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The soil environment plays an important role in urban ecosystems. To study the heavy metal contamination of soil in Beilun District, Ningbo, we collected soil samples from 60 points in urban and peri-urban areas of Beilun District and analyzed the spatiotemporal variation and sources of heavy metal pollution in various land-use types. The results shown that the heavy metal contents in 2015 and 2022 were higher than the background soil values of Ningbo city, and there was an accumulation of heavy metals over these 7 years. The contents of heavy metals in green belts and woodland in 2022 were higher than those in 2015, while there was no significant change in agricultural land. The heavy metal contents in both years were mainly in the order green belts > agricultural land > woodland. The spatiotemporal distribution of heavy metal content showed that heavy metal pollution in Beilun District was concentrated in five industrial areas, and there was a trend toward the disappearance of highly polluted points. But the single-factor pollution index, pollution load index (PLI), and geoaccumulation index (I geo ) indicated that there was no significant heavy metal pollution in Beilun District, and individual elements at specific points showed slight pollution. The source analysis results showed that the main source of Hg is chemical, As is mainly derived from agricultural, Cr, Ni and Cu are mainly derived from natural, the main sources of Zn and Cd are electroplating and machinery activities, and the main source of Pb is traffic. These results specify a reference for future investigation on urban soil heavy metals, and the source apportionment results provide a scientific foundation for subsequent soil heavy metal pollution treatment.

Surface ozone (O3), a critical air pollutant, poses significant challenges in urban environments, as exemplified by the city of Chaozhou in southeastern China. This study employs a novel combination of trend analysis and spatial source attribution techniques to evaluate the long-term dynamics of surface ozone and identify its sources. Utilizing the Kolmogorov–Zurbenko (KZ) filter and percentile regression, we analyzed the temporal trends of daily maximum 8 h moving average ozone (MDA8 O3) concentrations from 2014 to 2023. Our analysis revealed a general long-term downward trend in MDA8 O3 values alongside notable monthly fluctuations, with peak concentrations typically occurring in October and April. Additionally, the percentile regression analysis demonstrated a significant downward trend in MDA8 O3 concentrations across nearly all percentiles, with larger decline rates at higher percentiles, highlighting the effectiveness of local and regional O3 management strategies in Chaozhou. The changes in MDA8 O3 concentrations were mainly influenced by the short-term component, contributing 62.2%, while the contribution of the long-term fraction is relatively small. This suggests a significant influence of immediate meteorological conditions and transient pollution events on local O3 levels. To further elucidate the origins of high O3 concentrations, trajectory cluster analysis, trajectory sector analysis (TSA), and potential source contribution function (PSCF) analysis were conducted. The trajectory cluster analysis revealed that the northeast air mass was the main transport air mass in Chaozhou during the study period, accounting for 39.1% of occurrences. The northeast cluster C with medium-distance trajectories corresponds to higher concentration of O3, which may be the main transport pathway of O3 pollution in Chaozhou. TSA corroborates these findings, with northeast sectors 1, 2, and 3 accounting for 50.3% of trajectory residence time and contributing 52.2% to O3 levels in Chaozhou. PSCF results further indicate potential high O3 sources from the northeast, especially in autumn. This comprehensive analysis suggests that Chaozhou’s elevated O3 levels are influenced by both regional transport from the northeast and local emissions. These findings offer crucial insights into the temporal dynamics of surface O3 in Chaozhou, paving the way for more effective and targeted air quality management strategies.

The extended trading close (ETC) provides institutional investors an opportunity to trade at the closing price after the regular trading session (RTS) and disclosing the order imbalances to other market participants. ETCs exist in the Nasdaq, the SSE STAR, the SZSE ChiNext and the TWSE. To help a risk-averse institutional investor take advantage of the RTS and the ETC for liquidation, we develop a multistage dynamic programming model including the ETC, and derive recursive solutions for the multiple trading days scenario with closed-form solutions for the scenario with only two trading days. We also verify that the ETC is able to mitigate extreme price movements caused by fast liquidation, which is also a goal of the ETC set out by the SSE STAR and the SZSE ChiNext. Finally, we derive three results. First, an institutional investor can reduce execution costs after the introduction of the ETC. Second, a critical trading day exists, and to avoid prematurely revealing trading intentions, the investor should not trade in the ETC until such day. Third, even though the ETC orders submitted by the investor are unfilled, implementation of the ETC encourages the investor to change the liquidation strategy in the RTS, which reduces extreme price movements. In summary, the practical implications of this paper are that the investor should not trade during the ETC on the front few days to avoid prematurely revealing the investor’s trading intention by unfilled orders in the ETC and that introducing the ETC can reduce liquidation costs and extreme price movements.

Background Food intake affects body homeostasis and significantly changes circulating cell-free DNA (cfDNA). However, the source and elimination of postprandial cfDNA is difficult to trace, and it is unknown whether these changes can be revealed by cfDNA fragmentomics based on liquid biopsy. Methods We performed shallow whole-genome sequencing of 30 plasma samples from 10 healthy individuals at fasting and postprandial (30-min and 2-h time points). We assessed the effect of postprandial states on cfDNA fragment size distribution and utilized deconvolutional analysis of end motifs to determine the potential roles of DNA nucleases in cfDNA fragmentation. We correlated the fragmentation index (defined as the ratio of short-to-long fragments) with gene expression to estimate the relative contribution of various cellular and tissue sources to cfDNA. Results Compared to the fasting state, we observed a significant increase in short cfDNA fragments (70–150 bp) and a decrease in long fragments (151–250 bp) at the 30-minute postprandial state, followed by an inverse trend two hours later. Deconvolutional analysis of cfDNA end motifs showed that DNASE1L3 activity decreased at the 30-minute postprandial state, while DNASE1 and DFFB activities increased at the 2-hour postprandial state. We found that the expression of genes related to cellular metabolism and immune responses was upregulated at the postprandial state. Meanwhile, the contribution of cells and tissues involved in metabolic and immune progress to circulating plasma cfDNA was increased. Conclusions The fragmentation of cfDNA is considerably influenced by postprandial states, highlighting the significance of taking postprandial effects into account when evaluating cfDNA as a biomarker. Furthermore, our study reveals the potential application of cfDNA fragmentation features in monitoring metabolic and immune status changes.

Ascorbate peroxidase (APX) is a member of heme-containing peroxidases which catalyze the H2O2-dependent oxidation of a wide range of substrates in plants and animals. As is known, H2O2 acts as a signaling molecule in the regulation of fiber development. Our previous work reported that ascorbate peroxidase 1 (GhAPX1) was important for cotton fiber elongation. However, knowledge about APX gene family members and their evolutionary and functional characteristics in cotton is limited. Here, we report 26 GhAPX genes by genome-wide investigation of tetraploid cotton Gossypium hirsutum. Phylogenetic and gene structure analyses classified these APX members into five clades and syntenic analysis suggested two duplication events. Expression profiling of the 26 APXs revealed that ten members are expressed in cotton fibers. Notably, GhAPX10A, GhAPX10D, GhAPX12A, and GhAPX12D showed high expression levels in 30-day fiber, while GhAPX1A/D, GhAPX3A/D, and GhAPX6A/D showed very low expression levels. The enzyme activity and H2O2 content assays revealed that cotton fiber kept high enzyme activity and the lowest H2O2 level in 30-day fibers, indicating that other than GhAPX1, the newly reported APX members are responsible for the reactive oxygen species homeostasis in the cotton fiber maturation stages. Expression profiling of ten fiber-expressed APXs after phytohormone treatments revealed their regulation patterns by different stimuli, suggesting that GhAPX1, GhAPX12A, and GhAPX12D are responsible to most phytohormone treatments. Our data provided evolutionary and functional information of GhAPX gene family members and revealed that different members are responsible to redox homeostasis during different cotton fiber development stages.

The efficacy of adeno-associated virus (AAV)-based gene therapy is dependent on effective viral transduction, which might be inhibited by preexisting immunity to AAV acquired from infection or maternal delivery. Anti-AAV neutralizing Abs (NAbs) titer is usually measured by in vitro assay and used for patient enroll; however, this assay could not evaluate NAbs’ impacts on AAV pharmacology and potential harm in vivo. Here, we infused a mouse anti-AAV9 monoclonal antibody into Balb/C mice 2 h before receiving 1.2 × 1014 or 3 × 1013 vg/kg of rAAV9-coGAA by tail vein, a drug for our ongoing clinical trials for Pompe disease. The pharmacokinetics, pharmacodynamics, and cellular responses combined with in vitro NAb assay validated the different impacts of preexisting NAbs at different levels in vivo. Sustained GAA expression in the heart, liver, diaphragm, and quadriceps were observed. The presence of high-level NAb, a titer about 1:1000, accelerated vector clearance in blood and completely blocked transduction. The AAV-specific T cell responses tended to increase when the titer of NAb exceeded 1:200. A low-level NAbs, near 1:100, had no effect on transduction in the heart and liver as well as cellular responses, but decreased transduction in muscles slightly. Therefore, we propose to preclude patients with NAb titers > 1:100 from rAAV9-coGAA clinical trials.

This paper proposes a wireless network traffic prediction model based on Bayesian Gaussian tensor decomposition and recurrent neural network with rectified linear unit (BGCP-RNN-ReLU model), which can effectively predict the changes in the upstream and downstream network traffic in a short period of time in the future. The research is divided into two parts: (i) The missing observations are imputed by an algorithm based on Bayesian Gaussian tensor decomposition. (ii) The recurrent neural network is used to forecast the true observations only rather than both true and estimated observations. The results show that, compared with other combined models of missing data imputation and neural networks, the BGCP-RNN-ReLU model proposed in this paper has the smallest prediction error for both the upstream and downstream traffic. The new model achieves better forecasting precision, and thus can help to regulate the load of communication station to reduce resource consumption. Highlights The problem of forecasting wireless network traffic with missing values is divided in two stages to handle. A newly propose d method can more efficiently impute missing values in wireless network traffic data. Simple recurrent neural network obtains better prediction performance than other complex networks.

Background Two-dimensional electrophoresis (2-DE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) are widely used in plant proteomics research. However, these two techniques cannot be simultaneously satisfied by traditional protein extraction methods when investigate cotton leaf proteome. Results Here, we evaluated the efficiency of three different protein extraction methods for 2-DE and LC-MS/MS analyses of total proteins obtained from cotton leaves. The protein yield of the borax/PVPP/phenol (BPP) method (0.14%) was significantly lower than the yields of the trichloroacetic acid/acetone (TCA) precipitation method (1.42%) and optimized TCA combined with BPP (TCA-B) method (0.47%). The BPP method was failed to get a clear 2-DE electrophoretogram. Fifty pairs of protein spots were randomly selected from the 2-DE gels of TCA- and TCA-B-extracted proteins for identification by MALDI TOF/TOF, and the results of 42 pairs were consistent. High-throughput proteomic analysis showed that 6339, 9282 and 9697 unique proteins were identified from the total cotton leaf proteins extracted by the TCA, BPP and TCA-B methods, respectively. Gene Ontology (GO) analysis revealed that the proteins specifically identified by TCA method were primarily distributed in the plasma membrane, while BPP and TCA-B methods specific proteins distributed in the cytosol, indicating the sub-cellular preference of different protein extraction methods. Further, ATP-dependent zinc metalloprotease FTSH 8 could be observed in the 2-DE gels of TCA and TCA-B methods, and could only be detected in the LC-MS/MS results of the BPP and TCA-B methods, showing that TCA-B method might be the optimized choice for both 2-DE and LC-MS/MS. Conclusion Our data provided an improved TCA-B method for protein extraction that is compatible with 2-DE and LC-MS/MS for cotton leaves and similar plant tissues which is rich in polysaccharides and polyphenols.

Visual working memory (VWM) adopts a specific manner of object-based encoding (OBE) to extract perceptual information: Whenever one feature-dimension is selected for entry into VWM, the others are also extracted. Currently most studies revealing OBE probed an ‘irrelevant-change distracting effect’, where changes of irrelevant-features dramatically affected the performance of the target feature. However, the existence of irrelevant-feature change may affect participants’ processing manner, leading to a false-positive result. The current study conducted a strict examination of OBE in VWM, by probing whether irrelevant-features guided the deployment of attention in visual search. The participants memorized an object’s colour yet ignored shape and concurrently performed a visual-search task. They searched for a target line among distractor lines, each embedded within a different object. One object in the search display could match the shape, colour, or both dimensions of the memory item, but this object never contained the target line. Relative to a neutral baseline, where there was no match between the memory and search displays, search time was significantly prolonged in all match conditions, regardless of whether the memory item was displayed for 100 or 1000 ms. These results suggest that task-irrelevant shape was extracted into VWM, supporting OBE in VWM.

The rubber grass Taraxacum kok-saghyz (TKS) contains large amounts of natural rubber (cis-1,4-polyisoprene) in its enlarged roots and it is an alternative crop source of natural rubber. Natural rubber biosynthesis (NRB) and storage in the mature roots of TKS is a cascade process involving many genes, proteins and their cofactors. The TKS genome has just been annotated and many NRB-related genes have been determined. However, there is limited knowledge about the protein regulation mechanism for NRB in TKS roots. We identified 371 protein species from the mature roots of TKS by combining two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS). Meanwhile, a large-scale shotgun analysis of proteins in TKS roots at the enlargement stage was performed, and 3545 individual proteins were determined. Subsequently, all identified proteins from 2-DE gel and shotgun MS in TKS roots were subject to gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and most proteins were involved in carbon metabolic process with catalytic activity in membrane-bounded organelles, followed by proteins with binding ability, transportation and phenylpropanoid biosynthesis activities. Fifty-eight NRB-related proteins, including eight small rubber particle protein (SRPP) and two rubber elongation factor(REF) members, were identified from the TKS roots, and these proteins were involved in both mevalonate acid (MVA) and methylerythritol phosphate (MEP) pathways. To our best knowledge, it is the first high-resolution draft proteome map of the mature TKS roots. Our proteomics of TKS roots revealed both MVA and MEP pathways are important for NRB, and SRPP might be more important than REF for NRB in TKS roots. These findings would not only deepen our understanding of the TKS root proteome, but also provide new evidence on the roles of these NRB-related proteins in the mature TKS roots.