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Oxidized low‐density lipoprotein (oxLDL), a key component in atherosclerosis and hyperlipidemia, is a risk factor for atherothrombosis in dyslipidemia, yet its mechanism is poorly understood. In this study, we used oxLDL‐induced human aortic endothelial cells (HAECs) and high‐fat diet (HFD)‐fed mice as a hyperlipidemia model. Phosphatidylserine (PS) exposure, cytosolic Ca2+, reactive oxygen species (ROS), and lipid peroxidation were measured by flow cytometer. TMEM16F expression was detected by immunofluorescence, western blot, and reverse transcription polymerase chain reaction. Procoagulant activity (PCA) was measured by coagulation time, intrinsic/extrinsic factor Xase, and thrombin generation. We found that oxLDL‐induced PS exposure and the corresponding PCA of HAECs were increased significantly compared with control, which could be inhibited over 90% by lactadherin. Importantly, TMEM16F expression in oxLDL‐induced HAECs was upregulated by enhanced intracellular Ca2+ concentration, ROS, and lipid peroxidation, which led to PS exposure. Meanwhile, the knockdown of TMEM16F by short hairpin RNA significantly inhibited PS exposure in oxLDL‐induced HAECs. Moreover, we observed that HFD‐fed mice dramatically increased the progress of thrombus formation and accompanied upregulated TMEM16F expression by thromboelastography analysis, FeCl3‐induced carotid artery thrombosis model, and western blot. Collectively, these results demonstrate that TMEM16F‐mediated PS exposure may contribute to prothrombotic status under hyperlipidemic conditions, which may serve as a novel therapeutic target for the prevention of thrombosis in hyperlipidemia. Highlights: Oxidized low‐density lipoproteins (oxLDL) could increase phosphatidylserine (PS) exposure and procoagulant activity (PCA) of human aortic endothelial cells (HAECs) in a TMEM16F‐dependent manner.Increased intracellular Ca2+ and oxidative stress may contribute to TMEM16F‐mediated phospholipid scrambling.Hyperlipidemia exhibited a prothrombotic phenotype, which was likely related to TMEM16F‐mediated PS exposure on HAECs.Inhibition of TMEM16F or PS could be a novel therapeutic strategy to alleviate the thromboembolic complication of hyperlipidemia. [ABSTRACT FROM AUTHOR]

Lidar observations of metal layers play a significant role in research on the chemistry and dynamics of the mesosphere and lower thermosphere. This work reports on Fe lidar observations conducted in Beijing and Mohe. Utilizing the same laser emission system, a 1064 nm seed laser was injected into an Nd: YAG laser to generate a single longitudinal-mode pulse 532 nm laser, which pumped a dye laser to produce a 572 nm laser. The 572 nm laser and the remaining 1064 nm fundamental frequency laser passed through a sum–frequency module to generate a 372 nm laser to detect the Fe layer. According to a total of 52.6 h of observations for 10 nights in Beijing, the Fe layer has an average column density of 1.24 × 1010 cm−2, an RMS width of 4.4 km and a centroid altitude of 89.4 km. In Mohe, observed for 16 nights and a total of 91.5 h, the Fe layer has an average column density of 1.08 × 1010 cm−2, an RMS width of 4.6 km and a centroid altitude of 89.5 km. The probability of the occurrence of sporadic Fe layers was 42.4% in Beijing and 29.4% in Mohe. Compared to simultaneously observed Na layers, the occurrence probabilities of sporadic Fe layers were higher than those of sporadic Na layers in both stations. Based on the two cases observed in Beijing, it is conjectured that the formation mechanism of sporadic metal layers above approximately 100 km has a more significant influence on sporadic Fe layers than on sporadic Na layers. The lower thermospheric Fe layers with densities significantly larger than those of the main layer were observed during two nights in Mohe. This work contributes to the refinement of the global distribution of Fe layers and provides abundant observational data for the modeling and study of the metal layers. [ABSTRACT FROM AUTHOR]

Electric vehicles with hub motors have integrated the motor into the wheel, which increase the unsprung mass of the vehicle, and intensifies the vibration of the underspring components. The motor excitation during driving also intensifies the wheel vibration. The coupling effect between the two makes the performance of electric vehicles deteriorate. The article employed a disc-type permanent-magnet motor as the hub motor, taking into consideration the increase in sprung mass caused by the hub motor and the adverse effects of vertical vibration from motor excitation. Based on random road-surface excitation, and considering the secondary excitation caused by wheel motor drive and vehicle-road coupling, a coupled-dynamics model of a semi-active-suspension vehicle-road system for vertical vehicle motion is investigated under multiple excitations. Using body acceleration, suspension deflection, and dynamic tire load as evaluation indicators, a BP neural network PID controller based on the sparrow search algorithm optimization is proposed for the semi-active-suspension system. Compared with PID control and particle swarm optimization (PSO-BPNN-PID), the research findings indicate that the optimized semi-active suspension significantly improves the ride comfort of hub-motor electric vehicles, and meets the requirements for control performance under different vehicle driving conditions. [ABSTRACT FROM AUTHOR]

In March 2020, an all-solid-state dual-wavelength narrow-band lidar system was deployed. A total of 226 nights spanning from March 2020 to July 2022 were employed in order to investigate the seasonal variations of calcium atoms and ions in the mesosphere over Beijing (40.41°N, 116.01°E). The Ca+ layer shows general annual variation, while a semiannual variation is observed on the Ca layer. The calcium atomic column densities ranged from 2.0 × 106 to 1.1 × 108 cm−2, and the calcium ion column densities ranged from 1.6 × 106 to 4.2 × 108 cm−2. The mean centroid heights of Ca+ and Ca are 98.6 km and 93.0 km, respectively, and the centroid heights of Ca+ and Ca are mostly influenced by annual variations. The seasonal variation in the Ca+ and Ca layers in Beijing exhibits similarities to that of Kühlungsborn (54°N). While the peak density of Ca+ in Beijing are similar to those observed in Kühlungsborn, the peak density of the Ca layer in Beijing is about half of that reported in the Ca layer at 54°N. We provide an explanation for the disparities in the column abundance and centroid altitude of the Ca layer between Yanqing and Kühlungsborn, discussing variations in neutralization among different metal ions. [ABSTRACT FROM AUTHOR]

Regulating the composition and microstructure of nanomaterials is a major challenge in the development of high-performance materials for electromagnetic wave (EMW) absorption. This paper introduces a new lightweight EMW-absorbing material Co@N/C with a yolk–shell structure and compositions of ferromagnetic metal and carbon materials. The minimum reflection loss (RL min) of the as-designed Co@N/C nanospheres with a filler loading of 25 wt% reaches −67.68 dB and the effective absorption bandwidth of a 1.9 mm thickness is 5.3 GHz. The exceptional absorption performance of the EMW absorption is primarily achieved through the synergistic effect between the Co–carbonaceous material and the yolk–shell structure, which optimizes the impedance matching. The polarization loss, conductivity loss, magnetic loss, and multiple scattering mainly contribute to the excellent EMW-absorption ability of the materials. The proposed method for regulating the structure and morphology of Co@N/C can efficiently construct high-performance EMW absorbers. [Display omitted] • Yolk-Shell structure nanocomposite with excellent electromagnetic wave absorption properties was synthesized. • An excellent reflection loss (RL) of −67.68 dB at 15.88 GHz with an ultra-thin thickness (1.7 mm). • Effective absorption bandwidth (<−10 dB) up to 5.3 GHz under a single thickness (1.9 mm). [ABSTRACT FROM AUTHOR]

Spermidine, a natural polyamine, has been proven antioxidant function, but its pathway and mechanism of action remain unclear. Based on the oxidative stress model by 3-nitropropionic acid (3-NPA), the study explored the pathways by spermidine to rescue oxidative stress via autophagic process in goose granulosa cells by RNA-seq and RNA interference. In transcriptional regulation, in addition to KEGG pathways related to cell proliferation and differentiation, lots of KEGG pathways associated with inflammation, metabolism, and signaling were also significantly enriched in 3-NPA vs. 3-NPA + spermidine treatments. Six key genes (JUN , CD44 , KITLG , RND2 , BMP4 and KALRN) involved in spermidine-mediated anti-oxidative stress were screened. Furthermore, the experimental results showed that spermidine (80 μmol/L) significantly increased autophagic gene expression in goose granulosa cells, while EP300 -siRNA or MAP1S -siRNA also significantly increased autophagic process. The autophagic gene expressions were no difference between EP300 -siRNA and EP300 -siRNA + spermidine treatments, although spermidine significantly increased autophagic process of granulosa cells compared to MAP1S -siRNA alone. In addition, inhibition of mTOR pathway significantly increased autophagic gene expression, which was further enhanced by spermidine in combined with mTOR inhibitor. These results suggest that spermidine can alleviate oxidative stress by inducing autophagy regulated by EP300, MAP1S and mTOR as well as regulating other independent gene expressions in goose granulosa cells. • Spermidine improves oxidative stress in goose GCs by regulating autophagy and other independent gene expressions. • Transcriptomic techniques confirmed the target genes related to spermidine anti-oxidative stress by spermidine. • The autophagy pathway involved in anti-oxidative stress by spermidine was validated by gene interference analyses. [ABSTRACT FROM AUTHOR]

• A neural-network-based framework is proposed for performance prediction and inverse design of a porous auxetic metamaterial. • The real-time prediction towards the auxeticity and stiffness can improve the inverse design. • The framework can be extended to structural material design with complex characteristics. Auxetic metamaterials are widely applied in energy-absorbing systems and soft robots due to their superior mechanical properties. The properties of auxetic metamaterials are determined by their architectures, which means it is feasible to obtain metamaterials with target performance through structural design. This paper proposes a framework with neural networks to generate a nearly real-time prediction of the auxeticity and stiffness simultaneously of porous materials. Trained neural networks accurately provide computationally inexpensive predictions on response histories. Based on the prediction database given by the neural network, the parametric analysis can be conducted to provide the mutual influence and trend relationship of auxeticity and stiffness of the porous metamaterial. In addition, inverse design can also be conducted for seeking optimal architecture in terms of the auxeticity and stiffness quickly and accurately. With the method, the target nonlinear properties can be accurately and rapidly designed for porous metamaterials. The relative error of neural network predictions is less than 1.5% compared with experimental tests, and less than 8.0% compared with the numerical simulations obtained by the finite element method. The proposed framework can be extended to more structural materials to provide design guideline. [Display omitted] [ABSTRACT FROM AUTHOR]

As is known to all, environmental barrier coating requires high bonding strength and low thermal conductivity to extend the service life of ceramic matrix composite (CMC) components. In this work, a novel nanostructured Lu 2 Si 2 O 7 /Lu 2 SiO 5 environmental barrier coating was deposited successfully using as-synthetized Lu 2 Si 2 O 7 feedstocks and Lu 2 SiO 5 feedstocks. Meanwhile, the microstructure, bonding strength and thermal conductivity of Lu 2 Si 2 O 7 /Lu 2 SiO 5 coating were analysed systematically. Results indicate that the nanostructured Lu 2 Si 2 O 7 /Lu 2 SiO 5 environmental barrier coating processes a bi-model microstructure. The Lu 2 Si 2 O 7 /Lu 2 SiO 5 coating is relatively dense and the Lu 2 Si 2 O 7 layer and Lu 2 SiO 5 layer achieve the mechanical interlocking. The bonding strength of Lu 2 Si 2 O 7 /Lu 2 SiO 5 coating is 14.9 MPa. In addition, the thermal conductivity of Lu 2 Si 2 O 7 /Lu 2 SiO 5 coating is 0.59 W·m−1·K−1–1.24 W·m−1·K−1 from 25 °C to 1200 °C, which is visibly lower than that of Lu 2 SiO 5 coating. • A novel nanostructured Lu 2 Si 2 O 7 /Lu 2 SiO 5 environmental barrier coating was fabricated successfully. • The bonding strength of nanostructured Lu 2 Si 2 O 7 /Lu 2 SiO 5 coating is 14.9 MPa. • The thermal conductivity of Lu 2 Si 2 O 7 /Lu 2 SiO 5 coating is 0.59 W·m−1·K−1–1.24 W·m−1·K−1, which is lower than that of Lu 2 SiO 5 coating. [ABSTRACT FROM AUTHOR]

[Display omitted] • It proposed a detection method for the structural and quantitative analysis of GABA. • The limit of detection for GABA could reach up to 0.428% based on its THz spectrum. • The calculated results were in good agreement with their experimental results. • The vibrational motions of each THz and Raman peaks were quantitatively decomposed. γ-aminobutyric (GABA) is the most important inhibitory neurotransmitier in vertebrate central nervous systems. The content level of GABA is related to the different degree of malignancy gliomas. Thus, it can be considered a promising glioma biomarker. In this paper, the spectroscopic properties of GABA have been characterized by combining the THz spectroscopy with low-wavenumber Raman spectroscopy. The experimental results showed that, GABA exhibited three absorption peaks and three refractive index peaks in the range of 0.6–2.1 THz. The limit of detection can reach up to 0.428 % based on the absorption coefficient at the peak of 2.04 THz. Moreover, the low-wavenumber Raman spectrum of GABA showed seven characteristic peaks at 41.0, 50.8, 58.8, 77.2, 98.8, 115.6, 141.2 cm−1 in 0–150 cm−1 region. Moreover, the THz and low-wavenumber theoretical spectra of GABA were simulated with solid-state density function theory, respectively. The calculated results were in good agreement with the experimental observations. On the basis of calculated result, the vibrational motions of each THz and Raman characteristic modes were quantitatively decomposed by analytical mode-decoupling method, where the contribution percentages of external translation, external librations and intramolecular vibration of each vibration modes were analyzed Furthermore, the low-frequency characteristics of GABA was analyzed by combining the THz and low-wavenumber Raman spectroscopy. It is beneficial for the structural information analysis and quantitative identification of biomarker GABA in early stage diagnosis of glioma. [ABSTRACT FROM AUTHOR]

[Display omitted] • It provides Raman characteristics of the two specific brain tissues after bTBIs. • Four algorithms are performed to classify different bTBIs at different time points. • The highest accuracy is up to 95.3% for diagnosis of bTBIs at different time points. • It realizes diagnosis of bTBIs by combining Raman spectroscopy with machine learning. Blast-induced traumatic brain injury (bTBI) is a kind of nervous system disease, which results in a major health and economic problem to society. However, the rapid and label-free detection method with high sensitivity is still in great demand for the diagnosis of bTBI, especially for mild bTBI. In this paper, we report a new strategy for bTBI diagnosis through hippocampus and hypothalamus tissues based on Raman spectroscopy. The spectral characteristics of hippocampus and hypothalamus tissues of experimental bTBI in rats have been investigated for mild and moderate degrees at 3 h, 6 h, 24 h, 48 h, 72 h after blast exposure. The results show that the Raman spectra of mild and moderate bTBIs in 300–1700 cm−1 and 2800–3000 cm−1 regions exhibit significant differences at different time points compared with the control group. The main reason is the content change of proteins and lipids in hippocampus and hypothalamus tissues after bTBI. Moreover, four machine learning algorithms are used to automatically identify mild and moderate bTBIs at different time points (a total of 11 groups). The highest diagnostic accuracies are up to 95.3% and 88.5% based on Raman spectra of hippocampus and hypothalamus tissue, respectively. In addition, the classification performance of linear discriminant analysis classifier has been improved after data fusion. It is suggested that there has great potential as an alternative method for high-sensitive, rapid, label-free, economical diagnosis of bTBI. [ABSTRACT FROM AUTHOR]