Citations

Background— Regenerative cell-based therapies are associated with limited myocardial retention of delivered stem cells. The objective of this study is to develop an endocardial delivery system for enhanced cell retention. Methods and Results— Stem cell retention was simulated in silico using 1- and 3-dimensional models of tissue distortion and compliance associated with delivery. Needle designs, predicted to be optimal, were accordingly engineered using nitinol, a nickel and titanium alloy displaying shape memory and superelasticity. Biocompatibility was tested with human mesenchymal stem cells. Experimental validation was performed with species-matched cells directly delivered into Langendorff-perfused porcine hearts or administered percutaneously into the endocardium of infarcted pigs. Cell retention was quantified by flow cytometry and real-time quantitative polymerase chain reaction methodology. Models, computing optimal distribution of distortion calibrated to favor tissue compliance, predicted that a 75°-curved needle featuring small-to-large graded side holes would ensure the highest cell retention profile. In isolated hearts, the nitinol curved needle catheter (C-Cath) design ensured 3-fold superior stem cell retention compared with a standard needle. In the setting of chronic infarction, percutaneous delivery of stem cells with C-Cath yielded a 37.7±7.1% versus 10.0±2.8% retention achieved with a traditional needle without effect on biocompatibility or safety. Conclusions— Modeling-guided development of a nitinol-based curved needle delivery system with incremental side holes achieved enhanced myocardial stem cell retention.

Objective To determine the association between peri‐operative blood transfusion ( PBT ) and oncological outcomes in a large multi‐institutional cohort of patients undergoing radical cystectomy ( RC ) for urothelial carcinoma of the bladder ( UCB ). Patients and Methods We conducted a retrospective analysis of 2895 patients treated with RC for UCB . Univariable and multivariable C ox regression models were used to analyse the effect of PBT administration on disease recurrence, cancer‐specific mortality, and any‐cause mortality. Results Patients' median (interquartile range [ IQR ]) age was 67 (60, 73) years and the median ( IQR ) follow‐up was 36.1 (15, 84) months. Patients who received PBT were more likely to have advanced disease ( P < 0.001), high grade tumours ( P = 0.047) and nodal metastasis ( P = 0.004). PBT was associated with a higher risk of disease recurrence ( P = 0.003), cancer‐specific mortality ( P = 0.017), and any‐cause mortality ( P = 0.010) in univariable, but not multivariable, analyses ( P > 0.05). In multivariable analyses, pathological tumour stage, pathological nodal stage, soft tissue surgical margin, lymphovascular invasion and administration of adjuvant chemotherapy were independent predictors of disease recurrence, cancer‐specific mortality and any‐cause mortality (all P values <0.002). Conclusions Patients with UCB who underwent RC and received PBT had a greater risk of disease recurrence, cancer‐specific mortality and any‐cause mortality in univariable, but not multivariable, analysis. Although the greater need for PBT with more advanced disease is probably caused by a number of factors, including surgical and cancer‐related factors, the present analysis showed that the disease characteristics rather than need for PBT led to worse outcomes.

Abstract Background: Given the high technical reproducibility and orders of magnitude greater resolution than microarrays, next-generation sequencing of mRNA (RNA-Seq) is quickly becoming the de facto standard for measuring levels of gene expression in biological experiments. Two important questions must be taken into consideration when designing a particular experiment, namely, 1) how deep does one need to sequence? and, 2) how many biological replicates are necessary to observe a significant change in expression? Results: Based on the gene expression distributions from 127 RNA-Seq experiments, we find evidence that 91% ± 4% of all annotated genes are sequenced at a frequency of 0.1 times per million bases mapped, regardless of sample source. Based on this observation, and combining this information with other parameters such as biological variation and technical variation that we empirically estimate from our large datasets, we developed a model to estimate the statistical power needed to identify differentially expressed genes from RNA-Seq experiments. Conclusions: Our results provide a needed reference for ensuring RNA-Seq gene expression studies are conducted with the optimally sample size, power, and sequencing depth. We also make available both R code and an Excel worksheet for investigators to calculate for their own experiments.

Abstract Motivation: Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. Results: We present an extension of PCA to quantify the existence of batch effects, called guided PCA (gPCA). We describe a test statistic that uses gPCA to test whether a batch effect exists. We apply our proposed test statistic derived using gPCA to simulated data and to two copy number variation case studies: the first study consisted of 614 samples from a breast cancer family study using Illumina Human 660 bead-chip arrays, whereas the second case study consisted of 703 samples from a family blood pressure study that used Affymetrix SNP Array 6.0. We demonstrate that our statistic has good statistical properties and is able to identify significant batch effects in two copy number variation case studies. Conclusion: We developed a new statistic that uses gPCA to identify whether batch effects exist in high-throughput genomic data. Although our examples pertain to copy number data, gPCA is general and can be used on other data types as well. Availability and implementation: The gPCA R package (Available via CRAN) provides functionality and data to perform the methods in this article. Contact: reesese@vcu.edu or eckel@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.

ABSTRACTVenous thromboembolism (VTE) is a common, heritable disease resulting in high rates of hospitalization and mortality. Yet few associations between VTE and genetic variants, all in the coagulation pathway, have been established. To identify additional genetic determinants of VTE, we conducted a two‐stage genome‐wide association study (GWAS) among individuals of European ancestry in the extended cohorts for heart and aging research in genomic epidemiology (CHARGE) VTE consortium. The discovery GWAS comprised 1,618 incident VTE cases out of 44,499 participants from six community‐based studies. Genotypes for genome‐wide single‐nucleotide polymorphisms (SNPs) were imputed to approximately 2.5 million SNPs in HapMap and association with VTE assessed using study‐design appropriate regression methods. Meta‐analysis of these results identified two known loci, in F5 and ABO. Top 1,047 tag SNPs (P ≤ 0.0016) from the discovery GWAS were tested for association in an additional 3,231 cases and 3,536 controls from three case‐control studies. In the combined data from these two stages, additional genome‐wide significant associations were observed on 4q35 at F11 (top SNP rs4253399, intronic to F11) and on 4q28 at FGG (rs6536024, 9.7 kb from FGG; P < 5.0 × 10−13 for both). The associations at the FGG locus were not completely explained by previously reported variants. Loci at or near SUSD1 and OTUD7A showed borderline yet novel associations (P < 5.0 × 10−6) and constitute new candidate genes. In conclusion, this large GWAS replicated key genetic associations in F5 and ABO, and confirmed the importance of F11 and FGG loci for VTE. Future studies are warranted to better characterize the associations with F11 and FGG and to replicate the new candidate associations.

Abstract Zebrafish ( Danio rerio ) is a popular vertebrate model organism largely deployed using outbred laboratory animals. The nonisogenic nature of the zebrafish as a model system offers the opportunity to understand natural variations and their effect in modulating phenotype. In an effort to better characterize the range of natural variation in this model system and to complement the zebrafish reference genome project, the whole genome sequence of a wild zebrafish at 39-fold genome coverage was determined. Comparative analysis with the zebrafish reference genome revealed approximately 5.2 million single nucleotide variations and over 1.6 million insertion–deletion variations. This dataset thus represents a new catalog of genetic variations in the zebrafish genome. Further analysis revealed selective enrichment for variations in genes involved in immune function and response to the environment, suggesting genome-level adaptations to environmental niches. We also show that human disease gene orthologs in the sequenced wild zebrafish genome show a lower ratio of nonsynonymous to synonymous single nucleotide variations.