Fault Identification of Rotating Machinery Based on Dynamic Feature Reconstruction Signal Graph

To improve the performance in identifying the faults under strong noise for rotating machinery, this paper presents a dynamic feature reconstruction signal graph method, which plays the key role of the proposed end-to-end fault diagnosis model. Specifically, the original mechanical signal is first decomposed by wavelet packet decomposition (WPD) to obtain multiple subbands including coefficient matrix. Then, with originally defined two feature extraction factors MDD and DDD, a dynamic feature selection method based on L2 energy norm (DFSL) is proposed, which can dynamically select the feature coefficient matrix of WPD based on the difference in the distribution of norm energy, enabling each sub-signal to take adaptive signal reconstruction. Next the coefficient matrices of the optimal feature sub-bands are reconstructed and reorganized to obtain the feature signal graphs. Finally, deep features are extracted from the feature signal graphs by 2D-Convolutional neural network (2D-CNN). Experimental results on a public data platform of a bearing and our laboratory platform of robot grinding show that this method is better than the existing methods under different noise intensities

Design and preparation of a novel colon-targeted tablet of hydrocortisone

The objective of this research was to design a new colon-targeted drug delivery system based on chitosan. The properties of the films were studied to obtain useful information about the possible applications of composite films. The composite films were used in a bilayer system to investigate their feasibility as coating materials. Tensile strength, swelling degree, solubility, biodegradation degree, Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC), Scanning Electron Microscope (SEM) investigations showed that the composite film was formed when chitosan and gelatin were reacted jointly. The results showed that a 6:4 blend ratio was the optimal chitosan/gelatin blend ratio. In vitro drug release results indicated that the Eudragit- and chitosan/gelatin-bilayer coating system prevented drug release in simulated intestinal fluid (SIF) and simulated gastric fluid (SGF). However, the drug release from a bilayer-coated tablet in SCF increased over time, and the drug was almost completely released after 24h. Overall, colon-targeted drug delivery was achieved by using a chitosan/gelatin complex film and a multilayer coating system

Development and validation of a preoperative MRI-based radiomics nomogram to predict progression-free survival in patients with clival chordomas

ObjectivesThe aim of this study was to establish and validate a MRI-based radiomics nomogram to predict progression-free survival (PFS) of clival chordoma.MethodsA total of 174 patients were enrolled in the study (train cohort: 121 cases, test cohort: 53 cases). Radiomic features were extracted from multiparametric MRIs. Intraclass correlation coefficient analysis and a Lasso and Elastic-Net regularized generalized linear model were used for feature selection. Then, a nomogram was established via univariate and multivariate Cox regression analysis in the train cohort. The performance of this nomogram was assessed by area under curve (AUC) and calibration curve.ResultsA total of 3318 radiomic features were extracted from each patient, of which 2563 radiomic features were stable features. After feature selection, seven radiomic features were selected. Cox regression analysis revealed that 2 clinical factors (degree of resection, and presence or absence of primary chordoma) and 4 radiomic features were independent prognostic factors. The AUC of the established nomogram was 0.747, 0.807, and 0.904 for PFS prediction at 1, 3, and 5 years in the train cohort, respectively, compared with 0.582, 0.852, and 0.914 in the test cohort. Calibration and risk score stratified survival curves were satisfactory in the train and test cohort.ConclusionsThe presented nomogram demonstrated a favorable predictive accuracy of PFS, which provided a novel tool to predict prognosis and risk stratification. Our results suggest that radiomic analysis can effectively help neurosurgeons perform individualized evaluations of patients with clival chordomas

Differential gene expression and potential regulatory network of fatty acid biosynthesis during fruit and leaf development in yellowhorn (Xanthoceras sorbifolium), an oil-producing tree with significant deployment values

Xanthoceras sorbifolium (yellowhorn) is a woody oil plant with super stress resistance and excellent oil characteristics. The yellowhorn oil can be used as biofuel and edible oil with high nutritional and medicinal value. However, genetic studies on yellowhorn are just in the beginning, and fundamental biological questions regarding its very long-chain fatty acid (VLCFA) biosynthesis pathway remain largely unknown. In this study, we reconstructed the VLCFA biosynthesis pathway and annotated 137 genes encoding relevant enzymes. We identified four oleosin genes that package triacylglycerols (TAGs) and are specifically expressed in fruits, likely playing key roles in yellowhorn oil production. Especially, by examining time-ordered gene co-expression network (TO-GCN) constructed from fruit and leaf developments, we identified key enzymatic genes and potential regulatory transcription factors involved in VLCFA synthesis. In fruits, we further inferred a hierarchical regulatory network with MYB-related (XS03G0296800) and B3 (XS02G0057600) transcription factors as top-tier regulators, providing clues into factors controlling carbon flux into fatty acids. Our results offer new insights into key genes and transcriptional regulators governing fatty acid production in yellowhorn, laying the foundation for efforts to optimize oil content and fatty acid composition. Moreover, the gene expression patterns and putative regulatory relationships identified here will inform metabolic engineering and molecular breeding approaches tailored to meet biofuel and bioproduct demands

Plexin B2 and Semaphorin 4C Guide T Cell Recruitment and Function in the Germinal Center

Follicular T helper (TFH) cells orchestrate the germinal center (GC) response locally. TFH localization in GCs is controlled by chemo-guidance cues and antigen-specific adhesion. Here. we define an antigen-independent, contact-dependent, adhesive guidance system for TFH cells. Unusual for amoeboid cell migration, the system is composed of transmembrane plexin B2 (PlxnB2) molecule, which is highly expressed by GC B cells, and its transmembrane binding partner semaphorin 4C (Sema4C), which is upregulated on TFH cells. Sema4C on TFH cells serves as a receptor to sense the GC-presented PlxnB2 cue and biases TFH migration inwards at the GC edge to promote GC access. The absence of PlxnB2 from the GC or Sema4C from TFH cells causes TFH accumulation along the GC border, impairs T-B cell interactions in the GC, and is associated with defective plasma cell production and affinity maturation. Therefore, Sema4C and PlxnB2 regulate GC TFH recruitment and function and optimize antibody responses.This work was funded partly by the Ministry of Science and Technology 973 program (grant 2014CB542501 to H.Q.), the National Natural Science Foundation of China (grants 81425011 and 81330070 to H.Q. and grant 31200670 to L.W.), the Ministry of Science and Technology 863 program (grant 2012AA022403 to L.W.), a China Postdoctoral Science Foundation grant (2013M540970 to L.W.), and the Tsinghua-Peking Center for Life Sciences. H.Q. was supported partly by a Bayer Endowed Chair Professorship

Characterization of twenty-five ovarian tumour cell lines that phenocopy primary tumours

Currently available human tumour cell line panels consist of a small number of lines in each lineage that generally fail to retain the phenotype of the original patient tumour. Here we develop a cell culture medium that enables us to routinely establish cell lines from diverse subtypes of human ovarian cancers with >95% efficiency. Importantly, the 25 new ovarian tumour cell lines described here retain the genomic landscape, histopathology and molecular features of the original tumours. Furthermore, the molecular profile and drug response of these cell lines correlate with distinct groups of primary tumours with different outcomes. Thus, tumour cell lines derived using this methodology represent a significantly improved platform to study human tumour pathophysiology and response to therapy