Comparison of dimensional accuracies of stereolithography and powder binder printing

This paper presents a comparative experimental investigation of the dimensional accuracies of two widely used rapid prototyping (RP) processes: stereolithography (SLA) and powder binder printing (PBP). Four replicates of a purpose-designed component using each RP process were fabricated, and the measurements of the internal and external features of all surfaces were performed using a general-purpose coordinate measurement machine. The results showed that in both cases, the main cause of dimensional variations was the volumetric change inherent in the process. The precision of SLA was far better than that of PBP. The dimensional accuracy of SLA was better in the z direction, whereas PBP produced better dimensional accuracy in the x–y plane. In both RP processes, the height error consisted of two components: constant error and cumulative error. The constant error component was equal to the datum surface error. SLA yielded an average datum surface error that was 68 % higher than in PBP. The height error of SLA improved with the increase in nominal height, whereas it deteriorated in PBP

Increased blood pressure in adult offspring of families with Balkan Endemic Nephropathy: a prospective study

BACKGROUND: Previous studies have linked smaller kidney dimensions to increased blood pressure. However, patients with Balkan Endemic Nephropathy (BEN), whose kidneys shrink during the course of the disease, do not manifest increased blood pressure. The authors evaluated the relationship between kidney cortex width, kidney length, and blood pressure in the offspring of BEN patients and controls. METHODS: 102 offspring of BEN patients and 99 control offspring of non-BEN hospital patients in the Vratza District, Bulgaria, were enrolled in a prospective study and examined twice (2003/04 and 2004/05). Kidney dimensions were determined using ultrasound, blood pressure was measured, and medical information was collected. The parental disease of BEN was categorized into three groups: mother, father, or both parents. Repeated measurements were analyzed with mixed regression models. RESULTS: In all participants, a decrease in minimal kidney cortex width of 1 mm was related to an increase in systolic blood pressure of 1.4 mm Hg (p = 0.005). There was no association between kidney length and blood pressure. A maternal history of BEN was associated with an increase in systolic blood pressure of 6.7 mm Hg (p = 0.03); paternal BEN, +3.2 mm Hg (p = 0.35); or both parents affected, +9.9 mm Hg (p = 0.002). There was a similar relation of kidney cortex width and parental history of BEN with pulse pressure; however, no association with diastolic blood pressure was found. CONCLUSION: In BEN and control offspring, a smaller kidney cortex width predisposed to higher blood pressure. Unexpectedly, a maternal history of BEN was associated with average increased systolic blood pressure in offspring

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Search for B-s(0) - GT mu(+)mu(-) and B-0 - GT mu(+)mu(-) Decays in pp Collisions at root s=7 TeV

A search for the rare decays B-s(0) -- GT mu(+)mu(-) and B-0 -- GT mu(+)mu(-) is performed in pp collisions at root s = 7 TeV, with a data sample corresponding to an integrated luminosity of 1.14 fb(-1), collected by the CMS experiment at the LHC. In both cases, the number of events observed after all selection requirements is consistent with expectations from background and standard-model signal predictions. The resulting upper limits on the branching fractions are B(B-s(0) -- GT mu(+)mu(-)) LT 1.9 x 10(-8) and B(B-0 -- GT mu(+)mu(-)) LT 4.6 x 10(-9), at 95% confidence level