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In order to understand the current situation of secondary vocational education research in China, this paper adopts the literature research method to study the development of secondary vocational education in China. Firstly, we searched the literature of secondary vocational education research and found that the main research literature was focused on three areas: "research on secondary vocational education development", "research on school-enterprise cooperation and industry-education integration model of secondary vocational education", and "research on secondary vocational teaching reform". After analyzing the hotspots of secondary vocational education research, the future directions that researchers should focus on in the field of secondary education research in the future are generally "problems in the development of secondary vocational education", such as promoting the research of "school-enterprise cooperation and integration of industry-education" in secondary vocational schools. "The important role of secondary vocational education as a bridge", such as the promotion of the "double high" policy, which opens up new channels for higher education or vocational-technical universities through the creation of specialties. "Teacher training and pedagogical innovation in secondary vocational education" e.g. interdisciplinary cross-fertilization. It is strongly believed that these recommendations will be useful for researchers concerned with the field of secondary vocational education

A phosphine-promoted intermolecular annulation reaction of functionalized 3-benzoyl coumarin with alkynone has been disclosed. This reaction was found to be highly dependent on the nucleophilicity of the phosphine. Two classes of coumarin-fused cyclopentanones were selectively afforded in moderate to good yields with excellent diastereoselectivities under the mild reaction conditions.

A tertiary phosphine-mediated [3+2] cyclization reaction of ynones with fluorinated coumarin derivatives has been developed to give a series of coumarin-based CF3-containing furanones in moderate to good yields under mild reaction conditions. Preliminary investigation into their antitumor activities is also presented.

Severe working environments cause gas turbines to break down, which can directly affect their performance. Research on the diagnostic methods for gas turbine faults, such as, gas path faults and sensor failures, has always raised concerns. However, traditional fault diagnosis algorithms mostly use instantaneous data rather than time-series data, because they cannot efficiently use time-series analysis to extract fault features and improve algorithm accuracy. Problems with sparse fault samples and categories are also encountered with these algorithms. In this study, a gas turbine fault diagnostic method based on a 2D-wavelet transform and generative adversarial network (GAN) was proposed. The data preprocessing method, 2D-wavelet transform, of multiple time series images was used to obtain fault features. Based on the Fréchet inception distance, a performance evaluation index, an optimal generator built from a deep convolutional GAN model was selected to solve sparse or imbalanced datasets. The classification accuracy of the four algorithms, namely, random forest, support vector machine, convolutional neural network, and deep neural network, verified the performance of the data preprocessing and dataset building methods mentioned earlier. Compared with the original data, the 2D wavelet transform effectively improved the model accuracy. The generated samples also improved the misclassification issue caused by the imbalanced dataset; however, the ratio of real and generated samples in datasets still requires more attention.

A phosphine-mediated tandem [3 + 2] cyclization/intramolecular Wittig reaction of 3-aroylcoumarin with alkynone is described. The high efficiency of the tandem process allows the synthesis of 2-chromanone-fused bicyclo[3.2.0]heptenones in moderate to high yields with remarkably high regio- and diastereoselectivities under mild reaction conditions, which represents an extremely simple, economical and straightforward synthetic method to construct complex cyclic building blocks with potential biological applications.

Due to the special structure of the cylinder block, there is an off-center position and swing fault in the process of start-up and operation of the 50 MW extraction unit. Moreover, the lack of effective monitoring and early warning means seriously affects the safety of the unit operation. Therefore, it is very important to forewarn the fault of cylinder off-center position and swing. First of all, through the design of cylinder block offset amplifying mechanism for fault monitoring, the data of eccentric swing required for establishing mathematical model is obtained. Then, neural network is selected for data-driven modeling, two time series prediction models are obtained, and the influence of input and output parameters on the prediction accuracy is studied. Finally, by selecting reasonable early warning value and decision rules, an effective early warning of off-center position and swing fault is realized, and a monitoring device for real-time monitoring and fault early warning is developed. The actual application effect shows that this early warning method has important engineering value to avoid equipment damage caused by the swing fault for 50 MW unit.

Background Lung adenocarcinoma (LUAD) accounts for a significant proportion of lung cancer and there have been few diagnostic and therapeutic targets for LUAD due to the lack of specific biomarker. The aim of this study was to identify key long non-coding RNAs (lncRNAs) for LUAD. Methods The lncRNA and mRNA expression profiles of a large group of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA). The differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were identified. The optimal diagnostic lncRNA biomarkers for LUAD were identified by using feature selection procedure and classification model. We established classification models including random forests, decision tree and support vector machine to distinguish LUAD and normal tissues. The lncRNAs-mRNAs co-expression networks and module identification were established by weighted gene co-expression network analysis (WGCNA). Functional annotation of pink and green modules was performed. The expression of selected DElncRNAs were validated by qRT-PCR. Results A total of 1364 DEmRNAs (468 down-regulated and 896 up-regulated mRNAs) and 260 DElncRNAs (88 down-regulated and 172 up-regulated lncRNAs) between LUAD and normal tissue were obtained. LANCL1-AS1, MIR3945HG, LINC01270, RP5-1061H20.4, BLACAT1, LINC01703, CTD-2227E11.1 and RP1-244F24.1 were identified as optimal diagnostic lncRNA biomarkers for LUAD. The area under curve (AUC) of the random forests model, decision tree model and SVM model were 0.999, 0.937 and 0.999, and the specificity and sensitivity of the three model were 98.3% and 99.8%, 93.2% and 99% and 100% and 98.4%, respectively. Co-expression networks analysis showed that RP11-389C8.2, CTD-2510F5.4 and TMPO-AS1 were co-expressed with 44, 242 and 241 mRNAs, respectively. Cell cycle, DNA replication and p53 signaling pathway were three significantly enriched pathways. The qRT-PCR results were consistent with our integrated analysis, generally. The GSE32863 and GSE104854 validation was consistent with our integrated analysis, generally. Conclusion Our study identified eight DElncRNAs as potential diagnostic biomarkers of LUAD. Functional annotation of green module provided new evidences for exploring the precise roles of lncRNA in LUAD.

Vibrio cholerae can cause pandemic cholera in humans. The bacterium resides in aquatic environments worldwide. Identification of risk factors of V. cholerae in aquatic products is imperative for assuming food safety. In this study, we determined virulence-associated genes, cross-resistance between antibiotics and heavy metals, and genome fingerprinting profiles of non O1/O139 V. cholerae isolates (n = 20) recovered from 16 species of consumable aquatic animals. Secretomes and proteomes of V. cholerae with distinct genotypes and phenotypes were obtained by using two-dimensional gel electrophoresis (2D-GE) and/or liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques. Comparative secretomic analysis revealed 4 common and 45 differential extracellular proteins among 20 V. cholerae strains, including 13 virulence- and 8 resistance-associated proteins. A total of 21,972 intracellular proteins were identified, and comparative proteomic analysis revealed 215 common and 913 differential intracellular proteins, including 22 virulence- and 8 resistance-associated proteins. Additionally, different secretomes and proteomes were observed between V. cholerae isolates of fish and shellfish origins. A number of novel proteins with unknown function and strain-specific proteins were also discovered in the V. cholerae isolates. Significance V. cholerae can cause pandemic cholera in humans. The bacterium is distributed in aquatic environments worldwide. Identification of risk factors of V. cholerae in aquatic products is imperative for assuming food safety. Non-O1/O139 V. cholerae has been reported to cause sporadic cholera-like diarrhea and bacteremia diseases, which indicates virulence factors rather than the major cholera toxin (CT) exist. This study for the first time investigated proteomes and secretomes of non-O1/O139 V. cholerae originating from aquatic animals. This resulted in the identification of a number of virulence and coresistance-related factors, as well as novel proteins and strain-specific proteins in V. cholerae isolates recovered from 16 species of consumable aquatic animals. These results fill gaps for better understanding of pathogenesis and resistance of V. cholerae, and also support the increasing need for novel diagnosis and vaccine targets against the leading waterborne pathogen worldwide.

This study investigated the feasibility of combining targeted sequencing and ultra-low-pass whole-genome sequencing (ULP-WGS) for improved somatic copy number alteration (SCNA) detection, due to its role in tumorigenesis and prognosis. Cerebrospinal fluid and matched blood samples were obtained from 29 patients with brain metastasis derived from lung cancer. Samples were subjected to targeted sequencing (genomic coverage: 300 kb) and 2×ULP-WGS. The SCNA was detected by the CTLW_CNV, Control-FreeC, and CNVkit methods and their accuracy was analyzed. Eighteen tumor samples showed consistent SCNA results between the three methods, while a small fraction of samples resulted in different SCNA estimations. Further analysis indicated that consistency of SCNA highly correlated with the difference of baseline depth (normalized depth of regions without SCNA events) estimation between methods. Conflict Index showed that CTLW_CNV significantly improved the accuracy of SCNA detection through precise baseline depth estimation. CTLW_CNV combines targeted sequencing and ULP-WGS for improved SCNA detection. The improvement in detection accuracy is mainly due to a refined baseline depth estimation, guided by single-nucleotide polymorphism allele frequencies within the deeply sequenced region (targeted sequencing). This method is especially suitable for tumor samples with biased aneuploidy, a previously under-estimated genomic characteristic across different cancer types.

The performance of the unit is in a state of realtime degradation, and the traditional proprietary test method cannot accurately monitor this performance degradation in time. Aiming at the above problems, a real-time monitoring system and optimization scheme for steam turbine performance based on data driven model is proposed. Firstly, a steam turbine performance prediction model based on pattern recognition and prediction function is established, which can realize medium and long-term prediction of turbine operating economy and provide early warning for performance degradation. Then, performance analysis is performed for units performance degradation, respectively in thermal system and communication. The corresponding optimization scheme is proposed in the flow design. Finally, the 600MW supercritical unit is taken as the research case. The results show that the above method is effective and feasible in practice.

Background: Fusion of RET with several partner genes has been detected in papillary thyroid, lung, colorectal, pancreatic and breast cancers. FDA has approved Retevmo (Selpercatinib) for lung and thyroid cancers with RET gene mutations or fusions. Here we focused on the prevalence of RET fusions in a Multi-cancer cohort (besides lung and thyroid cancers) for patients (pts) whom might benefit from RET inhibitors in clinical development. Methods: Genomic profiling was performed on 12,888 lung cancer pts, 2,848 colorectal cancer pts, 1,785 liver cancer pts, 1,169 Gastric cancer pts and 232 thyroid cancer pts from Jan. 2017 to Dec. 2019 using next-generation sequencing (NGS), which covers all exons of RET and specific intron 7-11 containing the break points of fusions. The fusion patterns of RET were analyzed. Results: A total of 165 RET fusions were identified in approximately 0.86% (163/18,922) of this Chinese multi-cancer cohort. The RET fusion-positive rates were 1.05% (135/12,888) in lung cancer pts, 0.39% (11/2,848) in the colorectal cancer pts, 0.06% (1/1,785) in liver cancer pts, 0.09% (1/1,169) in the 1169 Gastric cancer pts and 6.03% (15/232) in the 232 thyroid cancer pts tested. The most common partners were KIF5B (62.04%) and CCDC6 (21.17%) in lung cancer, NCOA4 (45.45%) and CCDC6 (27.27%) in colorectal cancer, and CCDC6 (93.33%) and NCOA4 (6.67%) in thyroid cancer. The most frequent regions of RET fusions were intron 11 (140/165) and intron 10 (15/165). The common fusion partners detected in different cancers are variable, indicating that the same oncogene has different carcinogenic mechanisms in cancers, and the sensitivity of these fusions to RET inhibitors in different cancers needs to be further studied. Conclusions: This study revealed the molecular features of RET rearrangement in Chinese cancer pts, which might result in more effective personalized diagnoses and therapies. Citation Format: Ting Lei, Weiran Wang, Danhua Wang, Junfeng Fu, Yu Wang, Ze Wang, Zhe Fan, Zhenyang Lv, Tonghui Ma. Landscape of RET fusion identified by next-generation sequencing in a Chinese multi-cancer retrospective analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2215.

Purpose We examined the expression, clinical correlation and functional mechanisms of endogenous microRNA-424 (miR-424) in human non-small cell lung cancer (NSCLC). Methods Expression pattern of endogenous miR-424 was examined by qRT-PCR in clinical samples obtained from 233 NSCLC patients. Correlations between differential miR-424 expression level (low vs. high) and NSCLC patients’ clinicopathological parameters or survival were statistically examined. In in vitro NSCLC H596 and SW900 cells, miR-424 was either upregulated or downregulation by lentiviral transduction. Their effects on cancer cell viability, proliferation, and cell-cycle transition were also examined. Results MiR-424 expression was not different between NSCLC tumors and healthy lung tissues. However, it is much upregulated in NSCLC tumors associated with patients at advanced clinical stages. Statistical analyses demonstrated that high endogenous miR-424 expression in NSCLC tumors was significantly correlated with patients’ advanced clinical stages, aggressive tumor metastasis, and short survival. In addition, Cox regression model predicted that endogenous miR-424 might be an independent prognostic marker in NSCLC. In in vitro NSCLC cell lines, miR-424 downregulation had a significant suppressing effect on cancer proliferation and G1 to S phase cell-cycle transition. On the other hand, miR-424 upregulation had no effect on NSCLC in vitro. Conclusion High endogenous miR-424 expression in tumors may predict poor prognosis of patients with NSCLC. Inhibiting endogenous miR-424 may also serve an effective cancer suppressor in NSCLC.

BackgroundIn the last decade, integrative studies of microbiome and metabolome have experienced exponential growth in understanding their impact on human health and diseases. However, analyzing the resulting multi-omics data and their correlations remains a significant challenge in current studies due to the lack of a comprehensive computational tool to facilitate data integration and interpretation. In this study, we have developed a microbiome and metabolome integrative analysis pipeline (M2IA) to meet the urgent needs for tools that effectively integrate microbiome and metabolome data to derive biological insights.ResultsM2IA streamlines the integrative data analysis between metabolome and microbiome, including both univariate analysis and multivariate modeling methods. KEGG-based functional analysis of microbiome and metabolome are provided to explore their biological interactions within specific metabolic pathways. The functionality of M2IA was demonstrated using TwinsUK cohort data with 1116 fecal metabolites and 16s rRNA microbiome from 786 individuals. As a result, we identified two important pathways, i.e., the benzoate degradation and phosphotransferase system, were closely associated with obesity from both metabolome and microbiome.ConclusionsM2IA is a public available web server (http://m2ia.met-bioinformatics.cn) with the capability to investigate the complex interplay between microbiome and metabolome, and help users to develop mechanistic hypothesis for nutritional and personalized therapies of diseases.