dl for alpha-1 antitrypsin in predicting cardiac amyloidosis with 81.7% sensitivity and 83.9% specificity. Elevated alpha-1 antitrypsin levels may be an early diagnostic biomarker for cardiac amyloidosis.

Degradation of Photopic and Mesopic Contrast Sensitivity Function in High Myopes With Partial Posterior Vitreous Detachment.

Purpose: The purpose of this study was to evaluate the effects of posterior vitreous detachment (PVD) on visual quality in patients with high myopia, as well as investigate the associated factors of photopic and mesopic contrast sensitivity function (CSF) in high myopia. Methods: Visual quality was comprehensively assessed in patients with high myopia. Visual acuity, contrast sensitivity (CS) at four spatial frequencies (3, 6, 12, and 18 cycles per degree [c.p.d.]) under photopic and mesopic conditions, as well as the modulation transfer function cutoff value (MTFcutoff), the objective scatter index (OSI), the Strehl ratio (SR), and internal aberrations, were measured in this cross-sectional study. Results: This study included 94 eyes from 47 subjects with bilateral high myopia, including 23 eyes with complete PVD (cPVD), 21 eyes with partial PVD (pPVD), and 50 eyes without PVD (nPVD). There was no significant difference in visual quality between the cPVD group and the nPVD group. Whereas in eyes with pPVD, there was a degradation of overall photopic CSF (versus nPVD, P = 0.048), photopic CS at 3 c.p.d. (versus cPVD, P = 0.009 and versus nPVD, P = 0.032), photopic CS at 18 c.p.d. (versus nPVD, P = 0.033), overall mesopic CSF (versus nPVD, P = 0.033), and secondary astigmatism (versus cPVD, P = 0.044). Under photopic conditions, the factors affecting CSF were pPVD and SR, whereas the factors affecting mesopic CSF were pPVD, OSI, and ganglion cell-inner plexiform layer thickness. Conclusions: The pPVD impaired visual quality in patients with high myopia compared to nPVD or cPVD, and pPVD could be a factor explaining CSF at both photopic and mesopic illumination. Translational Relevance: Clinicians need to closely monitor patients with high myopia with pPVD due to the potential decline in visual quality and the development of vitreoretinal disorders.

Controlled Synthesis of Unconventional Phase Alloy Nanobranches for Highly Selective Electrocatalytic Nitrite Reduction to Ammonia.

The controlled synthesis of metal nanomaterials with unconventional phases is of significant importance to develop high-performance catalysts for various applications. However, it remains challenging to modulate the atomic arrangements of metal nanomaterials, especially the alloy nanostructures that involve different metals with distinct redox potentials. Here we report the general one-pot synthesis of IrNi, IrRhNi and IrFeNi alloy nanobranches with unconventional hexagonal close-packed (hcp) phase. Notably, the as-synthesized hcp IrNi nanobranches demonstrate excellent catalytic performance towards electrochemical nitrite reduction (NO2RR), with superior NH3 Faradaic efficiency and yield rate of 98.2% and 34.6 mg h-1 mgcat-1 (75.5 mg h-1 mgIr-1) at 0 and -0.1 V (vs reversible hydrogen electrode), respectively. Ex/in-situ characterizations and theoretical calculations reveal that the Ir-Ni interactions within hcp IrNi alloy improve electron transfer to benefit both nitrite activation and active hydrogen generation, leading to a stronger reaction trend of NO2RR by greatly reducing energy barriers of rate-determining step.

Individualized prediction of anxiety and depressive symptoms using gray matter volume in a non-clinical population.

Machine learning is an emerging tool in clinical psychology and neuroscience for the individualized prediction of psychiatric symptoms. However, its application in non-clinical populations is still in its infancy. Given the widespread morphological changes observed in psychiatric disorders, our study applies five supervised machine learning regression algorithms-ridge regression, support vector regression, partial least squares regression, least absolute shrinkage and selection operator regression, and Elastic-Net regression-to predict anxiety and depressive symptom scores. We base these predictions on the whole-brain gray matter volume in a large non-clinical sample (n = 425). Our results demonstrate that machine learning algorithms can effectively predict individual variability in anxiety and depressive symptoms, as measured by the Mood and Anxiety Symptoms Questionnaire. The most discriminative features contributing to the prediction models were primarily located in the prefrontal-parietal, temporal, visual, and sub-cortical regions (e.g. amygdala, hippocampus, and putamen). These regions showed distinct patterns for anxious arousal and high positive affect in three of the five models (partial least squares regression, support vector regression, and ridge regression). Importantly, these predictions were consistent across genders and robust to demographic variability (e.g. age, parental education, etc.). Our findings offer critical insights into the distinct brain morphological patterns underlying specific components of anxiety and depressive symptoms, supporting the existing tripartite theory from a neuroimaging perspective.

1T'-transition metal dichalcogenide monolayers stabilized on 4H-Au nanowires for ultrasensitive SERS detection.

Unconventional 1T'-phase transition metal dichalcogenides (TMDs) have aroused tremendous research interest due to their unique phase-dependent physicochemical properties and applications. However, due to the metastable nature of 1T'-TMDs, the controlled synthesis of 1T'-TMD monolayers (MLs) with high phase purity and stability still remains a challenge. Here we report that 4H-Au nanowires (NWs), when used as templates, can induce the quasi-epitaxial growth of high-phase-purity and stable 1T'-TMD MLs, including WS2, WSe2, MoS2 and MoSe2, via a facile and rapid wet-chemical method. The as-synthesized 4H-Au@1T'-TMD core-shell NWs can be used for ultrasensitive surface-enhanced Raman scattering (SERS) detection. For instance, the 4H-Au@1T'-WS2 NWs have achieved attomole-level SERS detections of Rhodamine 6G and a variety of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins. This work provides insights into the preparation of high-phase-purity and stable 1T'-TMD MLs on metal substrates or templates, showing great potential in various promising applications.

Non-Fluorinated Ethers to Mitigate Electrode Surface Reactivity in High-Voltage NCM811-Li Batteries.

Lithium (Li) metal batteries (LMBs) with nickel (Ni)-rich layered oxide cathodes exhibit twice the energy density of conventional Li-ion batteries. However, their lifespan is limited by severe side reactions caused by high electrode reactivity. Fluorinated solvent-based electrolytes can address this challenge, but they pose environmental and biological hazards. This work reports on the molecular engineering of fluorine (F)-free ethers to mitigate electrode surface reactivity in high-voltage Ni-rich LMBs. By merely extending the alkyl chains of traditional ethers, we effectively reduce the catalytic reactivity of the cathode towards the electrolyte at high voltages, which suppresses the oxidation decomposition of the electrolyte, microstructural defects and rock-salt phase formation in the cathode, and gas release issues. The high-voltage Ni-rich NCM811-Li battery delivers capacity retention of 80% after 250 cycles with a high Coulombic efficiency of 99.85%, even superior to that in carbonate electrolytes. Additionally, this strategy facilitates passivation of the Li anode by forming a robust solid-electrolyte interphase, boosting the Li reversibility to 99.11% with a cycling life of 350 cycles, which outperforms conventional F-free ether electrolytes. Consequently, the lifespan of practical LMBs has been prolonged by over 100% and 500% compared to those in conventional carbonate- and ether-based electrolytes, respectively.

FURION: modeling of FEL pulses propagation in dispersive soft X-ray beamline systems.

Modern X-ray free-electron lasers (XFELs) can generate pulses with durations ranging from femtoseconds to attoseconds. The numerical evaluation of ultra-short XFEL pulses through beamline systems is a critical process of beamline system design. However, the bandwidth of such ultra-short XFEL pulses is often non-negligible, and the propagation cannot be simply approximated using the central wavelength, especially in dispersive beamline systems. We developed a numerical model which is called Fourier optics based Ultrashort x-Ray pulse propagatION tool (FURION). This model can not only be used to simulate dispersive beamline systems but also to evaluate non-dispersive beamline systems. The FURION model utilizes Fresnel integral and angular spectrum integral to perform ultra-short XFEL pulse propagation in free space. We also present the method for XFEL pulse propagation through different types of dispersive gratings, which are commonly used in soft X-ray beamline systems. By using FURION, a start-to-end simulation of the FEL-1 beamline system at Shenzhen superconducting soft X-ray free electron laser (S3FEL) is carried out. This model can also be used to evaluate gratings-based spectrometers, beam splitters, pulse compressors, and pulse stretchers. This work provides valuable insights into the start-to-end simulation of X-ray beamline systems.

Highly Sensitive Iontronic Pressure Sensor with Side-by-Side Package Based on Alveoli and Arch Structure.

Flexible pressure sensors play a significant role in wearable devices and electronic skin. Iontronic pressure sensors with high sensitivity, wide measurement range, and high resolution can meet requirements. Based on the significant deformation characteristics of alveoli to improve compressibility, and the ability of the arch to disperse vertical pressure into horizontal thrust to increase contact area, a graded hollow ball arch (GHBA) microstructure is proposed, greatly improving sensitivity. The fabrication of GHBA ingeniously employs a double-sided structure. One side uses mold casting to create convex structures, while the other utilizes the evaporation of moisture during the curing process to form concave structures. At the same time, a novel side-by-side package structure is proposed, ensuring pressure on flexible substrate is maximally transferred to the GHBA microstructure. Within the range of 0.2 Pa-300 kPa, the iontronic pressure sensor achieves a maximum sensitivity of 10 420.8 kPa-1 , pressure resolution of 0.1% under the pressure of 100 kPa, and rapid response/recovery time of 40/35 ms. In wearable devices, it is capable of monitoring dumbbell curl exercises and wirelessly correcting sitting positions. In electronic skin, it can non-contactly detect the location of the wind source and achieve object classification prediction when combined with the CNN model.

Solvent-regulated self-assembled carbon nitride for photocatalytic reduction of U(VI) in water.

Manufacturing high-performance and reusable materials from radioactive uranium-containing wastewater remains a significant challenge. Herein, a supramolecular self-assembly strategy was proposed, using melamine and cyanuric acid as precursors and using intermolecular hydrogen bond force to form carbon nitride (CN-D) in different solvents through a single thermal polymerization strategy. Supramolecular self-assembly method is a promising strategy to synthesize a novel carbon nitride with molecular regulatory properties. In addition, 98% of U(VI) in wastewater can be removed by using CN-D for 60 min under visible light. After five cycles of recycling, more than 95% of U(VI) can still be reduced, indicating that it has good recyclability and reusability. This study not only provides an efficient photocatalytic method of uranium reduction, but also provides a new method for self-assembly synthesis.

Enhancing Sun-Dried Kelp Detection: Introducing K-YOLO, a Lightweight Model with Improved Precision and Recall.

Kelp, often referred to as a "sea vegetable", holds substantial economic significance. Currently, the drying process for kelp in China primarily relies on outdoor sun-drying methods. Detecting kelp in the field presents challenges arising from issues such as overlapping and obstruction. To address these challenges, this study introduces a lightweight model, K-YOLOv5, specifically designed for the precise detection of sun-dried kelp. YOLOv5-n serves as the base model, with several enhancements implemented in this study: the addition of a detection head incorporating an upsampling layer and a convolution module to improve the recognition of small objects; the integration of an enhanced I-CBAM attention mechanism, focusing on key features to enhance the detection accuracy; the replacement of the CBS module in the neck network with GSConv to reduce the computational burden and accelerate the inference speed; and the optimization of the IoU algorithm to improve the identification of overlapping kelp. Utilizing drone-captured images of sun-dried kelp, a dataset comprising 2190 images is curated. Validation on this self-constructed dataset indicates that the improved K-YOLOv5 model significantly enhances the detection accuracy, achieving 88% precision and 78.4% recall. These values represent 6.8% and 8.6% improvements over the original model, respectively, meeting the requirements for the real-time recognition of sun-dried kelp.

Loss of WIPI4 in neurodegeneration causes autophagy-independent ferroptosis.

ß-Propeller protein-associated neurodegeneration (BPAN) is a rare X-linked dominant disease, one of several conditions that manifest with neurodegeneration and brain iron accumulation. Mutations in the WD repeat domain 45 (WDR45) gene encoding WIPI4 lead to loss of function in BPAN but the cellular mechanisms of how these trigger pathology are unclear. The prevailing view in the literature is that BPAN is simply the consequence of autophagy deficiency given that WIPI4 functions in this degradation pathway. However, our data indicate that WIPI4 depletion causes ferroptosis-a type of cell death induced by lipid peroxidation-via an autophagy-independent mechanism, as demonstrated both in cell culture and in zebrafish. WIPI4 depletion increases ATG2A localization at endoplasmic reticulum-mitochondrial contact sites, which enhances phosphatidylserine import into mitochondria. This results in increased mitochondrial synthesis of phosphatidylethanolamine, a major lipid prone to peroxidation, thus enabling ferroptosis. This mechanism has minimal overlap with classical ferroptosis stimuli but provides insights into the causes of neurodegeneration in BPAN and may provide clues for therapeutic strategies.

A 3D-printed microhemispherical shell resonator with electrostatic tuning for a Coriolis vibratory gyroscope.

The emergence of microhemispherical resonant gyroscopes, which integrate the advantages of exceptional stability and long lifetime with miniaturization, has afforded new possibilities for the development of whole-angle gyroscopes. However, existing methods used for manufacturing microhemispherical resonant gyroscopes based on MEMS technology face the primary drawback of intricate and costly processing. Here, we report the design, fabrication, and characterization of the first 3D-printable microhemispherical shell resonator for a Coriolis vibrating gyroscope. We remarkably achieve fabrication in just two steps bypassing the dozen or so steps required in traditional micromachining. By utilizing the intricate shaping capability and ultrahigh precision offered by projection microstereolithography, we fabricate 3D high-aspect-ratio resonant structures and controllable capacitive air gaps, both of which are extremely difficult to obtain via MEMS technology. In addition, the resonance frequency of the fabricated resonators can be tuned by electrostatic forces, and the fabricated resonators exhibit a higher quality factor in air than do typical MEMS microhemispherical resonators. This work demonstrates the feasibility of rapidly batch-manufacturing microhemispherical shell resonators, paving the way for the development of microhemispherical resonator gyroscopes for portable inertial navigation. Moreover, this particular design concept could be further applied to increase uptake of resonator tools in the MEMS community.

High-grade serous papillary ovarian carcinoma combined with nonkeratinizing squamous cell carcinoma of the cervix: a case report.

Multiple primary malignant neoplasms are a rare gynecologic malignancy; particularly, cases originating from the heterologous organs, such as the ovary and cervix. Here, we report a case of two primary malignant neoplasms in a patient who had undergone laparoscopic radical hysterectomy + bilateral salpingo-oophorectomy + pelvic lymph node dissection + para-aortic lymphadenectomy + appendectomy + omentectomy + metastasectomy under general anesthesia. The patient experienced complete remission after six courses of postoperative chemotherapy with a standard Taxol and Carboplatin regimen. Genetic testing was performed to detect BRCA2 mutations, and poly (ADP-ribose) polymerase (PARP) inhibitors were used for maintenance therapy.

Development and internal validation of machine learning-based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke.

Aims: We developed new machine learning (ML) models and externally validated existing statistical models [ischaemic stroke predictive risk score (iScore) and totalled health risks in vascular events (THRIVE) scores] for predicting the composite of recurrent stroke or all-cause mortality at 90 days and at 3 years after hospitalization for first acute ischaemic stroke (AIS). Methods and results: In adults hospitalized with AIS from January 2005 to November 2016, with follow-up until November 2019, we developed three ML models [random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBOOST)] and externally validated the iScore and THRIVE scores for predicting the composite outcomes after AIS hospitalization, using data from 721 patients and 90 potential predictor variables. At 90 days and 3 years, 11 and 34% of patients, respectively, reached the composite outcome. For the 90-day prediction, the area under the receiver operating characteristic curve (AUC) was 0.779 for RF, 0.771 for SVM, 0.772 for XGBOOST, 0.720 for iScore, and 0.664 for THRIVE. For 3-year prediction, the AUC was 0.743 for RF, 0.777 for SVM, 0.773 for XGBOOST, 0.710 for iScore, and 0.675 for THRIVE. Conclusion: The study provided three ML-based predictive models that achieved good discrimination and clinical usefulness in outcome prediction after AIS and broadened the application of the iScore and THRIVE scoring system for long-term outcome prediction. Our findings warrant comparative analyses of ML and existing statistical method-based risk prediction tools for outcome prediction after AIS in new data sets.

Surface Reconstruction on Metal Nitride during Photo-oxidation.

The efficient conversion and storage of solar energy for chemical fuel production presents a challenge in sustainable energy technologies. Metal nitrides (MNs) possess unique structures that make them multi-functional catalysts for water splitting. However, the thermodynamic instability of MNs often results in the formation of surface oxide layers and ambiguous reaction mechanisms. Herein, we present on the photo-induced reconstruction of a Mo-rich@Co-rich bi-layer on ternary cobalt-molybdenum nitride (Co3 Mo3 N) surfaces, resulting in improved effectiveness for solar water splitting. During a photo-oxidation process, the uniform initial surface oxide layer is reconstructed into an amorphous Co-rich oxide surface layer and a subsurface Mo-N layer. The Co-rich outer layer provides active sites for photocatalytic oxygen evolution reaction (POER), while the Mo-rich sublayer promotes charge transfer and enhances the oxidation resistance of Co3 Mo3 N. Additionally, the surface reconstruction yields a shortened Co-Mo bond length, weakening the adsorption of hydrogen and resulting in improved performance for both photocatalytic hydrogen evolution reaction (PHER) and POER. This work provides insight into the surface structure-to-activity relationships of MNs in solar energy conversion, and is expected to have significant implications for the design of metal nitride-based catalysts in sustainable energy technologies.

Mechanism insights into the pleiotropic effects of nobiletin as a potential therapeutic agent on non-alcoholic fatty liver disease (NAFLD).

Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver diseases and is emerging as one of the fastest-growing causes of liver-related deaths worldwide. It is necessary to find strategies to effectively prevent and treat NAFLD, as no definitive drug has been approved. Nobiletin (NOB) is the critical active ingredient of Chinese herbal medicines such as Citrus aurantium and Citri Reticulatae Pericarpium, which have anti-inflammatory, antioxidant, lipid regulating, and insulin resistance regulating effects. Numerous studies have demonstrated that NOB can prevent and treat the onset and progression of NAFLD. In this review, the mechanisms of NOB for treating NAFLD have been summarized, hoping to provide a basis for subsequent studies of NOB and to provide a research ground for the development of therapeutic drugs for NAFLD.

IRF3 activates RB to authorize cGAS-STING-induced senescence and mitigate liver fibrosis.

Cytosolic double-stranded DNA surveillance by cyclic GMP-AMP synthase (cGAS)-Stimulator of Interferon Genes (STING) signaling triggers cellular senescence, autophagy, biased mRNA translation, and interferon-mediated immune responses. However, detailed mechanisms and physiological relevance of STING-induced senescence are not fully understood. Here, we unexpectedly found that interferon regulatory factor 3 (IRF3), activated during innate DNA sensing, forms substantial endogenous complexes in the nucleus with retinoblastoma (RB), a key cell cycle regulator. The IRF3-RB interaction attenuates cyclin-dependent kinase 4/6 (CDK4/6)-mediated RB hyperphosphorylation that mobilizes RB to deactivate E2 family (E2F) transcription factors, thereby driving cells into senescence. STING-IRF3-RB signaling plays a notable role in hepatic stellate cells (HSCs) within various murine models, pushing activated HSCs toward senescence. Accordingly, IRF3 global knockout or conditional deletion in HSCs aggravated liver fibrosis, a process mitigated by the CDK4/6 inhibitor. These findings underscore a straightforward yet vital mechanism of cGAS-STING signaling in inducing cellular senescence and unveil its unexpected biology in limiting liver fibrosis.

Identification of mine water sources using a multi-dimensional ion-causative nonlinear algorithmic model.

Based on the nonlinear algorithmic theory, the R-SVM water source discrimination model and prediction method were established by using the piper qualitatively to compare the differences between the ionic components and R-type factor approximation indicator input dimensions. Taking the mine water samples of Zhaogezhuang Coal Mine as an example, according to the chemical composition analysis of the water samples from different monitoring points, six indexes of Na+, Ca2+, Mg2+, Cl-, SO42- and HCO3- were selected as the discrimination factors. According to the water characteristics of each aquifer and the actual needs of discrimination, the water inrush sources in the mining area were divided into four categories: The goaf water is class I, Ordovician carbonate is class II, Sandstone fracture water from the 13 coal system is class III, and Sandstone fracture water from the 12 coal system is class IV. Taking 56 typical water inrush samples as training samples, 11 groups for prediction samples, establish the input index as typical ion content, output as water source type, using SPSS statistics and MATLAB to realize the R-SVM water source discriminant analysis model, automatically establishing the mapping relationship between the water quality indexes and the evaluation standards, which can achieve the purpose of rapid and accurate discrimination of the water sample data. The results showed that the accuracy of the R-SVM model classification was 90.90% in the verification of the water source discrimination example of Zhaogezhuang mine and the coupled model has high accuracy, good applicability and discriminant ability, and has certain guiding significance for the prevention and control of water damage and the related field work.

Engineered bone marrow mesenchymal stem cell-derived exosomes loaded with miR302 through the cardiomyocyte specific peptide can reduce myocardial ischemia and reperfusion (I/R) injury.

BACKGROUND: MicroRNA (miRNA)-based therapies have shown great potential in myocardial repair following myocardial infarction (MI). MicroRNA-302 (miR302) has been reported to exert a protective effect on MI. However, miRNAs are easily degraded and ineffective in penetrating cells, which limit their clinical applications. Exosomes, which are small bioactive molecules, have been considered as an ideal vehicle for miRNAs delivery due to their cell penetration, low immunogenicity and excellent stability potential. Herein, we explored cardiomyocyte-targeting exosomes as vehicles for delivery of miR302 into cardiomyocyte to potentially treat MI. METHODS: To generate an efficient exosomal delivery system that can target cardiomyocytes, we engineered exosomes with cardiomyocyte specific peptide (CMP, WLSEAGPVVTVRALRGTGSW). Afterwards, the engineered exosomes were characterized and identified using transmission electron microscope (TEM) and Nanoparticle Tracking Analysis (NTA). Later on, the miR302 mimics were loaded into the engineered exosomes via electroporation technique. Subsequently, the effect of the engineered exosomes on myocardial ischemia and reperfusion (I/R) injury was evaluated in vitro and in vivo, including MTT, ELISA, real-time quantitative polymerase chain reaction (PCR), western blot, TUNNEL staining, echocardiogram and hematoxylin and eosin (HE) staining. RESULTS: Results of in vitro experimentation showed that DSPE-PEG-CMP-EXO could be more efficiently internalized by H9C2 cells than unmodified exosomes (blank-exosomes). Importantly, compared with the DSPE-PEG-CMP-EXO group, DSPE-PEG-CMP-miR302-EXO significantly upregulated the expression of miR302, while exosomes loaded with miR302 could enhance proliferation of H9C2 cells. Western blot results showed that the DSPE-PEG-CMP-miR302-EXO significantly increased the protein level of Ki67 and Yap, which suggests that DSPE-PEG-CMP-miR302-EXO enhanced the activity of Yap, the principal downstream effector of Hippo pathway. In vivo, DSPE-PEG-CMP-miR302-EXO improved cardiac function, attenuated myocardial apoptosis and inflammatory response, as well as reduced infarct size significantly. CONCLUSION: In conclusion, our findings suggest that CMP-engineered exosomes loaded with miR302 was internalized by H9C2 cells, an in vitro model for cardiomyocytes coupled with potential enhancement of the therapeutic effects on myocardial I/R injury.