Foghbowen1547

Some studies reported the correlations between renal parenchymal stiffness measured by transient elastography or acoustic radiation force impulse (ARFI) and the extent of interstitial fibrosis. This study was prospectively designed to evaluate the correlation between clinical, histological findings and the kidney shear wave velocity (SWV, m/s) assessed by ARFI elastography to identify factors affecting the kidney SWV in normal patients.

Seventy-three adult living kidney transplantation donors were enrolled in our center between September 2010 and January 2013. Before transplantation, all donors were evaluated by ARFI elastography to identify the range of SWV in kidneys. Time-zero biopsies were performed on all graft kidneys before implantation.

Mean age of donors was 42.0 ± 11.3 years. The mean SWV and depth were 2.21 ± 0.58 m/s and 5.37 ± 1.06 cm. All histological findings showed mild degree of the Banff score, only grade I. In univariate analyses, the SWV was not associated with all histological parameters. Age (r = -0.274, P = .019) diastolic blood pressure (DBP, r = -0.255, P = .030) and depth for SWV measurement (r = -0.345, P = .003) were significantly correlated with the SWV. In multivariate linear regression analysis, age, gender, body mass index (BMI), and depth for SWV measurement were significantly correlated with the SWV (P = .003, .005, .002, and .004, respectively).

We demonstrated that all histological findings are not correlated with the SWV of donor kidney. Selleck AMG 487 Otherwise, factors influencing the kidney SWV assessed by ARFI elastography are age, gender, BMI, and depth for the SWV measurement in donors for kidney transplantation.

We demonstrated that all histological findings are not correlated with the SWV of donor kidney. Otherwise, factors influencing the kidney SWV assessed by ARFI elastography are age, gender, BMI, and depth for the SWV measurement in donors for kidney transplantation.

Pressure injuries, also known as pressure ulcers, are local skin injuries. Once a pressure injury occurs, clinical treatment is relatively difficult, the treatment cycle is long, and the treatment cost is high, which brings heavy burdens to patients and society. Therefore, look for a reliable pressure injuries treatment method is 1 of the focus of clinical nursing workers.

At present, there are many kinds of dressings to treat pressure injuries, and there is no uniform conclusion about which dressing is the most effective. Therefore, we systematically evaluate the effects of different dressings on the treatment of pressure injuries.

We systematically searched the Chinese and English databases PubMed, Embase, CENTRAL, CINAHL, Web of Science, CNKI, CBM, VIP, Wan Fang. Literature screening, data extraction, and quality evaluation were carried out by 2 researchers, and finally, use R software to carry out network meta-analysis.

This study is ongoing and the results will be submitted to a peer-reviewed journal for publication.

Ethical approval is not applicable, since this is an overview based on published articles.

INPLASY2020100087.

INPLASY2020100087.

Gliomas are an intractable tumor in the central nervous system. The present study aimed to identify the differentially expressed genes (DEGs) between glioblastoma multiforme (GBM) and low-grade gliomas (LGG) in order to investigate the mechanisms of different grades of gliomas. The Cancer Genome Atlas (TCGA) database was used to identify DEGs between GBM and LGG, and 2641 genes have been found differentially expressed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to determine the related functions and pathways of DEGs. Protein-protein interaction (PPI) network extracted a total of 444 nodes and 1953 interactions, and identified the top 6 hub genes in gliomas. The microarray data of the datasets GSE52009 and GSE4412, which were obtained from Gene Expression Omnibus (GEO) database, were used to externally validate DEGs expression levels. Gene Expression Profiling Interactive Analysis (GEPIA) database which was based on TCGA was used to explore the survival of hub geays of DEGs. Protein-protein interaction (PPI) network extracted a total of 444 nodes and 1953 interactions, and identified the top 6 hub genes in gliomas. The microarray data of the datasets GSE52009 and GSE4412, which were obtained from Gene Expression Omnibus (GEO) database, were used to externally validate DEGs expression levels. Gene Expression Profiling Interactive Analysis (GEPIA) database which was based on TCGA was used to explore the survival of hub genes in LGG and GBM. Additionally, the Oncomine database and Chinese Glioma Genome Atlas (CGGA) database were used to validate the mRNA expression level and prognostic value of hub genes. Gene Set Enrichment Analysis (GSEA) identified further hub genes-related pathways. In summary, through biological information and survival analysis, 6 hub genes may be new biomarkers for diagnosis and for guiding the choice of treatment strategies for different grades of gliomas.

The quality of life of patients with malignant tumor can be affected by the severity and treatment of the disease. After chemotherapy, the main symptoms are gastrointestinal reactions, including nausea, vomiting, loss of appetite, and so on, and hematologic response including leukopenia, anemia, and bleeding in severe cases. Currently, moxibustion is conducted to improve the living life of patients after chemotherapy. This article will make a comprehensive and objective discussion in terms of the effect of moxibustion on quality of life after chemotherapy in patients with malignant tumors.

After searching the Chinese database (CNKI, VIP, Wanfang Database, and Chinese Biomedical Database) and English database (PubMed, Embase, the Cochrane Library Web of Science), Meta-analysis was performed according to the randomized controlled trial of moxibustion after chemotherapy in patients with malignant tumors. The retrieval time was limited from the time of building the repository to October 2020. Two researchers independently conducted data extraction and quality evaluation of literature on the included studies, and RevMan5.