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Maize (Zea mays L.) C-type cytoplasmic male sterility (CMS-C) is a highly used CMS system for maize commercial hybrid seed production. Rf4 is the major dominant restorer gene for CMS-C. Inbreds were recently discovered which contain the restoring Rf4 allele yet are unable to restore fertility due to the lack of an additional gene required for Rf4's restoration. To find this additional gene, QTL mapping and positional cloning were performed using an inbred that contained Rf4 but was incapable of restoring CMS-C. The QTL was mapped to a 738-kb interval on chromosome 2, which contains a Pentatricopeptide Repeat (PPR) gene cluster. Allele content comparisons of the inbreds identified three potential candidate genes responsible for fertility restoration in CMS-C. Complementation via transformation of these three candidate genes showed that PPR153 (Zm00001eb114660) is required for Rf4 to restore fertility to tassels. The PPR153 sequence is present in B73 genome, but it is not capable of restoring CMS-C without Rf4. Analysis using NAM lines revealed that Rf4 requires the presence of PPR153 to restore CMS-C in diverse germplasms. This research uncovers a major CMS-C genetic restoration pathway and can be used for identifying inbreds suitable for maize hybrid production with CMS-C cytoplasm. [ABSTRACT FROM AUTHOR]

A region-growing-based point cloud extraction algorithm for roof surfaces is proposed to address the issue of low extraction accuracy caused by vegetation interference in airborne LiDAR point cloud data. Firstly, the filtering treatment is conducted to obtain the non-ground point cloud. Then, the neighborhood feature information of the roof point is used to extract roof surface seed points, in which the vegetation index and RGB difference information are introduced as growth constraints to segment the roof surface point cloud. Finally, the extracted results are filtered and optimized by using the elevation and area values of the roof surface to get the point cloud of the roof surface. The experiment is carried out by selecting three groups of test data from different scenarios, such as rural areas, urban and factory. In accordance with the results, it indicates that the Kappa coefficients reach 97.29%, 97.82% and 97.13% respectively, a relatively better building roof surface extraction effect can be realized, and a good adaptability for different building scenes is embodied. [ABSTRACT FROM AUTHOR]

Owing to the fuzzy structure, small background difference, diverse types and complex data distribution, the defect detection of railway communication cable fasteners is still a challenge. Aiming at the problem that the existing CNN methods are sensitive to the distribution of defect data, the unsupervised GAN is introduced, and a block-reconstruction-GAN-based algorithm is proposed. Firstly, the YOLOv5-M model is used to locate the image of the leaky cable fastener. Then, a block-removing approach based on existing Skip-GANomaly is proposed to split the fastener training samples, which can alleviate the overfitting problem of Skip-GANomaly during the reconstruction process of defect fastener by dispersing fastener features and increasing the number of samples. In addition, the cosine similarity is proposed to calculate the similarity score between the original fastener image and reconstructed image, which will be used to distinguish the defect fastener. The experiments are carried out on the cable fastener dataset collected by the comprehensive inspection vehicle and the experimental results show that the AUC value of the proposed algorithm for multi-type fastener defect recognition reaches 0.961, which is 3% higher than that of Skip-GANomaly algorithm. In addition, the visualization results show that compared with other two classical anomaly scores, the method based on cosine similarity can better distinguish defect fastener from the normal fastener. [ABSTRACT FROM AUTHOR]

Tetrahymenosis, caused by about 10 Tetrahymena species, is an emerging problem inflicting a significant economic loss on the aquaculture industry worldwide. However, in the order Tetrahymenida, there are many unresolved evolutionary relationships among taxa. Here we report 21 new sequences, including SSU‐rRNA, ITS1‐5.8S‐ITS2 rRNA and LSU‐rRNA, genes of 10 facultative parasitic Tetrahymena associated with tetrahymenosis, and conduct phylogenetic analyses based on each individual gene and a three‐gene concatenated dataset. The main findings are: (1) All the parasitic and facultative parasitic species cluster in borealis group. (2) With the addition of new sequences, Tetrahymena is still divided into three groups, namely the "borealis group", the "australis group," and the "paravorax group." (3) the cluster pattern of all the newly sequenced facultative parasitic Tetrahymena species shows that members of the "borealis" group may be more susceptible to parasitism. (4) phylogeny based on concatenated genes show that T. pyriformis, T. setosa, and T. leucophrys have close relationship. [ABSTRACT FROM AUTHOR]

The blood-brain barrier (BBB) is a dynamic barrier separating neurocytes and brain tissues from blood that is extremely sealed and strictly regulated by transporters such as aquaporin-4 (AQP-4), glucose transporter (GLUT), and specialized tight junctional complexes (TJCs) including tight junctions (TJs), adherens junctions (AJs), and Zonulae occludens (ZOs). With specifically selective transcellular and paracellular permeability, the BBB maintains a homeostatic microenvironment to protect the central nervous system (CNS). In recent years, increasing attention has been paied to the importance of BBB disruption and dysfunction in the pathology of neurological disorders and diseases, such as Alzheimer's diseases (AD), Parkinson diseases (PD), stroke and cerebral edema. However, the further research on how the integral structure and function of BBB are altered under the physiological or pathological conditions is still needed. Focusing on the ultrastructural features of the BBB and combining the latest research on associated proteins and transporters, physiological regulation and pathological change of the BBB were elucidated. By summarizing the protective effects of known bioactive compounds derived from marine life on the BBB, this review aims to highlight the BBB as a key to the treatment of several major neurological diseases instead of a normally described obstacle to drug absorption and transport. Overall, the BBB's morphological characteristics and physiological function and their regulation provide the theoretical basis for the study on the BBB and inspire the diagnosis of and therapy for neurological diseases. [ABSTRACT FROM AUTHOR]

Plant pathogens cause significant crop loss worldwide, and new resistance genes deployed to combat diseases can be overcome quickly. Understanding the existing resistance gene diversity within the germplasm of major crops, such as maize, is crucial for the development of new disease‐resistant varieties. We analysed the nucleotide‐binding leucine‐rich repeat receptors (NLRs) of 26 recently sequenced diverse founder lines from the maize nested association mapping (NAM) population and compared them to the R gene complement present in a wild relative of maize, Zea luxurians. We found that NLRs in both species contain a large diversity of atypical integrated domains, including many domains that have not previously been found in the NLRs of other species. Additionally, the single Z. luxurians genome was found to have greater integrated atypical domain diversity than all 26 NAM founder lines combined, indicating that this species may represent a rich source of novel resistance genes. NLRs were also found to have very high sequence diversity and presence–absence variation among the NAM founder lines, with a large NLR cluster on Chr10 representing a diversity hotspot. Additionally, NLRs were shown to be mobile within maize genomes, with several putative interchromosomal translocations identified. [ABSTRACT FROM AUTHOR]

Northern corn leaf blight, caused by the fungal pathogen Exserohilum turcicum, is a major disease of maize. The first major locus conferring resistance to E. turcicum race 0, Ht1, was identified over 50 years ago, but the underlying gene has remained unknown. We employed a map‐based cloning strategy to identify the Ht1 causal gene, which was found to be a coiled‐coil nucleotide‐binding, leucine‐rich repeat (NLR) gene, which we named PH4GP‐Ht1. Transgenic testing confirmed that introducing the native PH4GP‐Ht1 sequence to a susceptible maize variety resulted in resistance to E. turcicum race 0. A survey of the maize nested association mapping genomes revealed that susceptible Ht1 alleles had very low to no expression of the gene. Overexpression of the susceptible B73 allele, however, did not result in resistant plants, indicating that sequence variations may underlie the difference between resistant and susceptible phenotypes. Modelling of the PH4GP‐Ht1 protein indicated that it has structural homology to the Arabidopsis NLR resistance gene ZAR1, and probably forms a similar homopentamer structure following activation. RNA sequencing data from an infection time course revealed that 1 week after inoculation there was a threefold reduction in fungal biomass in the PH4GP‐Ht1 transgenic plants compared to wild‐type plants. Furthermore, PH4GP‐Ht1 transgenics had significantly more inoculation‐responsive differentially expressed genes than wild‐type plants, with enrichment seen in genes associated with both defence and photosynthesis. These results demonstrate that the NLR PH4GP‐Ht1 is the causal gene underlying Ht1, which represents a different mode of action compared to the previously reported wall‐associated kinase northern corn leaf blight resistance gene Htn1/Ht2/Ht3. [ABSTRACT FROM AUTHOR]

In response to the problems of complex background in the aerial images of the UAV which brings about seriously missed detection as well as poor detection precision, and excessive parameters as well as slow detection speed in the present deep network, an object detection algorithm of UAV vehicle based on Eficientnet is proposed. Firstly, Eficientnet, the lightweight network, is introduced as the feature extraction network of the YOLOv3 model, reducing the size of the model parameters and improving the detection speed of the algorithm. Secondly, the UAV vehicle dataset is clustered by the K-means algorithm to obtain the better bounding box size, thus improving the detection precision. Finally, with the CIoU bounding box loss function, the regression loss of the model is improved, thus enhancing the convergence ability of the model. Experimental results show that mAP of 92.60% and FPS of 31.15 can be achieved in the self-made UAV vehicle dataset based on the improved algorithm, which is 2.12 percentage points and 9.87 higher than the original algorithm, respectively. Therefore, it is more suitable for vehicle detection tasks in UAV scenarios. [ABSTRACT FROM AUTHOR]

Summary: Southern corn leaf blight (SLB), caused by the necrotrophic pathogen Cochliobolus heterostrophus, is one of the maize foliar diseases and poses a great threat to corn production around the world. Identification of genetic variations underlying resistance to SLB is of paramount importance to maize yield and quality. Here, we used a random‐open‐parent association mapping population containing eight recombinant inbred line populations and one association mapping panel consisting of 513 diversity maize inbred lines with high‐density genetic markers to dissect the genetic basis of SLB resistance. Overall, 109 quantitative trait loci (QTLs) with predominantly small or moderate additive effects, and little epistatic effects were identified. We found 35 (32.1%) novel loci in comparison with the reported QTLs. We revealed that resistant alleles were significantly enriched in tropical accessions and the frequency of about half of resistant alleles decreased during the adaptation process owing to the selection of agronomic traits. A large number of annotated genes located in the SLB‐resistant QTLs were shown to be involved in plant defence pathways. Integrating genome‐wide association study, transcriptomic profiling, resequencing and gene editing, we identified ZmFUT1 and MYBR92 as the putative genes responsible for the major QTLs for resistance to C. heterostrophus. Our results present a comprehensive insight into the genetic basis of SLB resistance and provide resistant loci or genes as direct targets for crop genetic improvement. [ABSTRACT FROM AUTHOR]

In the class Colpodea, there are many unresolved evolutionary relationships among taxa. Here, we report 30 new sequences including SSU‐rRNA, ITS1‐5.8S‐ ITS2 rRNA, and the mitochondrial small subunit ribosomal RNA (mtSSU‐rRNA) genes of five colpodeans, and conduct phylogenetic analyses based on each individual gene and a two‐gene concatenated dataset. For the first time, multi‐genes were used to analyze phylogenetic relationships in the class Colpodea. The main findings are: (1) SSU‐rRNA, ITS1‐5.8S‐ ITS2 rRNA, and mtSSU‐rRNA gene sequences of C. reniformis and C. grandis are provided for the first time, and these two species group into the clade including C. inflata, C. lucida, C. cucullus, and C. henneguyi; (2) clustering pattern and morphological similarity indicate that Bresslauides discoideus has a close relation with Colpodidae spp.; (3) Emarginatophrya genus diagnosis is improved to be 'Hausmanniellidae with sharply shortened and isometric leftmost 1‐4 ciliary rows' and Colpoda elliotti is transferred to Emarginatophrya; (4) the genus Colpoda is still non‐monophyletic with the addition of 10 populations from five Colpoda species sequences, but there are only two Colpoda groups left based on the present work: Group I comprises C. inflata, C. lucida, C. cucullus, C. henneguyi, C. reniformis, and C. grandis, Group II comprises C. maupasi and C. ecaudata, and the presence of diagonal grooves and the way the vestibular opens might be the two key features that differentiates Colpoda species groups; (5) a close molecular relationship, and highly similar merotelokinetal mode, somatic ciliary pattern, and basic organization of the oral apparatus with P. steinii suggests Bromeliothrix metopoides should be temporarily assigned to Colpodidae. [ABSTRACT FROM AUTHOR]

The application of molecular techniques to accurately identify protozoan species can correct previous misidentifications based on traditional morphological identification. Colpodea ciliates have many toxicological and cytological applications, but their subtle morphological differences and small body size hinder species delineation. Herein, we used Cox I and β-tubulin genes, alongside fluorescence in situ hybridization (FISH), to evaluate each method in delineating Colpodea species. For this analysis, Colpoda harbinensis n. sp., C. reniformis, two populations of C. inflata, Colpoda compare grandis, and five populations of Paracolpoda steinii, from the soil in northeastern China, were used. We determined that (1) the Cox I gene was more suitable than the β-tubulin gene as a molecular marker for defining intra- and interspecific level relationships of Colpoda. (2) FISH probes designed for Colpoda sp., C. inflata, Colpoda compare grandis, and Paracolpoda steinii, provided rapid interspecific differentiation of Colpodea species. (3) Colpoda harbinensis n. sp. was established and mainly characterized by its size in vivo (approximately 80 × 60 μ m), a reniform body in outline, one macronucleus, its spherical shape, a sometimes nonexistent micronucleus, 11–15 somatic kineties, and five or six postoral kineties. In conclusion, combining oligonucleotide probes, DNA barcoding, and morphology for the first time, we have greatly improved the delineation of Colpodea and confirmed that Cox I gene was a promising DNA barcoding marker for species of Colpodea, and FISH could provide useful morphological information as complementing traditional techniques such as silver carbonate. [ABSTRACT FROM AUTHOR]

Most current rolling bearing fault diagnostic approaches presume that sufficient labeled data are available for training. However, labeled fault data collection in realistic engineering is time-consuming and expensive, whereas the majority of data available are unlabeled, restricting diagnostic performance. To alleviate the dependence of feature self-extraction model on rolling bearing fault data and improve the feature capture ability, a bearing fault diagnosis method based on feature-enhanced generative adversarial networks with an auxiliary classifier (AC-FEGAN) is proposed in this paper. Firstly, the non-saturating loss with gradient penalty term is introduced to circumvent the gradient vanishing and improve learning stability. Then, employing identity mapping of residual networks introduced into AC-FEGAN, representative faulty features can be automatically extracted, overcoming the restrictions of shallow convolutional neural networks in feature extraction. Simultaneously, to improve feature learning ability, the self-attention module embedded in the residual network accomplishes refined feature extraction by incorporating appropriate weight matrices into the faulty feature maps. Finally, the auxiliary classifier is employed as a pre-training model for the fault diagnosis model, with generated and unlabeled samples employed to fine-tune the auxiliary classifier to identify faulty bearings. The experimental results show that the proposed method can significantly improve the quality of generated samples while eliminating the reliance of existing diagnosis methods on data volume to achieve more accurate and effective fault diagnosis. [ABSTRACT FROM AUTHOR]

A high-density genetic map of maize (Zea mays L.), integrated with a high-resolution bacterial artificial chromosome (BAC) contig map compiled from two inbred lines, B73 and Mo17, was used to determine gene density and recombination frequency along chromosomes and to compare the distribution of these features as a function of physical distance. Recombination frequency is well correlated with gene density for each chromosome (r = 0.767-0.960), although in centromeric regions, recombination is more depressed than a strict correlation with gene density would indicate. In addition, the distribution of major retrotransposon classes and of Mu and Hefitron insertion sites were examined. Overall retratransposon density is equal at all maize chromosomes (r: 0.996), although different classes of retrotransposons display preferential insertion into different chromosome regions. Cinful, Zeon, and Prem are more common near the centromere, while Opie, Ji, and Huck preferentially reside at the subtelomeric segments of chromosomes. Grande does not show preference in distribution relative to physical location on the chromosome. Comparison of the distribution of genic overgo probe hybridization-positive BACs from maize inbred line B73 to those of the inbred Mo17 indicates that nonshared genic segments, many of which correspond to pseudogenes carried by the Hefitron elements, tend to be less common in the centromeric region. As previously reported, Mu transposons seem to preferentially insert in the vicinity of genes, as indicated by their paucity in centromeric regions, and moderate correlation (r= 0.759) with gene density.