Objective To evaluate the role of nutritional support in the patients with gastrointestinal neoplasms on nutritional status after surgical procedure. Methods Totally 51 patients with gastrointestinal carcinoma and malnutrition were involved in this study. The patients were randomly assigned to receive only routine intravenous infusion without any nutritional support for 5 to 7 d postoperatively (control group) or early postoperative enteral nutrition for 5 to 7 d (group) or total parenteral nutrition support after operation for 3 to 5 d (total parental nutrition group). The nutrition status of the patients was detected before and after operation. Results The serum level of TSP, albumin, proalbumin, transferrin of enteral nutrition and total parental nutrition groups postoperatively decreased as compared with that before operation, but with no difference postoperatively between the two groups. In the control group, the postoperative serum level of total protein, albumin, proalbumin and transferrin decreased significantly (P0.05) as compared to the preoperative level. The occurrence of postoperative complications and hospital stay of the enteral nutrition group and the total parental nutrition group were less than that of the control group. Conclusion The present study suggests that early postoperative total parental nutrition and enteral nutrition support can improve the patients’ nutritional status, reduce the incidence of postoperative complications and hospital stay. Nutritional support at early stage after operation is safe, feasible and effective.
Abstract The vibration signal of a bearing is closely related to its fault. The quality of the features extracted from the signal has a great impact on the accuracy of fault diagnosis. In this paper, a new method combining multi-scale autoencoder (AE) and generative adversarial network is proposed to extract the depth-sensitive features of the signal, and unite with the classifier for fault diagnosis. The AE is used as the generator (i.e. the generator is composed of encoder and decoder), and the idea of confrontation and reconstruction is used for training. The better the training of the generator, the better the training of the encoder, which means that the extracted feature of the encoder (the output of the encoder) is better. Then take these features as new inputs, send them to the classifier for classification, and finally get the fault type. This method solves the problems of weak representation and over-reliance on professional knowledge of the traditional method for bearing fault diagnosis. Meanwhile, compared with most existing neural network models for fault diagnosis, it has higher accuracy, especially in difficult diagnosis tasks. To further verify the effectiveness of the proposed model, a bearing test rig is established, and the collected data are used for fault diagnosis to prove the superiority of the proposed method.
Adenosine receptor A2B ( ADORA2B ) encodes a protein belonging to the G protein–coupled receptor superfamily. Abnormal expression of ADORA2B may play a pathophysiological role in some human cancers. We investigated whether ADORA2B is a potential diagnostic and prognostic biomarker for lung adenocarcinoma (LUAD). The expression, various mutations, copy number variations, mRNA expression levels, and related network signaling pathways of ADORA2B were analyzed using bioinformatics-related websites, including Oncomine, UALCAN, cBioPortal, GeneMANIA, LinkedOmics, KM Plotter, and TIMER. We found that ADORA2B was overexpressed and amplified in LUAD, and a high ADORA2B expression predicted a poor prognosis for LUAD patients. Pathway analyses of ADORA2B in LUAD revealed ADORA2B -correlated signaling pathways, and the expression level of ADORA2B was associated with immune cell infiltration. Furthermore, ADORA2B mRNA and protein levels were significantly higher in human LUAD cell lines (A549 cells and NCl-H1299 cells) than in normal human bronchial epithelial (HBE) cells, and the transcript levels of genes positively or negatively correlated with ADORA2B were consistent and statistically significant. siRNA transfection experiments and functional experiments further confirmed these results. In vitro results were also consistent with those of bioinformatics analysis. Our findings provide a foundation for studying the role of ADORA2B in tumorigenesis and support the development of new drug targets for LUAD.
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