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The galloyl group in catechins was confirmed to be crucial for their health benefits. However, whether the catechins’ galloyl group had a contribution to their anti-inflammation remains unclear. This study investigated the anti-inflammation properties and mechanisms of catechins in RAW264.7 cells by using ELISA, fluorometry, flow cytometer, Western blot, and molecular docking. Results showed that the galloyl group enhanced the inhibitory abilities of catechins on inflammatory cytokines (NO, PGE2, IL-1β, and TNF-α) and ROS release in LPS-induced cells. This suppression was likely mediated by delaying cells from the G0/G1 to the S phase, blocking COX-2 and iNOS via the TLR4/MAPK/NF-κB pathway with PU.1 as an upstream target. The research proved that the existence of galloyl groups in catechins was indispensable for their anti-inflammatory capacities and offered a theoretical basis for the anti-inflammatory mechanism of galloylated catechins. Future research is needed to verify the anti-inflammatory effects of catechins in various sources of macrophages or the Caco-2/RAW264.7 cell co-culture system.

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) stands as one of the pivotal afforestation tree species and timber resources in southern China. Nevertheless, the occurrence of seed abortion and a notably high proportion of astringent seeds significantly curtail the yield and quality of elite seeds, resulting in substantial economic losses. The development of astringent seeds is accompanied by significant physiological and biochemical alterations. Here, the first combined lipidomic and metabolomic analysis was performed to gain a comprehensive understanding of astringent seed traits. A total of 744 metabolites and 616 lipids were detected, of which 489 differential metabolites and 101 differential lipids were identified. In astringent seeds, most flavonoids and tannins, as well as proline and γ-aminobutyric acid, were more accumulated, along with a notable decrease in lipid unsaturation, indicating oxidative stress in the cells of astringent seeds. Conversely, numerous elemental metabolites were less accumulated, including amino acids and their derivatives, saccharides and alcohols, organic acids and nucleotides and their derivatives. Meanwhile, most lipid subclasses, mainly associated with energy storage (triglyceride and diglyceride) and cell membrane composition (phosphatidic acid, phosphatidylcholine, phosphatidylethanolamine), also exhibited significant reductions. These results reflected a disruption in the cellular system or the occurrence of cell death, causing a reduction in viable cells within astringent seeds. Furthermore, only one lipid subclass, sphingosine phosphate (SoP), was more accumulated in astringent seeds. Additionally, lower accumulation of indole-3-acetic acid and more accumulation of salicylic acid (SA) were also identified in astringent seeds. Both SA and SoP were closely associated with the promotion of programmed cell death in astringent seeds. Collectively, our study revealed significant abnormal changes in phytohormones, lipids and various metabolites in astringent seeds, allowing us to propose a model for the development of astringent seeds in Chinese fir based on existing research and our findings. This work enriches our comprehension of astringent seeds and presents valuable bioindicators for the identification of astringent seeds.

With the development of urban underground space and increased infrastructure functions, both the scale of engineering construction and engineering difficulties have increased globally. In the construction of structures in soft strata, especially in coastal areas, the limited bearing capacity of the foundations poses a significant challenge. The composite pile technologies employing an organic combination of the rigid pile andthe flexible column can enable efficient soft ground treatment. In light of prominent global environmental issues, low-carbon energy-saving curing technologies have been rapidly developed for application in geotechnical engineering. This paper discusses progress in research on the mechanical properties of the efficient and low-carbon pile technologies, including the stiffened deep mixing (SDM) column, squeezed branch pile, pre-bored grouting plated nodular (PGPN) pile, precast cement pile reinforced by cemented soil with a variable section (PCCV), and carbonized composite pile (CCP). In addition, it reviews the technical characteristics and recent progress of feasible low-carbon energy-efficient curing technologies. The paper also proposes future directions for theoretical research and technological development of low-carbon pile technologies. The key contribution of this review is to provide insights into efficient and low-carbon pile technologies. In addition, the findings from the study of the pile technologies used in extra-thick soft strata also provide industry practitioners with a comprehensive guide regarding the specific applications and mechanical performance of the pile technologies, which can serve as a stepping stone to facilitate the technological development of the underground space industry.

Urban forest parks play a crucial role in contributing to the urban environment, residential well-being, and social welfare. Visitors’ perception of multi-sensory interactive experiences in urban forest parks is an important source of information for landscape planning. Whilst data elicited from visitors via questionnaires are temporally and spatially restricted, online media provide a public platform for the direct and comprehensive expression of park experiences beyond such restrictions. To look into visitors’ multi-sensory interactive experiences in an urban forest park in China, a total of 7447 reviews of such were collected from four authoritative online platforms using Python, and the ROSTCM tool was used to generate semantic and social networks out of the data set. The results showed that urban forest park visitors’ sensory experiences are dominated by visual and olfactory perceptions, followed by audio-visual and visual-tactile interactions. Among them, visual perception displays the highest degree of specificity and diversity, while tactile and gustatory perceptions are relatively infrequent and singular. The landscapes that affect visitors’ perceptual preferences mainly include floriculture, green vegetation, soundscapes, and sanitation utilities. Moreover, both the fresh air and the agreeable environment have a significant positive impact on visitors’ perceptions. The above findings not only have practical implications for the landscape planning and design of urban forest parks, but also provide theoretical insights into the evaluation of natural landscapes in urban forest parks from the perspective of tourists’ multi-sensory experiences.

Differential evolution of apoptosis, programmed necrosis, and autophagy, parthanatos is a form of cell death mediated by poly(ADP-ribose) polymerase 1 (PARP1), which is caused by DNA damage. PARP1 hyper-activation stimulates apoptosis-inducing factor (AIF) nucleus translocation, and accelerates nicotinamide adenine dinucleotide (NAD+) and adenosine triphosphate (ATP) depletion, leading to DNA fragmentation. The mechanisms of parthanatos mainly include DNA damage, PARP1 hyper-activation, PAR accumulation, NAD+ and ATP depletion, and AIF nucleus translocation. Now, it is reported that parthanatos widely exists in different diseases (tumors, retinal diseases, neurological diseases, diabetes, renal diseases, cardiovascular diseases, ischemia-reperfusion injury...). Excessive or defective parthanatos contributes to pathological cell damage; therefore, parthanatos is critical in the therapy and prevention of many diseases. In this work, the hallmarks and molecular mechanisms of parthanatos and its related disorders are summarized. The questions raised by the recent findings are also presented. Further understanding of parthanatos will provide a new treatment option for associated conditions.

Engineered cementitious composite (ECC) is a unique material, which can significantly contribute to self-healing based on ongoing hydration. However, it is difficult to model and predict the self-healing performance of ECC. Although different machine learning (ML) algorithms have been utilized to predict several properties of concrete, the application of ML on self-healing prediction is considerably rare. This paper aims to provide a comparative analysis on the performance of various machine learning models in predicting the self-healing capability of ECC. These models include four individual methods, linear regression (LR), back-propagation neural network (BPNN), classification and regression tree (CART), and support vector regression (SVR). To improve prediction accuracy, three ensemble methods, namely bagging, AdaBoost, and stacking, were also studied. A series of experimental works on the self-healing performance of ECC samples was conducted, and the results were used to develop and compare the accuracy among the ML models. The comparison results showed that the Stack_LR model had the best predictive performance, showing the highest coefficient of determination (R2), the lowest root-mean-squared error (RMSE), and the smallest prediction error (MAE). Among all individual models studies, the BPNN model performed the best in terms of the RMSE and R2, while SVR performed the best in terms of the MAE. Furthermore, SVR had the smallest prediction error (MAE) for crack widths less than 60 μm or greater than 100 μm, while CART had the smallest prediction error (MAE) for crack widths between 60 μm and 100 μm. The study concluded that the individual and ensemble methods can be used to predict the self-healing of ECC. Ensemble models were able to improve the accuracy of prediction compared to the individual model used as their base learner, i.e., a 2.3% to 4.9% reduction in MAE. However, selecting an appropriate individual and ensemble method is critical. To improve the performance accuracy, researchers should employ different ensemble methods to compare their effectiveness with different ML models.

Optimal fast charging is an important factor in battery management systems (BMS). Traditional charging strategies for lithium-ion batteries, such as the constant current–constant voltage (CC–CV) pattern, do not take capacity aging mechanisms into account, which are not only disadvantageous in the life-time usage of the batteries, but also unsafe. In this paper, we employ the dynamic optimization (DP) method to achieve the optimal charging current curve for a lithium-ion battery by introducing limits on the intercalation-induced stresses and the solid–liquid interface film growth based on an electrochemical–thermal model. Furthermore, the backstepping technique is utilized to control the temperature to avoid overheating. This paper concentrates on solving the issue of minimizing charging time in a given target State of Charge (SoC), while limiting the capacity loss caused by intercalation-induced stresses and film formation. The results indicate that the proposed optimal charging method in this paper offers a good compromise between the charging time and battery aging.

In recent years, offshore wind farms have frequently encountered engineering geological disasters such as seabed liquefaction and scouring. Consequently, in situ monitoring has become essential for the safe siting, construction, and operation of these installations. Current technologies are hampered by limitations in single-parameter monitoring and insufficient probe-penetration depth, hindering comprehensive multi-parameter dynamic monitoring of seabed sediments. To address these challenges, we propose a foldable multi-sensor probe and establish an underwater adaptive continuous penetration system capable of concurrently measuring seabed elevation changes and sediment pore water pressure profiles. The reliability of the equipment design is confirmed through static analysis of the frame structure and sealed cabin. Furthermore, laboratory tests validate the stability and accuracy of the electrical and mechanical sensor measurements. Preliminary tests conducted in a harbor environment demonstrate the system’s effectiveness.