Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees

BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR. The collection of microarray datasets from the Gene Expression Omnibus, four breast cancer datasets were pooled for predicting five-year breast cancer relapse. After data compilation, 757 subjects, 5 clinical variables and 13,452 genetic variables were aggregated. The bootstrap method, Mann–Whitney U test and 20-fold cross-validation were performed to investigate candidate genes with 100 most-significant p-values. The predictive powers of DT, LR and ANN models were assessed using accuracy and the area under ROC curve. The associated genes were evaluated using Cox regression. RESULTS: The DT models exhibited the lowest predictive power and the poorest extrapolation when applied to the test samples. The ANN models displayed the best predictive power and showed the best extrapolation. The 21 most-associated genes, as determined by integration of each model, were analyzed using Cox regression with a 3.53-fold (95% CI: 2.24-5.58) increased risk of breast cancer five-year recurrence… CONCLUSIONS: The 21 selected genes can predict breast cancer recurrence. Among these genes, CCNB1, PLK1 and TOP2A are in the cell cycle G2/M DNA damage checkpoint pathway. Oncologists can offer the genetic information for patients when understanding the gene expression profiles on breast cancer recurrence

Personality and social media : usage intensity, self-disclosure and motivations

As social media gains popularity, research into social media is also expanding. With individual differences in social media usage patterns, extensive research has looked at personality factors such as Big Five, narcissism and self-esteem to provide clarifications to these differences. This paper provides a review of the literature regarding the relationship between personality and social media usage in three broad areas namely, usage intensity (e.g. time spent and frequency of use), self-disclosure (e.g. breadth and depth) and motivations (e.g. social and informational motives). Overall, review of literature seems to suggest that the findings related to personality on social media are unclear as contradictory findings are presented. The paper analyses methodological and research base issues such as sampling characteristics, measures, methods and publication biases, and how these issues may have played a role in the inconclusive findings. Finally, suggestions for future directions are given to improve the literature surrounding this field.Bachelor of Art

A systematic review and network meta-analysis of randomized controlled trials on choice of central venous access device for delivery of chemotherapy

Ensuring reliable central venous access with the fewest complications is vital for cancer patients receiving chemotherapy. A systematic review and network meta-analysis was conducted to compare the safety, quality of life, and cost-effectiveness of different types of central venous access devices (CVADs) for patients receiving chemotherapy

Pathway analysis.

<p>Histogram shows a summary of DAVID pathway annotation analysis. The 65 genes which were commonly regulated in H99 versus three environmental strains were selected and analyzed. The number of significant genes and their percentages of genes in the database are as indicated.</p

Lung–infiltrating T helper 17 cells as the major source of interleukin-17A production during pulmonary Cryptococcus neoformans infection

Background: IL-17A has emerged as a key player in the pathologies of inflammation, autoimmune disease, and immunity to microbes since its discovery two decades ago. In this study, we aim to elucidate the activity of IL-17A in the protection against Cryptococcus neoformans, an opportunistic fungus that causes fatal meningoencephalitis among AIDS patients. For this purpose, we examined if C. neoformans infection triggers IL-17A secretion in vivo using wildtype C57BL/6 mice. In addition, an enhanced green fluorescence protein (EGFP) reporter and a knockout (KO) mouse models were used to track the source of IL-17A secretion and explore the protective function of IL-17A, respectively. Results: Our findings showed that in vivo model of C. neoformans infection demonstrated induction of abundant IL-17A secretion. By examining the lung bronchoalveolar lavage fluid (BALF), mediastinal lymph node (mLN) and spleen of the IL-17A-EGFP reporter mice, we showed that intranasal inoculation with C. neoformans promoted leukocytes lung infiltration. A large proportion (~ 50%) of the infiltrated CD4+ helper T cell population secreted EGFP, indicating vigorous TH17 activity in the C. neoformans-infected lung. The infection study in IL-17A-KO mice, on the other hand, revealed that absence of IL-17A marginally boosted fungal burden in the lung and accelerated the mouse death. Conclusion: Therefore, our data suggest that IL-17A is released predominantly from TH17 cells in vivo, which plays a supporting role in the protective immunity against C. neoformans infection

Genome-Wide Transcription Study of <i>Cryptococcus neoformans</i> H99 Clinical Strain versus Environmental Strains

<div><p>The infection of <i>Cryptococcus neoformans</i> is acquired through the inhalation of desiccated yeast cells and basidiospores originated from the environment, particularly from bird’s droppings and decaying wood. Three environmental strains of <i>C</i>. <i>neoformans</i> originated from bird droppings (H4, S48B and S68B) and <i>C</i>. <i>neoformans</i> reference clinical strain (H99) were used for intranasal infection in C57BL/6 mice. We showed that the H99 strain demonstrated higher virulence compared to H4, S48B and S68B strains. To examine if gene expression contributed to the different degree of virulence among these strains, a genome-wide microarray study was performed to inspect the transcriptomic profiles of all four strains. Our results revealed that out of 7,419 genes (22,257 probes) examined, 65 genes were significantly up-or down-regulated in H99 versus H4, S48B and S68B strains. The up-regulated genes in H99 strain include <i>Hydroxymethylglutaryl-CoA synthase</i> (<i>MVA1</i>), <i>Mitochondrial matrix factor 1</i> (<i>MMF1</i>), <i>Bud-site-selection protein 8</i> (<i>BUD8</i>), <i>High affinity glucose transporter 3</i> (<i>SNF3</i>) and <i>Rho GTPase-activating protein 2</i> (<i>RGA2</i>). Pathway annotation using DAVID bioinformatics resource showed that metal ion binding and sugar transmembrane transporter activity pathways were highly expressed in the H99 strain. We suggest that the genes and pathways identified may possibly play crucial roles in the fungal pathogenesis.</p></div

Microarray analysis.

<p>(A) Pairwise correlation matrix. Four <i>C</i>. <i>neoformans</i> strains (H99, H4, S48B and S68B) were compared. Two independent samples were prepared for each fungal strain. Rep1–2: replicates of samples. Numbers in the box represents correlation coefficient values among groups. Dark box: high correlation; light box: low correlation. (B) Gene expression heat map. Dendrogram represents the colour-coded expression levels of the significantly regulated genes. The groups of genes which showed differential expressions in H99 versus other strains were as indicated. Low levels in H99 category indicates the genes with low expression levels in H99 (green) but high expression in the environmental strains (red). In contrast, high levels in H99 category indicates the genes with high expression levels in H99 (red) but show low expression in the environmental strains (green). Hierachrical cluster was performed with Euclidean distance metric and Ward’s Linkage rule clustering. Colour range represents log₁₀ (FC) of the microarray intensities.</p

Pathway annotation by DAVID bioinformatics resource.

<p>The 65 significant genes (133 overlapped probes) which were differentially regulated in H99 compared to environmental strains were analyzed. Shown were representative of each annotation cluster detected. Count represents number of genes which match the pathway database, and % represents the percentage of gene hits among the total genes in the pathway database. Enrichment score (ES) of each group was measured by the geometric mean of the EASE Scores (modified Fisher Exact) associated with the enriched annotation terms that belong to this gene group. Population hit (Pop Hits) represents how many have the function name in your gene list of interest, and population total (Pop Total) represents how many genes in overall population has that function name in the background genome (all genes in the species of interest in DAVID database). False discovery rate (FDR) represents the percentages of test which might be false positive. <i>P</i> values were analyzed using Fisher exact score to identify which sub-populations are over- or under-represented in a sample. Data were considered significant if *<i>P</i><0.05.</p