Search

Abstract: Terrestrial groundwater travels through subterranean estuaries before reaching the sea. Groundwater‐derived nutrients drive coastal water quality, primary production, and eutrophication. We determined how dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and dissolved organic nitrogen (DON) are transformed within subterranean estuaries and estimated submarine groundwater discharge (SGD) nutrient loads compiling > 10,000 groundwater samples from 216 sites worldwide. Nutrients exhibited complex, nonconservative behavior in subterranean estuaries. Fresh groundwater DIN and DIP are usually produced, and DON is consumed during transport. Median total SGD (saline and fresh) fluxes globally were 5.4, 2.6, and 0.18 Tmol yr−1 for DIN, DON, and DIP, respectively. Despite large natural variability, total SGD fluxes likely exceed global riverine nutrient export. Fresh SGD is a small source of new nutrients, but saline SGD is an important source of mostly recycled nutrients. Nutrients exported via SGD via subterranean estuaries are critical to coastal biogeochemistry and a significant nutrient source to the oceans.

Fluvalinate is widely used in apiculture as an acaricide for removing Varroa mites, but there have been growing concerns about the negative effects of fluvalinate on honeybees in recent years. Previous research revealed changes in the miRNA and mRNA expression profiles of Apis mellifera ligustica brain tissues during fluvalinate exposure, as well as key genes and pathways. The role of circRNAs in this process, however, is unknown. The goal of this study was to discover the fluvalinate-induced changes in circular RNA (circRNA) expression profiles of brain tissue of A. mellifera ligustica workers. A total of 10,780 circRNAs were detected in A. mellifera ligustica brain tissue, of which eight were differentially expressed between at least two of the four time periods before and after fluvalinate administration, and six circRNAs were experimentally verified to be structurally correct, and their expression patterns were consistent with transcriptome sequencing results. Furthermore, ceRNA analysis revealed that five differentially expressed circRNAs (DECs) (novel_circ_012139, novel_circ_011690, novel_circ_002628, novel_circ_004765, and novel_circ_010008) were primarily involved in apoptosis-related functions by competitive binding with miRNAs. This study discovered changes in the circRNA expression profile of A. mellifera ligustica brain tissue caused by fluvalinate exposure, and it provides a useful reference for the biological function study of circRNAs in A. mellifera ligustica.

Fluvalinate is a widely used and relatively safe acaricide for honeybees, but it still has a negative impact on honeybee colonies. Such negative effects may be related to fluvalinate-induced brain nerve tissue damage, but the detailed molecular regulatory mechanism of this phenomenon is still poorly understood. In this study, we analyzed the miRNA expression profile changes in the brain tissue of Apis mellifera ligustica by miRNA sequencing after fluvalinate treatment. A total of 1,350 miRNAs were expressed in Apis mellifera ligustica brain tissue, of which only 180 were previously known miRNAs in honeybees. Among all known and novel miRNAs, 15 were differentially expressed between at least two of the four time periods before and after fluvalinate administration. Further analysis revealed five significantly enriched KEGG pathways of the differentially expressed miRNA (DEM) potential target genes, namely, “Hippo signaling pathway-fly,” “Phototransduction-fly,” “Apoptosis-fly,” “Wnt signaling pathway,” and “Dorso-ventral axis formation,” which indicates that differentially expressed miRNA function may be related to cell apoptosis and memory impairment in the fluvalinate-treated Apis mellifera ligustica brain. Ame-miR-3477-5p, ame-miR-375-3p, and miR-281-x were identified as key miRNAs. Overall, our research provides new insights into the roles of miRNAs in brain tissue during the process of fluvalinate-induced Apis mellifera ligustica poisoning.

A new 1,3,4-oxadiazole derivative (BPOXD-B8) was synthesized. The emission properties of BPOXD-B8 in different solutions were studied. BPOXD-B8 could form organogels in different solvents, especially in methanol. The gelation and self-assembly properties of BPOXD-B8 were investigated by SEM, X-ray diffraction (XRD), temperature-dependent FTIR, and UV-vis. The main driving forces during self-assembly are π–π interaction and the van der Waals force. In addition, the BPOXD-B8 solution showed fluorescence sensing properties for Fe3+ ions. BPOXD-B8 with a relatively low detection limit (0.079 μM) and relatively small standard deviations (<5%) indicate that the present system is indeed suitable for real-life sample analysis. [ABSTRACT FROM AUTHOR]

Abstract Background The adaptation of organisms to changing environments is self-evident, with the adaptive evolution of organisms to environmental changes being a fundamental problem in evolutionary biology. Bees can pollinate in various environments and climates and play important roles in maintaining the ecological balance of the earth. Results We performed an analysis of 462 Apis cerana (A. cerana) specimens from 31 populations in 11 regions and obtained 39 representative morphological features. We selected 8 A. cerana samples from each population and performed 2b-RAD simplified genome sequencing. A total of 11,506 high-quality single nucleotide polymorphism (SNP) loci were obtained. For these SNPs, the minor allele frequency (MAF) was > 1%, the average number of unique labels for each sample was 49,055, and the average depth was 72.61x. The ratios of the unique labels of all samples were 64.27–86.33%. Conclusions Using 39 morphological characteristics as the data set, we proposed a method for the rapid classification of A. cerana. Using genomics to assess population structure and genetic diversity, we found that A. cerana has a large genetic difference at the ecotype level. A comparison of A. cerana in North China revealed that some physical obstacles, especially the overurbanization of the plains, have isolated the populations of this species. We identified several migration events in North China and Central China. By comparing the differences in the environmental changes in different regions, we found that A. cerana has strong potential for climate change and provides a theoretical basis for investigating and protecting A. cerana.

Rapid expansion of mariculture during past decades has raised substantial concerns about impacts on the coastal environment, notably eutrophication. This study focuses on one of the world's highest density mariculture sites, Sansha Bay, Fujian Province, China, featuring integrated multi-trophic aquaculture practices involving croaker, kelp and oyster, based on examination of nutrient distributions and releases. A two-endmembers-mixing model showed significant addition of dissolved inorganic nitrogen (DIN; 6.9 ± 4.1 μmol L-1) and phosphorus (DIP; 0.45 ± 0.29 μmol L-1) associated with mariculture activities in spring 2020. A mass balance model estimated an annual release of N and P from cage fish farming systems fed with mixed trash fish feed and formulated feed of (2.42 ± 0.15)×104 tons and (5.33 ± 0.37)×103 tons, respectively. Of the total feed input, 52.8 ± 4.7 % of DIN and 33.0 ± 3.7 % of DIP were released into seawater, values much higher than the riverine input and exchange with offshore coastal waters. A co-culture strategy involving kelp and oyster production in 2020 removed (1.08 ± 0.01)×103 tons of N and (1.56 ± 0.08) ×102 tons of P, respectively. Therefore, adjusting feed strategies and improving feed conversion rates could alleviate eutrophication caused by mariculture expansion in this ecosystem. [ABSTRACT FROM AUTHOR]

The Asian honeybee, Apis cerana, is an ecologically and economically important pollinator. Mapping its genetic variation is key to understanding population‐level health, histories and potential capacities to respond to environmental changes. However, most efforts to date were focused on single nucleotide polymorphisms (SNPs) based on a single reference genome, thereby ignoring larger scale genomic variation. We employed long‐read sequencing technologies to generate a chromosome‐scale reference genome for the ancestral group of A. cerana. Integrating this with 525 resequencing data sets, we constructed the first pan‐genome of A. cerana, encompassing almost the entire gene content. We found that 31.32% of genes in the pan‐genome were variably present across populations, providing a broad gene pool for environmental adaptation. We identified and characterized structural variations (SVs) and found that they were not closely linked with SNP distributions; however, the formation of SVs was closely associated with transposable elements. Furthermore, phylogenetic analysis using SVs revealed a novel A. cerana ecological group not recoverable from the SNP data. Performing environmental association analysis identified a total of 44 SVs likely to be associated with environmental adaptation. Verification and analysis of one of these, a 330 bp deletion in the Atpalpha gene, indicated that this SV may promote the cold adaptation of A. cerana by altering gene expression. Taken together, our study demonstrates the feasibility and utility of applying pan‐genome approaches to map and explore genetic feature variations of honeybee populations, and in particular to examine the role of SVs in the evolution and environmental adaptation of A. cerana. [ABSTRACT FROM AUTHOR]

In this study, we propose a new gray model called "normalized beta function gray model". Its main idea is to use the normalized beta function to optimize the linear gray action quantity into a nonlinear form. It is worth mentioning that when solving the nonlinear parameters of the newly proposed model, we construct a nonlinear optimization problem with constraints by taking the mean square error of the model as the objective function, and find the optimal solution under the given precision by using the simulated annealing algorithm. We use the new gray model to predict gasoline consumption and PM2.5 concentration, compared with the other three gray models, the proposed gray model reduces the mean absolute percentage error to 2.99% and 32.75%, respectively, which is 88.67% and 60.25% lower than the maximum value of mean absolute percentage error of four gray models. We also apply the newly proposed gray model to the simulation studies, which shows excellent prediction ability. [ABSTRACT FROM AUTHOR]