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Osteoporosis is currently the most prevalent bone disorder worldwide and is characterized by low bone mineral density and an overall increased risk of fractures. To treat osteoporosis, a range of drugs targeting bone homeostasis have emerged in clinical practice, including anti-osteoclast agents such as bisphosphonates and denosumab, bone formation stimulating agents such as teriparatide, and selective oestrogen receptor modulators. However, traditional clinical medicine still faces challenges related to side effects and high costs of these types of treatments. Nanomaterials (particularly gold nanoparticles [AuNPs]), which have unique optical properties and excellent biocompatibility, have gained attention in the field of osteoporosis research. AuNPs have been found to promote osteoblast differentiation, inhibit osteoclast formation, and block the differentiation of adipose-derived stem cells, which thus is believed to be a novel and promising candidate for osteoporosis treatment. This review summarizes the advances and drawbacks of AuNPs in their synthesis and the mechanisms in bone formation and resorption in vitro and in vivo, with a focus on their size, shape, and chemical composition as relevant parameters for the treatment of osteoporosis. Additionally, several important and promising directions for future studies are also discussed, which is of great significance for prevention and treatment of osteoporosis.

Peptide-based fluorescent probes have found widespread applications in biomedical research, including bio-imaging, disease diagnosis, drug discovery, and image-guided surgery. Their favorable properties-such as small molecular size, low toxicity, minimal immunogenicity, and high targeting specificity-have contributed to their growing utility in both basic research and translational medicine. This review provides a comprehensive overview of recent advances in peptide-based fluorescent probes, emphasizing design strategies, biological targets, and diverse functional applications. Key areas of focus include the integration of molecular targeting with imaging capabilities, the emergence of multimodal imaging techniques, and the development of activatable probes responsive to specific biological stimuli. Applications are discussed in the context of tumor cell membrane recognition, subcellular organelle targeting, non-cancer disease diagnosis, and detection of both metal ions and non-metal ions. Notably, responsive probes for reactive oxygen species (ROS) and other biologically relevant non-metal ions are also highlighted, underscoring their diagnostic and therapeutic potential. The review also addresses key limitations-such as poor in vivo stability, limited targeting accuracy, and delivery efficiency-and outlines future directions including smart peptide probe platforms, self-reporting systems, and high-throughput screening based on peptide libraries to accelerate next-generation probe development.

Background Oil palm ( Elaeis guineensis ), a tropical crop, is highly sensitive to temperature fluctuations, with low temperatures significantly limiting its growth, development, and geographical distribution. Understanding the adaptive mechanisms of oil palm under low-temperature stress is essential for developing cold-tolerant varieties. This study focused on analyzing the physiological and metabolomic responses of annual thin-shell oil palm seedlings to low-temperature exposure (8 °C) for different time periods: 0 h (CK), 0.5 h (CD05), 1 h (CD1), 2 h (CD2), 4 h (CD4), and 8 h (CD8). Results Physiological analysis showed a significant increase in the activity of antioxidant enzymes, such as superoxide dismutase (SOD) and peroxidase (POD), highlighting the activation of oxidative stress defense mechanisms. Concurrently, elevated relative conductivity, indicated cell membrane damage, a common consequence of cold-induced oxidative stress. Metabolomic profiling using LC-MS/MS revealed significant changes in metabolite composition, with differential metabolites predominately enriched in key metabolic pathways such as arginine and proline metabolism, glycine, serine, and threonine metabolism, plant hormone biosynthesis, and flavonoid biosynthesis pathways. Notable metabolites such as citric acid, L-aspartic acid, L-tryptophan, and vitexin showed significant accumulation, indicating their roles in enhancing cold tolerance through improved antioxidant defenses, promoting osmoregulation, and stabilizing cellular structures. Correlation analysis further emphasized the importance of flavonoids and plant hormones in the cold stress response. In particular, vitexin, isovitexin, and apigenin 6-C-glucoside were significantly enriched, suggesting their contribution to antioxidant and stress signaling networks. Furthermore, metabolites involved in amino acid metabolism, including L-glutamic acid, sarcosine, and proline, were upregulated, supporting enhanced protein synthesis and cellular repair under stress. This metabolic reprogramming correlated with physiological improvements, as evidenced by increased relative conductivity and post cold exposure growth recovery. Conclusion This study provides critical insights into the physiological and metabolic adaptations of oil palm to cold stress, emphasizing the significant role of secondary metabolites—such as flavonoids, amino acids, and plant hormones—in enhancing cold tolerance. Theses metabolites contribute to oxidative stress protection, osmotic regulation, and cell wall stabilization enabling the plant to better withstand with low temperature condition. The findings provide a strong foundation for molecular research and breeding initiatives aimed at developing cold tolerant oil palm varieties, a crop of siginificant economic value. By combining metabolomic profiling with physiological analyses, provides a holistic understanding of the adaptive mechanisms in oil palm under cold stress.This integrated approach identifies key metabolic pathways that can be targeted in breeding programs to enhance cold resilience, paving the way for improved crop performance in challenging environments.

In this paper, a state estimation method of distributed electric drive articulated vehicle dynamics parameters based on the forgetting factor unscented Kalman filter with singular value decomposition (SVD-UKF) is proposed. The 7DOF nonlinear dynamics model of a distributed electric drive articulated vehicle is established. The unscented Kalman filter algorithm is the foundation, with singular value decomposition replacing the Cholesky decomposition. A forgetting factor is introduced to dynamically adapt the observation noise covariance matrix in real time, resulting in a centralized parameter state estimator for the articulated vehicle. The proposed parameter state estimation method based on the forgetting factor SVD-UKF is simulated and compared with the unscented Kalman filter (UKF) estimation method. Key dynamic parameters are estimated, such as the lateral and longitudinal velocities and accelerations, angular velocity, articulated angle, wheel speeds, and longitudinal and lateral tire forces of both the front and rear vehicle bodies. The results show that the proposed forgetting factor SVD-UKF method outperforms the traditional UKF method. Furthermore, a prototype vehicle test is conducted to compare the estimated values of various dynamic parameters with the actual values, demonstrating minimal errors. This verifies the effectiveness of the proposed dynamic parameter estimation method for articulated vehicles.

Coconut meat and coconut water have garnered significant attention for their richness in healthful flavonoids. However, the dynamics of flavonoid metabolites in coconut water during different developmental stages remain poorly understood. This study employed the metabolomics approach using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate the changes in flavonoid metabolite profiles in coconut water from two varieties, ‘Wenye No.5’(W5) and Hainan local coconut (CK), across six developmental stages. The results showed that a total of 123 flavonoid metabolites including chalcones, dihydroflavonoids, dihydroflavonols, flavonoids, flavonols, flavonoid carboglycosides, and flavanols were identified in the coconut water as compared to the control. The total flavonoid content in both types of coconut water exhibited a decreasing trend with developmental progression, but the total flavonoid content in CK was significantly higher than that in W5. The number of flavonoid metabolites that differed significantly between the W5 and CK groups at different developmental stages were 74, 74, 60, 92, 40 and 54, respectively. KEGG pathway analysis revealed 38 differential metabolites involved in key pathways for flavonoid biosynthesis and secondary metabolite biosynthesis. This study provides new insights into the dynamics of flavonoid metabolites in coconut water and highlights the potential for selecting and breeding high-quality coconuts with enhanced flavonoid content. The findings have implications for the development of coconut-based products with improved nutritional and functional properties.

Ancient canal towns in Jiangnan have become important tourist destinations due to their unique water town scenery and historical value. Creating a unique tourist image boosts these ancient towns’ competitive edge in tourism and contributes significantly to their preservation and growth. The vast amount of data from social media has become an essential source for uncovering tourism perceptions. This study takes two ancient towns in Shanghai, Zhaojialou and Fengjing, as case study areas. In order to explore and compare the destination images of the towns, in the perception of tourists and in official publicity, machine learning approaches like word embedding and K-means clustering are adopted to process the comments on Sina Weibo and publicity articles, and statistical analysis and correspondence analysis are used for comparative study. The results reveal the following: (1) Using k-means clustering, destination perceptions were categorized into 16 groups spanning three dimensions, “space, activity, and sentiment”, with the most keywords in “activity” and the fewest in “sentiment”. (2) The perception of tourists often differs significantly from the official promotional materials. Official promotions place a strong emphasis on shaping the image of ancient towns based on their historical resources, presenting a more general picture. Tourist perception, which is fragmented, highlights emerging elements and the experiential activities, along with the corresponding emotional experiences. (3) Comparing the two towns, Fengjing Ancient Town stands out, with more diverse tourist perceptions and richer emotional experiences. This underscores the effectiveness of tourism activities that use space as a media to evoke emotions, surpassing the impact of the spaces themselves.

Lignans play a crucial role in maintaining plant growth, development, metabolism and stress resistance. Computed tomography (CT) imaging technology can be used to explore the internal structure and morphology of plants, and understanding the correlation between the two is highly significant. In this study, the content of lignan metabolites in coconut water was determined using liquid chromatography. The internal structure data of coconut fruit was obtained by CT scanning, and the relationship between lignan metabolites and CT image data at different developmental stages was evaluated using partial least square (PLS) regression. The results showed that the total lignan content in coconut water initially decreased, then increased, and gradually decreased after the maturity stage. The Wenye No. 5 variety exhibited higher levels of Epiturinol, Turbinol, Isobarinin-9′-o-glucoside, 5′-methoxy-rohanoside, Rohan rosin-4,4′-di-o-glucoside, turbinol-4-O-glucoside, cycloisoperinolin-4-O-glucoside compared to local coconuts. Coconut meat had the greatest effect on Rohan rosin-4,4′-di-o-glucoside, coconut water on Daphne, and coconut shell and coconut fiber on Larinin-4′-o-glucoside. The data from different parts of coconut fruit’s images showed a significant correlation with the content of lignan metabolites. This study has preliminarily explored the correlation between non-destructive testing of coconut fruit and its development process of coconut fruit, providing a new approach and method for further research on non-destructive testing of coconut fruit development.

With the continuous progress of technology, computed tomography (CT) technology has expanded from medicine to agriculture and other industries. With the advantages of non-destructiveness, high resolution, and high precision, CT technology shows great application potential in the agricultural field. However, there are still some problems with this technology that need to be solved. This paper aims to show the application of CT technology in the agricultural field, find technical challenges, and put forward specific countermeasures, so that CT technology can be better applied in the agricultural field. This paper summarizes the application of CT technology in the quality detection of agricultural products, disease and insect pest identification, seed screening, soil analysis, and precision agriculture management, and focuses on the current challenges and the countermeasures, and looks into the role of this technology in promoting agricultural development in the future. Despite various challenges, CT technology has far more advantages than disadvantages, and it is expected to become an indispensable part of all the links of agricultural production and promote the development of precision agriculture and smart agriculture.

Pathogenesis-related (PR) proteins play an important role in the disease resistance response. To better understand the function of rice PR proteins, we examined the expressions of ten PR proteins in rice leaves at different developmental stages with or without the interaction between rice and Xanthomonas oryzae pv. oryzae (Xoo). The results showed that most of the PR proteins were expressed in rice leaves in normal growth conditions, suggesting that they play a role in rice growth. Six out of ten PR proteins (PR1, PR2, PR3, PR4b, PR8, and PR-pha) showed enhanced expression in Xa21-mediated resistance responses at late stages after inoculation with Xoo. The remaining four PR proteins (PR5, PR6, PR15, and PR16) did not show changes in expression in the resistance response. The expressions of PR proteins in the resistance reaction were further compared with those in the susceptible reaction and a mock treatment. Interestingly, several of the PR proteins were expressed at the highest levels in the susceptible reaction and at the lowest levels in the mock treatment. Among the other four PR proteins, PR5 and PR16 showed changes in the abundance only in the susceptible response, while PR6 and PR15 showed no detectable difference in expression. These data provide fundamental knowledge about the expression of PR proteins in the interaction between rice and Xoo.

The present study aimed to investigate the serum levels of adiponectin (APN) and adiponectin receptor 1 (AdipoR1) in patients with type 2 diabetes mellitus (T2DM) combined with macrovascular complications (MVC), as well as their correlation with clinical parameters. A total of 60 T2DM patients were divided into 2 groups according to the presence of MVC: T2DM + MVC group (n=30) and T2DM group (n=30). Additionally, 30 healthy people were selected as control group (NC group). Clinical data and biological parameters were detected and recorded. T test was performed to compare the differences between two groups, and the results were corrected using Bonferroni method. Meanwhile, the correlation analysis and multiple stepwise regression analysis were used to analyze the association of APN and AdipoR1 with clinical factors. The levels of APN and AdipoR1 were significantly decreased in T2DM group and T2DM + MVC group compared with NC group, with the lowest value in T2DM + MVC group (all P<0.01). Serum APN levels were positively correlated with FINS and TG (r = 0.412, 0.316, respectively; both P<0.05), and negatively correlated with SBP, DBP and LDL-C (r = -0.292, -0.383, -0.334, respectively; all P<0.05). Serum levels of AdipoR1 were positively correlated with APN (r = 0.726, P<0.01), and negatively correlated with BMI, SBP, DBP, FBG, TC and LDL-C (r = -0.440, -0.446, -0.374, -0.444, -0.344, -0.709, respectively; all P<0.01). Serum levels of APN and AdipoR1 are significantly lower in T2DM group and T2DM + MVC group, showing lowest value in T2DM + MVC group. APN and AdipoR1 levels may influence glucose and lipid metabolism in T2DM patients.