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Traditional methods for identifying endocrine-disrupting chemicals (EDCs) that activate androgen receptors (AR) are costly, time-consuming, and low-throughput. This study developed a knowledge-based deep neural network model (AR-DNN) to predict AR-mediated adverse outcomes on female zebrafish fertility. This model started with chemical fingerprints as the input layer and was implemented through a five-layer virtual AR-induced adverse outcome pathway (AOP). Results indicated that the AR-DNN effectively and accurately screens new reproductive toxicants (AUC = 0.94, accuracy = 0.85), providing potential toxicity pathways. Furthermore, 1477 and 2448 chemicals that could lead to infertility were identified in the plastic additives list (PLASTICMAP, n = 7112) and the Inventory of Existing Chemical Substances in China (IECSC, n = 17741), respectively. Colourants containing steroid-like structures are the major active plastic additives that might lower female zebrafish fertility through AR binding, DNA binding, and transcriptional activation. While active IECSC chemicals primarily have the same fragments, such as benzonitrile, nitrobenzene, and quinolone. The predicted toxicity pathways were consistent with existing fish evidence, demonstrating the model’s applicability. This knowledge-based approach offers a promising computational toxicology strategy for predicting and characterising the endocrine-disrupting effects and toxic mechanisms of organic chemicals, potentially leading to more efficient and cost-effective screening of EDCs.

A mixed nitrate (NO3−) and ammonium (NH4+) supply can promote root growth in maize (Zea mays), however, the changes in root morphology and the related physiological mechanism under different N forms are still unclear. Here, maize seedlings were grown hydroponically with three N supplied in three different forms (NO3− only, 75/25 NO3−/NH4+ and NH4+ only). Compared with sole NO3− or NH4+, the mixed N supply increased the total root length of maize but did not affect the number of axial roots. The main reason was the increased total lateral root length, while the average lateral root (LR) length in each axle was only slightly increased. In addition, the average LR density of 2nd whorl crown root under mixed N was also increased. Compared with sole nitrate, mixed N could improve the N metabolism of roots (such as the N influx rate, nitrate reductase (NR) and glutamine synthase (GS)enzyme activities and total amino content of the roots). Experiments with exogenously added NR and GS inhibitors suggested that the increase in the average LR length under mixed N was related to the process of N assimilation, and whether the NR mediated NO synthesis participates in this process needs further exploration. Meanwhile, an investigation of the changes in root-shoot ratio and carbon (C) concentration showed that C transportation from shoots to roots may not be the key factor in mediating lateral root elongation, and the changes in the sugar concentration in roots further proved this conclusion. Furthermore, the synthesis and transportation of auxin in axial roots may play a key role in lateral root elongation, in which the expression of ZmPIN1B and ZmPIN9 may be involved in this pathway. This study preliminarily clarified the changes in root morphology and explored the possible physiological mechanism under a mixed N supply in maize, which may provide some theoretical basis for the cultivation of crop varieties with high N efficiency.

Abstract The traditional flood hazard assessment system for emergency departments is based on the average hazard index of administrative regions. However, this approach may overlook errors with significant hazards caused by the transition from watershed hazard maps to administrative hazard maps. In our study, we propose an innovative approach that utilizes fuzzy sets to represent flood risk grades, incorporating the upper and lower boundaries of membership variety to effectively indicate higher and lower risks errors, respectively. The introduction of fuzzy set risk grades not only incorporates conventional information but also addresses local risk errors caused by the conversion, enabling Emergency Departments to allocate disaster prevention funds accurately for all risk spots. The fund allocation coefficient, based on fuzzy risk grades, strongly correlates with the proportion of flood‐affected populations over time, highlighting the robustness of utilizing fuzzy set risk grades.

To explore the molecular mechanisms of the Litopenaeus vannamei response to infection by Photobacterium damselae, reveal its immune response and energetic metabolic effect, and provide a valuable genetic data source for the scientific prevention and control of Vibrio infection, transcriptomic analysis, RT-qPCR, and physiological and biochemical tests were conducted. The results showed that the expression of key genes involved in lipid and carbohydrate transport, such as apolipoprotein and TPS, was upregulated after pathogenic infection, which brought the accumulation of triacylglycerol and trehalose into the hemolymph. Additionally, the pathogenic infection selectively triggered an immune response in infected L. vannamei, activating certain immune pathways, such as the serpins and MAPK pathways. The pathogenic infection suppressed the activity of phenoloxidase (PO), and the prophenoloxidase (PPO) cascade responses were suppressed by the invasive bacteria. This paper will help us understand the energetic metabolism, immune response, and activation of the immune recognition response after pathogenic infection by P. damselae, and it lays a theoretical foundation for the biological prevention and control of P. damselae infection.

Influenza A viruses (IAVs) continue to cause tremendous economic losses to the global animal industry and respiratory diseases and deaths among humans. The nuclear import of the vRNP complex, composed of polymerase basic protein 1 (PB1), polymerase basic protein 2 (PB2), polymerase acidic protein (PA), nucleoprotein (NP), and viral RNA, is essential for the efficient replication of IAV. Host factors involved in this process can be targeted for the development of countermeasures against IAV infection. Here, we found that Ankyrin Repeat and BTB Domain Containing 1 (ABTB1) promotes the replication of IAV, and positively regulates the nuclear import of the vRNP complex. ABTB1 did not interact directly with NP, indicating that ABTB1 plays an indirect role in facilitating the nuclear import of the vRNP complex. Immunoprecipitation and mass spectrometry revealed that Tripartite Motif Containing 4 (TRIM4) interacts with ABTB1. We found that TRIM4 relies on its E3 ubiquitin ligase activity to inhibit the replication of IAV by targeting and degrading NP within the incoming vRNP complex as well as the newly synthesized NP. ABTB1 interacted with TRIM4, leading to TRIM4 degradation through the proteasome system. Notably, ABTB1-mediated degradation of TRIM4 blocked the effect of TRIM4 on NP stability, and largely counteracted the inhibitory effect of TRIM4 on IAV replication. Our findings define a novel role for ABTB1 in aiding the nuclear import of the vRNP complex of IAV by counteracting the destabilizing effect of TRIM4 on the viral NP protein.

The aim of this study was to investigate the dynamic changes in the microbial communities of both the environment and gut of Litopenaeus vannamei, as well as to elucidate the mechanisms underlying microbial community assembly in greenhouse farming. 16S rDNA high-throughput sequencing and bioinformatics methods were used to carry out the research on the community structure of the microorganisms under greenhouse culture conditions in water, sediment, and gut microorganisms; correlations pertaining to environmental factors; the feasibility of using Source Tracker; and the mechanisms of community construction. The results show that the dominant microorganisms in water, sediment, and gut farming in a greenhouse environment varied and were subject to dynamic change. A variety of beneficial microbiota such as Bacillus were found in the gut, whereas a variety of microorganisms such as Marivita and Pseudomonas, which function as nitrogen and phosphorus removers, were present in water. Source Tracker and environmental correlation analyses showed that changes in the gut were associated with eutrophication indicators (total nitrogen, total phosphorus, ammonia nitrogen) and changes in environmental microorganisms (in water and sediment). The results of the community-building mechanism analysis show that stochastic processes determine the community-building directions of environmental and gut microorganisms. These findings will help us to understand the microbiota characteristics of shrimp ponds under greenhouse farming conditions, and the complex interactions between the shrimp gut and the environmental microbiota and environmental variables, as well as revealing the changing rules of the gut microbiota.

Abstract Background and Aims The Coronavirus Disease‐19 (COVID‐19) is posing an ongoing threat to human health. Patients of diabetic foot ulcer (DFU) are susceptible to COVID‐19‐induced adverse outcomes. Nevertheless, investigations into their mutual molecular mechanisms have been limited to date. In the present work, we tried to uncover the shared pathogenesis and regulatory gene targets of COVID‐19 and DFU. Methods In this study, we chose GSE161281 as the COVID‐19 data set, which contained severe acute respiratory syndrome coronavirus 2 infected human induced embryonic stem cell‐derived peripheral neurons (n = 2) with uninfected controls (n = 2). The GSE134431 designated as the DFU data set, comprising full‐thickness DFU (n = 13) and diabetic foot skin (n = 8) samples from diabetic patients. The differential expressed genes (DEGs) were identified from GSE161281 and GSE134431, and the common DEGs between COVID‐19 and DFU were extracted. Multifactor regulatory network and co‐expression network of the common DEGs were analyzed, along with candidate drug prediction. Results Altogether, six common DEGs (dickkopf‐related protein 1 [DKK1], serine proteinase inhibitor A3 [SERPINA3], ras homolog family member D [RHOD], myelin protein zero like 3 [MPZL3], Claudin‐11 [CLDN11], and epidermal growth factor receptor pathway substrate 8‐like 1 [EPS8L1]) were found between COVID‐19 and DFU. Functional analyses indicated that pathways of apoptotic and Wnt signaling may contribute to progression of COVID‐19. Gene co‐expression network implied the shared pathways of immune regulation and cytokine response participated collectively in the development of DFU and COVID‐19. A multifactor regulatory network was constructed integrating the corresponding microRNAs (miRNAs) and transcription factors. Additionally, we proposed potential drug objects for the combined therapy. Conclusion Our study revealed the shared molecular mechanisms underlying COVID‐19 and DFU. The identified pivotal targets and common pathways can provide new perspectives for further research and assist the development of management strategies in patients of DFU complicated with COVID‐19.

Abstract High altitude exposure leads to various cognitive impairments. The cerebral vasculature system plays an integral role in hypoxia‐induced cognitive defects by reducing oxygen and nutrition supply to the brain. RNA N6‐methyladenosine (m6A) is susceptible to modification and regulates gene expression in response to environmental changes, including hypoxia. However, the biological significance of m6A in endothelial cell performance under hypoxic conditions is unknown. Using m6A‐seq, RNA immunoprcipitation‐seq, and transcriptomic co‐analysis, the molecular mechanism of vascular system remodeling under acute hypoxia is investigated. A novel m6A reader protein, proline‐rich coiled‐coil 2B (PRRC2B), exists in endothelial cells. PRRC2B knockdown promoted hypoxia‐induced endothelial cell migration by regulating alternative splicing of the alpha 1 chain of collagen type XII in an m6A‐dependent manner and the decay of matrix metallopeptidase domain 14 and ADAM metallopeptidase domain 19 mRNA in an m6A‐independent manner. In addition, conditional knockout of PRRC2B in endothelial cells promotes hypoxia‐induced vascular remodeling and cerebral blood flow redistribution, thus alleviating hypoxia‐induced cognitive decline. Therefore, PRRC2B is integral in the hypoxia‐induced vascular remodeling process as a novel RNA‐binding protein. These findings provide a new potential therapeutic target for hypoxia‐induced cognitive decline.

There is limited knowledge about the impact of circulating lipids and lipid-modifying drugs on pterygium development, with conflicting results reported. Our study aimed to address these questions by applying the Mendelian randomization (MR) approach. A two-step MR model was developed. In the first step, bidirectional two-sample MR was employed to establish the causal relationship between circulating lipids and pterygium risk. In the second step, drug-target MR analysis was conducted to assess the causal effect of proprotein convertase subtilisin/kexin type 9 (PCSK9) and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibitors on pterygium outcomes. Genetically predicted low-density lipoprotein cholesterol (LDL-c) levels were found to be significantly associated with an increased risk of pterygium (Inverse variance weighted [IVW] odds ratio [OR] = 2.227; P = 1.53 × 10–4). Similarly, higher total cholesterol (TC) levels exhibited a suggestive association with greater susceptibility to pterygium (IVW OR = 1.806; P = 1.70 × 10–3). Through drug-target MR, a positive causal association was noted between HMGCR-mediated LDL-c levels and pterygium (IVW OR = 6.999; P = 0.016), suggesting that statins may be effective in reducing pterygium risk. The present findings suggest that circulating TC and LDL-c are risk factors for pterygium. Additionally, the results indicate that HMGCR inhibitors, which lower LDL-c levels, have a potential protective effect on pterygium outcomes. Further research is warranted to elucidate the underlying mechanisms involved in pterygium pathogenesis, with a particular focus on cholesterol metabolism.

The ridge-tail white prawn, Exopalaemon carinicauda, is an important economic shrimp in the mariculture of China, especially in Jiangsu Province. The “zombie disease” of ridge-tail prawn is a new epidemic that is a highly transmissible and pathogenic fungal disease caused by Metschnikowia bicuspidate infection. To understand the response mechanism of E. carinicauda after M. bicuspidate infection, the hepatopancreas of shrimp injected with M. bicuspidate MQ2101 and normal saline solution were used for proteomics analysis. A total of 5078 proteins were identified, of which 1708 proteins were identified as differentially expressed proteins (DEPs, 1311 upregulated and 397 downregulated) using a 1.2-fold change in expression as a physiologically significant benchmark. These DEPs were mainly involved in cellular processes, single-organism processes, and metabolic processes in the GO enrichment analysis and metabolism, translation, signal transduction, cell growth and death, and immune system pathways in the KEGG enrichment analysis. The DEPs related to immunity and metabolism were significantly changed, such as CTSB, CPs, DSP1, GDP, and ADH3, and these proteins might be potential determinants of E. carinicauda responses to M. bicuspidata infection. qRTPCR was used to detect changes in the expression of nine DEP-related genes at the transcriptional level to validate the proteomics analysis results, and the results of the transcription tendencies in qRTPCR were consistent with proteomics analysis. The results of this study might provide an important theoretical basis for the response mechanism of ridge-tail white prawns to M. bicuspidate infection and scientific prevention and control of this fungus in ridge-tail white prawn aquaculture. Availability of data and materials: The data that support the results of this present study are available from the corresponding author upon reasonable request.

Temperature is an important factor in the physiological processes of aquatic organisms and can seriously affect several chemical and biological processes in their bodies, including respiratory metabolism, antioxidant capacity, immune capacity, and signal transduction. In this study, physiological, transcriptomic, and metabolomic analyses were used to investigate the response of Penaeus vannamei to cold stress. The results indicated that cold stress disrupted nucleotide metabolism and inhibited gluconeogenesis. However, shrimp exhibited response mechanisms in order to enhance cold tolerance, regulating changes in key genes and metabolites in amino acid and lipid metabolism to increase energy supply and protect cell membrane stability. In addition, the response included regulating Ca2+ pumps and ion channels to maintain intracellular ion homeostasis and osmotic balance. When the temperature dropped further, oxidative damage occurred due to overwhelming of the antioxidant defense system, and immune function was inhibited. This research provides some references regarding the molecular mechanisms involved in responding to cold stress and potential strategies to improve cold tolerance in P. vannamei; these are important references for studying the cold stress response of shrimp.

Abstract Hyperuricemia (HUA) seriously harms human health but the exact etiology and pathogenesis of HUA are not fully understood. Therefore, it is still of great significance to find effective biomarkers and explore the pathogenesis of HUA. Metabolomics reflects the influence of internal and external factors on system metabolism, explains the changes in metabolite levels during the development of diseases, and reveals the molecular mechanism of pathogenesis. Metabolomics is divided into untargeted metabolomics and targeted metabolomics according to different research modes. Each other's advantages can be fully utilized by combining the two so that the results of metabolomics research can be consummated. 20 HUA patients and 20 healthy individuals participated in the experiment, and untargeted metabolomics was employed to find 50 differential metabolites in HUA serum samples. Twelve candidate biomarkers were screened based on literature research and ROC Curve analysis for subsequent verification. Based on the UPLC-TQ-MS analysis platform, the targeted metabolomics detection methods were established and the content of 12 candidate biomarkers was precisely quantified. Compare with the results of untargeted metabolomics, the targeted metabolomics results were considered more reliable.

IntroductionGrowing evidence shows that long non-coding RNA small nucleolar RNA host genes (lncRNA SNHGs) enact an pivotal regulatory roles in the shorter survival outcome of colorectal cancer (CRC). However, no research has systematically evaluated the correlation among lncRNA SNHGs expression and survival outcome of CRC. This research indented to screen whether exist potential prognostic effect of lncRNA SNHGs in CRC patientss using comprehensive review and meta-analysis.MethodsSystematic searches were performed from the six relevant databases from inception to October 20, 2022. The quality of published papers was evaluated in details. We pooled the hazard ratios (HR) with 95% confidence interval (CI) through direct or indirect collection of effect sizes, and odds ratios (OR) with 95% CI by collecting effect sizes within articles. Detailed downstream signaling pathways of lncRNA SNHGs were summarized in detailResults25 eligible publications including 2,342 patients were finally included to appraise the association of lncRNA SNHGs with prognosis of CRC. Elevated lncRNA SNHGs expression was revealed in colorectal tumor tissues. High lncSNHG expression means bad survival prognosis in CRC patients (HR=1.635, 95% CI: 1.405–1.864, P

Bacterial biofilms pose a serious threat to human health, as they prevent the penetration of antimicrobial agents. Developing nanocarriers that can simultaneously permeate biofilms and deliver antibacterial agents is an attractive means of treating bacterial biofilm infections. Herein, photosensitive metal–organic framework (MOF) nanoparticles were developed to promote the penetration of antibiotics into biofilms, thereby achieving the goal of eradicating bacterial biofilms through synergistic photodynamic and antibiotic therapy. First, a ligand containing benzoselenadiazole was synthesized and incorporated into MOF skeletons to construct benzoselenadiazole-doped MOFs (Se-MOFs). The growth of the Se-MOFs could be regulated to obtain nanoparticles (Se-NPs) in the presence of benzoic acid. The singlet oxygen (1O2) generation efficiencies of the Se-MOFs and Se-NPs were evaluated. The results show that the Se-NPs exhibited a higher 1O2 generation efficacy than the Se-MOF under visible-light irradiation because the small size of the Se-NPs was conducive to the diffusion of 1O2. Afterward, an antibiotic drug, polymyxin B (PMB), was conjugated onto the surface of the Se-NPs via amidation to yield PMB-modified Se-NPs (PMB-Se-NPs). PMB-Se-NPs exhibit a synergistic antibacterial effect by specifically targeting the lipopolysaccharides present in the outer membranes of Gram-negative bacteria through surface-modified PMB. Benefiting from the synergistic therapeutic effects of antibiotic and photodynamic therapy, PMB-Se-NPs can efficiently eradicate bacterial biofilms at relatively low antibiotic doses and light intensities, providing a promising nanocomposite for combating biofilm infections.

Abstract Background Plantaginis Semen has been widely used as folk medicine and health care food against hyperuricemia (HUA) and gout, but its pharmacological mechanism remains unclear. This study investigated the therapeutic mechanism of Plantaginis Semen extract on potassium oxonate -induced HUA rats based on a lipidomics approach. Methods A model of HUA was established by potassium oxonate intragastric administration. 42 Sprague-Dawley (SD) male rats were randomly divided into the control group, model group, benzbromarone group (10 mg/kg) and three Plantaginis Semen groups (n = 7). The Plantaginis Semen groups were treated orally with Plantaginis Semen, 0.9375, 1.875 or 3.75 g/kg for 28 days. The levels of serum uric acid (UA), creatinine (Cr), triacylglycerol (TG) and tumor necrosis factor-α (TNF-α) were measured using enzyme-linked immunosorbent assay kits. Ultra performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-Q-TOF/MS) was used for the serum lipidomics analysis, multivariate statistical analysis and independent samples t-test were carried out for the pattern recognition and characteristic metabolites identification. The relative levels of critical regulatory factors were determined by quantitative real-time polymerase chain reaction (RT-qPCR). Results Compared with the model group, the levels of serum UA, Cr, TG and TNF-α were significantly (p

Hyperoside is a natural flavonol glycoside, which has antioxidation, antitumor, and anticancer activities together with other healthy effects like improving cardiovascular function, protecting the liver, and regulating the immune system. It is a popular compound used in the traditional Chinese medicine and different studies on hyperoside are present in the literature. However, studies on the metabolism of hyperoside in vivo were not comprehensive. In this study, UPLC-Q-Exactive Orbitrap MS technology was used to establish a rapid and comprehensive analysis strategy to explore the metabolites and metabolic process of hyperoside in rats. The metabolites of hyperoside were systematically identified in rat plasma, urine, and feces. According to the hyperoside standard substance and relevant works of literature, a total of 33 metabolites were identified, including 16 in plasma, 31 in urine, and 14 in feces. Among them, the metabolites quercetin and dihydroquercetin were unambiguously confirmed by comparison with standard substances. In addition, 13 metabolites had not been reported in hyperoside metabolism-related articles at present. The metabolic reactions of hyperoside in vivo were further explored, including phase I metabolism (hydroxylation, dehydroxylation, glycoside hydrolysis, hydrogenation, and hydration) and phase II metabolism (methylation, acetylation, sulfation, and glucuronide conjugation). The fragment ions of hyperoside and its metabolites were usually produced by glucoside bond hydrolysis, the neutral loss of (CO + OH), COH, CO, O, and Retro-Diels Alder (RDA) cleavage. In conclusion, this study comprehensively characterized the metabolism of hyperoside in rats, providing a basis for exploring its various biological activities.

The cost effectiveness of using exogenous phosphorus to remediate heavy metals in soil, which would alter the structure of the soil microbial community, had been widely acknowledged. In the present study, phospholipid fatty acid (PLFA) technology was taken as the breakthrough point, and rhizosphere soil microorganisms in different growth stages (jointing stage and maturity stage) of Minghui 86 (MH) and Yangdao No.6 (YD) rice were taken as the research objects. As revealed by the results, the rhizosphere soil microorganisms of MH and YD had distinct sensitivities to exogenous phosphorus and had a certain inhibitory effect on MH and YD enhancement. The sensitivity of rice root soil microorganisms to exogenous phosphorus also varied in different growth stages of rice. Bacteria were the dominant microorganism in the soil microbial community of rice roots, and the gain of exogenous phosphorus had a certain impact on the structure of the two soil microbial communities. Through analysis of the microbial community characteristics of MH rice and YD soil after adding exogenous phosphorus, further understanding was attained with respect to the effect of exogenous phosphorus on the microbial community characteristics of rice rhizosphere soil and the impact thereof on ecological functions.

Bacterial biofilms are difficult to treat due to their resistance to traditional antibiotics. Although photodynamic therapy (PDT) has made significant progress in biomedical applications, most photosensitizers have poor water solubility and can thus aggregate in hydrophilic environments, leading to the quenching of photosensitizing activity in PDT. Herein, a benzoselenadiazole-containing ligand was designed and synthesized to construct the zirconium (IV)-based benzoselenadiazole-doped metal-organic framework (Se-MOF). Characterizations revealed that Se-MOF is a type of UiO-68 topological framework with regular crystallinity and high porosity. Compared to the MOF without benzoselenadiazole, Se-MOF exhibited a higher 1O2 generation efficacy and could effectively kill Staphylococcus aureus bacteria under visible-light irradiation. Importantly, in vitro biofilm experiments confirmed that Se-MOF could efficiently inhibit the formation of bacteria biofilms upon visible-light exposure. This study provides a promising strategy for developing MOF-based PDT agents, facilitating their transformation into clinical photodynamic antibacterial applications.

Increasing evidences have showed that a tight link among pathogen infection, physiological indicators and intestinal microbiota. To investigate effects of Enterocytozoon hepatopenaei (EHP) infection to growth retardation and intestinal microbiota, different sized Pacific white shrimp (Penaeus vannamei) infecting with EHP were studied. The shrimp with big, medium and small sized groups were from same batch of postlarvae and reared in one pond under the same diet and environmental conditions. Number of EHP copies revealed that the more EHP copies the smaller size of shrimp individuals. Denaturing gradient gel electrophoresis (DGGE) profiles showed intestinal bacterial patterns of small sized shrimp were similar to the middle sized shrimp, rather than the big sized shrimp. It implied that intestinal microbiota were influenced by severity of EHP infection and suggested the different sizes of shrimp were due to the successive infection period of EHP. Among the different sized groups, the relative abundance of Vibrio of small group was the highest, suggesting EHP infection could result in higher susceptibility to pathogen invasion. Our findings provided the evidence intestinal bacterial patterns altered by infection of EHP, the more EHP copies the smaller size of shrimp, and different sized individuals due to successive infection period of EHP.

Walnut (Juglans regia) is an important woody oil-bearing plant with high nutritional value. For better understanding of the underlying molecular mechanisms of its oil accumulation in the Qinghai Plateau, in this study we monitored walnut fruit development, and 15 cDNA libraries were constructed from walnut seed kernels collected at 72, 79, 93, 118 and 135 days after flowering (DAF). The candidate genes were identified using sequencing and expression analysis. The results showed that the oil content in the kernels increased dramatically in late July and reached the maximum value of 69% in mature seed. More than 90% of the oils were unsaturated fatty acids (UFAs) and linoleic acid (18:2) was the predominant UFA accumulated in mature seed. Differentially expressed genes (DEGs) in 15 KEGG pathways of lipid metabolism were detected. We identified 119 DEGs related to FA de novo biosynthesis (38 DEGs), FA elongation and desaturation (39 DEGs), triacylglycerol (TAG) assembly (24 DEGs), oil bodies (12 DEGs), and transcription factors (TFs, 6 DEGs). The abundantly expressed oleosins, caleosins and steroleosins may be important for timely energy reserve in oil bodies. Weighted gene coexpression network analysis (WGCNA) showed that AP2/ERF and bHLH were the key TFs, and were co-expressed with ACC1, α-CT, BCCP, MAT, KASII, LACS, FATA, and PDCT. Our transcriptome data will enrich public databases and provide new insights into functional genes related to the seed kernel lipid metabolism and oil accumulation in J. regia.

Very deep convolutional neural networks (CNNs) have recently achieved great success in stereo matching. It is still highly desirable to learn a robust feature map to improve ill-posed regions, such as weakly textured regions, reflective surfaces, and repetitive patterns. Therefore, we propose an end-to-end multi-dimensional residual dense attention network (MRDA-Net) in this paper, focusing on more comprehensive pixel-wise feature extraction. Our proposed network consists of two parts: the 2D residual dense attention net for feature extraction and the 3D convolutional attention net for matching. Our designed 2D residual dense attention net uses a dense network structure to fully exploit the hierarchical features from preceding convolutional layers and uses residual network structure to fuse low-level structure information and high-level semantic information. The 2D attention module of the net aims to adaptively recalibrate channel-wise features to be more concerned about informative features. Our proposed 3D convolutional attention net further expands attention mechanism for matching. The stacked hourglass module of the net is exploited to extract multi-scale context information as well as geometry information. The novel 3D attention module of the net aggregates hierarchical sub-cost volumes adaptively instead of manually and then achieves a comprehensive recalibrated cost volume for more correct disparity computation. The experiments demonstrate that our approach achieves the state-of-the-art accuracy on Scene Flow dataset and KITTI 2012 and KITTI 2015 Stereo datasets.

Motivated by recent successes on learning 3D feature representations, we present a Siamese network to generate representative 3D descriptors for 3D point matching in point cloud registration. Our system, dubbed HAF-Net, consists of feature extraction module, hierarchical feature reweighting and recalibration module (HRR), as well as feature aggregation and compression module. The HRR module is proposed to adaptively integrate multi-level features through learning, acting as a hierarchical attention fusion mechanism. The learnable feature pooling technique VLAD is extended into our aggregation module, which is further utilized to extract principal components of features and compress them into a low dimensional feature vector. To train our model, we amass a large dataset for 3D point matching. The dataset is composed of matched and unmatched point block pairs, which are automatically searched from existing reconstruction datasets with known poses. The experiments demonstrate that the proposed HAF-Net not only outperforms other state-of-the-art approaches in 3D feature representation but also has a good generalization ability in various tasks and datasets.

Influenza A virus (IAV) is an important zoonotic pathogen, posing a severe burden for the health of both animals and humans. Many host factors are involved in the life cycle of IAV to regulate its replication. Herein, we identified sorting nexin-16 (SNX16) as a new host factor that negatively modulates the replication of IAV. When transiently overexpressed in cells, SNX16 appears to be expressed as two obvious bands. Mutagenesis analysis indicated that the amino acid residue R144 of SNX16 was responsible for its two-band expression phenotype. We found that the R144A mutation of SNX16 changed its cellular distribution in A549 cells and partially weakened the inhibitory effect of SNX16 on IAV replication. Further investigation revealed that SNX16 could negatively regulate the early stage of the replication cycle of IAV. Taken together, our results demonstrated that SNX16 is a novel restriction host factor for the replication of IAV by engaging in the early stage of IAV life cycle, and a single amino acid residue at position 144 plays an important role in the cellular distribution and anti-influenza function of SNX16.

We present a simple yet highly efficient method to eliminate spurious trails of dynamic objects for 3-D point cloud map updating. First, we extract the view overlaps based on view frustum filter. Then, we obtain spurious trails via bidirectional searching of view overlaps using a KD tree. Finally, in terms of the situation where moving objects occlude part of background due to the limits of the RGB-D camera, we design a ray tracing principle-based filter to supplement the missing background in the whole point cloud map. Our method can be integrated into any SLAM or 3-D reconstruction systems with RGB-D data input, and it is suitable for both static and dynamic environments. We validate our approach in real-world scenes of our laboratory office using a Kinect system for robot obstacles avoidance and navigation. Moreover, experiments on the KITTI odometry benchmark illustrate that the proposed approach is highly efficient for dynamic spurious trails rejection and 3-D map updating.

This paper presents an optimized level set evolution (LSE) without reinitialization (LSEWR) model and a shape prior embedded level set model (LSM) for robust image segmentation. Firstly, by performing probability weighting and coefficient adaptive processing on the original LSEWR model, the optimized image energy term required by the proposed model is constructed. The purpose of the probability weighting is to introduce region information into the edge stop function to enhance the model’s ability to capture weak edges. The introduction of the adaptive coefficient enables the evolution process to automatically adjust its amplitude and direction according to the current image coordinate and local region information, thus completely solving the initialization sensitivity problem of the original LSEWR model. Secondly, a shape prior term driven by kernel density estimation (KDE) is additionally introduced into the optimized LSEWR model. The role of the KDE-driven shape prior term is to overcome the problem of image segmentation in the presence of geometric transformation and pattern interference. Even if there is obvious affine transformation in the shape prior and the target to be segmented, the target contour can still be reconstructed correctly. The extensive experiments on a large variety of synthetic and real images show that the proposed algorithm achieves excellent performance. In addition, several key factors affecting the performance of the proposed algorithm are analyzed in detail.

In order to achieve the automation drilling of the improved CMJ2-27 drill, kinematic analysis of the drill rig is conducted aiming the collision between the arms and the roadway during the operation process. By suing the Denavit-Hartenberg (D-H) method, the transformation matrix of coordinate system is obtained, then the coordinates of each joint and the ends are derived. The collision detection approach between the arm and the roadway is given. Theoretical calculation and the motion simulation experiment are conducted by using the detection method for a 88-hole drilling program for a mine. The research results show that the method is feasible and has the characteristics of simple procedures and high efficiency.

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.

To understand the prevalence of functional constipation in pregnant women and to analyze the impact of its risk factors.We searched hospital databases for women who were 37-41 weeks pregnant (1698 cases) from July 2012 to January 2014 in four hospitals in Shanghai. We reviewed factors including general data, living and eating habits, psychological history, past history of defecation in the 6 months before pregnancy and defecation after pregnancy. Data were analyzed using SPSS software.Pregnant women who were more than 35 years old, with a pre-pregnancy body mass index >24, who were highly educated and employed in a sedentary occupation, showed a higher prevalence of functional constipation. Multivariate logistic regression analysis indicated that the prevalence of functional constipation among pregnant women was related to age, pre-pregnancy body mass index, diet, exercise, occupation, psychological factors, threatened abortion in early pregnancy and constipation history.The prevalence rate of functional constipation in pregnant women was significantly higher than in the general population.