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Objective: This study aimed to comprehensively analyze metabolites in Lycium fruits and identify differential metabolites among different Lycium species for the purpose of providing a reference for in-depth exploitation and utilization of Lycium fruits of different species. Methods: Metabolites in the dried fruits of Lycium ruthenicum Murr and Lycium barbarum L. var. auranticarpum K. F. Ching were identified and compared by widely targeted metabolomic analysis based on ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Results: A total of 1 098 metabolites were detected belonging to 12 classes including amino acids and their derivatives, phenolic acids, flavonoids, alkaloids and lipids, among which phenolic acids, flavonoids and alkaloids accounted for the highest proportions. Through principal component analysis (PCA) and cluster analysis, it was found that 235 differential metabolites were up-regulated and 252 differential metabolites were down-regulated in L. ruthenicum Murr compared with L. barbarum L. var. auranticarpum K. F. Ching. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the differential metabolites between the two Lycium species were mainly involved in the biosynthesis of flavonoids, tropane, piperidine and pyridine alkaloids, secondary metabolites, and ABC transport. Conclusion: Lycium fruits of different species have significant differences in the contents of metabolites. This study provides some theoretical guidance for the development and utilization of Lycium ruthenicum Murr and Lycium barbarum L. var. auranticarpum K. F. Ching.

Simple Summary: The fruit fly, Neoceratitis asiatica Becker, is a frugivorous pest that causes substantial losses in the production of the goji berry, Lycium barbarum L. Identifying its distribution is significant for the monitoring and prevention of the pest. In this study, the MaxEnt model with optimized parameters was employed to predict the current and future (2050s and 2070s) distribution of the pest. We found that temperature and precipitation were the primary environmental factors influencing its distribution. The suitable habitats were predominantly distributed in northwestern China under various climate scenarios, and the projected suitable area in the future generally exhibited a decrease compared with the current projections. Climate warming affects the growth and development of pests, resulting in changes in their geographical distribution, which increases the difficulty in terms of prevention and control. The fruit fly, Neoceratitis asiatica (Becker), is a predominant frugivorous pest that causes serious yield loss in the goji berry, Lycium barbarum L. In recent years, with the expansion of cultivation area, the damage induced by the pest has become increasingly severe, significantly impeding the production of the goji berry. In this study, the potential suitable habitats of N. asiatica under current and future climate scenarios were simulated and predicted using the optimal MaxEnt model, based on the screening distribution records and environmental factors. The changes in the pest distribution under climate change were determined using ArcGIS. The results showed that the best combination of parameters for MaxEnt were feature combination (FC) = LQPT and regularization multiplier (RM) = 1. The dominant environmental factors influencing pest distribution were mean temperature of driest quarter, mean temperature of coldest quarter and precipitation of coldest quarter. Under different climate conditions, the suitable habitats of the pest primarily ranged between 27°–47° N and 73°–115° E. Under current climate conditions, the area of moderately and highly suitable habitats was 42.18 × 104 km2, and mainly distributed in Inner Mongolia (13.68 × 104 km2), Gansu (9.40 × 104 km2), Ningxia (5.07 × 104 km2), Qinghai (4.10 × 104 km2), and Xinjiang (3.97 × 104 km2) Provinces. Under future climate scenarios, the suitable area was projected to be lower than the current ones, except SSP245–2050s and SSP370–2070s, and the centroids of suitable habitats were mainly shifted to the northeast, except SSP370–2050s and SSP585–2070s. Our results provide valuable guidance for the monitoring and management of N. asiatica, as well as the selection of pest-free goji berry cultivation sites. [ABSTRACT FROM AUTHOR]

Picea Mill. species are important components of boreal and subalpine forests. They have a wide geographical range in the Northern Hemisphere, extending from the Eurasian continent to North America. In this study, publications on Picea species from 2002 to 2016 were identified via the Web of Science (WoS) and the China National Knowledge Infrastructure (CNKI) databases, and subjected to relationship network visualization using CiteSpace software. This study represents the first such analysis of Picea and provides a reference for bibliometrics in forest tree species research. The results show that the total number of publications on Picea archived in WoS was 20,958 and that the number of papers published annually has increased over time, peaking at 1725 in 2013. The studies were mainly conducted in North America, Europe and Asia; among them, Canada published the most papers and showed the strongest betweenness centrality (0.11). Among research institutions, the Swedish University of Agricultural Sciences in Uppsala had the highest publication record. The research contributions of the Chinese Academy of Sciences, the Chinese Academy of Forestry, and Beijing Forestry University have improved rapidly in recent years, greatly enhancing the international impact of Chinese research in this field. The research contents were grouped into five categories: forest ecosystems, pest resistance, extraction and functional analyses of active ingredients from various plant organs, nursery and afforestation techniques, and timber quality research. In China, the number of papers from the CNKI database was 4532, increasing at an even pace. The research topics on Picea included forest ecosystems, seedling and afforestation techniques, basic studies on individual species and populations, and pests and diseases. Within and outside China, hotspots in Picea research included the relationships between Picea and environmental factors, and the genomic sequences of Picea. [ABSTRACT FROM AUTHOR]

Image synthesis is a critical task in various computer vision technologies, and lots of methods tried to translate semantic images into realistic ones for controllable synthesis. With the increasing image resolution, networks are becoming larger, and applications of related methods are restricted. To alleviate the problem, we propose a lightweight mutable network for semantic image synthesis. The network is based on generative adversarial networks. We introduce the feature pyramid architecture to the generator and reduce the hidden node numbers. We also design a mutable scheme where the pyramid will involve fewer layers for smaller images. To improve the performance of the lightweight generator, we further propose a weighted discriminator and a refined loss. The experiments on several public datasets show that our method is effective and achieves competitive performance, proving that a small network can also achieve high-quality semantic image synthesis. [ABSTRACT FROM AUTHOR]

Wolfberry, esteemed as a traditional Chinese medicinal material and functional food, is replete with nutrients and boasts a diverse array of health benefits, including hypoglycemic, antitumor, antioxidant, anti-inflammatory, and immune-enhancing properties. Notably, inflammation is a pivotal factor in the onset and progression of numerous diseases. Despite this, there is a paucity of research on the comprehensive evaluation of the components found in different wolfberries, and the exploration of their primary active components is limited. To address this issue, we conducted a comprehensive targeted metabolomics analysis, employing statistical methods such as principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), KEGG pathway analysis, and volcano plots to delineate the compositional differences among red, black, and yellow wolfberries. Furthermore, we investigated the anti-inflammatory effects of their primary components through in vitro experiments. Our analysis revealed a total of 1,104 chemical compositions in the three wolfberries, with alkaloids, phenolic acids, flavonoids, and lipids being the predominant nutritional components. KEGG enrichment analysis indicated that these compositions were primarily involved in the biosynthesis of secondary metabolites, ABC transport, and galactose metabolism pathway. Moreover, our study demonstrated that quercetin exhibited dose-dependent anti-inflammatory activity in LPS-stimulated HUVECs. It effectively inhibited the production of inflammatory factors such as TNF-α, MCP-1, and IL-1β, while also down-regulating the gene and protein expression levels of ICAM-1 and VCAM-1. In conclusion, our findings indicate that there are variations in compositions among the three wolfberries, with flavonoids being the most abundant, and in vitro studies also confirmed the anti-inflammatory potential of quercetin. It is worth noting that Lycium ruthenicum contains higher levels of antioxidant components and possesses greater nutritional value, providing valuable insights for the future development and utilization of the three wolfberries., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Lan, Duan, Qi, Almezgagi, Fan and Ma.)