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Objectives: This study aims to elucidate the role of Fe2+ overload in kainic acid (KA)‐induced excitotoxicity, investigate the involvement of ferritinophagy selective cargo receptor NCOA4 in the pathogenesis of excitotoxicity. Methods: Western blotting was used to detect the expression of FTH1, NCOA4, Lamp2, TfR, FPN, and DMT1 after KA stereotaxic injection into the unilateral striatum of mice. Colocalization of Fe2+ with lysosomes in KA‐treated primary cortical neurons was observed by using confocal microscopy. Desferrioxamine (DFO) was added to chelate free iron, a CCK8 kit was used to measure cell viability, and the Fe2+ levels were detected by FerroOrange. BODIPY C11 was used to determine intracellular lipid reactive oxygen species (ROS) levels, and the mRNA levels of PTGS2, a biomarker of ferroptosis, were measured by fluorescent quantitative PCR. 3‐Methyladenine (3‐MA) was employed to inhibit KA‐induced activation of autophagy, and changes in ferritinophagy‐related protein expression and the indicated biomarkers of ferroptosis were detected. Endogenous NCOA4 was knocked down by lentivirus transfection, and cell viability and intracellular Fe2+ levels were observed after KA treatment. Results: Western blot results showed that the expression of NCOA4, DMT1, and Lamp2 was significantly upregulated, while FTH1 was downregulated, but there were no significant changes in TfR and FPN. The fluorescence results indicated that KA enhanced the colocalization of free Fe2+ with lysosomes in neurons. DFO intervention could effectively rescue cell damage, reduce intracellular lipid peroxidation, and decrease the increased transcript levels of PTGS2 caused by KA. Pretreatment with 3‐MA effectively reversed KA‐induced ferritinophagy and ferroptosis. Endogenous interference with NCOA4 significantly improved cell viability and reduced intracellular free Fe2+ levels in KA‐treated cells. Conclusion: KA‐induced excitotoxicity activates ferritinophagy, and targeting ferritinophagy effectively inhibits downstream ferroptosis. Interference with NCOA4 effectively attenuates KA‐induced neuronal damage. This study provides a potential therapeutic target for excitotoxicity related disease conditions. [ABSTRACT FROM AUTHOR]

Eye-in-hand robotic binocular sensor systems are indispensable equipment in the modern manufacturing industry. However, because of the intrinsic deficiencies of the binocular sensor, such as the circle of confusion and observed error, the accuracy of the calibration matrix between the binocular sensor and the robot end is likely to decline. These deficiencies cause low accuracy of the matrix calibrated by the traditional method. In order to address this, an improved calibration method for the eye-in-hand robotic vision system based on the binocular sensor is proposed. First, to improve the accuracy of data used for solving the calibration matrix, a circle of confusion rectification method is proposed, which rectifies the position of the pixel in images in order to make the detected geometric feature close to the real situation. Subsequently, a transformation error correction method with the strong geometric constraint of a standard multi-target reference calibrator is developed, which introduces the observed error to the calibration matrix updating model. Finally, the effectiveness of the proposed method is validated by a series of experiments. The results show that the distance error is reduced to 0.080 mm from 0.192 mm compared with the traditional calibration method. Moreover, the measurement accuracy of local reference points with updated calibration results from the field is superior to 0.056 mm.

Image dense matching plays a crucial role in the reconstruction of three-dimensional models of buildings. However, large variations in target heights and serious occlusion lead to obvious mismatches in areas with discontinuous depths, such as building edges. To solve this problem, the present study mines the geometric and semantic information of line segments to produce a constraint for the dense matching process. First, a disparity consistency-based line segment matching method is proposed. This method correctly matches line segments on building structures in discontinuous areas based on the assumption that, within the corresponding local areas formed by two corresponding line pairs, the disparity obtained by the coarse-level matching of the hierarchical dense matching is similar to that derived from the local homography estimated from the corresponding line pairs. Second, an adaptive guide parameter is designed to constrain the cost propagation between pixels in the neighborhood of line segments. This improves the rationality of cost aggregation paths in discontinuous areas, thereby enhancing the matching accuracy near building edges. Experimental results using satellite and aerial images show that the proposed method efficiently obtains reliable line segment matches at building edges with a matching precision exceeding 97%. Under the constraint of the matched line segments, the proposed dense matching method generates building edges that are visually clearer, and achieves higher accuracy around edges, than without the line segment constraint.

Abstract Interleukin-37b (hereafter called IL-37) was identified as fundamental inhibitor of natural and acquired immunity. The molecular mechanism and function of IL-37 in colorectal cancer (CRC) has been elusive. Here, we found that IL-37 transgenic (IL-37tg) mice were highly susceptible to colitis-associated colorectal cancer (CAC) and suffered from dramatically increased tumor burdens in colon. Nevertheless, IL-37 is dispensable for intestinal mutagenesis, and CRC cell proliferation, apoptosis, and migration. Notably, IL-37 dampened protective cytotoxic T cell-mediated immunity in CAC and B16-OVA models. CD8+ T cell dysfunction is defined by reduced retention and activation as well as failure to proliferate and produce cytotoxic cytokines in IL-37tg mice, enabling tumor evasion of immune surveillance. The dysfunction led by IL-37 antagonizes IL-18–induced proliferation and effector function of CD8+ T cells, which was dependent on SIGIRR (single immunoglobulin interleukin-1 receptor-related protein). Finally, we observed that IL-37 levels were significantly increased in CRC patients, and positively correlated with serum CRC biomarker CEA levels, but negatively correlated with the CD8+ T cell infiltration in CRC patients. Our findings highlight the role of IL-37 in harnessing antitumor immunity by inactivation of cytotoxic T cells and establish a new defined inhibitory factor IL-37/SIGIRR in cancer-immunity cycle as therapeutic targets in CRC.

Tumor cells can secret various cytokines and chemokines, which affect the tumor cells themselves and the neighboring cells. Here, we observed that human ovarian cancer (OC) cells developed resistance to paclitaxel treatment following culture with the conditioned medium (CM) derived from paclitaxel-resistant OC (OCTR) cells. A cytokine array revealed that both OCTR cells secreted large amounts of CC chemokine ligand 2 (CCL2). CCL2 and its receptor, CCR2, were overexpressed in OCTR cells. CCL2 expression was associated with worse progression-free survival in patients with ovarian cancer. The inhibition of the CCL2/CCR2 axis suppressed the chemoresistance induced by OCTR-CM. The enhanced expression and production of CCL2 in OC cells were mediated via the NF-κB pathway, and stimulated the activation of the PI3K/Akt pathway, which resulted in the development of paclitaxel resistance in OC cells. Additionally, the OCTR cells significantly increased the migration of macrophages, which was also associated with the overproduction of CCL2 in chemoresistant cancer cells. The macrophages stimulated by OCTR cells expressed high levels of markers of M2 phenotype, and their CM significantly decreased the paclitaxel responsiveness of OC cells. The administration of a CCR2 inhibitor to a murine model significantly improved the paclitaxel sensitivity. These data suggested that apart from inducing chemoresistance in OC cells by acting as an autocrine factor, CCL2 also functions as a chemokine that induces the chemotaxis of macrophages, which may contribute to chemoresistance. Therefore, targeting the CCL2/CCR2 signaling axis may improve the therapeutic response of patients with ovarian cancer to paclitaxel.

Abstract Alternative splicing (AS) increases the diversity of transcripts and proteins through the selection of different splice sites and plays an important role in the growth, development and stress tolerance of plants. With the release of the reference genome of the tea plant (Camellia sinensis) and the development of transcriptome sequencing, researchers have reported the existence of AS in tea plants. However, there is a lack of a platform, centered on different RNA-seq datasets, that provides comprehensive information on AS. To facilitate access to information on AS and reveal the molecular function of AS in tea plants, we established the first comprehensive AS database for tea plants (TeaAS, http://www.teaas.cn/index.php ). In this study, 3.96 Tb reads from 66 different RNA-seq datasets were collected to identify AS events. TeaAS supports four methods of retrieval of AS information based on gene ID, gene name, annotation (non-redundant/Kyoto encyclopedia of genes and genomes/gene ontology annotation or chromosomal location) and RNA-seq data. It integrates data pertaining to genome annotation, type of AS event, transcript sequence, and isoforms expression levels from 66 RNA-seq datasets. The AS events resulting from different environmental conditions and that occurring in varied tissue types, and the expression levels of specific transcripts can be clearly identified through this online database. Moreover, it also provides two useful tools, Basic Local Alignment Search Tool and Generic Genome Browser, for sequence alignment and visualization of gene structure. The features of the TeaAS database make it a comprehensive AS bioinformatics platform for researchers, as well as a reference for studying AS events in woody crops. It could also be helpful for revealing the novel biological functions of AS in gene regulation in tea plants.

Differences in nitrogen (N) form preference among species may lead to niche differentiation that facilitates species coexistence. In alpine wetlands, N niche differentiation may exist between dominant plant species, and such differentiation may be modified by soil moisture. To test these hypotheses, we conducted a 15N labeling experiment along three soil moisture gradients (low vs. medium vs. high, i.e. 30.6% vs. 52.1% vs. 69.9% of volumetric water content) in an alpine wetland dominated by Carex muliensis Hand-Mazz. and Potentilla anserina L. on the eastern Qinghai-Tibetan Plateau. We labeled plants and soils with ammonium-15N, nitrate-15N or glycine-15N. N uptake rate was significantly higher in P. anserina than in C. muliensis, irrespective of soil moisture. Under medium soil moisture, C. muliensis absorbed more ammonium-N than nitrate-N and glycine-N as the soil contained more ammonium-N. Under high soil moisture, however, C. muliensis took up more nitrate-N than ammonium-N and glycine-N because the soil contained more nitrate-N. Potentilla anserina preferred ammonium-N to nitrate-N and glycine-N and such preference did not change with soil moisture. These results suggest that dominant species in alpine wetlands prefer to take up inorganic N rather than organic N and that soil moisture may alter inorganic N form preference of alpine wetland plant species.

Abstract Background Several studies have shown that N-terminal pro-B-type natriuretic peptide (NT-proBNP) is strongly correlated with the complexity of coronary artery disease and the prognosis of patients with non-ST segment elevation acute coronary syndrome (NSTE-ACS), However, it remains unclear about the prognostic value of NT-proBNP in patients with NSTE-ACS and multivessel coronary artery disease (MCAD) undergoing percutaneous coronary intervention (PCI). Therefore, this study aimed to reveal the relationship between NT-proBNP levels and the prognosis for NSTE-ACS patients with MCAD undergoing successful PCI. Methods This study enrolled 1022 consecutive NSTE-ACS patients with MCAD from January 2010 to December 2014. The information of NT-proBNP levels was available from these patients. The primary outcome was in-hospital all-cause death. In addition, the 3-year follow-up all-cause death was also ascertained. Results A total of 12 (1.2%) deaths were reported during hospitalization. The 4th quartile group of NT-proBNP (> 1287 pg/ml) showed the highest in-hospital all-cause death rate (4.3%) (P 1568 pg/ml is related to the all-cause and in-hospital deaths.

Image datasets acquired from orchards are commonly characterized by intricate backgrounds and an imbalanced distribution of disease categories, resulting in suboptimal recognition outcomes when attempting to identify apple leaf diseases. In this regard, we propose a novel apple leaf disease recognition model, named RFCA ResNet, equipped with a dual attention mechanism and multi-scale feature extraction capacity, to more effectively tackle these issues. The dual attention mechanism incorporated into RFCA ResNet is a potent tool for mitigating the detrimental effects of complex backdrops on recognition outcomes. Additionally, by utilizing the class balance technique in conjunction with focal loss, the adverse effects of an unbalanced dataset on classification accuracy can be effectively minimized. The RFB module enables us to expand the receptive field and achieve multi-scale feature extraction, both of which are critical for the superior performance of RFCA ResNet. Experimental results demonstrate that RFCA ResNet significantly outperforms the standard CNN network model, exhibiting marked improvements of 89.61%, 56.66%, 72.76%, and 58.77% in terms of accuracy rate, precision rate, recall rate, and F1 score, respectively. It is better than other approaches, performs well in generalization, and has some theoretical relevance and practical value.

Lily is a very important bulb crop, and interspecific distant hybridization is a crucial method of lily breeding. However, F1 interspecific hybrids tend to be highly sterile due to low levels of genetic homozygosity. This can be addressed by meiotic polyploidization, which has the advantage of reducing breeding time and being able to promote genetic recombination resulting in many variant progenies. High temperatures have been proven to induce 2n gametes via hindering a spindle formation in several plants, but little has been reported in lilies. In the present study, after observing the correlation between the development of the pollen mother cells (PMCs) and the length of the buds, 28–31 mm long buds were selected as the experimental material, which were at the stage of prophase I–metaphase I. Individual buds were induced at different temperatures (40 °C, 42 °C, and 44 °C) and durations (4 h and 6 h) using self-made multiwire heating equipment, and successfully induced fertile male gametes.. The best results were achieved with treatment of 42 °C for 4 h, reaching a maximum fertile pollen induction rate of 36.64%, while bud mortality was 40%. Two chemicals, colchicine and oryzalin, were also used by injection, and only the treatment with oryzalin obtained fertile gametes, with the highest fertile gamete rate of 15.39% at a concentration of 0.005%, while the bud mortality was 36.67%. This suggests that high temperatures have a superior effect on lily 2n gamete induction. In addition, the pollen obtained from the 6 h induction of high temperature was significantly larger than that from the 4 h induction, with an average diameter of 138.64 μm and 107.88 μm, respectively, 2.35 and 1.84 times wider than haploid pollen. The fertile pollen was crossed with four cultivars and two species, and a total of 267 embryonic seeds were obtained, with the highest embryonic rate of 4.52% in OT lily ‘Mister Cas’ as the parent, which had a germination rate of 26.27%. This suggests that the method of high-temperature induction for fertile gametes probably has important significance for ploidy and distant hybrid breeding in lilies.

Abstract Background Shotgun metagenomics based on untargeted sequencing can explore the taxonomic profile and the function of unknown microorganisms in samples, and complement the shortage of amplicon sequencing. Binning assembled sequences into individual groups, which represent microbial genomes, is the key step and a major challenge in metagenomic research. Both supervised and unsupervised machine learning methods have been employed in binning. Genome binning belonging to unsupervised method clusters contigs into individual genome bins by machine learning methods without the assistance of any reference databases. So far a lot of genome binning tools have emerged. Evaluating these genome tools is of great significance to microbiological research. In this study, we evaluate 15 genome binning tools containing 12 original binning tools and 3 refining binning tools by comparing the performance of these tools on chicken gut metagenomic datasets and the first CAMI challenge datasets. Results For chicken gut metagenomic datasets, original genome binner MetaBat, Groopm2 and Autometa performed better than other original binner, and MetaWrap combined the binning results of them generated the most high-quality genome bins. For CAMI datasets, Groopm2 achieved the highest purity (> 0.9) with good completeness (> 0.8), and reconstructed the most high-quality genome bins among original genome binners. Compared with Groopm2, MetaBat2 had similar performance with higher completeness and lower purity. Genome refining binners DASTool predicated the most high-quality genome bins among all genomes binners. Most genome binner performed well for unique strains. Nonetheless, reconstructing common strains still is a substantial challenge for all genome binner. Conclusions In conclusion, we tested a set of currently available, state-of-the-art metagenomics hybrid binning tools and provided a guide for selecting tools for metagenomic binning by comparing range of purity, completeness, adjusted rand index, and the number of high-quality reconstructed bins. Furthermore, available information for future binning strategy were concluded.

Abstract To study the characteristics of the 5-prismatic–spherical–spherical (PSS)/universal–prismatic–universal (UPU) parallel mechanism with elastically active branched chains, the dynamics modeling and solutions of the parallel mechanism were investigated. First, the active branched chains and screw sliders were considered as spatial beam elements and plane beam element models, respectively, and the dynamic equations of each element model were derived using the Lagrange method. Second, the equations of the 5-PSS/UPU parallel mechanism were obtained according to the kinematic coupling relationship between the active branched chains and moving platform. Finally, based on the parallel mechanism dynamic equations, the natural frequency distribution of the 5-PSS/UPU parallel mechanism in the working space and elastic displacement of the moving platform were obtained. The results show that the natural frequency of the 5-PSS/UPU parallel mechanism under a given motion situation is greater than its operating frequency. The maximum position error is − 0.096 mm in direction Y, and the maximum orientation error is − 0.29° around the X-axis. The study provides important information for analyzing the dynamic performance, dynamic optimization design, and dynamic control of the 5-PSS/UPU parallel mechanism with elastically active branched chains.

The accuracy and reliability of solid oxide fuel cell (SOFC) modeling mainly depend on the precise extraction and optimization of some unknown parameters. However, the SOFC model is a multi-peak, nonlinear, multivariable, and strongly combined system. In the previous decisive optimization methods, it is difficult to achieve satisfactory parameter extraction. Therefore, this article proposes a SOFC parameter extraction method based on the superhuman algorithm and extracts several important parameters of the SOFC model. In addition, the electrochemical model (ECM), which is a typical SOFC model, has also been studied to verify the extraction performance of the glass jump optimization algorithm (GOA) under various working conditions. Simulation results based on MATLAB show that GOA can greatly improve the accuracy, speed, and stability of inferring these unknown parameters through a comprehensive comparison with the particle swarm optimization (PSO) algorithm.

Objective Cyclin D1 was an important molecular involved in the pathological process of osteoarthritis (OA). The purpose of this study was to identify the effect and potential mechanism of Cyclin D1 for the proliferation and apoptosis of OA chondrocytes.Methods We used polymerase chain reaction (PCR) method to identify the expression levels of Cyclin D1 and down-stream Wnt/β-catenin pathway-related genes in OA chondrocytes according to the grade of OA. Small interfering RNA (siRNA) or overexpression of Cyclin D1 were used to identify the role of Cyclin D1 in cell proliferation and apoptosis. Next, we used XAV-939 to inhibit the Wnt/β-catenin pathway and explore the relevant mechanism.Results Cyclin D1 was significantly decreased with OA grade (p < .05). After siCyclin D1 transfection, the expression level of WNT3 and nuclear β-catenin were significantly increased, while Wnt10a and total β-catenin were not obviously changed. Co-cultured with XAV-939 and siCyclin D1 abolished the effects of siCyclin D1 on proliferation and apoptosis of OA chondrocytes (p < .05).Conclusions Cyclin D1 regulated chondrocyte proliferation and apoptosis through Wnt3/β-catenin instead of Wnt10a/β-catenin signalling pathway.

Large-scale components usually have complex structures with high local stiffness, and the holes on them are required to be machined with high precision, which makes it important and challenging to study how to efficiently and precisely drill in the large-scale components. This article presents mobile hybrid machining equipment that consists of a five-axis parallel module, a 2-degree-of-freedom (DoF) robotic, arm and an automated guide vehicle (AGV) connected in series. With the ability of wide-range positioning and precise local processing, it has potential advantages in the drilling processing of large-scale components. Stiffness is one of the most important performances for machining equipment, and it’s highly related to the its configuration. For the discussed equipment, the stiffness is determined by the two-stage-positioning hybrid machining robot, which comprises a five-axis parallel module and a two-DoF robotic arm. The redundant motion of the hybrid machining robot makes it possible to optimize its configuration by reasonably planning redundant motion. Therefore, a redundant motion-planning method based on stiffness performance is proposed. A kinematic analysis of the five-axis parallel module, the robotic arm, and the hybrid machining robot is carried out. A hybrid robot usually consists of several subsystems, and to take the compliance of each subsystem into consideration, the stiffness-modeling method for the hybrid robot with n subsystems connected in series is proposed. The stiffness model of the hybrid machining robot is established by using this method, and the variation of the stiffness magnitude has the same trend as that obtained by using FEA software. Stiffness magnitude and isotropy indices are proposed to evaluate the robot’s stiffness performance along the axis of the spindle and in the plane perpendicular to the axis of the spindle. The redundant motion of the hybrid machining robot is planned by maximizing the stiffness magnitude along the spindle axis, with priority to the stiffness isotropy index. Finally, the drilling experiment is carried out, and the results show that the relative error of the hole diameter obtained under the optimal configuration of the hybrid machining robot is 1.63%, which is smaller than those obtained under the other two configurations for comparison with relative errors of 3.75% and 3.50%, respectively. It proves the validity of the redundant motion-planning method. The proposed stiffness-modeling method and the stiffness-performance indices are also applicable to other hybrid machining robots.