Objective To explore the factors associated with the quality of life (QOL) in patients after liver and kidney transplantation.Methods A multicenter cross-sectional survey was carried out in 5 Level Ⅲ Class A hospitals.153 liver transplant recipients and 301 kidney transplant recipients of outpatient clinic follow-up from March to December in 2015 were selected and investigated with a self-designed general state questionnaire,and Quality of Life Scale for Liver and Kidney Transplant Recipients which developed by our research group.Results There were significant differences in QOL total score in liver and kidney transplant recipients among groups of marital status and occupation.Divorced,unemployed and low-educated patients showed lower QOL total score than married,employed and high-educated ones (P ＜ 0.05).As compared with non-living-related transplantation group,patients undergoing living-related transplantation presented a better status in QOL total scores (P＜0.05).The QOL total score was obviously lower in patients suffering from complications and rejection than in those without occurrence of complications and rejection (P＜ 0.01).Postoperative time was correlated positively and significantly with QOL scores,and variances existed among different stages postoperation (P ＜ 0.01).Multivariable regression analysis demonstrated that education,marital status,postoperative time,type of donor and chemotherapy were the factors influencing liver transplant recipients' QOL,while marital status,postoperative time,type of donor,medical care assurance,complications and rejection after operation had effect on kidney transplant recipients.Conclusion Attaching importance to QOF among liver and kidney transplant recipients,and implementing scientific and effective nursing intervention based on the characteristics of them are necessary.

Purpose: We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML. Methods: We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR. Results: We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05). Conclusion We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

Purpose: We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML. Methods: We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR. Results: We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05). Conclusion We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

Purpose: We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML. Methods: We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein–protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR. Results: We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05). Conclusion We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

OBJECTIVETo set up thalassemia population intervention model in order to decrease the birth of thalassemia major, relying on population and family planning service system.

METHODSPregnant women and their husbands were educated about thalassemia, and participated in screening and prenatal diagnosis if the couple were carriers of thalassemia in the areas of Huangpu, Panyu, Zengcheng and Tianhe districts of Guangzhou.

RESULTSThe network of thalassemia intervention mainly dependent on family planning service system was set up in these regions. A total of 10 695 families participated in thalassemia screening and 16 thalassemia major fetuses were diagnosed in the last two years. No one was thalassemia major in the 8360 newborn.

CONCLUSIONThalassemia population intervention model was set up relying on family planning service system and it significantly decreased the birth of thalassemia major.

Family Planning Services ; methods ; Female ; Genetic Counseling ; Heterozygote ; Humans ; Infant, Newborn ; Male ; Mass Screening ; methods ; Pregnancy ; Prenatal Diagnosis ; methods ; Spouses ; Thalassemia ; diagnosis ; genetics ; prevention & control

Antibody-mediated rejection (AMR) is a rare and serious complication after lung transplantation, with no characteristic of pathological manifestation, no systematic standard treatment, and the poor efficacy and prognosis. We reported a case of early AMR after lung transplantation and the relevant literature has been reviewed. A male patient presented with symptoms of cold 99 days after transplantation and resolved after symptomatic treatment. He admitted to the hospital 14 days later because of a sudden dyspnea and fever. Anti-bacteria, anti-fungi, anti-virus, and anti-pneumocystis carinii treatment were ineffective, and a dose of 1 000 mg methylprednisolone did not work too. The patient's condition deteriorated rapidly and tracheal intubation was done to maintain breathing. Serum panel reactive antibody and donor specific antibody showed postive in humen leukocyte antigen (HLA) II antibody. Pathological examination after transbronchial transplantation lung biopsy showed acute rejection. Clinical AMR was diagnosed combined the donor-specific antibody with the pathological result. The patient was functionally recovered after combined treatment with thymoglobuline, rituximab, plasmapheresis, and immunoglobulin. No chronic lung allograft dysfunction was found after 3 years follow up. We should alert the occurrence of AMR in lung transplantation recipient who admitted to hospital with a sudden dyspnea and fever while showed no effect after common anti-infection and anti-rejection treatment. Transbronchial transplantation lung biopsy and the presence of serum donor-specific antibody are helpful to the diagnosis. The treatment should be preemptive and a comprehensive approach should be adopted.
Graft Rejection ; Graft Survival ; HLA Antigens ; Humans ; Isoantibodies ; Lung Transplantation/adverse effects* ; Male