ABSTRACT
In modern industry, due to the poor working environment and the complex working conditions of mechanical equipment, the characteristics of the impact signals caused by faults are often submerged in strong background signals and noises. Therefore, it is difficult to effectivelyextract the fault features. In this paper, a fault feature extraction method based on improved VMD multi-scale dispersion entropy and TVD-CYCBD is proposed. First, the marine predator algorithm (MPA) is used to optimize the modal components and penalty factors in VMD. Second, the optimized VMD is used to model and decompose the fault signal, and then the optimal signal components are filtered according to the combined weight index criteria. Third, TVD is used to denoise the optimal signal components. Finally, CYCBD filters the de-noised signal and then envelope demodulation analysis is carried out. Through the simulation signal experiment and the actual fault signal experiment, the results verified that multiple frequency doubling peaks can be seen from the envelope spectrum, and there is little interference near the peak, which shows the good performance of the method.
ABSTRACT
Background: Stage IV Thyroid cancer (TC) has a relatively poor prognosis and lacks a precise and efficient instrument to forecast prognosis. Our study aimed to construct a nomogram for predicting the prognosis of patients with stage IV TC based on data from the SEER programme. Methods: We enrolled patients diagnosed with TC from 2004 to 2015 in the study. Furthermore, the median survival time (MST) for the patients equalled 25 months. The patients were split into two groups: the training group and validation group. We used descriptive statistics to calculate demographic and clinical variables, Student's t test was used to describe continuous variables, and the chi-square test was used to describe classified variables. We used the concordance index (C-index) to evaluate discrimination ability and calibration plots to evaluate calibration ability. The improvement of the nomogram compared with the AJCC TNM system was evaluated by the net weight classification index (NRI), comprehensive discriminant rate improvement (IDI) and decision curve analysis (DCA). Results: There were 3501 patients contained within our cohort, and the median follow-up was 25 months [quartile range (IQR): 6-60] in the whole population, 25 months (IQR: 6-60) in the training cohort, and 25 months (IQR: 5-59) in the validation cohort. The C-index value of the training cohort equalled 0.86 (95% CI: 0.85-0.87), and the value of the validation cohort equalled 0.85 (95% CI: 0.84-0.86). The NRI values were as follows: training queue: 1.16 for three-year and 1.12 for five-year OS prediction; authentication group: 1.22 for three-year and 1.21 for five-year OS prediction. The IDI values were as follows: training cohort: 0.25 for three-year and 0.21 for five-year OS prediction; validation cohort: 0.27 for three-year and 0.21 for five-year OS prediction. The DCA diagram showed that the nomogram was superior in predicting the three-year and five-year trends. Conclusions: Our nomogram can be used to forecast the survival of patients with stage IV TC.
ABSTRACT
Background: Acute myelogenous leukemia (AML) is nosocomial with the highest pediatric mortality rates and a relatively poor prognosis. C4.4A(LYPD3) is a tumorigenic and high-glycosylated cell surface protein that has been proven to be linked with the carcinogenic effects in solid tumors, but no hematologic tumors have been reported. We focus on exploring the molecular mechanism of LYPD3 in the regulation of the occurrence and development of AML to provide a research basis for the screening of markers related to the treatment and prognosis. Methods: Datasets on RNA Sequencing (RNA-seq) and mRNA expression profiles of 510 samples were obtained from The Cancer Genome Atlas Program/The Genotype-Tissue Expression (Tcga-gtex) on 10 March 2021, which included the information on 173 AML tumorous tissue samples and 337 normal blood samples. The differential expression, identification of prognostic genes based on the COX regression model, and LASSO regression were analyzed. In order to better verify, experiments including gene knockdown mediated by small interfering RNA (siRNA), cell proliferation assays, and Western blot were prefomed. We studied the possible associated pathways through which LYPD3 may have an impact on the pathogenesis and prognosis of AML by gene set enrichment analysis (GSEA). Results: A total of 11,490 differential expression genes (DEGs) were identified. Among them, 4,164 genes were upregulated, and 7,756 genes were downregulated. The univariate Cox regression analysis and LASSO regression analysis found that 28 genes including LYPD3, DNAJC8, and other genes were associated with overall survival (OS). After multivariate Cox analysis, a total of 10 genes were considered significantly correlated with OS in AML including LYPD3, which had a poor impact on AML (p <0.05). The experiment results also supported the above conclusion. We identified 25 pathways, including the E2F signaling pathway, p53 signaling pathway, and PI3K_AKT signaling pathway, that were significantly upregulated in AML samples with high LYPD3 expression (p < 0.05) by GSEA. Further, the results of the experiment suggested that LYPD3 participates in the development of AML through the p53 signaling pathway or/and PI3K/AKT signaling pathway. Conclusion: This study first proved that the expression of LYPD3 was elevated in AML, which was correlated with poor clinical characteristics and prognosis. In addition, LYPD3 participates in the development of AML through p53 or/and the PI3K/AKT signaling pathway.
ABSTRACT
3D printing consisted of in-situ UV-curing module can build complex 3D structures, in which direct ink writing can handle versatile materials. However, UV-based direct ink writing (DIW) is facing a trade-off between required curing intensity and effectiveness range, and it cannot implement multiscale parallelization at ease. We overcome these difficulties by ink design and introducing near-infrared (NIR) laser assisted module, and this increases the scalability of direct ink writing to solidify the deposited filament with diameter up to 4 mm, which is much beyond any of existing UV-assisted DIW. The NIR effectiveness range can expand to tens of centimeters and deliver the embedded writing capability. We also demonstrate its parallel manufacturing capability for simultaneous curing of multi-color filaments and freestanding objects. The strategy owns further advantages to be integrated with other types of ink-based 3D printing technologies for extensive applications.
