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Objective To investigate the effect of miR-429 on the proliferation and migration of breast cancer cells and its mechanism. Methods RT-qPCR and Western blotting were used to measure the relative mRNA and protein expression levels of eIF4E in breast cancer MCF-7, MDA-MB-231, MDA-MB-468, and BT-549 cells and normal breast epithelial MCF-10A cells. MCF-7 cells were transfected with miR-429 mimics (group A), mimics NC (group B), miR-429 inhibitors (group C), and inhibitors NC (group D), and RT-qPCR, CCK-8 assay, wound healing assay, and Western blotting were used to measure the expression of miR-429, cell proliferation and migration, and the relative mRNA and protein expression levels of eIF4E in groups A-D. The 293T cells were transfected with eIF4E-3'UTR-Wt+miR-429 mimics (group E), eIF4E-3'UTR-Wt+mimics NC (group F), eIF4E-3'UTR-Mut+miR-429 mimics (group G), and eIF4E-3'UTR-Mut+mimics NC (group H), and relative luciferase activity was measured for groups E-H. The targeted regulatory effect of miR-429 on eIF4E was analyzed. Results RT-qPCR and Western blotting showed that the relative mRNA and protein expression levels of eIF4E in MCF-7, MDA-MB-231, MDA-MB-468, and BT-549 cells were significantly higher than those in normal breast epithelial MCF-10A cells (F=74.414,1 981.243,P

Primary bone marrow diffuse large B-cell lymphoma is an exceedingly rare form of non-Hodgkin lymphoma. It may demonstrate a leukemic presentation, and a proportion of cases have CD5 expression. The prognostic implications of this CD5-positivity remain unknown. Here, we present a 78-year-old man who presented with circulating peripheral blood lymphoma cells and a hypercellular marrow involved by diffuse large B-cell lymphoma, germinal center B-cell subtype. The patient responded favorably to six cycles of etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin, and rituximab (EPOCH-R) and intrathecal methotrexate. He unfortunately relapsed in several enlarged inguinal lymph nodes and succumbed to the lymphoma approximately one year after diagnosis, demonstrating the particularly aggressive clinical course of his disease.

In order to enable users to quickly make a reasonable choice from a large number of manufacturing cloud services with similar functions, on the basis of diversity of the evaluation indicators and the uncertainty of evaluation information, the evaluation method of manufacturing cloud services was proposed in conjunction with grey theory. Firstly, the QoS evaluation model of manufacturing cloud service was constructed and described. Secondly, evaluation structure was established, and the non-quantitative indicator was also defined by intuitionistic fuzzy number. Furthermore, the manufacturing cloud service ranking method based on intuitionistic fuzzy and grey theory was designed. With constructing intuitionistic fuzzy comprehensive matrix and obtaining optimal attribute matrix, the grey correlation coefficients between evaluation attributes and the optimal service attributes were solved for each manufacturing cloud service, and then the correlation degree was determined so as to provide a ranking reference for users. The experimental results show that: Then the proposed algorithm changes with the attribute weight value, and the ranking results of the candidate services also change, indicating that the algorithm has a certain flexibility. Finally, the service quality of the candidate manufacturing cloud service was compared with the proposed algorithm and the intuitive fuzzy TOPSIS method and the entropy right TOPSIS method. The closeness of the proposed algorithm is all greater than the comparison algorithm, which is improved by about 12% compared with the intuitive fuzzy TOPSIS method and about 44% compared with the entropy right TOPSIS method, which verifies its rationality and practicability.

Byline: Juan. Yang, Haijing. Sui, Haihan. Song, Ronghong. Jiao, Xiaohui. Zhao Conclusions: Increased RDW may be considered as a biomarker of MCI. Background and Objective: Previous literature has reported that [...]

Objective To analyze the feasibility of hospitalized treatment of inpatients' mental disorders in a general hospital by an innovative consultation-liaison psychiatric hospitalized treatment mode. Methods Retrospective study involved the patients in the department of physical diseases of Peking Union Medical College Hospital who received hospitalized treatment in the Department of Psychological Medicine from July 1, 2020 to June 30, 2021(study group). All patients who received consultation-liaison psychiatry (CLP) services by Department of Psychological Medicine from January 1 to December 31 in 2019 were taken as the control group. The control group conducted liaison consultation and invited consultation based on the CLP concept, whereas the study group integrated a three-level check-in and follow-up system based on the CLP concept to facilitate the diagnosis and treatment of inpatient mental disorders through consultation and follow-up. According to the consultation records, the diagnosis results and intervention methods were extracted, and the consultation rate and follow-up rate were calculated. Results A total of 1196 patients (1647 times of consultation) were included in the study group and 1269 patients (1558 times of consultation) in control group. The consultation departments involved all the physical disease departments of the hospital. Compared with the control group, in the study group the general consultation rate[1.21%(1196/98 496) vs. 1.10%(1269/114 917)], the general follow-up rate[23.08%(276/1196) vs. 17.65%(224/1269)] were improved to varying degrees. The diagnosis results of consultation-liaison hospitalized treatment involved almost all mental disorders, among which anxiety disorder (18.76%, 309/1647), depressive disorder (17.1%, 282/1647) and brain organic mental disorder (16.45%, 271/1647) accounted for a high proportion. As for the intervention mode of patients, 30.66% (505/1647) only needed psychological counseling or treatment, and almost all patients had non-drug treatment intervention. Conclusion It is feasible for general hospitals to realize hospitalized treatment of mental disorders based on CLP concept, combined with three-level ward round and follow-up system, which can improve the accessibility of mental medical services.

The characteristics of non-smoothness and uncertainty of gearbox fault vibration signal lead to the low accuracy of gearbox fault diagnosis. To address this problem, a gearbox fault diagnosis method based on local mean decomposition (LMD) cloud model feature extraction combined with particle swarm optimization (PSO) kernel extreme learning machine (KELM) is proposed. Firstly, the fault vibration signal is decomposed by LMD to obtain several PF components, and the PF components with higher correlation are screened out using the correlation coefficient principle. Secondly, the screened PF components are input into the cloud model, and the feature vectors are extracted using the inverse cloud generator and input into PSO-KELM for fault diagnosis. Finally, the performance of the method is analyzed using the measured data of the QPZZ-Ⅱ test-bed gearbox. The results show that the recognition accuracy of the method is 97.65%, and compared with various methods this method has the best recognition performance.