Publications by authors named "Christiane Fuchs"

43 Publications

Prevalence and Risk Factors of Infection in the Representative COVID-19 Cohort Munich.

Int J Environ Res Public Health 2021 03 30;18(7). Epub 2021 Mar 30.

Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802 Munich, Germany.

Given the large number of mild or asymptomatic SARS-CoV-2 cases, only population-based studies can provide reliable estimates of the magnitude of the pandemic. We therefore aimed to assess the sero-prevalence of SARS-CoV-2 in the Munich general population after the first wave of the pandemic. For this purpose, we drew a representative sample of 2994 private households and invited household members 14 years and older to complete questionnaires and to provide blood samples. SARS-CoV-2 seropositivity was defined as Roche N pan-Ig ≥ 0.4218. We adjusted the prevalence for the sampling design, sensitivity, and specificity. We investigated risk factors for SARS-CoV-2 seropositivity and geospatial transmission patterns by generalized linear mixed models and permutation tests. Seropositivity for SARS-CoV-2-specific antibodies was 1.82% (95% confidence interval (CI) 1.28-2.37%) as compared to 0.46% PCR-positive cases officially registered in Munich. Loss of the sense of smell or taste was associated with seropositivity (odds ratio (OR) 47.4; 95% CI 7.2-307.0) and infections clustered within households. By this first population-based study on SARS-CoV-2 prevalence in a large German municipality not affected by a superspreading event, we could show that at least one in four cases in private households was reported and known to the health authorities. These results will help authorities to estimate the true burden of disease in the population and to take evidence-based decisions on public health measures.
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http://dx.doi.org/10.3390/ijerph18073572DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038115PMC
March 2021

stochprofML: stochastic profiling using maximum likelihood estimation in R.

BMC Bioinformatics 2021 Mar 15;22(1):123. Epub 2021 Mar 15.

Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany.

Background: Tissues are often heterogeneous in their single-cell molecular expression, and this can govern the regulation of cell fate. For the understanding of development and disease, it is important to quantify heterogeneity in a given tissue.

Results: We present the R package stochprofML which uses the maximum likelihood principle to parameterize heterogeneity from the cumulative expression of small random pools of cells. We evaluate the algorithm's performance in simulation studies and present further application opportunities.

Conclusion: Stochastic profiling outweighs the necessary demixing of mixed samples with a saving in experimental cost and effort and less measurement error. It offers possibilities for parameterizing heterogeneity, estimating underlying pool compositions and detecting differences between cell populations between samples.
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http://dx.doi.org/10.1186/s12859-021-03970-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7958472PMC
March 2021

Multi-faceted enhancement of full-thickness skin wound healing by treatment with autologous micro skin tissue columns.

Sci Rep 2021 Jan 18;11(1):1688. Epub 2021 Jan 18.

Wellman Center for Photomedicine, Massachusetts General Hospital, Thier 2, 50 Blossom Street, Boston, MA, 02114, USA.

Impaired wound healing is an immense medical challenge, and while autologous skin grafting remains the "gold-standard" therapeutic option for repairing wounds that cannot be closed by primary or secondary intention, it is limited by substantial donor site morbidity. We previously developed the alternative approach of harvesting full-thickness skin tissue in the form of "micro skin tissue columns" (MSTCs), without causing scarring or any other long-term morbidity. In this study we investigated how MSTC treatment affects the different cellular processes involved in wound healing. We found that MSTC-derived cells were able to remodel and repopulate the wound volume, and positively impact multiple aspects of the wound healing process, including accelerating re-epithelialization by providing multiple cell sources throughout the wound area, increasing collagen deposition, enhancing dermal remodeling, and attenuating the inflammatory response. These effects combined to enhance both epidermal and dermal wound healing. This MSTC treatment approach was designed for practical clinical use, could convey many benefits of autologous skin grafting, and avoids the major drawback of donor site morbidity.
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http://dx.doi.org/10.1038/s41598-021-81179-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814113PMC
January 2021

Bayesian inference for diffusion processes: using higher-order approximations for transition densities.

R Soc Open Sci 2020 Oct 7;7(10):200270. Epub 2020 Oct 7.

Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.

Modelling random dynamical systems in continuous time, diffusion processes are a powerful tool in many areas of science. Model parameters can be estimated from time-discretely observed processes using Markov chain Monte Carlo (MCMC) methods that introduce auxiliary data. These methods typically approximate the transition densities of the process numerically, both for calculating the posterior densities and proposing auxiliary data. Here, the Euler-Maruyama scheme is the standard approximation technique. However, the MCMC method is computationally expensive. Using higher-order approximations may accelerate it, but the specific implementation and benefit remain unclear. Hence, we investigate the utilization and usefulness of higher-order approximations in the example of the Milstein scheme. Our study demonstrates that the MCMC methods based on the Milstein approximation yield good estimation results. However, they are computationally more expensive and can be applied to multidimensional processes only with impractical restrictions. Moreover, the combination of the Milstein approximation and the well-known modified bridge proposal introduces additional numerical challenges.
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http://dx.doi.org/10.1098/rsos.200270DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7657901PMC
October 2020

Asthma in farm children is more determined by genetic polymorphisms and in non-farm children by environmental factors.

Pediatr Allergy Immunol 2021 Feb 15;32(2):295-304. Epub 2020 Oct 15.

The German Center for Lung Research (DZL), Germany.

Background: The asthma syndrome is influenced by hereditary and environmental factors. With the example of farm exposure, we study whether genetic and environmental factors interact for asthma.

Methods: Statistical learning approaches based on penalized regression and decision trees were used to predict asthma in the GABRIELA study with 850 cases (9% farm children) and 857 controls (14% farm children). Single-nucleotide polymorphisms (SNPs) were selected from a genome-wide dataset based on a literature search or by statistical selection techniques. Prediction was assessed by receiver operating characteristics (ROC) curves and validated in the PASTURE cohort.

Results: Prediction by family history of asthma and atopy yielded an area under the ROC curve (AUC) of 0.62 [0.57-0.66] in the random forest machine learning approach. By adding information on demographics (sex and age) and 26 environmental exposure variables, the quality of prediction significantly improved (AUC = 0.65 [0.61-0.70]). In farm children, however, environmental variables did not improve prediction quality. Rather SNPs related to IL33 and RAD50 contributed significantly to the prediction of asthma (AUC = 0.70 [0.62-0.78]).

Conclusions: Asthma in farm children is more likely predicted by other factors as compared to non-farm children though in both forms, family history may integrate environmental exposure, genotype and degree of penetrance.
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http://dx.doi.org/10.1111/pai.13385DOI Listing
February 2021

CLUE: a bioinformatic and wet-lab pipeline for multiplexed cloning of custom sgRNA libraries.

Nucleic Acids Res 2020 07;48(13):e78

Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, Ludwig Maximilians University of Munich (LMU), 80337 Munich, Germany.

The systematic perturbation of genomes using CRISPR/Cas9 deciphers gene function at an unprecedented rate, depth and ease. Commercially available sgRNA libraries typically contain tens of thousands of pre-defined constructs, resulting in a complexity challenging to handle. In contrast, custom sgRNA libraries comprise gene sets of self-defined content and size, facilitating experiments under complex conditions such as in vivo systems. To streamline and upscale cloning of custom libraries, we present CLUE, a bioinformatic and wet-lab pipeline for the multiplexed generation of pooled sgRNA libraries. CLUE starts from lists of genes or pasted sequences provided by the user and designs a single synthetic oligonucleotide pool containing various libraries. At the core of the approach, a barcoding strategy for unique primer binding sites allows amplifying different user-defined libraries from one single oligonucleotide pool. We prove the approach to be straightforward, versatile and specific, yielding uniform sgRNA distributions in all resulting libraries, virtually devoid of cross-contaminations. For in silico library multiplexing and design, we established an easy-to-use online platform at www.crispr-clue.de. All in all, CLUE represents a resource-saving approach to produce numerous high quality custom sgRNA libraries in parallel, which will foster their broad use across molecular biosciences.
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http://dx.doi.org/10.1093/nar/gkaa459DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367185PMC
July 2020

Skin Microcolumns as a Source of Paracrine Signaling Factors.

Adv Wound Care (New Rochelle) 2020 04 7;9(4):174-183. Epub 2020 Feb 7.

Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, Massachusetts.

We recently developed the approach of using "microcolumns" of autologous full-thickness skin tissue for wound repair. The small size of these micro skin tissue columns (MSTCs, ∼0.5 mm in diameter) allows donor sites to heal quickly without scarring. Treatment with MSTCs significantly accelerate wound healing, and suppled various skin cell types and skin structures to replenish the wound volume. This technology is now starting clinical use. In this study, we investigate whether MSTCs may also influence wound healing by releasing soluble signaling factors. Freshly harvested MSTCs were incubated in culture medium for 24 h. The conditioned medium was collected and tested for its effects on migration and proliferation of human dermal fibroblasts, and its ability to induce tube formation by human umbilical vein endothelial cells (HUVECs). Proteins released into the conditioned medium were characterized by multiplex enzyme-linked immunosorbent assay (ELISA), and compared with medium conditioned by an equivalent mass of intact full-thickness skin. MSTC-conditioned medium increased fibroblast migration and proliferation, as well as HUVEC tube formation. MSTCs released many soluble factors known to play prominent roles in wound healing. A subset of proteins showed significantly different release profiles compared with intact full-thickness skin. The technology for harvesting and using MSTCs to augment wound healing was recently developed as an alternative to conventional autologous skin grafting. This study shows that MSTCs could also function as "cytokine factories." In addition to supplying autologous cells to repopulate the wound volume, MSTCs can also function as a source of growth factors and cytokines to further enhance wound healing.
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http://dx.doi.org/10.1089/wound.2019.1045DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7047113PMC
April 2020

When Wounds Are Good for You: The Regenerative Capacity of Fractional Resurfacing and Potential Utility in Chronic Wound Prevention.

Adv Wound Care (New Rochelle) 2019 Dec 6;8(12):679-691. Epub 2019 Nov 6.

Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, Massachusetts.

Fractional resurfacing involves producing arrays of microinjuries on the skin, by thermal or mechanical means, to trigger tissue regeneration. Originally developed for cosmetic enhancement, fractional resurfacing induces a broad array of improvements in the structural and functional qualities of the treated skin and is especially effective at returning defective skin to a more normal state. In addition to fascinating questions about the nature of this remarkable regenerative capacity, there may be potential utility in ulcer prevention by halting or even reversing the progressive decline in overall skin quality that usually precedes chronic wound development. Photoaging and scarring are the two skin defects most commonly treated by fractional resurfacing, and the treatment produces profound and long-lasting improvements in skin quality, both clinically and at the cellular/histologic level. Chronic wounds usually occur in skin that is compromised by various pathologic factors, and many of the defects found in this ulcer-prone skin are similar to those that have seen improvements after fractional resurfacing. The mechanisms responsible for the regenerative capacity of fractional resurfacing are mostly unknown, as is how ulcer-prone skin, which is usually afflicted by stressors external to the skin tissue itself, would respond to fractional resurfacing. Better understanding of the cellular and molecular mechanisms underlying the unique healing response to fractional resurfacing could reveal fundamental information about adult tissue regeneration, lead to improvements in current applications, as well as new therapies in other pathologic conditions.
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http://dx.doi.org/10.1089/wound.2019.0945DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6862960PMC
December 2019

Pheno-seq - linking visual features and gene expression in 3D cell culture systems.

Sci Rep 2019 08 26;9(1):12367. Epub 2019 Aug 26.

Digital Health Center, Berlin Institute of Health (BIH)/Charité-Universitätsmedizin Berlin, Berlin, Germany.

Patient-derived 3D cell culture systems are currently advancing cancer research since they potentiate the molecular analysis of tissue-like properties and drug response under well-defined conditions. However, our understanding of the relationship between the heterogeneity of morphological phenotypes and the underlying transcriptome is still limited. To address this issue, we here introduce "pheno-seq" to directly link visual features of 3D cell culture systems with profiling their transcriptome. As prototypic applications breast and colorectal cancer (CRC) spheroids were analyzed by pheno-seq. We identified characteristic gene expression signatures of epithelial-to-mesenchymal transition that are associated with invasive growth behavior of clonal breast cancer spheroids. Furthermore, we linked long-term proliferative capacity in a patient-derived model of CRC to a lowly abundant PROX1-positive cancer stem cell subtype. We anticipate that the ability to integrate transcriptome analysis and morphological patho-phenotypes of cancer cells will provide novel insight on the molecular origins of intratumor heterogeneity.
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http://dx.doi.org/10.1038/s41598-019-48771-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710272PMC
August 2019

Purinergic P2Y receptors modulate endothelial sprouting.

Cell Mol Life Sci 2020 Mar 5;77(5):885-901. Epub 2019 Jul 5.

Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, AUVA Research Center, Donaueschingenstrasse 13, 1200, Vienna, Austria.

Purinergic P2 receptors are critical regulators of several functions within the vascular system, including platelet aggregation, vascular inflammation, and vascular tone. However, a role for ATP release and P2Y receptor signalling in angiogenesis remains poorly defined. Here, we demonstrate that blood vessel growth is controlled by P2Y receptors. Endothelial sprouting and vascular tube formation were significantly dependent on P2Y expression and inhibition of P2Y using a selective antagonist blocked microvascular network generation. Mechanistically, overexpression of P2Y in endothelial cells induced the expression of the proangiogenic molecules CXCR4, CD34, and angiopoietin-2, while expression of VEGFR-2 was decreased. Interestingly, elevated P2Y expression caused constitutive phosphorylation of ERK1/2 and VEGFR-2. However, stimulation of cells with the P2Y agonist UTP did not influence sprouting unless P2Y was constitutively expressed. Finally, inhibition of VEGFR-2 impaired spontaneous vascular network formation induced by P2Y overexpression. Our data suggest that P2Y receptors have an essential function in angiogenesis, and that P2Y receptors present a therapeutic target to regulate blood vessel growth.
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http://dx.doi.org/10.1007/s00018-019-03213-2DOI Listing
March 2020

A strategy for high-dimensional multivariable analysis classifies childhood asthma phenotypes from genetic, immunological, and environmental factors.

Allergy 2019 07 31;74(7):1364-1373. Epub 2019 Mar 31.

Department of Pulmonary and Allergy, Dr. von Hauner Children's Hospital, LMU, Munich, Germany.

Background: Associations between childhood asthma phenotypes and genetic, immunological, and environmental factors have been previously established. Yet, strategies to integrate high-dimensional risk factors from multiple distinct data sets, and thereby increase the statistical power of analyses, have been hampered by a preponderance of missing data and lack of methods to accommodate them.

Methods: We assembled questionnaire, diagnostic, genotype, microarray, RT-qPCR, flow cytometry, and cytokine data (referred to as data modalities) to use as input factors for a classifier that could distinguish healthy children, mild-to-moderate allergic asthmatics, and nonallergic asthmatics. Based on data from 260 German children aged 4-14 from our university outpatient clinic, we built a novel multilevel prediction approach for asthma outcome which could deal with a present complex missing data structure.

Results: The optimal learning method was boosting based on all data sets, achieving an area underneath the receiver operating characteristic curve (AUC) for three classes of phenotypes of 0.81 (95%-confidence interval (CI): 0.65-0.94) using leave-one-out cross-validation. Besides improving the AUC, our integrative multilevel learning approach led to tighter CIs than using smaller complete predictor data sets (AUC = 0.82 [0.66-0.94] for boosting). The most important variables for classifying childhood asthma phenotypes comprised novel identified genes, namely PKN2 (protein kinase N2), PTK2 (protein tyrosine kinase 2), and ALPP (alkaline phosphatase, placental).

Conclusion: Our combination of several data modalities using a novel strategy improved classification of childhood asthma phenotypes but requires validation in external populations. The generic approach is applicable to other multilevel data-based risk prediction settings, which typically suffer from incomplete data.
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http://dx.doi.org/10.1111/all.13745DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767756PMC
July 2019

Impact of Brain Fatty Acid Signaling on Peripheral Insulin Action in Mice.

Exp Clin Endocrinol Diabetes 2020 Jan 5;128(1):20-29. Epub 2018 Nov 5.

German Center for Diabetes Research (DZD), Neuherberg, Germany.

Aims And Methods: Glucose homeostasis and energy balance are under control by peripheral and brain processes. Especially insulin signaling in the brain seems to impact whole body glucose homeostasis and interacts with fatty acid signaling. In humans circulating saturated fatty acids are negatively associated with brain insulin action while animal studies suggest both positive and negative interactions of fatty acids and insulin brain action. This apparent discrepancy might reflect a difference between acute and chronic fatty acid signaling. To address this question we investigated the acute effect of an intracerebroventricular palmitic acid administration on peripheral glucose homeostasis. We developed and implemented a method for simultaneous monitoring of brain activity and peripheral insulin action in freely moving mice by combining radiotelemetry electrocorticography (ECoG) and euglycemic-hyperinsulinemic clamps. This method allowed gaining insight in the early kinetics of brain fatty acid signaling and its contemporaneous effect on liver function , which, to our knowledge, has not been assessed so far in mice.

Results: Insulin-induced brain activity in the theta and beta band was decreased by acute intracerebroventricular application of palmitic acid. Peripherally it amplified insulin action as demonstrated by a significant inhibition of endogenous glucose production and increased glucose infusion rate. Moreover, our results further revealed that the brain effect of peripheral insulin is modulated by palmitic acid load in the brain.

Conclusion: These findings suggest that insulin action is amplified in the periphery and attenuated in the brain by acute palmitic acid application. Thus, our results indicate that acute palmitic acid signaling in the brain may be different from chronic effects.
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http://dx.doi.org/10.1055/a-0735-9533DOI Listing
January 2020

The Importance of Biophysical and Biochemical Stimuli in Dynamic Skeletal Muscle Models.

Front Physiol 2018 22;9:1130. Epub 2018 Aug 22.

Department of Biochemical Engineering, University of Applied Sciences Technikum Wien, Vienna, Austria.

Classical approaches to engineer skeletal muscle tissue based on current regenerative and surgical procedures still do not meet the desired outcome for patient applications. Besides the evident need to create functional skeletal muscle tissue for the repair of volumetric muscle defects, there is also growing demand for platforms to study muscle-related diseases, such as muscular dystrophies or sarcopenia. Currently, numerous studies exist that have employed a variety of biomaterials, cell types and strategies for maturation of skeletal muscle tissue in 2D and 3D environments. However, researchers are just at the beginning of understanding the impact of different culture settings and their biochemical (growth factors and chemical changes) and biophysical cues (mechanical properties) on myogenesis. With this review we intend to emphasize the need for new skeletal muscle (disease) models to better recapitulate important structural and functional aspects of muscle development. We highlight the importance of choosing appropriate system components, e.g., cell and biomaterial type, structural and mechanical matrix properties or culture format, and how understanding their interplay will enable researchers to create optimized platforms to investigate myogenesis in healthy and diseased tissue. Thus, we aim to deliver guidelines for experimental designs to allow estimation of the potential influence of the selected skeletal muscle tissue engineering setup on the myogenic outcome prior to their implementation. Moreover, we offer a workflow to facilitate identifying and selecting different analytical tools to demonstrate the successful creation of functional skeletal muscle tissue. Ultimately, a refinement of existing strategies will lead to further progression in understanding important aspects of muscle diseases, muscle aging and muscle regeneration to improve quality of life of patients and enable the establishment of new treatment options.
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http://dx.doi.org/10.3389/fphys.2018.01130DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6113794PMC
August 2018

High risk of recurrent venous thromboembolism in BCR-ABL-negative myeloproliferative neoplasms after termination of anticoagulation.

Ann Hematol 2019 Jan 28;98(1):93-100. Epub 2018 Aug 28.

University Clinic for Hematology, Oncology, Hemostaseology and Palliative Care, Johannes Wesling Medical Center Minden, University of Bochum, Hans-Nolte-Straße 1, 32429, Minden, Germany.

Venous thromboembolism (VTE) is a major burden in patients with BCR-ABL-negative myeloproliferative neoplasms (MPN). In addition to cytoreductive treatment anticoagulation is mandatory, but optimal duration of anticoagulation is a matter of debate. In our single center study, we retrospectively included 526 MPN patients. In total, 78 of 526 MPN patients (14.8%) had 99 MPN-associated VTE. Median age at first VTE was 52.5 years (range 23-81). During a study period of 3497 years, a VTE event rate of 1.7% per patient/year was detected. 38.4% (38/99) of all VTEs appeared before or at MPN diagnosis and 55.6% (55/99) occurred at "uncommon" sites like splanchnic or cerebral veins. MPN patients with VTEs were significantly more female (p = 0.028), JAK2 positive (p = 0.018), or had a polycythemia vera (p = 0.009). MPN patients without VTEs were more often CALR positive (p = 0.023). Total study period after first VTE was 336 years with 20 VTE recurrences accounting for a recurrence rate of 6% per patient/year. In 36 of 71 MPN patients with anticoagulation therapy after first VTE event (50.7%), prophylactic anticoagulation was terminated after a median time of 6 months (range 1-61); 13 of those 36 patients (36.1%) had a VTE recurrence after a median of 13 months (range 4-168). In contrast, only three of 35 (8.6%) patients with ongoing anticoagulation had a VTE recurrence (p = 0.0127). Thus, termination of prophylactic anticoagulation was associated with a significantly higher risk of VTE recurrence. Our data suggest that in MPN patients with VTE, a prolonged duration of anticoagulation may be beneficial.
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http://dx.doi.org/10.1007/s00277-018-3483-6DOI Listing
January 2019

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

Comput Math Methods Med 2017 24;2017:7847531. Epub 2017 Sep 24.

Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany.

Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package .
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http://dx.doi.org/10.1155/2017/7847531DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5632994PMC
September 2018

A DREAM Challenge to Build Prediction Models for Short-Term Discontinuation of Docetaxel in Metastatic Castration-Resistant Prostate Cancer.

JCO Clin Cancer Inform 2017 11;1:1-15

Fatemeh Seyednasrollah and Laura L. Elo, Turku Centre for Biotechnology; University of Turku; Åbo Akademi University, Turku, Finland; Devin C. Koestler, University of Kansas Medical Center, Kansas City, KS; Tao Wang, University of Texas Southwestern Medical Center, Dallas, TX; Stephen R. Piccolo, Brigham Young University, Provo; University of Utah, Salt Lake City, Utah, UT; Roberto Vega, Russell Greiner, and Luke Kumar, University of Alberta; Alberta Innovates Centre for Machine Learning, Edmonton, Alberta, Canada; Christiane Fuchs, Helmholtz Zentrum München, Neuherberg; Technische Universität München, Garching, Germany; Eyal Gofer, The Hebrew University, Jerusalem, Israel; Russell D. Wolfinger, SAS Institute, Cary, NC; Kimberly Kanigel Winner and James C. Costello, University of Colorado, Anschutz Medical Campus, Aurora, CO; Chris Bare, Elias Chaibub Neto, Thomas Yu, Thea Norman, and Justin Guinney, Sage Bionetworks, Seattle, WA; Liji Shen and Fang Liz Zhou, Sanofi, Bridgewater, NJ; Kald Abdallah, AstraZeneca, Gaithersburg, MD; Gustavo Stolovitzky, IBM Research, Yorktown Heights; Howard I. Scher, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY; Howard R. Soule, Prostate Cancer Foundation, Santa Monica; Charles J. Ryan, University of California, San Francisco, CA; Christopher J. Sweeney, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Oliver Sartor, Tulane University, New Orleans, LA.

Purpose: Docetaxel has a demonstrated survival benefit for patients with metastatic castration-resistant prostate cancer (mCRPC); however, 10% to 20% of patients discontinue docetaxel prematurely because of toxicity-induced adverse events, and the management of risk factors for toxicity remains a challenge.

Patients And Methods: The comparator arms of four phase III clinical trials in first-line mCRPC were collected, annotated, and compiled, with a total of 2,070 patients. Early discontinuation was defined as treatment stoppage within 3 months as a result of adverse treatment effects; 10% of patients discontinued treatment. We designed an open-data, crowd-sourced DREAM Challenge for developing models with which to predict early discontinuation of docetaxel treatment. Clinical features for all four trials and outcomes for three of the four trials were made publicly available, with the outcomes of the fourth trial held back for unbiased model evaluation. Challenge participants from around the world trained models and submitted their predictions. Area under the precision-recall curve was the primary metric used for performance assessment.

Results: In total, 34 separate teams submitted predictions. Seven models with statistically similar area under precision-recall curves (Bayes factor ≤ 3) outperformed all other models. A postchallenge analysis of risk prediction using these seven models revealed three patient subgroups: high risk, low risk, or discordant risk. Early discontinuation events were two times higher in the high-risk subgroup compared with the low-risk subgroup. Simulation studies demonstrated that use of patient discontinuation prediction models could reduce patient enrollment in clinical trials without the loss of statistical power.

Conclusion: This work represents a successful collaboration between 34 international teams that leveraged open clinical trial data. Our results demonstrate that routinely collected clinical features can be used to identify patients with mCRPC who are likely to discontinue treatment because of adverse events and establishes a robust benchmark with implications for clinical trial design.
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http://dx.doi.org/10.1200/CCI.17.00018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874023PMC
November 2017

netReg: network-regularized linear models for biological association studies.

Bioinformatics 2018 03;34(5):896-898

Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.

Summary: Modelling biological associations or dependencies using linear regression is often complicated when the analyzed data-sets are high-dimensional and less observations than variables are available (n ≪ p). For genomic data-sets penalized regression methods have been applied settling this issue. Recently proposed regression models utilize prior knowledge on dependencies, e.g. in the form of graphs, arguing that this information will lead to more reliable estimates for regression coefficients. However, none of the proposed models for multivariate genomic response variables have been implemented as a computationally efficient, freely available library. In this paper we propose netReg, a package for graph-penalized regression models that use large networks and thousands of variables. netReg incorporates a priori generated biological graph information into linear models yielding sparse or smooth solutions for regression coefficients.

Availability And Implementation: netReg is implemented as both R-package and C ++ commandline tool. The main computations are done in C ++, where we use Armadillo for fast matrix calculations and Dlib for optimization. The R package is freely available on Bioconductorhttps://bioconductor.org/packages/netReg. The command line tool can be installed using the conda channel Bioconda. Installation details, issue reports, development versions, documentation and tutorials for the R and C ++ versions and the R package vignette can be found on GitHub https://dirmeier.github.io/netReg/. The GitHub page also contains code for benchmarking and example datasets used in this paper.

Contact: simon.dirmeier@bsse.ethz.ch.
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http://dx.doi.org/10.1093/bioinformatics/btx677DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030897PMC
March 2018

Improvement of adipose tissue-derived cells by low-energy extracorporeal shock wave therapy.

Cytotherapy 2017 09 19;19(9):1079-1095. Epub 2017 Jul 19.

Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, Austrian Workers' Compensation Board (AUVA) Research Center, Vienna, Austria; Austrian Cluster for Tissue Regeneration, Vienna, Austria.

Background: Cell-based therapies with autologous adipose tissue-derived cells have shown great potential in several clinical studies in the last decades. The majority of these studies have been using the stromal vascular fraction (SVF), a heterogeneous mixture of fibroblasts, lymphocytes, monocytes/macrophages, endothelial cells, endothelial progenitor cells, pericytes and adipose-derived stromal/stem cells (ASC) among others. Although possible clinical applications of autologous adipose tissue-derived cells are manifold, they are limited by insufficient uniformity in cell identity and regenerative potency.

Methods: In our experimental set-up, low-energy extracorporeal shock wave therapy (ESWT) was performed on freshly obtained human adipose tissue and isolated adipose tissue SVF cells aiming to equalize and enhance stem cell properties and functionality.

Results: After ESWT on adipose tissue we could achieve higher cellular adenosine triphosphate (ATP) levels compared with ESWT on the isolated SVF as well as the control. ESWT on adipose tissue resulted in a significantly higher expression of single mesenchymal and vascular marker compared with untreated control. Analysis of SVF protein secretome revealed a significant enhancement in insulin-like growth factor (IGF)-1 and placental growth factor (PLGF) after ESWT on adipose tissue.

Discussion: Summarizing we could show that ESWT on adipose tissue enhanced the cellular ATP content and modified the expression of single mesenchymal and vascular marker, and thus potentially provides a more regenerative cell population. Because the effectiveness of autologous cell therapy is dependent on the therapeutic potency of the patient's cells, this technology might raise the number of patients eligible for autologous cell transplantation.
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http://dx.doi.org/10.1016/j.jcyt.2017.05.010DOI Listing
September 2017

Inferring catalysis in biological systems.

IET Syst Biol 2016 Dec;10(6):210-218

Center for Mathematics, Chair of Mathematical Modeling of Biological Systems, Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany.

In systems biology, one is often interested in the communication patterns between several species, such as genes, enzymes or proteins. These patterns become more recognisable when temporal experiments are performed. This temporal communication can be structured by reaction networks such as gene regulatory networks or signalling pathways. Mathematical modelling of data arising from such networks can reveal important details, thus helping to understand the studied system. In many cases, however, corresponding models still deviate from the observed data. This may be due to unknown but present catalytic reactions. From a modelling perspective, the question of whether a certain reaction is catalysed leads to a large increase of model candidates. For large networks the calibration of all possible models becomes computationally infeasible. We propose a method which determines a substantially reduced set of appropriate model candidates and identifies the catalyst of each reaction at the same time. This is incorporated in a multiple-step procedure which first extends the network by additional latent variables and subsequently identifies catalyst candidates using similarity analysis methods. Results from synthetic data examples suggest a good performance even for non-informative data with few observations. Applied on CD95 apoptotic pathway our method provides new insights into apoptosis regulation.
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http://dx.doi.org/10.1049/iet-syb.2015.0087DOI Listing
December 2016

CORALINA: a universal method for the generation of gRNA libraries for CRISPR-based screening.

BMC Genomics 2016 11 14;17(1):917. Epub 2016 Nov 14.

Epigenetic Engineering, Institute of Stem Cell Research, Helmholtz Zentrum, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.

Background: The bacterial CRISPR system is fast becoming the most popular genetic and epigenetic engineering tool due to its universal applicability and adaptability. The desire to deploy CRISPR-based methods in a large variety of species and contexts has created an urgent need for the development of easy, time- and cost-effective methods enabling large-scale screening approaches.

Results: Here we describe CORALINA (comprehensive gRNA library generation through controlled nuclease activity), a method for the generation of comprehensive gRNA libraries for CRISPR-based screens. CORALINA gRNA libraries can be derived from any source of DNA without the need of complex oligonucleotide synthesis. We show the utility of CORALINA for human and mouse genomic DNA, its reproducibility in covering the most relevant genomic features including regulatory, coding and non-coding sequences and confirm the functionality of CORALINA generated gRNAs.

Conclusions: The simplicity and cost-effectiveness make CORALINA suitable for any experimental system. The unprecedented sequence complexities obtainable with CORALINA libraries are a necessary pre-requisite for less biased large scale genomic and epigenomic screens.
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http://dx.doi.org/10.1186/s12864-016-3268-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5109649PMC
November 2016

Desmin enters the nucleus of cardiac stem cells and modulates Nkx2.5 expression by participating in transcription factor complexes that interact with the nkx2.5 gene.

Biol Open 2016 Jan 19;5(2):140-53. Epub 2016 Jan 19.

Department of Medical Biochemistry, Max F. Perutz Laboratories, Medical University of Vienna, Vienna Biocenter, Vienna A1030, Austria

The transcription factor Nkx2.5 and the intermediate filament protein desmin are simultaneously expressed in cardiac progenitor cells during commitment of primitive mesoderm to the cardiomyogenic lineage. Up-regulation of Nkx2.5 expression by desmin suggests that desmin may contribute to cardiogenic commitment and myocardial differentiation by directly influencing the transcription of the nkx2.5 gene in cardiac progenitor cells. Here, we demonstrate that desmin activates transcription of nkx2.5 reporter genes, rescues nkx2.5 haploinsufficiency in cardiac progenitor cells, and is responsible for the proper expression of Nkx2.5 in adult cardiac side population stem cells. These effects are consistent with the temporary presence of desmin in the nuclei of differentiating cardiac progenitor cells and its physical interaction with transcription factor complexes bound to the enhancer and promoter elements of the nkx2.5 gene. These findings introduce desmin as a newly discovered and unexpected player in the regulatory network guiding cardiomyogenesis in cardiac stem cells.
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http://dx.doi.org/10.1242/bio.014993DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4823984PMC
January 2016

Identifying latent dynamic components in biological systems.

IET Syst Biol 2015 Oct;9(5):193-203

Center for Mathematics, Chair of Mathematical Modeling of Biological Systems, Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany.

In computational systems biology, the general aim is to derive regulatory models from multivariate readouts, thereby generating predictions for novel experiments. In the past, many such models have been formulated for different biological applications. The authors consider the scenario where a given model fails to predict a set of observations with acceptable accuracy and ask the question whether this is because of the model lacking important external regulations. Real-world examples for such entities range from microRNAs to metabolic fluxes. To improve the prediction, they propose an algorithm to systematically extend the network by an additional latent dynamic variable which has an exogenous effect on the considered network. This variable's time course and influence on the other species is estimated in a two-step procedure involving spline approximation, maximum-likelihood estimation and model selection. Simulation studies show that such a hidden influence can successfully be inferred. The method is also applied to a signalling pathway model where they analyse real data and obtain promising results. Furthermore, the technique can be employed to detect incomplete network structures.
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http://dx.doi.org/10.1049/iet-syb.2014.0013DOI Listing
October 2015

A novel bioreactor for the generation of highly aligned 3D skeletal muscle-like constructs through orientation of fibrin via application of static strain.

Acta Biomater 2015 Sep 30;24:251-65. Epub 2015 Jun 30.

Austrian Cluster for Tissue Regeneration, Vienna, Austria; Department of Biochemical Engineering, UAS Technikum Wien, Vienna, Austria; City of Vienna Competence Team Bioreactors, UAS Technikum Wien, Vienna, Austria.

Unlabelled: The generation of functional biomimetic skeletal muscle constructs is still one of the fundamental challenges in skeletal muscle tissue engineering. With the notion that structure strongly dictates functional capabilities, a myriad of cell types, scaffold materials and stimulation strategies have been combined. To further optimize muscle engineered constructs, we have developed a novel bioreactor system (MagneTissue) for rapid engineering of skeletal muscle-like constructs with the aim to resemble native muscle in terms of structure, gene expression profile and maturity. Myoblasts embedded in fibrin, a natural hydrogel that serves as extracellular matrix, are subjected to mechanical stimulation via magnetic force transmission. We identify static mechanical strain as a trigger for cellular alignment concomitant with the orientation of the scaffold into highly organized fibrin fibrils. This ultimately yields myotubes with a more mature phenotype in terms of sarcomeric patterning, diameter and length. On the molecular level, a faster progression of the myogenic gene expression program is evident as myogenic determination markers MyoD and Myogenin as well as the Ca(2+) dependent contractile structural marker TnnT1 are significantly upregulated when strain is applied. The major advantage of the MagneTissue bioreactor system is that the generated tension is not exclusively relying on the strain generated by the cells themselves in response to scaffold anchoring but its ability to subject the constructs to individually adjustable strain protocols. In future work, this will allow applying mechanical stimulation with different strain regimes in the maturation process of tissue engineered constructs and elucidating the role of mechanotransduction in myogenesis.

Statement Of Significance: Mechanical stimulation of tissue engineered skeletal muscle constructs is a promising approach to increase tissue functionality. We have developed a novel bioreactor-based 3D culture system, giving the user the possibility to apply different strain regimes like static, cyclic or ramp strain to myogenic precursor cells embedded in a fibrin scaffold. Application of static mechanical strain leads to alignment of fibrin fibrils along the axis of strain and concomitantly to highly aligned myotube formation. Additionally, the pattern of myogenic gene expression follows the temporal progression observed in vivo with a more thorough induction of the myogenic program when static strain is applied. Ultimately, the strain protocol used in this study results in a higher degree of muscle maturity demonstrated by enhanced sarcomeric patterning and increased myotube diameter and length. The introduced bioreactor system enables new possibilities in muscle tissue engineering as longer cultivation periods and different strain applications will yield tissue engineered muscle-like constructs with improved characteristics in regard to functionality and biomimicry.
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http://dx.doi.org/10.1016/j.actbio.2015.06.033DOI Listing
September 2015

Atrx promotes heterochromatin formation at retrotransposons.

EMBO Rep 2015 Jul 26;16(7):836-50. Epub 2015 May 26.

Adolf-Butenandt-Institute, Ludwig Maximilians University and Munich Center for Integrated Protein Science (CiPS), Munich, Germany

More than 50% of mammalian genomes consist of retrotransposon sequences. Silencing of retrotransposons by heterochromatin is essential to ensure genomic stability and transcriptional integrity. Here, we identified a short sequence element in intracisternal A particle (IAP) retrotransposons that is sufficient to trigger heterochromatin formation. We used this sequence in a genome-wide shRNA screen and identified the chromatin remodeler Atrx as a novel regulator of IAP silencing. Atrx binds to IAP elements and is necessary for efficient heterochromatin formation. In addition, Atrx facilitates a robust and largely inaccessible heterochromatin structure as Atrx knockout cells display increased chromatin accessibility at retrotransposons and non-repetitive heterochromatic loci. In summary, we demonstrate a direct role of Atrx in the establishment and robust maintenance of heterochromatin.
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http://dx.doi.org/10.15252/embr.201439937DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4515123PMC
July 2015

Inter-chromosomal contact networks provide insights into Mammalian chromatin organization.

PLoS One 2015 11;10(5):e0126125. Epub 2015 May 11.

Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, Freising, Germany; Institute for Bioinformatics and Systems Biology, HMGU German Research Center for Environmental Health, Neuherberg, Germany; Department of Bioinformatics, St Petersburg State Polytechnical University, St Petersburg, Russia.

The recent advent of conformation capture techniques has provided unprecedented insights into the spatial organization of chromatin. We present a large-scale investigation of the inter-chromosomal segment and gene contact networks in embryonic stem cells of two mammalian organisms: humans and mice. Both interaction networks are characterized by a high degree of clustering of genome regions and the existence of hubs. Both genomes exhibit similar structural characteristics such as increased flexibility of certain Y chromosome regions and co-localization of centromere-proximal regions. Spatial proximity is correlated with the functional similarity of genes in both species. We also found a significant association between spatial proximity and the co-expression of genes in the human genome. The structural properties of chromatin are also species specific, including the presence of two highly interactive regions in mouse chromatin and an increased contact density on short, gene-rich human chromosomes, thereby indicating their central nuclear position. Trans-interacting segments are enriched in active marks in human and had no distinct feature profile in mouse. Thus, in contrast to interactions within individual chromosomes, the inter-chromosomal interactions in human and mouse embryonic stem cells do not appear to be conserved.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0126125PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427453PMC
February 2016

Bayesian blind source separation for data with network structure.

J Comput Biol 2014 Nov 10;21(11):855-65. Epub 2014 Oct 10.

Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; and Institute for Mathematical Sciences. Technische Universität München , Munich, Germany .

In biology, more and more information about the interactions in regulatory systems becomes accessible, and this often leads to prior knowledge for recent data interpretations. In this work we focus on multivariate signaling data, where the structure of the data is induced by a known regulatory network. To extract signals of interest we assume a blind source separation (BSS) model, and we capture the structure of the source signals in terms of a Bayesian network. To keep the parameter space small, we consider stationary signals, and we introduce the new algorithm emGrade, where model parameters and source signals are estimated using expectation maximization. For network data, we find an improved estimation performance compared to other BSS algorithms, and the flexible Bayesian modeling enables us to deal with repeated and missing observation values. The main advantage of our method is the statistically interpretable likelihood, and we can use model selection criteria to determine the (in general unknown) number of source signals or decide between different given networks. In simulations we demonstrate the recovery of the source signals dependent on the graph structure and the dimensionality of the data.
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http://dx.doi.org/10.1089/cmb.2014.0117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224047PMC
November 2014

In vitro extracorporeal shock wave treatment enhances stemness and preserves multipotency of rat and human adipose-derived stem cells.

Cytotherapy 2014 Dec 28;16(12):1666-78. Epub 2014 Aug 28.

Austrian Cluster for Tissue Regeneration, Vienna, Austria; University of Applied Sciences Technikum Wien-Department of Biochemical Engineering, Vienna, Austria.

Background Aims: Adipose-derived progenitor/stem cells (ASCs) are discussed as a promising candidate for various tissue engineering approaches. However, its applicability for the clinic is still difficult due to intra- and inter-donor heterogeneity and limited life span in vitro, influencing differentiation capacity as a consequence to decreased multipotency.

Methods: Extracorporeal shock wave treatment has been proven to be a suitable clinical tool to improve regeneration of a variety of tissues for several decades, whereas the mechanisms underlying these beneficial effects remain widely unknown.

Results: In this study we show that human and rat adipose derived stem cells respond strongly to repetitive shock wave treatment in vitro, resulting not only in maintenance and significant elevation of mesenchymal markers (CD73, CD90, CD105), but also in significantly increased differentiation capacity towards the osteogenic and adipogenic lineage as well as toward Schwann-cell like cells even after extended time in vitro, preserving multipotency of ASCs.

Conclusions: ESWT might be a promising tool to improve ASC quality for cell therapy in various tissue engineering and regenerative medicine applications.
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http://dx.doi.org/10.1016/j.jcyt.2014.07.005DOI Listing
December 2014

Shock wave treatment enhances cell proliferation and improves wound healing by ATP release-coupled extracellular signal-regulated kinase (ERK) activation.

J Biol Chem 2014 Sep 12;289(39):27090-27104. Epub 2014 Aug 12.

Department of Biochemical Engineering, University of Applied Sciences Technikum Wien, 1200 Vienna, Austria,; The Austrian Cluster for Tissue Regeneration, Vienna, Austria.

Shock wave treatment accelerates impaired wound healing in diverse clinical situations. However, the mechanisms underlying the beneficial effects of shock waves have not yet been fully revealed. Because cell proliferation is a major requirement in the wound healing cascade, we used in vitro studies and an in vivo wound healing model to study whether shock wave treatment influences proliferation by altering major extracellular factors and signaling pathways involved in cell proliferation. We identified extracellular ATP, released in an energy- and pulse number-dependent manner, as a trigger of the biological effects of shock wave treatment. Shock wave treatment induced ATP release, increased Erk1/2 and p38 MAPK activation, and enhanced proliferation in three different cell types (C3H10T1/2 murine mesenchymal progenitor cells, primary human adipose tissue-derived stem cells, and a human Jurkat T cell line) in vitro. Purinergic signaling-induced Erk1/2 activation was found to be essential for this proliferative effect, which was further confirmed by in vivo studies in a rat wound healing model where shock wave treatment induced proliferation and increased wound healing in an Erk1/2-dependent fashion. In summary, this report demonstrates that shock wave treatment triggers release of cellular ATP, which subsequently activates purinergic receptors and finally enhances proliferation in vitro and in vivo via downstream Erk1/2 signaling. In conclusion, our findings shed further light on the molecular mechanisms by which shock wave treatment exerts its beneficial effects. These findings could help to improve the clinical use of shock wave treatment for wound healing.
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http://dx.doi.org/10.1074/jbc.M114.580936DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4175346PMC
September 2014

Metabolite profiling reveals new insights into the regulation of serum urate in humans.

Metabolomics 2014 20;10(1):141-151. Epub 2013 Jul 20.

Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.

Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia.
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http://dx.doi.org/10.1007/s11306-013-0565-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3890072PMC
July 2013