Objective To investigate the cognitive status of nursing of cancer patients among nurses of cardiothoracic surgery department,to discuss countermeasures to improve nursing quality of tumor patients of cardiothoracic surgery department. Methods 150 nurses of cardiothoracic surgery department from November 2009 to November 2010 in five hospitals of a certain city were selected as the research object.The elf-made questionnaire about cognition of cancer patients nursing was adopted for investigation.The cognition condition of health education,psychological care,death education,care of cancer pain of 150 nurses was taken for statistics. Results The study showed that 150 cardiothoracic surgical nurses mastered the health education knowledge best,the average score was(88.6 ± 11.3).The knowledge of death related knowledge was the worst,the average score was (64.5 ± 21.6).The differences of mastering degree of psychological care and pain related knowledge level for 5 hospital nurses were quite significant.The differences of psychological care knowledge levels of hospital A and C,D were significant.The differences of care of cancer pain of hospital B and A,E,F were significant. Conclusions Based on the cognitive status of cardiothoracic surgery nurses for nursing of cancer patients,appropriate theoretical and practical training can be adopted in order to improve cognitive level of related knowledge about nursing of cancer patients among cardiothoracic surgery nurses,so that the nursing quality for cancer patients can be improved.

Objective:To identify additional loci associated with depression and the hippocampus (HIP) through genome-wide association study.Methods:The depression-related genome-wide association study (GWAS) meta summary data was downloaded from the official website of the Psychiatric Genomics Consortium, which had involved 170 756 cases and 329 443 controls. The left and right hippocampal volume GWAS data sets were downloaded from the UK Biobank, which involved 33 224 participants. The conditional false discovery rate (condFDR) was used to identify novel genetic loci for depression and left and right hippocampal volumes, and a conjunctional false discovery rate (conjFDR) was used to evaluate the enrichment of pleiotropic loci between depression and left and right hippocampal volumes.Results:Respectively, 7, 13, and 12 new loci have been associated with depression, left hippocampal volume and right hippocampal volume, with a significant threshold of condFDR < 0.01. A site of rs1267073 locus was found to be shared by the depression and right hippocampal volume with a threshold of conjFDR < 0.01.Conclusion:Above findings have provided more insights into the genetic mechanisms underlying the volume of hippocampus and the risk for depression. The results may also provide evidence for future clinical trials for treating depression.

OBJECTIVETo explore common biological pathways for attention deficit hyperactivity disorder (ADHD) and low birth weight (LBW).

METHODSThei-Gsea4GwasV2 software was used to analyze the result of genome-wide association analysis (GWAS) for LBW (pathways were derived from Reactome), and nominally significant (P< 0.05, FDR< 0.25) pathways were tested for replication in ADHD.Significant pathways were analyzed with DAPPLE and Reatome FI software to identify genes involved in such pathways, with each cluster enriched with the gene ontology (GO). The Centiscape2.0 software was used to calculate the degree of genetic networks and the betweenness value to explore the core node (gene). Weighed gene co-expression network analysis (WGCNA) was then used to explore the co-expression of genes in these pathways.With gene expression data derived from BrainSpan, GO enrichment was carried out for each gene module.

RESULTSEleven significant biological pathways was identified in association with LBW, among which two (Selenoamino acid metabolism and Diseases associated with glycosaminoglycan metabolism) were replicated during subsequent ADHD analysis. Network analysis of 130 genes in these pathways revealed that some of the sub-networksare related with morphology of cerebellum, development of hippocampus, and plasticity of synaptic structure. Upon co-expression network analysis, 120 genes passed the quality control and were found to express in 3 gene modules. These modules are mainly related to the regulation of synaptic structure and activity regulation.

CONCLUSIONADHD and LBW share some biological regulation processes. Anomalies of such proces sesmay predispose to ADHD.

Objective: Schizophrenia (SCZ) is one of the most common and severe mental disorders. Modified electroconvulsive therapy (MECT) is the most effective therapy for all kinds of SCZ, and the underlying molecular mechanism remains unclear. This study is aim to detect the molecule mechanism by constructing the transcriptome dataset from SCZ patients treated with MECT and health controls (HCs). Methods: Transcriptome sequencing was performed on blood samples of 8 SCZ (BECT: before MECT; AECT: after MECT) and 8 HCs, weighted gene co-expression network analysis (WGCNA) was used to cluster the different expression genes, enrichment and protein-protein interaction (PPI) enrichment analysis were used to detect the related pathways. Results: Three gene modules (black, blue and turquoise) were significantly associated with MECT, enrichment analysis found that the long-term potentiation pathway was associated with MECT. PPI enrichment p-value of black, blue, turquoise module are 0.00127, <1×10-16 and 1.09×10-13, respectively. At the same time, EP300 is a key node in the PPI for genes in black module, which got from the transcriptome sequencing data. Conclusion It is suggested that the long-term potentiation pathways were associated with biological mechanism of MECT.

Objective: Schizophrenia (SCZ) is one of the most common and severe mental disorders. Modified electroconvulsive therapy (MECT) is the most effective therapy for all kinds of SCZ, and the underlying molecular mechanism remains unclear. This study is aim to detect the molecule mechanism by constructing the transcriptome dataset from SCZ patients treated with MECT and health controls (HCs). Methods: Transcriptome sequencing was performed on blood samples of 8 SCZ (BECT: before MECT; AECT: after MECT) and 8 HCs, weighted gene co-expression network analysis (WGCNA) was used to cluster the different expression genes, enrichment and protein-protein interaction (PPI) enrichment analysis were used to detect the related pathways. Results: Three gene modules (black, blue and turquoise) were significantly associated with MECT, enrichment analysis found that the long-term potentiation pathway was associated with MECT. PPI enrichment p-value of black, blue, turquoise module are 0.00127, <1×10-16 and 1.09×10-13, respectively. At the same time, EP300 is a key node in the PPI for genes in black module, which got from the transcriptome sequencing data. Conclusion It is suggested that the long-term potentiation pathways were associated with biological mechanism of MECT.

BackgroundPrevious investigations have illuminated the correlation between smoking and C-reactive protein （CRP）， but previous research findings may be influenced by other confounding factors. The causal relationship of CRP in smoking-related pathological process requires further exploration. ObjectiveTo investigate the causal relationship between smoking behavior and CRP by utilizing the cumulative statistical data from existing genome-wide association studies （GWAS）， so as to provide references for formulating relevant public health policies and smoking intervention measures. MethodsThis research utilized the GWAS summary statistics for CRP and four smoking phenotypes： age of initiation of regular smoking， smoking initiation， smoking cessation and cigarettes per day-selecting independent genetic loci correlated with smoking and CRP as instrumental variables. The study employed the inverse variance weighted method （IVW） and the weighted median approach for two-sample Mendelian randomization （MR） analysis to explore the bidirectional causal relationship between smoking and CRP. The Cochran's Q test was applied to assess heterogeneity among single nucleotide polymorphisms （SNPs）. MR pleiotropy residual sum and outlier was used to detect SNP outliers. MR-Egger intercept test examined the horizontal pleiotropy of SNPs. Leave-one-out sensitivity analysis assessed the impact of individual SNP on the Mendelian randomization results. ResultsThe MR analysis revealed a bidirectional causal relationship between CRP and smoking initiation （β=0.170， P=0.01） （with smoking initiationas the exposure）， （β=0.040， P=0.001） （with CRP as the exposure）. ConclusionSmoking may lead to alterations in CRP levels， while changes in CRP levels could also influence individual's propensity to initiate smoking.

Objective:To explore the white matter structural characteristics in patients with bipolar disorder(BD)using diffusion tensor imaging(DTI)and investigate their relationship with cognitive function.Methods:A total of 15 patients with BD type Ⅰ and 26 patients with BD type Ⅱ who met the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition(DSM-Ⅳ)diagnostic criteria and 37 normal controls were included.Cognitive function was assessed with the Trail Making Test(TMT)and Repeatable Battery for the Assessment of Neuropsy-chological Status(RBANS).The tract-based spatial statistics(TBSS)method was used to explore the differences in fractional anisotropy(FA)and mean diffusivity(MD)among the three groups and perform correlation analyses with cognitive function.Results:Patients with BD Ⅰ and BD Ⅱ had lower scores in attention(P＜0.001),delayed memory(P＜0.01),and total scores(P＜0.001)on the RBANS compared to the normal control group.They also exhibited lower FA values in the corpus callosum and right superior corona radiata compared to the normal control group(P＜0.05).In the BD Ⅰ group,there was a positive correlation between FA values in the genu of corpus cal-losum and visuospatial/constructional scores(r=0.74,P＜0.05),while in the BD Ⅱ group,a positive correlation was found between FA values in the same region and language function scores(r=0.55,P＜0.05).Conclusion:It suggests that patients with bipolar disorder may have impaired white matter integrity in the corpus callosum and right superior corona radiata,which may be associated with cognitive impairment.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.