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Accurate understanding of 3D objects in complex scenes plays essential roles in the fields of intelligent transportation and autonomous driving technology. Recent deep neural networks have made significant progress in 3D visual tasks by using point cloud data. However, the acquisition of geometric features and the expression of local fine-grained features in point clouds are still not sufficient for the classification and segmentation tasks. Inspired by the application of transformer structures in 2D and 3D computer vision tasks, in this paper, a multi-scale neighborhood aggregation transformer network (MNAT-Net) is proposed for point cloud classification and segmentation, which captures the global semantic information and local geometric structure features of point clouds by aggregating the receptive field and node weights. MNAT-Net consists of three key components, namely the multi-scale neighborhood feature aggregation module, the global transformer module and the category-weighted focal loss. The neighborhood features learned by the MNAT-Net network is sent to the global transformer module to fully enrich the contextual representation. Experimental results show that MNAT-Net achieves competitive performance on publicly available ModelNet40, ShapeNet, S3DIS and SemanticKITTI data sets in comparison to related methods.

Nucleic acid hybridization is crucial in target recognition with respect to in vitroand in vivonucleic acid biosensing. Conventional linear probes and molecular beacons encounter challenges in multiplexing and specific recognition of intractable nucleic acids. Advances in nucleic acid nanotechnologies have resulted in a set of novel structural probes: junction probes (JPs), which make full use of the advantages of specificity, stability, programmability and predictability of Watson–Crick base pairing. In recent years, junction probes have been regularly implemented in constructing systems related to biosensing, synthetic biology and gene regulation. Herein, we summarize the latest advances in JP designs as potential nucleic acid biosensing systems and their expansive applications, and provide some general guidelines for developing JP based sensing strategies for implementation of such systems.

Background: Calcium ions usually act as a second messenger in the signal transmission process and a major element required by plants. In Hevea, calcium ion could alleviate the negative effects of long-term ethylene application to a certain extent. However, the molecular mechanisms remain unclear. Methods: Two-dimensional electrophoresis was used to determine the pattern of protein changes in latex after treatments with calcium and/or ethylene. Quantitative real-time polymerase chain reaction and Western blotting were used to determine the expression levels of some proteins and genes. STRING software was used to determine the protein-protein interaction network of the identified proteins. Results: Comparative proteomics identified 145 differentially expressed proteins, which represented 103 unique proteins. The abundance change patterns of some proteins involved in signal transduction, rubber particle aggregation, and natural rubber biosynthesis were altered upon calcium stimulation. Quantitative real-time polymerase chain reaction analysis of 29 proteins showed that gene expression did not always maintain the same trend as protein expression. The increased enzyme activities of superoxide dismutase, ascorbate peroxidase, and glutathione reductase suggested that calcium can enhance the antistress ability of plants by increasing the activity of their antioxidant enzyme systems. Conclusion: These results supplement the rubber latex proteome, and provide evidence for investigating the molecular mechanisms by which calcium alleviates the negative effects of ethylene stimulation.

Proteomic analysis of upland cotton was performed to profile the global detectable proteomes of ovules and fibers using two-dimensional electrophoresis (2DE). A total of 1,203 independent protein spots were collected from representative 2DE gels, which were digested with trypsin and identified by matrix-assisted laser desorption and ionization-time-offlight/ time-of-flight (MALDI-TOF/TOF) mass spectrometry. The mass spectrometry or tandem mass spectrometry (MS or MS/MS) data were then searched against a local database constructed from Gossypium hirsutumgenome sequences, resulting in successful identification of 975 protein spots (411 for ovules and 564 for fibers). Functional annotation analysis of the 975 identified proteins revealed that ovule-specific proteins were mainly enriched in functions related to fatty acid elongation, sulfur amino acid metabolism and post-replication repair, while fiber-specific proteins were enriched in functions related to root hair elongation, galactose metabolism and D-xylose metabolic processes. Further annotation analysis of the most abundant protein spots showed that 28.96% of the total proteins in the ovule were mainly located in the Golgi apparatus, endoplasmic reticulum, mitochondrion and ribosome, whereas in fibers, 27.02% of the total proteins were located in the cytoskeleton, nuclear envelope and cell wall. Quantitative real-time polymerase chain reaction (qRT-PCR) analyses of the ovule-specific protein spots P61, P93 and P198 and fiber-specific protein spots 230, 477 and 511 were performed to validate the proteomics data. Protein-protein interaction network analyses revealed very different network cluster patterns between ovules and fibers. This work provides the largest protein identification dataset of 2DE-detectable proteins in cotton ovules and fibers and indicates potentially important roles of tissue-specific proteins, thus providing insights into the cotton ovule and fiber proteomes on a global scale.

Lutoids are specific vacuole-based organelles within the latex-producing laticifers in rubber tree Hevea brasiliensis. Primary and secondary lutoids are found in the primary and secondary laticifers, respectively. Although both lutoid types perform similar roles in rubber particle aggregation (RPA) and latex coagulation, they vary greatly at the morphological and proteomic levels. To compare the differential proteins and determine the shared proteins of the two lutoid types, a proteomic analysis of lutoid membranes and inclusions was performed, revealing 169 proteins that were functionally classified into 14 families. Biological function analysis revealed that most of the proteins are involved in pathogen defense, chitin catabolism, and proton transport. Comparison of the gene and protein changed patterns and determination of the specific roles of several main lutoid proteins, such as glucanase, hevamine, and hevein, demonstrated that Chitinase and glucanase appeared to play crucial synergistic roles in RPA. Integrative analysis revealed a protein-based metabolic network mediating pH and ion homeostasis, defense response, and RPA in lutoids. From these findings, we developed a modified regulation model for lutoid-mediated RPA that will deepen our understanding of potential mechanisms involved in lutoid-mediated RPA and consequent latex coagulation.

Thellungiella halophila, a close relative of Arabidopsis, is a model halophyte used to study plant salt tolerance. The proteomic/physiological/transcriptomic analyses of Thellungiella plant leaves subjected to different salinity levels, reported herein, indicate an extraordinary ability of Thellungiella to adapt to large concentrations of exogenous saline by compartmentalizing Na+into cell vacuoles and accumulating proline and soluble sugars as organic osmolytes. Salinity stress stimulated the accumulation of starch in chloroplasts, which resulted in a greatly increased content of starch and total sugars in leaves. Comparative proteomics of Thellungiella leaves identified 209 salt-responsive proteins. Among these, the sequences of 108 proteins were strongly homologous to Arabidopsis protein sequences, and 30 had previously been identified as Thellungiella proteins. Functional classification of these proteins into 16 categories indicated that the majority are involved in carbohydrate metabolism, followed by those involved in energy production and conversion, and then those involved in the transport of inorganic ions. Pathway analysis revealed that most of the proteins are involved in starch and sucrose metabolism, carbon fixation, photosynthesis, and glycolysis. Of these processes, the most affected were starch and sucrose metabolism, which might be pivotal for salt tolerance. The gene expression patterns of the 209 salt-responsive proteins revealed through hierarchical clustering of microarray data and the expression patterns of 29 Thellungiella genes evaluated via quantitative RT-PCR were similar to those deduced via proteomic analysis, which underscored the possibility that starch and sucrose metabolism might play pivotal roles in determining the salt tolerance ability of Thellungiella. Our observations enabled us to propose a schematic representation of the systematic salt-tolerance phenotype in Thellungiella and suggested that the increased accumulation of starch, soluble sugars, and proline, as well as subcellular compartmentalization of sodium, might collectively denote important mechanisms for halophyte salt tolerance.

This paper presents a new face recognition method that extracts multiple discriminant features based on multiscale image enhancement technique and kernel-based orthogonal feature extraction improvements with several interesting characteristics. First, it can extract more discriminative multiscale face feature than traditional pixel-based or Gabor-based feature. Second, it can effectively deal with the small sample size problem as well as feature correlation problem by using eigenvalue decomposition on scatter matrices. Finally, the extractor handles nonlinearity efficiently by using kernel trick. Multiple recognition experiments on open face data set with comparison to several related methods show the effectiveness and superiority of the proposed method.

Automatic measurement of vessels from fundus images is a crucial step for assessing vessel anomalies in ophthalmological community, where the change in retinal vessel diameters is believed to be indicative of the risk level of diabetic retinopathy. In this paper, a new retinal vessel diameter measurement method by combining vessel orientation estimation and filter response is proposed. Its interesting characteristics include: (1) different from the methods that only fit the vessel profiles, the proposed method extracts more stable and accurate vessel diameter by casting this problem as a maximal response problem of a variation of Gabor filter; (2) the proposed method can directly and efficiently estimate the vessel's orientation, which is usually captured by time-consuming multi-orientation fitting techniques in many existing methods. Experimental results shows that the proposed method both retains the computational simplicity and achieves stable and accurate estimation results.

•Aspirated cellular RNA analysis technique based on needle biopsies was firstly described on prostate cancer (PCa).•Aspirated cellular RNA analysis can provide urgent information for PCa diagnosis and staging.•This technique enables fast and reliable review of whole-biopsy molecular profile prior to histopathological diagnosis.