Statistical analysis of network data and evolution on GPUs: High-performance statistical computing

Network analysis typically involves as set of repetitive tasks that are particularly amenable to poor-man's parallelization. This is therefore an ideal application are for GPU architectures, which help to alleviate the tedium inherent to statistically sound analysis of network data. Here we will illustrate the use of GPUs in a range of applications, which include percolation processes on networks, the evolution of protein-protein interaction networks, and the fusion of different types of biomedical and disease data in the context of molecular interaction networks. We will pay particular attention to the numerical performance of different routines that are frequently invoked in network analysis problems. We conclude with a review over recent developments in the generation of random numbers that address the specific requirements posed by GPUs and high-performance computing needs

Hydrogel based protein biochip for parallel detection of biomarkers for diagnosis of a Systemic Inflammatory Response Syndrome (SIRS) in human serum

The Systemic Inflammatory Response Syndrome (SIRS), a sepsis related inflammatory state, is a self-defense mechanism against specific and nonspecific stimuli. The six most extensively studied inflammatory biomarkers for the clinical diagnosis of SIRS are interleukin 4 (hIL-4), interleukin 6 (hIL-6), interleukin 10 (hIL-10), tumor necrosis factor alpha (hTNF-a), interferon gamma (hIFN-gamma) and procalcitonin (hPCT). These biomarkers are naturally present (but usually only at low concentration) in SIRS infected patients [1, 2] and thus the development of a highly sensitive detection method is of major clinical interest. However, the existing analytical techniques are lacking in required analytical sensitivity and parallel determination of these biomarkers. We developed a fast, easy and cost-efficient protein microarray biochip where the capture molecules are attached on hydrogel spots, enabling SIRS diagnosis by parallel detection of these six clinically relevant biomarkers with a sample volume of 25 mu l. With our hydrogel based protein microarray biochip we achieved a limit of detection for hIL-4 of 75.2 pg/ml, for hIL-6 of 45.1 pg/ml, for hIL-10 of 71.5 pg/ml, for hTNF-alpha of 56.7 pg/ml, for IFN-gamma of 46.4 pg/ml and for hPCT of 1.1 ng/ml in spiked human serum demonstrating sufficient sensitivity for clinical usage. Additionally, we demonstrated successful detection of two relevant SIRS biomarkers in clinical patient samples with a turnaround time of the complete analysis from sample-to-answer in less than 200 minutes

Derivative processes for modelling metabolic fluxes.

MOTIVATION: One of the challenging questions in modelling biological systems is to characterize the functional forms of the processes that control and orchestrate molecular and cellular phenotypes. Recently proposed methods for the analysis of metabolic pathways, for example, dynamic flux estimation, can only provide estimates of the underlying fluxes at discrete time points but fail to capture the complete temporal behaviour. To describe the dynamic variation of the fluxes, we additionally require the assumption of specific functional forms that can capture the temporal behaviour. However, it also remains unclear how to address the noise which might be present in experimentally measured metabolite concentrations. RESULTS: Here we propose a novel approach to modelling metabolic fluxes: derivative processes that are based on multiple-output Gaussian processes (MGPs), which are a flexible non-parametric Bayesian modelling technique. The main advantages that follow from MGPs approach include the natural non-parametric representation of the fluxes and ability to impute the missing data in between the measurements. Our derivative process approach allows us to model changes in metabolite derivative concentrations and to characterize the temporal behaviour of metabolic fluxes from time course data. Because the derivative of a Gaussian process is itself a Gaussian process, we can readily link metabolite concentrations to metabolic fluxes and vice versa. Here we discuss how this can be implemented in an MGP framework and illustrate its application to simple models, including nitrogen metabolism in Escherichia coli. AVAILABILITY AND IMPLEMENTATION: R code is available from the authors upon request

The effects of incomplete protein interaction data on structural and evolutionary inferences

BACKGROUND: Present protein interaction network data sets include only interactions among subsets of the proteins in an organism. Previously this has been ignored, but in principle any global network analysis that only looks at partial data may be biased. Here we demonstrate the need to consider network sampling properties explicitly and from the outset in any analysis. RESULTS: Here we study how properties of the yeast protein interaction network are affected by random and non-random sampling schemes using a range of different network statistics. Effects are shown to be independent of the inherent noise in protein interaction data. The effects of the incomplete nature of network data become very noticeable, especially for so-called network motifs. We also consider the effect of incomplete network data on functional and evolutionary inferences. CONCLUSION: Crucially, when only small, partial network data sets are considered, bias is virtually inevitable. Given the scope of effects considered here, previous analyses may have to be carefully reassessed: ignoring the fact that present network data are incomplete will severely affect our ability to understand biological systems

Evidence of re-osseointegration after electrolytic cleaning and regenerative therapy of peri-implantitis in humans: a case report with four implants.

OBJECTIVE To evaluate re-osseointegration after electrolytic cleaning and regenerative therapy of dental implants with peri-implantitis in humans. MATERIAL AND METHODS Four dental implants that developed peri-implantitis underwent electrolytic cleaning followed by regenerative therapy with guided bone regeneration. All four implants developed recurrent peri-implantitis and were therefore explanted 6 to 13 months later. Radiographic bone level, probing depth, and bleeding on probing were determined at the time of surgery, 6 months later, and before implant retrieval. The peri-implant tissues were histologically and histomorphometrically analyzed. RESULTS All four implants demonstrated radiographic and histological bone gain, reduced probing depth, and bleeding on probing. Radiographic bone gain was 5.8 mm mesially and 4.8 mm distally for implant #1, 3.3 mm and 2.3 mm for implant #2, 3.1 mm and 0.5 mm for implant #3, and 3.5 mm and 2.8 mm for implant #4. The histometric mean and maximum vertical bone gain for implant #1 to #4 was 1.65 mm and 2.54 mm, 3.04 mm and 3.47 mm, 0.43 mm and 1.27 mm, and 4.16 mm and 5.22 mm, respectively. The percentage of re-osseointegration for implant #1 to #4 was 21.0%, 36.9%, 5.7%, and 39.0%, respectively. In one implant, the newly formed bone was deposited directly onto calculus on the implant surface. CONCLUSIONS We found that (1) re-osseointegration is possible on a formerly contaminated implant surface and (2) the electrolytic cleaning process seems to be effective enough at sites with calculus residues. CLINICAL RELEVANCE Since re-osseointegration can be achieved by electrolytic cleaning, this decontamination technique may be considered as a future treatment concept

A Matemática na fabricação de Sabão: algumas reflexões sobre o uso da Etnomodelagem em sala de aula

A necessidade de separar, reciclar e reutilizar os resíduos gerados têm emergido com uma das principais formas de minimizar os impactos ambientais referentes à extração e produção de novos itens, um exemplo disso, é a fabricação caseira de sabão a partir de restos de gordura animal ou de óleo de cozinha realizada no oeste catarinense. Sabendo da importância de resgatar os contextos culturais dos alunos e estabelecer relações com os tópicos abordados dentro da sala de aula, esse artigo tem o intuito de relatar uma oficina que relacionou Matemática e a fabricação do sabão. Em decorrência da pandemia, a oficina foi realizada de forma remota por meio de encontros via Google Meet, com uma turma do 8° ano do Ensino Fundamental de uma escola de Educação Básica de um município de Concórdia - Santa Catarina. Tendo em vista que Educação Ambiental é geradora de uma nova maneira de interpretar e de conviver em harmonia com o meio ambiente, a oficina abordou também a importância da conscientização sobre os malefícios do uso desordenado dos recursos naturais, bem como formas de auxiliar na sua preservação e manutenção destes. Como resultado da oficina, percebeu-se que, por meio da Matemática, os alunos compreenderam a importância e a necessidade de reutilizar, separar, consumir e produzir menos resíduos. Promovendo, assim, a formação de cidadãos reflexivos e conscientes sobre suas ações e o impacto destas no meio ambiente, ao mesmo tempo em que ampliaram conhecimentos matemáticos relacionados ao tema.

FAST: Förder-Assessment-Center für Studierende - Auch an Universitäten ist Fachwissen nicht alles

Universitäten legen in der Ausbildung von Studenten vor allem Wert auf die Vermittlung von Fachwissen, die gezielte Entwicklung von sozialen Kompetenzen oder Selbstmanagementkompetenzen tritt demgegenüber in den Hintergrund. Vor dieser Ausgangslage wurde an der Universität Regensburg ein Förder-Assessment-Center für Studierende, abgekürzt FAST, entwickelt, das darauf abzielt, einen Beitrag zur Förderung dieser an Universitäten oftmals vernachlässigten Fähigkeiten zu leisten. FAST basiert auf einer empirischen Analyse der Anforderungen, die im Studienalltag an Studierende gestellt werden. Auf dieser Grundlage wurden ein Anforderungsprofil definiert, das die für die Bewältigung dieser Anforderungen notwendigen Fähigkeiten beschreibt, sowie Übungen entwickelt, die prototypische Anforderungssituationen darstellen. Teilnehmer an FAST absolvieren diese Übungen und werden dabei im Hinblick auf das Anforderungsprofil beobachtet und beurteilt. Am Ende des Verfahrens erhalten die Teilnehmer eine differenzierte und verhaltensnahe individuelle Rückmeldung, wie ihre Fähigkeiten in Bezug auf diese Anforderungen ausgeprägt sind. Die Rückmeldung soll den Teilnehmern dabei helfen, ihre eigenen Stärken und Schwächen zu erkennen und zu verstehen, um daraus persönliche Entwicklungsstrategien und -schritte abzuleiten. In diesem Beitrag werden die Ziele und die Konstruktion von FAST dargestellt. Erfahrungen und Resultate einer ersten Durchführung von FAST werden berichtet und ein Ausblick auf den weiteren Einsatz dieses Verfahrens erfolgt. 08.12.2004 | Ulrich Graner, Silke Heiss, Peter Joscht, Nicola Stahl, Verena Stengel, Thomas Symanik & Siegfried Stumpf (Regensburg

Adapting Low-Cost Drone Technology to CubeSats for Environmental Monitoring and Management: Harmful Algal Bloom Satellite-1 (HABsat-1)

HABsat-1 is designed to improve our understanding of algal bloom dynamics and their causes on land by addressing several current limiting factors for this application using existing satellites. For example, there is suboptimal imager design for water, insufficient spatial resolution for precise co-registration of surface observations, and too few satellites with such capabilities to defeat cloud cover in maritime, tropical and temperate climates. We will overcome these problems by merging a new low-cost multispectral imaging technology with a low-cost CubeSat bus. CubeSats cost roughly 1/100th to 1/1000th of most current long-life imaging satellites. Such cost decreases are necessary to improve upon the temporal coverage (number of appropriate satellites) and spatial resolution of current imaging satellites, such as Landsat-8, Sentinel-2 and Sentinel-3 (MERIS/OLCI). Numerous low-cost satellites reduce both overall mission cost and individual launch risks associated with large production satellites, such as Landsat, while providing the temporal and spatial resolution necessary for the study of highly dynamic and spatially variable algal blooms. A team of undergraduate aerospace engineers (the UC CubeCats), computer scientists and aerospace and geographic information science faculty have been funded by the Ohio Department of Higher Education and NOAA to adapt low-cost multispectral imagers designed for use on small drones to 3U CubeSats to further reduce the cost of environmental monitoring. This team will create a working on-orbit prototype for a constellation of CubeSat’s for routine drinking water monitoring known as Harmful Algal Bloom Satellite 1 (HABsat-1)

A boundary exchange influence on deglacial neodymium isotope records from the deep western Indian Ocean

The use of neodymium (Nd) isotopes to reconstruct past water mass mixing relies upon the quasi-conservative behaviour of this tracer, whereas recent studies in the modern oceans have suggested that boundary exchange, involving the addition of Nd from ocean margin sediments, may be an important process in the Nd cycle. Here we suggest that the relative importance of water mass advection versus boundary exchange can be assessed where the deep western boundary current in the Indian Ocean flows past the Madagascan continental margin; a potential source of highly unradiogenic Nd. Foraminiferal coatings and bulk sediment reductive leachates are used to reconstruct bottom water Nd isotopic composition (εNd) in 8 Holocene age coretops, with excellent agreement between the two methods. These data record spatial variability of ∼4 εNd units along the flow path of Circumpolar Deep Water; εNd≈−8.8 in the deep southern inflow upstream of Madagascar, which evolves towards εNd≈−11.5 offshore northern Madagascar, whereas εNd≈−7.3 where deep water re-circulates in the eastern Mascarene Basin. This variability is attributed to boundary exchange and, together with measurements of detrital sediment εNd, an isotope mass balance suggests a deep water residence time for Nd of ≤400 yr along the Madagascan margin. Considering deglacial changes, a core in the deep inflow upstream of Madagascar records εNd changes that agree with previous reconstructions of the Circumpolar Deep Water composition in the Southern Ocean, consistent with a control by water mass advection and perhaps indicating a longer residence time for Nd in the open ocean away from local sediment inputs. In contrast, sites along the Madagascan margin record offset εNd values and reduced glacial–interglacial variability, underlining the importance of detecting boundary exchange before inferring water mass source changes from Nd isotope records. The extent of Madagascan boundary exchange appears to be unchanged between the Holocene and Late Glacial periods, while a consistent shift towards more radiogenic εNd values at all sites in the Late Glacial compared to the Holocene may represent a muted signal of a change in water mass source or composition