Enhanced In Vitro Efficacy of Verbascoside in Suppressing Hepatic Stellate Cell Activation via ROS Scavenging with Reverse Microemulsion.

Numerous approaches targeting hepatic stellate cells (HSCs) have emerged as pivotal therapeutic strategies to mitigate liver fibrosis and are currently undergoing clinical trials. The investigation of herbal drugs or isolated natural active compounds is particularly valuable, due to their multifaceted functions and low risk of side effects. Recent studies have hinted at the potential efficacy of verbascoside (VB) in ameliorating renal and lung fibrosis, yet its impact on hepatic fibrosis remains to be elucidated. This study aims to evaluate the potential effects of VB on liver fibrosis by assessing its ability to inhibit HSC activation. VB demonstrated significant efficacy in suppressing the expression of fibrogenic genes in activated LX-2 cells. Additionally, VB inhibited the migration and proliferation of these activated HSCs by scavenging reactive oxygen species (ROS) and downregulating the AMPK pathway. Furthermore, a biosafe reverse microemulsion loaded with VB (VB-ME) was developed to improve VB's instability and low bioavailability. The optimal formulation of VB-ME was meticulously characterized, revealing substantial enhancements in cellular uptake, ROS-scavenging capacity, and the suppression of HSC activation.

Negative corona discharge strategy for efficient quantum dot light-emitting diodes.

In colloid quantum dot light-emitting diodes (QLEDs), the control of interface states between ZnO and quantum dots (QDs) plays a vital role. We present a straightforward and efficient method using a negative corona discharge to modify the QD film, creating a dipole moment at the interface of QDs and magnesium-doped ZnO (ZnMgO) for balanced charge carrier distribution within the QDs. This process boosts external quantum efficiencies in red, green, and blue QLEDs to 17.71%, 14.53%, and 9.04% respectively. Notably, optimized devices exhibit significant enhancements, especially at lower brightness levels (1000 to 10,000 cd·m-2), vital for applications in mobile displays, TV screens, and indoor lighting.

Large-scale research on durability test cycle of fuel cell system based on CATC.

Durability is one of the technical bottlenecks restricting fuel cell electric vehicle development. As a result, significant time and resources have been invested in research related to this area worldwide. Current durability research mainly focuses on the single cell and stack levels, which is quite different from the usage scenarios of actual vehicles. There is almost no research on developing durability test cycles on the fuel cell system level. This paper proposes a universal model for developing a durability test cycle for fuel cell system based on the China automotive test cycle. Large-scale comparison tests of the fuel cell systems are conducted. After 1000 h test, the output performance degradation of three mass-produced fuel cell system is 14.49%, 9.59%, and 4.21%, respectively. The test results show that the durability test cycle proposed in this paper can effectively accelerate the durability test of the fuel cell system and evaluate the durability performance of the fuel cell system. Moreover, the methodology proposed in this paper could be used in any other test cycles such as NEDC (New European Driving Cycle), WLTC (Worldwide Harmonized Light Vehicles Test Procedure), etc. And it has comprehensive application value and are significant for reducing the cost of durability testing of fuel cell systems and promoting the industrialization of fuel cell electric vehicles.

Data-Driven Controlled Synthesis of Oriented Quasi-Spherical CsPbBr3 Perovskite Materials.

Controlled synthesis of lead-halide perovskite crystals is challenging yet attractive because of the pivotal role played by the crystal structure and growth conditions in regulating their properties. This study introduces data-driven strategies for the controlled synthesis of oriented quasi-spherical CsPbBr3, alongside an investigation into the synthesis mechanism. High-throughput rapid characterization of absorption spectra and color under ultraviolet illumination was conducted using 23 possible ligands for the synthesis of CsPbBr3 crystals. The links between the absorption spectra slope (difference in the absorbance at 400 nm and 450 nm divided by a wavelength interval of 50 nm) and crystal size were determined through statistical analysis of more than 100 related publications. Big data analysis and machine learning were employed to investigate a total of 688 absorption spectra and 652 color values, revealing correlations between synthesis parameters and properties. Ex situ characterization confirmed successful synthesis of oriented quasi-spherical CsPbBr3 perovskites using polyvinylpyrrolidone and Acacia. Density functional theory calculations highlighted strong adsorption of Acacia on the (110) facet of CsPbBr3. Optical properties of the oriented quasi-spherical perovskites prepared with these data-driven strategies were significantly improved. This study demonstrates that data-driven controlled synthesis facilitates morphology-controlled perovskites with excellent optical properties.

Augmented Concentration of Isopentyl-Deoxynyboquinone in Tumors Selectively Kills NAD(P)H Quinone Oxidoreductase 1-Positive Cancer Cells through Programmed Necrotic and Apoptotic Mechanisms.

Lung and breast cancers rank as two of the most common and lethal tumors, accounting for a substantial number of cancer-related deaths worldwide. While the past two decades have witnessed promising progress in tumor therapy, developing targeted tumor therapies continues to pose a significant challenge. NAD(P)H quinone oxidoreductase 1 (NQO1), a two-electron reductase, has been reported as a promising therapeutic target across various solid tumors. ß-Lapachone (ß-Lap) and deoxynyboquinone (DNQ) are two NQO1 bioactivatable drugs that have demonstrated potent antitumor effects. However, their curative efficacy has been constrained by adverse effects and moderate lethality. To enhance the curative potential of NQO1 bioactivatable drugs, we developed a novel DNQ derivative termed isopentyl-deoxynyboquinone (IP-DNQ). Our study revealed that IP-DNQ treatment significantly increased reactive oxygen species generation, leading to double-strand break (DSB) formation, PARP1 hyperactivation, and catastrophic energy loss. Notably, we discovered that this novel drug induced both apoptosis and programmed necrosis events, which makes it entirely distinct from other NQO1 bioactivatable drugs. Furthermore, IP-DNQ monotherapy demonstrated significant antitumor efficacy and extended mice survival in A549 orthotopic xenograft models. Lastly, we identified that in mice IP-DNQ levels were significantly elevated in the plasma and tumor compared with IB-DNQ levels. This study provides novel preclinical evidence supporting IP-DNQ efficacy in NQO1+ NSCLC and breast cancer cells.

Association between dietary intake of omega-3 polyunsaturated fatty acids and all-cause and cardiovascular mortality among hypertensive adults: Results from NHANES 1999-2018.

BACKGROUND: Hypertensive adults are at a higher risk of cardiovascular morbidity and mortality. Dietary omega-3 polyunsaturated fatty acids (N3-PUFA) intake has been associated with cardiovascular benefits. However, few studies have specifically investigated whether dietary intake of N3-PUFA is associated with lower risk of all-cause and cardiovascular mortality among hypertensive adults in the U.S. METHODS: This prospective cohort study included 26,914 hypertensive individuals 18 years or older who participated in 10 NHANES cycles from 1999 to 2018. Dietary levels of N3-PUFA were obtained from the 24-hour dietary recalls. The dietary data were linked to mortality records from the National Death Index through December 31, 2019. The associations between dietary N3-PUFA levels and mortality were evaluated by constructing the Multivariable Cox Proportional Hazards models. RESULTS: We observed an increasing trend of dietary N3-PUFA intake levels over the years, mainly driven by alpha-linolenic acid (ALA). Lower all-cause mortality risk was observed among hypertensive adults with higher consumption of total N3-PUFA [adjusted hazards ratio, 95% confidence interval: 0.91 (0.86, 0.97)], plant-based ALA [0.88 (0.83, 0.93)], fish oil-based eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA) [0.91 (0.83, 0.99)], EPA [0.93 (0.88, 0.98)], docosapentaenoic acid (DPA) [0.73 (0.58, 0.91)], or DHA [0.95 (0.90, 0.99)]. Hypertensive adults were at lower risk of cardiovascular mortality if their diet contained higher levels of total N3-PUFA [0.68 (0.53, 0.88)], ALA [0.89 (0.80, 0.99)], EPA [0.87 (0.79, 0.97)] or DPA [0.86 (0.78, 0.95)]. Weighted quantile sum analysis showed that ALA, EPA, and DPA were the main contributors of the N3-PUFA benefits against mortality among hypertensive adults. CONCLUSIONS: Dietary intake of N3-PUFA, particularly ALA, EPA, and DPA, was associated with lower risk of all-cause and cardiovascular mortality among U.S. hypertensive adults. These findings suggest that increasing dietary intake of N3-PUFA may serve as a potential strategy to lower hypertension-associated mortality risk.

LSD1-Based Reversible Inhibitors Virtual Screening and Binding Mechanism Computational Study.

As one of the crucial targets of epigenetics, histone lysine-specific demethylase 1 (LSD1) is significant in the occurrence and development of various tumors. Although several irreversible covalent LSD1 inhibitors have entered clinical trials, the large size and polarity of the FAD-binding pocket and undesired toxicity have focused interest on developing reversible LSD1 inhibitors. In this study, targeting the substrate-binding pocket of LSD1, structure-based and ligand-based virtual screenings were adopted to expand the potential novel structures with molecular docking and pharmacophore model strategies, respectively. Through drug-likeness evaluation, ADMET screening, molecular dynamics simulations, and binding free energy screening, we screened out one and four hit compounds from the databases of 2,029,554 compounds, respectively. Generally, these hit compounds can be divided into two categories, amide (Lig2 and Comp2) and 1,2,4-triazolo-4,3-α-quinazoline (Comp3, Comp4, Comp7). Among them, Comp4 exhibits the strongest binding affinity. Finally, the binding mechanisms of the hit compounds were further calculated in detail by the residue free energy decomposition. It was found that van der Waals interactions contribute most to the binding, and FAD is also helpful in stabilizing the binding and avoiding off-target effects. We believe this work not only provides a solid theoretical foundation for the design of LSD1 substrate reversible inhibitors, but also expands the diversity of parent nucleus, offering new insights for synthetic chemists.

Metal mixture exposure and the risk for immunoglobulin A nephropathy: Evidence from weighted quantile sum regression.

Immunoglobulin A nephropathy (IgAN) is the most common type of glomerulonephritis in adults worldwide. Environmental metal exposure has been reported to be involved in the pathogenic mechanisms of kidney diseases, yet no further epidemiological study has been conducted to assess the effects of metal mixture exposure on IgAN risk. In this study, we conducted a matched case‒control design with three controls for each patient to investigate the association between metal mixture exposure and IgAN risk. A total of 160 IgAN patients and 480 healthy controls were matched for age and sex. Plasma levels of arsenic, lead, chromium, manganese, cobalt, copper, zinc, and vanadium were measured using inductively coupled plasma mass spectrometry. We used a conditional logistic regression model to assess the association between individual metals and IgAN risk, and a weighted quantile sum (WQS) regression model to analyze the effects of metal mixtures on IgAN risk. Restricted cubic splines were used to evaluate overall associations between plasma metal concentrations and estimated glomerular filtration rate (eGFR) levels. We observed that except for Cu, all the metals analyzed were nonlinearly associated with decreased eGFR, and higher concentrations of arsenic and lead were associated with elevated IgAN risk in both single-metal [3.29 (1.94, 5.57), 6.10 (3.39, 11.0), respectively] and multiple-metal [3.04 (1.66, 5.57), 4.70 (2.47, 8.97), respectively] models. Elevated manganese [1.76 (1.09, 2.83)] levels were associated with increased IgAN risk in the single-metal model. Copper was inversely related to IgAN risk in both single-metal [0.392 (0.238, 0.645)] and multiple-metal [0.357 (0.200, 0.638)] models. The WQS indices in both positive [2.04 (1.68, 2.47)] and negative [0.717 (0.603, 0.852)] directions were associated with IgAN risk. Lead, arsenic, and vanadium contributed significant weights (0.594, 0.195, and 0.191, respectively) in the positive direction; copper, cobalt, and chromium carried significant weights (0.538, 0.253, and 0.209, respectively). In conclusion, metal exposure was related to IgAN risk. Lead, arsenic, and copper were all significantly weighted factors of IgAN development, which may require further investigation.

New insights into the proton pumping mechanism of ba3 cytochrome c oxidase: the functions of key residues and water.

As the terminal oxidase of cell respiration in mitochondria and aerobic bacteria, the proton pumping mechanism of ba3-type cytochrome c oxidase (CcO) of Thermus thermophiles is still not fully understood. Especially, the functions of key residues which were considered as the possible proton loading sites (PLSs) above the catalytic center, as well as water located above and within the catalytic center, remain unclear. In this work, molecular dynamic simulations were performed on a set of designed mutants of key residues (Asp287, Asp372, His376, and Glu126II). The results showed that Asp287 may not be a PLS, but it could modulate the ability of the proton transfer pathway to transfer protons through its salt bridge with Arg225. Maintaining the closed state of the water pool above the catalytic center is necessary for the participation of inside water molecules in proton transfer. Water molecules inside the water pool can form hydrogen bond chains with PLS to facilitate proton transfer. Additional quantum cluster models of the Fe-Cu metal catalytic center are established, indicating that when the proton is transferred from Tyr237, it is more likely to reach the OCu atom directly through only one water molecule. This work provides a more profound understanding of the functions of important residues and specific water molecules in the proton pumping mechanism of CcO.

The unsupervised machine learning to analyze the use strategy of statins for ischaemic stroke patients with elevated transaminase.

BACKGROUND AND PURPOSE: Statins could elevate hepatic transaminase in ischemic stroke patients. There needed to be more evidence on which method stopped statins or adjusting the dose of statins was better for patients. And no evidence showed which way more suit for some patients. METHODS: We collected ischaemic stroke patients with elevated hepatic transaminase when they take statins. The outcome was a recurrent stroke rate, transaminase value after stopping or adjusted, mortality, and favorable functional outcome (FFO). We compare outcome events between the stopped group and the adjustment group. We grouped all patients by unsupervised machine learning and analyzed data characters by the different groups. RESULTS: The patients stopping statins had a higher stroke recurrence and rate of FFO (mRS 0-2), a lower mean value of transaminase, and mortality. By difference unsupervised machine learning group, the km2 group had the lowest stroke recurrence (p = 0.046), lowest mortality (p = 0.049), and highest FFO (p = 0.023). The patients of the km2 group were younger (p < 0.001), more male (p < 0.001), had lesser National Institutes of Health Stroke Scale (NIHSS) scores (p < 0.001), and had slightly higher values of blood pressure (p = 0.002). The group of unsupervised machine learning could improve models' performance. CONCLUSION: For ischemic patients with elevated hepatic transaminase, stopping statins temporarily was a better choice of treatment strategy. These patients who were younger, male, with a lesser NIHSS score at admission and a slightly higher blood lipid value at admission, could have had a better prognosis.

Initial low-dose computed tomography screening results and summary of participant characteristics: based on the latest Chinese guideline.

Background: Low-dose computed tomography (LDCT) has been promoted as a promising screening strategy for early detection of lung cancer. China released the latest lung cancer screening guideline in 2021. The compliance of the individuals who received LDCT for lung cancer screening with the guideline is unknown yet. It is necessary to summarize the distribution of guideline-defined lung cancer-related risk factors in the Chinese population so as to inform the selection of target population for the future lung cancer screening. Methods: A single-center, cross-sectional study design was adopted. All participants were individuals who underwent LDCT at a tertiary teaching hospital in Hunan, China, between 1 January and 31 December 2021. LDCT results were derived along with guideline-based characteristics for descriptive analysis. Results: A total of 5,486 participants were included. Over one-quarter (1,426, 26.0%) of the participants who received screening did not meet the guideline-defined high-risk population, even among non-smokers (36.4%). Most of the participants (4,622, 84.3%) were found to have lung nodules, while no clinical intervention was required basically. The detection rate of positive nodules varied from 46.8% to 71.2% when using different cut-off values for positive nodules. Among non-smoking women, ground glass opacity appeared to be more significantly common compared with non-smoking men (26.7% vs. 21.8%). Conclusion: Over one-quarter of individuals who received LDCT screening did not meet the guideline-defined high-risk populations. Appropriate cut-off values for positive nodules need to be continuously explored. More precise and localized criteria for high-risk individuals are needed, especially for non-smoking women.

Death attitudes and associated factors among health professional students in China.

Background: China is entering an era of aging population with an increased mortality rate among this category of population. Health professional students' attitudes toward death directly affect their quality of palliative care in their future careers. It is thus important to understand their death attitudes and associated factors to guide future educational and training development. Objectives: This study aimed to investigate death attitudes and analyze the associated factors among health professional students in China. Methods: In this cross-sectional study, 1,044 health professional students were recruited from 14 medical colleges and universities. The Chinese version of the Death Attitude Profile-Revised (DAP-R) was used to evaluate their death attitudes. A multiple linear regression model was used to analyze the influencing factors of attitudes toward death. Results: Health professional students tended to accept death more neutrally. Multivariate analysis showed that their negative death attitudes were associated with age (ß = -0.31, p < 0.001) and religious belief (ß = 2.76, p = 0.015), while positive death attitudes were associated with age (ß = -0.42, p < 0.001), hearing of Advance Care Plan (ACP) (ß = 2.21, p = 0.001), and attending funeral/memorial services (ß = 2.69, p = 0.016). Conclusion: Our study stresses the importance of including death and palliative care education in healthcare courses among health professional students in China. Incorporation of ACP education along with experiences of funeral/memorial services may help promote health professional students' positive attitudes toward death and improve the quality of palliative care in their future careers.

Urban public health spatial planning using big data technology and visual communication in IoT.

The planning of urban public health spatial can not only help people's physical and mental health but also help to optimize and protect the urban environment. It is of great significance to study the planning methods of urban public health spatial. The application effect of traditional urban public health spatial planning is poor, in this paper, urban public health spatial planning using big data technology and visual communication in the Internet of Things (IoT) is proposed. First, the urban public health spatial planning architecture is established in IoT, which is divided into the perception layer, the network layer and the application layer; Second, information collection is performed at the perception layer, and big data technology is used at the network layer to simplify spatial model information, automatically sort out spatial data, and establish a public health space evaluation system according to the type and characteristics of spatial data; Finally, the urban public health space is planned based on the health assessment results and the visual communication design concept through the application layer. The results show that when the number of regions reaches 60,000, the maximum time of region merging is 7.86s. The percentage of spatial fitting error is 0.17. The height error of spatial model is 0.31m. The average deviation error of the spatial coordinates is 0.23, which can realize the health planning of different public spaces.

Oral nicotinamide mononucleotide (NMN) to treat chronic insomnia: protocol for the multicenter, randomized, double-blinded, placebo-controlled trial.

BACKGROUND: The treatment of insomnia, which is the most common sleep disorder, includes drug and behavioral treatment, but each treatment measure has its limitations. So new treatment method needs to be taken to improve the treatment effect. MN supplementation is a potential promising new method for the treatment of insomnia, resulting in a rising need for methodological research towards verifying its efficacy. METHODS/DESIGN: We describe a proposal for a multicenter, patient-assessor-blinded, randomized controlled trial with two parallel arms. A total of 400 chronic insomnia patients will be allocated 1:1 to the intervention group (treatment with oral NMN 320 mg/day) or control group (treatment with oral placebo). All subjects are clinical chronic insomnia patients who meet all inclusion criteria. All subjects are treated by taking NMN or placebo. The primary outcome is the score on the Pittsburgh Sleep Quality Index (PSQI). Secondary outcomes are the score on the Insomnia Severity Index (ISI) and Epworth Sleeping Scale (ESS), the total sleep time (TST), sleep efficiency (SE), sleep latency, and REM sleep latency to assess sleep quality changes. Subjects are assessed at two time points: baseline and follow-up. The duration of the clinical trial is 60 days. DISCUSSION: This study will provide more evidence on the effects of NMN on improving sleep quality among patients with chronic insomnia. If proven effective, NMN supplement can be used as a new treatment for chronic insomnia in the future. TRIAL REGISTRATION: Chinese Clinical Trial Registry (chictr.org.cn) ChiCTR2200058001. Registered on 26 March 2022.

Depth-Guided Optimization of Neural Radiance Fields for Indoor Multi-View Stereo.

In this work, we present a new multi-view depth estimation method NerfingMVS that utilizes both conventional reconstruction and learning-based priors over the recently proposed neural radiance fields (NeRF). Unlike existing neural network based optimization method that relies on estimated correspondences, our method directly optimizes over implicit volumes, eliminating the challenging step of matching pixels in indoor scenes. The key to our approach is to utilize the learning-based priors to guide the optimization process of NeRF. Our system first adapts a monocular depth network over the target scene by finetuning on its MVS reconstruction from COLMAP. Then, we show that the shape-radiance ambiguity of NeRF still exists in indoor environments and propose to address the issue by employing the adapted depth priors to monitor the sampling process of volume rendering. Finally, a per-pixel confidence map acquired by error computation on the rendered image can be used to further improve the depth quality. We further present NerfingMVS++, where a coarse-to-fine depth priors training strategy is proposed to directly utilize sparse SfM points and the uniform sampling is replaced by Gaussian sampling to boost the performance. Experiments show that our NerfingMVS and its extension NerfingMVS++ achieve state-of-the-art performances on indoor datasets ScanNet and NYU Depth V2. In addition, we show that the guided optimization scheme does not sacrifice the original synthesis capability of neural radiance fields, improving the rendering quality on both seen and novel views. Code is available at https://github.com/weiyithu/NerfingMVS.

High-Performance Photoinitiating Systems for LED-Induced Photopolymerization.

Currently, increasing attention has been focused on light-emitting diodes (LEDs)-induced photopolymerization. The common LEDs (e.g., LED at 365 nm and LED at 405 nm) possess narrow emission bands. Due to their light absorption properties, most commercial photoinitiators are sensitive to UV light and cannot be optimally activated under visible LED irradiation. Although many photoinitiators have been designed for LED-induced free radical polymerization and cationic polymerization, there is still the issue of the mating between photoinitiators and LEDs. Therefore, the development of novel photoinitiators, which could be applied under LED irradiation, is significant. Many photoinitiating systems have been reported in the past decade. In this review, some recently developed photoinitiators used in LED-induced photopolymerization, mainly in the past 5 years, are summarized and categorized as Type Ⅰ photoinitiators, Type Ⅱ photoinitiators, and dye-based photoinitiating systems. In addition, their light absorption properties and photoinitiation efficiencies are discussed.

Minimally-Invasive Corneal Neurotization (MICN): 10 Year Update in Technique and Lessons Learned Including Novel Donor Transfer of the Great Auricular Nerve.

VIDEO PLUS SUBMISSION SUMMARY: Corneal anesthesia, caused by lack of corneal innervation, is a rare but devastating condition that can lead to neurotrophic keratopathy 1, corneal ulceration, scarring, and blindness. Minimally-Invasive Corneal Neurotization (MICN) enables transfer of regional donor sensory nerves to the cornea to provide sensation and ocular protection. Here, we provide an update on technical advances and modifications that have arisen over ten years that have refined the surgery. We provide intraoperative step by step videos of corneal neurotization, noting its critical steps, pitfalls, and caveats. This video submission will focus on the novel technique of utilizing the greater auricular nerve with a sural nerve graft extension as the donor nerve for the procedure. The steps and considerations depicted will allow surgeons to carry out corneal neurotization efficiently, safely, and effectively.

Prediction-Based Human-Robot Collaboration in Assembly Tasks Using a Learning from Demonstration Model.

Most robots are programmed to carry out specific tasks routinely with minor variations. However, more and more applications from SMEs require robots work alongside their counterpart human workers. To smooth the collaboration task flow and improve the collaboration efficiency, a better way is to formulate the robot to surmise what kind of assistance a human coworker needs and naturally take the right action at the right time. This paper proposes a prediction-based human-robot collaboration model for assembly scenarios. An embedded learning from demonstration technique enables the robot to understand various task descriptions and customized working preferences. A state-enhanced convolutional long short-term memory (ConvLSTM)-based framework is formulated for extracting the high-level spatiotemporal features from the shared workspace and predicting the future actions to facilitate the fluent task transition. This model allows the robot to adapt itself to predicted human actions and enables proactive assistance during collaboration. We applied our model to the seats assembly experiment for a scale model vehicle and it can obtain a human worker's intentions, predict a coworker's future actions, and provide assembly parts correspondingly. It has been verified that the proposed framework yields higher smoothness and shorter idle times, and meets more working styles, compared to the state-of-the-art methods without prediction awareness.

Discovery of cinnamamide-barbiturate hybrids as a novel class of Nrf2 activator against myocardial ischemia/reperfusion injury.

Myocardial ischemia/reperfusion (MI/R) has been a challenge for global public health. Activation of nuclear factor erythroid-2-related factor 2 (Nrf2) signaling could attenuate MI/R injury by maintaining cell redox balance and reducing oxidative damage. Cinnamamide derivatives have been proven to be a class of potential Nrf2 activators and cardioprotective agents. The development of novel cinnamamide derivatives to combat oxidative stress in cardiomyocytes is highly desirable. In this study, twenty-three cinnamamide-barbiturate hybrids were studied. Cell-based assays showed that most of the compounds exhibited excellent protective activity against H2O2-induced oxidative injury in H9c2 cells. Notably, compound 7w, which had the highest activity and low cytotoxicity, was demonstrated to remarkably reduce intracellular ROS accumulation by activating the mRNA expression of Nrf2 and its downstream antioxidant gene HO-1, indicating a novel promising antioxidant and Nrf2 activator. The probable binding mode between protein Keap1 and compound 7w was also studied via molecule docking. Furthermore, we found that the administration of compound 7w could significantly reduce the cardiac infarct size and improve the cardiac function against MI/R injury in rats, as well as decrease cardiac oxidative stress. Taken together, we report, for the first time, that cinnamamide-barbiturate hybrids are a novel class of potential cardioprotective agents. The excellent cardioprotective action of such compounds rely on enhancing the endogenous antioxidative system by upregulating the Nrf2 signaling pathway in vitro and in vivo against MI/R damage. These findings provide a new perspective for designing cinnamamide-barbiturate hybrids as a novel class of Nrf2 activator against cardiovascular diseases.