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Abstract Acrossocheilus fasciatus is a stream-dwelling fish species of the Barbinae subfamily. It is valued for its colorfully striped appearance and delicious meat. This species is also characterized by apparent sexual dimorphism and toxic ovum. Biology and aquaculture researches of A. fasciatus are hindered by the lack of a high-quality reference genome. Here, we report chromosome-level genome assemblies of the male and female A. fasciatus. The HiFi-only genome assemblies for both female and male individuals were 899.13 Mb (N50 length of 32.58 Mb) and 885.68 Mb (N50 length of 33.06 Mb), respectively. Notably, a substantial proportion of the assembled sequences, accounting for 96.15% and 98.35% for female and male genomes, respectively, were successfully anchored onto 25 chromosomes utilizing Hi-C data. We annotated the female assembly as a reference genome and identified a total of 400.62 Mb (44.56%) repetitive sequences, 27,392 protein-coding genes, and 35,869 ncRNAs. The high-quality male and female reference genomes will provide genomic resources for developing sex-specific molecular markers, inform single-sex breeding, and elucidate genetic mechanisms of sexual dimorphism.

Elucidating the temporal process of immune remodeling under immunosuppressive treatment after liver transplantation (LT) is critical for precise clinical management strategies. Here, we performed a single-cell multi-omics analysis of peripheral blood mononuclear cells (PBMCs) collected from LT patients (with and without acute cellular rejection [ACR]) at 13 time points. Validation was performed in two independent cohorts with additional LT patients and healthy controls. Our study revealed a four-phase recovery process after LT and delineated changes in immune cell composition, expression programs, and interactions along this process. The intensity of the immune response differs between the ACR and non-ACR patients. Notably, the newly identified inflamed NK cells, CD14+RNASE2+ monocytes, and FOS-expressing monocytes emerged as predictive indicators of ACR. This study illuminates the longitudinal evolution of the immune cell landscape under tacrolimus-based immunosuppressive treatment during LT recovery, providing a four-phase framework that aids the clinical management of LT patients.

The emergence of new coronaviruses poses a significant threat to animal husbandry and human health. Porcine epidemic diarrhea virus (PEDV) is considered a re-emerging porcine enteric coronavirus, which causes fatal watery diarrhea in piglets. Currently, there are no effective drugs to combat PEDV. Drug repurposing screens have emerged as an attractive strategy to accelerate antiviral drug discovery and development. Here, we screened 206 natural products for antiviral activity using live PEDV infection in Vero cells and identified ten candidate antiviral agents. Among them, Tubercidin, a nucleoside analog derived from Streptomyces tubercidicus, showed promising antiviral activity against PEDV infection. Furthermore, we demonstrated that Tubercidin exhibited significant antiviral activity against both classical and variant PEDV. Time of addition assay showed that Tubercidin displayed a significant inhibitory effect on viral post-entry events but not during other periods. Molecular docking analysis indicated that Tubercidin had better docking efficiency and formed hydrophobic interactions with the active pocket of RNA-dependent RNA polymerase (RdRp) of PEDV and other nidoviruses. Additionally, Tubercidin can effectively suppress other porcine nidoviruses, such as SADS-CoV and PRRSV, demonstrating its broad-spectrum antiviral properties. In summary, our findings provide valuable evidence for the antiviral activity of Tubercidin and offer insights into the development of new strategies for the prevention and treatment of coronavirus infections.

Chrysanthemum is one of the four major cut flowers in the world, with high ornamental and economic value. Fragrance is an important ornamental character of chrysanthemum flowers, especially those consumed as tea and other foods, and the flower fragrance is the major determinant of the commercial value of chrysanthemum cultivars. Currently, however, the research on chrysanthemum flower fragrance is mainly focused on the composition and content of fragrant compounds, and a clear classification of fragrance types is lacking. Here, we divided chrysanthemum fragrance into six categories based on sensory evaluation and determined the identity and content of fragrant compounds of chrysanthemum accessions representative of each fragrance type by GC-MS. In addition, we analyzed the conserved aromatic substances responsible for the fruity fragrance type chrysanthemum with multi-functional development potential, providing a theoretical basis for creating new chrysanthemum germplasm with specific fragrance types. The results of this study can accelerate the breeding process of chrysanthemum accessions with new fragrance types.

BackgroundLiver cancer is the sixth most commonly diagnosed cancer and the third leading cause of cancer-related death worldwide. Hepatocellular carcinoma accounts for an estimated 90% of all liver cancers. Many enzymes of the GPAT/AGPAT family are required for the synthesis of triacylglycerol. Expression of AGPAT isoenzymes has been reported to be associated with an increased risk of tumorigenesis or development of aggressive phenotypes in a variety of cancers. However, whether members of the GPAT/AGPAT gene family also influence the pathophysiology of HCC is unknown.MethodsHepatocellular carcinoma datasets were obtained from the TCGA and ICGC databases. Predictive models related to the GPAT/AGPAT gene family were constructed based on LASSO-Cox regression using the ICGC-LIRI dataset as an external validation cohort. Seven immune cell infiltration algorithms were used to analyze immune cell infiltration patterns in different risk groups. IHC, CCK-8, Transwell assay, and Western blotting were used for in vitro validation.ResultsCompared with low-risk patients, high-risk patients had shorter survival and higher risk scores. Multivariate Cox regression analysis showed that risk score was a significant independent predictor of overall survival (OS) after adjustment for confounding clinical factors (p < 0.001). The established nomogram combined risk score and TNM staging to accurately predict survival at 1, 3, and 5 years in patients with HCC with AUC values of 0.807, 0.806, and 0.795, respectively. This risk score improved the reliability of the nomogram and guided clinical decision-making. In addition, we comprehensively analyzed immune cell infiltration (using seven algorithms), response to immune checkpoint blockade, clinical relevance, survival, mutations, mRNA expression-based stemness index, signaling pathways, and interacting proteins related to the three core genes of the prognostic model (AGPAT5, LCLAT1, and LPCAT1). We also performed preliminary validation of the differential expression, oncological phenotype, and potential downstream pathways of the three core genes by IHC, CCK-8, Transwell assay, and Western blotting.ConclusionThese results improve our understanding of the function of GPAT/AGPAT gene family members and provide a reference for prognostic biomarker research and individualized treatment of HCC.

We profile genome-wide histone 3 lysine 27 acetylation (H3K27ac) of 3 major brain cell types from hippocampus and dorsolateral prefrontal cortex (dlPFC) of subjects with and without Alzheimer’s Disease (AD). We confirm that single nucleotide polymorphisms (SNPs) associated with late onset AD (LOAD) show a strong tendency to reside in microglia-specific gene regulatory elements. Despite this significant colocalization, we find that microglia harbor more acetylation changes associated with age than with amyloid-β (Aβ) load. In contrast, we detect that an oligodendrocyte-enriched glial (OEG) population contains the majority of differentially acetylated peaks associated with Aβ load. These differential peaks reside near both early onset risk genes (APP, PSEN1, PSEN2) and late onset AD risk loci (including BIN1, PICALM, CLU, ADAM10, ADAMTS4, SORL1, FERMT2), Aβ processing genes (BACE1), as well as genes involved in myelinating and oligodendrocyte development processes. Interestingly, a number of LOAD risk loci associated with differentially acetylated risk genes contain H3K27ac peaks that are specifically enriched in OEG. These findings implicate oligodendrocyte gene regulation as a potential mechanism by which early onset and late onset risk genes mediate their effects, and highlight the deregulation of myelinating processes in AD. More broadly, our dataset serves as a resource for the study of functional effects of genetic variants and cell type specific gene regulation in AD.

Achieving seamless integration between virtual objects and real scenes has always been an important issue in augmented reality (AR) research. To achieve this, it is necessary to provide virtual objects with real-time and accurate lighting conditions from a real scene. Therefore, the purpose of this study is to realize lighting consistency rendering for real-time AR systems in outdoor environments, aiming to enhance the user’s sense of immersion. In this paper, we propose a lighting consistency technique for real-time AR systems in outdoor environments based on multi-source geographical information (MGI). Specifically, we introduce MGI into the study of lighting consistency and construct a comprehensive database to store and manage the acquired MGI data. Based on this, we proposed a sky radiance model driven using the MGI. Finally, we utilized the sky radiance model along with light sensor data to render the virtual objects in outdoor scenes. The experimental results show that the shadow angular error is reduced to 5.2°, and the system frame rate is increased to 94.26. This means that our method achieves a high level of realism in the fusion of virtual objects and real scenes while ensuring a high frame rate in the system. With this technology, users can conveniently and extensively realize the lighting consistency rendering of real-time AR systems in outdoor scenes using mobile devices.

Monitoring grassland growth in large areas usually needs multiple images from different sensors or on different dates to cover the study area completely. Images from different sensors or on different dates need consistency correction to eliminate the sharp differences between images. The main contribution of this study is to promote a method for consistency correction of images on different days by constructing a linear regression equation of land cover types and the classification pixel mean. Taking a prefecture-level area in China as a test area, the consistency corrected images were applied for monitoring grassland growth. The results showed the following. First, compared with the normal correction equation constructed for two images, taking all features into account, the coefficient of determination of the equation corrected by the land cover types was improved, and the root mean square error was also significantly reduced. Secondly, the areas of consistency in the corrected image were improved compared with the original image, with an improvement rate of 21% for images from the same sensor and 25% for images from different sensors. The pixel average was much closer to the benchmark images, indicating that the corrected image was more consistent than the original image. Thirdly, when applied for monitoring grassland growth, consistency correction can solve the problem of misjudging grassland degradation. Grassland that was judged to be degraded using direct imagery, in fact, showed stable growth after consistency correction, and this type accounted for 7.33% of the regional grassland area. The seasonal characteristics of grass growth in the region were also obtained by monitoring the growth of grass in the region throughout the year. The application test showed that an effective image consistency correction method can improve the accuracy of grassland growth monitoring across a large area.

Abstract Recently, flexible strain sensors have been intensively studied in order to meet the growing demands of detecting multiscale mechanical deformations. However, it remains a big challenge to integrate high stretchability and high sensitivity in a strain sensor simultaneously. In this study, a highly stretchable and sensitive strain sensor is successfully fabricated by constructing ionogel/silver synergistic conductive network. The transmetalation reaction is utilized to transform the copper atoms in the copper/ionogel nanocomposite into more silver atoms with larger radius, which eliminates the interspace among the nanoparticles, and therefore a silver/ionogel nanocomposite with high conductivity is obtained. Owing to the fragility of the conductive network, the obtained nanocomposite possesses high sensitivity. In addition, as the polymer substrate, the conductive ionogel can connect the crack of the silver conductive network during stretching, endowing the nanocomposite with high stretchability. Hence, the obtained strain sensor exhibits a high sensitivity in a wide sensing range and can detect various human activities. Therefore, this strategy can be envisioned as promising strategy for fabricating high‐performance strain sensors and other flexible electronics.

Abstract Introduction Based on the schema theory advanced by Rumelhart and Norman, we shed light on the individual variability in brain dynamics induced by hybridization of learning methodologies, particularly alternating unsupervised learning and supervised learning in language acquisition. The concept of “schema” implies a latent knowledge structure that a learner holds and updates as intrinsic to his or her cognitive space for guiding the processing of newly arriving information. Methods We replicated the cognitive experiment of Onnis and Thiessen on implicit statistical learning ability in language acquisition but included additional factors of prosodic variables and explicit supervised learning. Functional magnetic resonance imaging was performed to identify the functional network connections for schema updating by alternately using unsupervised and supervised artificial grammar learning tasks to segment potential words. Results Regardless of the quality of task performance, the default mode network represented the first stage of spontaneous unsupervised learning, and the wrap‐up accomplishment for successful subjects of the whole hybrid learning in concurrence with the task‐related auditory language networks. Furthermore, subjects who could easily “tune” the schema for recording a high task precision rate resorted even at an early stage to a self‐supervised learning, or “superlearning,” as a set of different learning mechanisms that act in synergy to trigger widespread neuro‐transformation with a focus on the cerebellum. Conclusions Investigation of the brain dynamics revealed by functional connectivity imaging analysis was able to differentiate the synchronized neural responses with respect to learning methods and the order effect that affects hybrid learning.

Porcine deltacoronavirus (PDCoV) mainly causes severe diarrhea and intestinal pathological damage in piglets and poses a serious threat to pig farms. Currently, no effective reagents or vaccines are available to control PDCoV infection. Single-chain fragment variable (scFv) antibodies can effectively inhibit virus infection and may be a potential therapeutic reagent for PDCoV treatment. In this study, a porcine phage display antibody library from the peripheral blood lymphocytes of piglets infected with PDCoV was constructed and used to select PDCoV-specific scFv. The library was screened with four rounds of biopanning using the PDCoV N protein, and the colony with the highest affinity to the PDCoV N protein was obtained (namely, N53). Then, the N53-scFv gene fragment was cloned into plasmid pFUSE-hIgG-Fc2 and expressed in HEK-293T cells. The scFv-Fc antibody N53 (namely, scFv N53) was purified using Protein A-sepharose. The reactive activity of the purified antibody with the PDCoV N protein was confirmed by indirect enzyme-linked immunosorbent assay (ELISA), western blot and indirect immunofluorescence assay (IFA). Finally, the antigenic epitopes that the scFv N53 recognized were identified by a series of truncated PDCoV N proteins. The amino acid residues 82GELPPNDTPATTRVT96 of the PDCoV N protein were verified as the minimal epitope that can be recognized by the scFv-Fc antibody N53. In addition, the interaction between the scFv-Fc antibody N53 and the PDCoV N protein was further analyzed by molecule docking. In conclusion, our research provides some references for the treatment and prevention of PDCoV.

Southwest China has abundant grassland resources, but they are mainly scattered across fragmented mountainous terrain with frequently cloudy and rainy weather, making their accurate identification by remote sensing challenging. Therefore, the goal of this study was to generate prefecture-level city-scale mountainous grassland distribution data to support the development of sustainable grassland husbandry. Here, we proposed a sample selection method and comprehensively utilized multi-source data to obtain the quasi-10 m southwest grassland distribution data. The sample selection method was to first determine the sample selection range based on multi-source land use/cover database, and then to randomly select the samples under the constraint of secondary land use types, multiple factors of terrain and pure pixels. This method can deal with the difficulty in identifying the fragmented grassland distribution caused by steep mountains and hills. In addition, a multispectral time series dataset was constructed based on the fusion of Landsat 8 OLI and Sentinel-2A/B data due to cloudy and rainy weather and was used as one of the input features along with synthetic aperture radar Sentinel-1 time series data and the terrain multi-factor data. Finally, a remote sensing method to accurately identify grassland distribution in southwest China was constructed based on the Google Earth Engine (GEE) platform. Taking Zhaotong City, a prefecture-level city in Yunnan Province, as an example, a thematic map of grassland distribution with an overall accuracy of 88.21% was obtained using the above method. This map has been used by the local government of Zhaotong City in their planning of the development of sustainable grassland husbandry.

Porcine deltacoronavirus (PDCoV) is a novel coronavirus that causes diarrhea in nursing piglets. Studies showed that PDCoV uses porcine aminopeptidase N (pAPN) as an entry receptor, but the infection of pAPN-knockout cells or pigs with PDCoV revealed that pAPN might be not a critical functional receptor, implying there exists an unidentified receptor involved in PDCoV infection. Herein, we report that sialic acid (SA) can act as an attachment receptor for PDCoV invasion and facilitate its infection. We first demonstrated that the carbohydrates destroyed on the cell membrane using NaIO4 can alleviate the susceptibility of cells to PDCoV. Further study showed that the removal of SA, a typical cell-surface carbohydrate, could influence the PDCoV infectivity to the cells significantly, suggesting that SA was involved in the infection. The results of plaque assay and Western blotting revealed that SA promoted PDCoV infection by increasing the number of viruses binding to SA on the cell surface during the adsorption phase, which was also confirmed by atomic force microscopy at the microscopic level. In in vivo experiments, we found that the distribution levels of PDCoV and SA were closely relevant in the swine intestine, which contains huge amount of trypsin. We further confirmed that SA-binding capacity to PDCoV is related to the pre-treatment of PDCoV with trypsin. In conclusion, SA is a novel attachment receptor for PDCoV infection to enhance its attachment to cells, which is dependent on the pre-treatment of trypsin on PDCoV. This study paves the way for dissecting the mechanisms of PDCoV–host interactions and provides new strategies to control PDCoV infection.

Volatile composition is an important feature that determines flavor, which actively affects the overall evaluation of chrysanthemum tea. In this study, HS-GC-IMS (headspace-gas chromatography-ion mobility spectrometry) was performed to characterize the volatile profiles of different chrysanthemum tea subtypes. Forty-seven volatiles of diverse chemical nature were identified and quantified. Partial least squares discriminant analysis (PLS-DA) revealed that four chrysanthemum teas were distinct from each other based on their volatile compounds. Furthermore, this work provides reference methods for detecting novel volatile organic compounds in chrysanthemum tea plants and products.

Travel mode identification is one of the essential steps in travel information detection with Global Positioning System (GPS) survey data. This paper presents a Support Vector Classification (SVC) model for travel mode identification with GPS data. Genetic algorithm (GA) is employed for optimizing the parameters in the model. The travel modes of walking, bicycle, subway, bus, and car are recognized in this model. The results indicate that the developed model shows a high level of accuracy for mode identification. The estimation results also present GA’s contribution to the optimization of the model. The findings can be used to identify travel mode based on GPS survey data, which will significantly enhance the efficiency and accuracy of travel survey and data processing. By providing crucial trip information, the results also contribute to the modeling and analyzing of travel behavior and are readily applicable to a wide range of transportation practices.

The quantification of ascorbic acid (AA), dopamine (DA), and uric acid (UA) has been an important area of research, as these molecules’ determination directly corresponds to the diagnosis and control of diseases of nerve and brain physiology. In our research, graphene oxide (GO) with nano pores deposited with gold nanoparticles were self-assembled to form three-dimensional (3D) Au/holey-graphene oxide (Au/HGO) composite structures. The as-prepared 3DAu/HGO composite structures were characterized for their structures by X-ray diffraction, Raman spectrum, scanning electron microscopy, and transmission electron microscopy coupled with cyclic voltammograms. Finally, the proposed 3DAu/HGO displayed high sensitivity, excellent electron transport properties, and selectivity for the simultaneous electrochemical determination of AA, DA and UA with linear response ranges of 1.0⁻500 μM, 0.01⁻50 μM and 0.05⁻50 μM respectively. This finding paves the way for graphene applications as a biosensor for detecting three analytes in human serum.

We profile genome-wide histone 3 lysine 27 acetylation (H3K27ac) of 3 major brain cell types from hippocampus and dorsolateral prefrontal cortex (dlPFC) of subjects with and without Alzheimer’s Disease (AD). We confirm that single nucleotide polymorphisms (SNPs) associated with late onset AD (LOAD) show a strong tendency to reside in microglia-specific gene regulatory elements. Despite this significant colocalization, we find that microglia harbor more acetylation changes associated with age than with amyloid-β (Aβ) load. In contrast, we detect that an oligodendrocyte-enriched glial (OEG) population contains the majority of differentially acetylated peaks associated with Aβ load. These differential peaks reside near both early onset risk genes (APP, PSEN1, PSEN2) and late onset AD risk loci (including BIN1, PICALM, CLU, ADAM10, ADAMTS4, SORL1, FERMT2), Aβ processing genes (BACE1), as well as genes involved in myelinating and oligodendrocyte development processes. Interestingly, a number of LOAD risk loci associated with differentially acetylated risk genes contain H3K27ac peaks that are specifically enriched in OEG. These findings implicate oligodendrocyte gene regulation as a potential mechanism by which early onset and late onset risk genes mediate their effects, and highlight the deregulation of myelinating processes in AD. More broadly, our dataset serves as a resource for the study of functional effects of genetic variants and cell type specific gene regulation in AD. [ABSTRACT FROM AUTHOR]

Background: Porcine parvovirus (PPV) is a single-stranded DNA virus that causes porcine reproductive failure. It is of critical importance to study PPV pathogenesis for the prevention and control of the disease. NS1, a PPV non-structural protein, is participated in viral DNA replication, transcriptional regulation, and cytotoxicity. Our previous research showed that PPV can activate nuclear factor kappa B (NF-κB) signaling pathway and then up-regulate the expression of interleukin (IL)-6. Objectives: Herein, the purpose of this study is to determine whether the non-structural protein NS1 of PPV also has the same function. Methods: Real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR), enzyme-linked immunosorbent assay, western blot, immunofluorescence assay and small interfering RNA (siRNA) were used. Results: Our findings demonstrated that PPV NS1 protein can up-regulate the expression levels of IL-6 and tumor necrosis factor-alpha in a dose-dependent manner. Moreover, PPV NS1 protein was found to induce the phosphorylation of IκBa, then leading to the phosphorylation and nuclear translocation of NF-κB. In addition, the NS1 protein activated the upstream pathways of NF-κB. Meanwhile, TLR2-siRNA assay showed TLR2 plays an important role in the activation of NF-κB signaling pathway induced by PPV-NS1. Conclusions: These findings indicated that PPV NS1 protein induced the up-regulated of IL-6 expression through activating the TLR2 and NF-κB signaling pathways. In conclusion, these findings provide a new avenue to study the innate immune mechanism of PPV infection. [ABSTRACT FROM AUTHOR]

Porcine deltacoronavirus (PDCoV) is an emerging swine enteric coronavirus that causes diarrhea in piglets. However, the biological characteristics of PDCoV are unclear. In this study, the hemagglutination (HA) abilities of two PDCoV strains (CH-01 and HNZK-04) were investigated. Our results showed that PDCoV has the ability to agglutinate rabbit erythrocytes after virion pretreatment with trypsin or neuraminidase. Additionally, the HA assay results showed a significant positive correlation with the infectious viral titer. Our results suggest that assessing the HA activity of PDCoV may be a useful diagnostic method for investigating and surveilling PDCoV infections. [ABSTRACT FROM AUTHOR]

A key strategy of sustainable transportation, parking pricing can directly contribute to decreased greenhouse gas emissions and air pollution. This paper describes an optimal structure of parking rates in terms of parking locations and time of day. A two-level parking model based on game theory is established using parking survey data collected in Beijing in 2014. The model was estimated based on Stackelberg game and the Nash equilibrium. Using the two-level parking model, the optimal structure of parking rates for inside/outside business zones and during peak/off-peak hours was calculated. In addition, the relationship between the government (which represents the public benefit) and car users, as well as the relationships among car users in the parking system were investigated. The results indicate that equilibrium among all of the agents in the parking system can be obtained using the proposed parking rate structure. The findings provide a better understanding of parking behavior, and the two-level parking model presented in the paper can be used to determine the optimal parking rate to balance the temporal and spatial distribution of parking demand in urban areas. This research helps reduce car use and the parking-related cruising time and thus contributes to the reduction of carbon emissions and air pollution. [ABSTRACT FROM AUTHOR]