Loss of myocytes caused by cell death plays a key role during heart failure (HF). Activated autophagy and increased ferroptosis have been observed in HF and proved to promote its progression. ...However, the underlying mechanisms remain unclear. Here, results from integrated bioinformatical analysis showed TLR4 and NADPH oxidase 4 (NOX4) were included in up-regulated differentially expressed genes (DEGs), and had an interaction between each other inferred by the DEGs-associated protein-protein interaction (PPI) network. To explore the role of TLR4-NOX4 in autophagy and ferroptosis, knock-down of TLR4 and NOX4 through lentiviral delivery of siRNA to the myocardium were applied respectively in HF rats induced by aortic banding, and the indicators of autophagy and ferroptosis were detected. Results revealed that either TLR4 or NOX4 knock-down significantly improved left ventricular remodeling and reduced myocytes death. Simultaneously, activated autophagy and ferroptosis in rats with HF were remarkably retarded by either TLR4 and NOX4 knock-down, suggesting TLR4-NOX4 as a potential therapeutic target for HF through inhibiting autophagy- and ferroptosis-mediated cell death.
•TLR4 and NOX4 were up-regulated accompanied by activated autophagy and increased ferroptosis during heart failure.•Either TLR4- or NOX4 knock-down significantly reduced myocyte death.•Either TLR4- or NOX4 knock-down significantly inhibited autophagy and ferroptosis.
Heart failure (HF) is the end stage of cardiovascular disease and is characterized by the loss of myocytes caused by cell death. Puerarin has been found to improve HF clinically, and animal study ...findings have confirmed its anti-cell-death properties. However, the underlying mechanisms remain unclear, especially with respect to the impact on ferroptosis, a newly defined mechanism of iron-dependent non-apoptotic cell death in HF. Here, ferroptosis-like cell death was observed in erastin- or isoprenaline (ISO)-treated H9c2 myocytes in vitro and in rats with aortic banding inducing HF, characterized by reduced cell viability with increased lipid peroxidation and labile iron pool. Interestingly, the increased iron overload and lipid peroxidation observed in either rats with HF or H9c2 cells incubated with ISO were significantly blocked by puerarin administration. These results provide compelling evidence that puerarin plays a role in inhibiting myocyte loss during HF, partly through ferroptosis mitigation, suggesting a new mechanism of puerarin as a potential therapy for HF.
•Ferroptosis is involved in the loss of myocytes during heart failure.•Puerarin exerted protective effects against heart failure through inhibition of ferroptosis.•Regulation of Nox4 signaling might be involved in puerarin inhibiting ferroptosis.
In this work, thermoplastic polyurethane based conductive polymer composites containing carbon nanotubes (CNTs) and synthesized silver nanoparticles (AgNPs) were used to fabricate highly elastic ...strain sensors via fused deposition modeling. The printability of the materials was improved with the introduction of the nanofillers, and the size and content of the AgNPs significantly influenced the sensing performance of the 3D printed sensors. When the CNTs:AgNPs weight ratio was 5:1, the sensors exhibited outstanding performance with high sensitivity (GF = 43260 at 250% strain), high linearity (R2 = 0.97 within 50% strain), fast response (~57 ms), and excellent repeatability (1000 cycles) due to synergistic effects. A modeling study based on the Simmons' tunneling theory was also undertaken to analyze the sensing mechanism. The sensor was applied to monitor diverse joint movements and facial motion, showing its potential for application in intelligent robots, prosthetics, and wearable devices where customizability are usually demanded.
Road detection is a key component of autonomous driving; however, most fully supervised learning road detection methods suffer from either insufficient training data or high costs of manual ...annotation. To overcome these problems, we propose a semisupervised learning (SSL) road detection method based on generative adversarial networks (GANs) and a weakly supervised learning (WSL) method based on conditional GANs. Specifically, in our SSL method, the generator generates the road detection results of labeled and unlabeled images, and then they are fed into the discriminator, which assigns a label on each input to judge whether it is labeled. Additionally, in WSL method we add another network to predict road shapes of input images and use them in both generator and discriminator to constrain the learning progress. By training under these frameworks, the discriminators can guide a latent annotation process on the unlabeled data; therefore, the networks can learn better representations of road areas and leverage the feature distributions on both labeled and unlabeled data. The experiments are carried out on KITTI ROAD benchmark, and the results show our methods achieve the state-of-the-art performances.
In this study, high-performance flexible strain sensors based on carbon nanotube (CNT) and graphene nanoplatelet (GNP) filled thermoplastic polyurethane (TPU) composites were fabricated via Fused ...Filament Fabrication (FFF) 3D printing. The introduction of GNPs generated a more complete conductive network of the composites due to the improved nanofiller dispersion. Due to the synergy of CNTs and GNPs, the printed CNT/GNP(3:1)/TPU sensor shows higher sensitivity (GF = 136327.4 at 250% strain), larger detectable range (0–250% strain), and better stability (3000 cycles) compared with the CNT/TPU and GNP/TPU sensors with a nanofiller content of 2 wt%. Furthermore, the printed sensors can accurately detect strains at different frequencies (0.01–1 Hz). A modelling study based on tunneling theory was conducted to analysis the strain sensing mechanism, and the theoretical results agreed well with the experimental data. The capability of the sensors in monitoring physiological activities and speech recognition has also been demonstrated.
Plant secondary metabolites are highly valued for their applications in pharmaceuticals, nutrition, flavors, and aesthetics. It is of great importance to elucidate plant secondary metabolic pathways ...due to their crucial roles in biological processes during plant growth and development. However, understanding plant biosynthesis and degradation pathways remains a challenge due to the lack of sufficient information in current databases. To address this issue, we proposed a transfer learning approach using a pre-trained hybrid deep learning architecture that combines Graph Transformer and convolutional neural network (GTC) to predict plant metabolic pathways. GTC provides comprehensive molecular representation by extracting both structural features from the molecular graph and textual information from the SMILES string. GTC is pre-trained on the KEGG datasets to acquire general features, followed by fine-tuning on plant-derived datasets. Four metrics were chosen for model performance evaluation. The results show that GTC outperforms six other models, including three previously reported machine learning models, on the KEGG dataset. GTC yields an accuracy of 96.75%, precision of 85.14%, recall of 83.03%, and F1_score of 84.06%. Furthermore, an ablation study confirms the indispensability of all the components of the hybrid GTC model. Transfer learning is then employed to leverage the shared knowledge acquired from the KEGG metabolic pathways. As a result, the transferred GTC exhibits outstanding accuracy in predicting plant secondary metabolic pathways with an average accuracy of 98.30% in fivefold cross-validation and 97.82% on the final test. In addition, GTC is employed to classify natural products. It achieves a perfect accuracy score of 100.00% for alkaloids, while the lowest accuracy score of 98.42% for shikimates and phenylpropanoids. The proposed GTC effectively captures molecular features, and achieves high performance in classifying KEGG metabolic pathways and predicting plant secondary metabolic pathways via transfer learning. Furthermore, GTC demonstrates its generalization ability by accurately classifying natural products. A user-friendly executable program has been developed, which only requires the input of the SMILES string of the query compound in a graphical interface.
•Experimental study of methane storage and diffusion in shale.•Pore size distribution was studied using N2 adsorption and SEM.•Bidisperse model was applied to describe the diffusion data.•Sample ...particle size has little effect on gas storage and diffusion measurement.•Moisture reduces gas storage and diffusion rate significantly.
Understanding gas storage and transport mechanisms in shale is crucial for reservoir evaluation and gas production forecast. The shale matrix has a complex pore structure, with sizes ranging from nanometres to micrometres. Although diffusion plays a significant role in shale gas transport in the reservoir, systematic studies of gas diffusion in shale are rare. This paper studied the methane diffusion behaviour of shale based on pore structure, as well as the effects of sample particle size and water on gas adsorption and diffusion. The combined N2 adsorption and SEM experimental results showed that the shale sample had a bimodal pore size distribution. The diffusion data were able to be described adequately by the bidisperse model, and the parameters were consistent with pore size distribution results obtained from the N2 adsorption and SEM results. It was found that both Fickian diffusion and Knudsen diffusion play important roles in shale gas diffusion and they show different gas pressure dependence. Adsorption isotherm and calculated diffusivity showed little particle size dependence. However, gas adsorption and diffusivity were significantly reduced in moist samples, showing that water reduces gas storage capacity and transport rate in shale.
Phosphorylated celluloses (PCFs) were obtained via reaction of microcrystalline cellulose with phosphorous acid in molten urea. Fourier transform infrared spectroscopy and scanning electron ...microscopy were used to observe the chemical structure and microstate of the PCFs. A flame retardant glutaraldehyde cross‐linked poly (vinyl alcohol)/PCF aerogel was fabricated using a melt cross‐link and freeze‐dried method. The results of thermogravimetric analysis confirmed that the thermal stability of the poly(vinyl alcohol) (PVA) aerogels incorporating PCF is more outstanding. The peak of heat release rate (PHRR) and the total heat release (THR) values of the PCA/PCF10 aerogel deceased obviously by 33.8 and 64%, respectively, compared to the corresponding values for the pure PVA aerogel; these changes confirm that the PCA/PCF aerogel had better flame‐retardant properties than the pure PVA aerogel. Moreover, the fire performance index and fire growth index indicate that the introduction of PCF would diminish the occurrence of fire.
Poly(vinyl alcohol)/phosphate cellulose cross‐linked aerogels were designed and prepared for enhancing flame‐retardant properties. The cross‐linked structure favored better thermal performance and higher flame retardant performance compared to pure poly(vinyl alcohol) aerogel.
PDF
