6D Effective Action of Heterotic Compactification on K3 with nontrivial Gauge Bundles

We compute the six-dimensional effective action of the heterotic string compactified on K3 for the standard embedding and for a class of backgrounds with line bundles and appropriate Yang-Mills fluxes. We compute the couplings of the charged scalars and the bundle moduli as functions of the geometrical K3 moduli from a Kaluza-Klein analysis. We derive the D-term potential and show that in the flux backgrounds U(1) vector multiplets become massive by a Stuckelberg mechanism.Comment: 41 pages, typos corrected, references adde

A distinct metabolic signature predicts development of fasting plasma glucose

ABSTRACT: BACKGROUND: High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called `omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods. METHODS: We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort. RESULTS: We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis. CONCLUSIONS: We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods

miR-34a: a new player in the regulation of T cell function by modulation of NF-κB signaling

NF-κB functions as modulator of T cell receptor-mediated signaling and transcriptional regulator of miR-34a. Our in silico analysis revealed that miR-34a impacts the NF-κB signalosome with miR-34a binding sites in 14 key members of the NF-κB signaling pathway. Functional analysis identified five target genes of miR-34a including PLCG1, CD3E, PIK3CB, TAB2, and NFΚBIA. Overexpression of miR-34a in CD4+ and CD8+ T cells led to a significant decrease of NFΚBIA as the most downstream cytoplasmic NF-κB member, a reduced cell surface abundance of TCRA and CD3E, and to a reduction of T cell killing capacity. Inhibition of miR-34a caused an increase of NFΚBIA, TCRA, and CD3E. Notably, activation of CD4+ and CD8+ T cells entrails a gradual increase of miR-34a. Our results lend further support to a model with miR-34a as a central NF-κB regulator in T cells

Aging Studies for the Large Honeycomb Drift Tube System of the Outer Tracker of HERA-B

The HERA-B Outer Tracker consists of drift tubes folded from polycarbonate foil and is operated with Ar/CF4/CO2 as drift gas. The detector has to stand radiation levels which are similar to LHC conditions. The first prototypes exposed to radiation in HERA-B suffered severe radiation damage due to the development of self-sustaining currents (Malter effect). In a subsequent extended R&D program major changes to the original concept for the drift tubes (surface conductivity, drift gas, production materials) have been developed and validated for use in harsh radiation environments. In the test program various aging effects (like Malter currents, gain loss due to anode aging and etching of the anode gold surface) have been observed and cures by tuning of operation parameters have been developed.Comment: 14 pages, 6 figures, to be published in the Proceedings of the International Workshop On Aging Phenomena In Gaseous Detectors, 2-5 Oct 2001, Hamburg, German

Primary cerebral alveolar rhabdomyosarcoma in adult

Primary cerebral rhabdomyosarcomas are very rare and malignant tumors that occur predominantly in the posterior fossa of pediatric patients. We report a rare case of primary cerebral rhabdomyosarcoma located in the supratentorial compartment of a 51 year-old woman together with a review of the pertinent Literature especially regarding the histological diagnosis and pitfalls

Unraveling the microbiome of a thermophilic biogas plant by metagenome and metatranscriptome analysis complemented by characterization of bacterial and archaeal isolates

One of the most promising technologies to sustainably produce energy and to mitigate greenhouse gas emissions from combustion of fossil energy carriers is the anaerobic digestion and biomethanation of organic raw material and waste towards biogas by highly diverse microbial consortia. In this context, the microbial systems ecology of thermophilic industrial-scale biogas plants is poorly understood

The Systems Biology Research Tool: evolvable open-source software

BACKGROUND: Research in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput) experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level. RESULTS: We introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT) to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology. CONCLUSION: The Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability), to facilitate cooperation among researchers, and to expedite progress in the field of systems biology

Genomics and prevalence of bacterial and archaeal isolates from biogas-producing microbiomes

Background: To elucidate biogas microbial communities and processes, the application of high-throughput DNA analysis approaches is becoming increasingly important. Unfortunately, generated data can only partialy be interpreted rudimentary since databases lack reference sequences. Results: Novel cellulolytic, hydrolytic, and acidogenic/acetogenic Bacteria as well as methanogenic Archaea originating from different anaerobic digestion communities were analyzed on the genomic level to assess their role in biomass decomposition and biogas production. Some of the analyzed bacterial strains were recently described as new species and even genera, namely Herbinix hemicellulosilytica T3/55T, Herbinix luporum SD1DT, Clostridium bornimense M2/40T, Proteiniphilum saccharofermentans M3/6T, Fermentimonas caenicola ING2-E5BT, and Petrimonas mucosa ING2-E5AT. High-throughput genome sequencing of 22 anaerobic digestion isolates enabled functional genome interpretation, metabolic reconstruction, and prediction of microbial traits regarding their abilities to utilize complex bio-polymers and to perform specific fermentation pathways. To determine the prevalence of the isolates included in this study in different biogas systems, corresponding metagenome fragment mappings were done. Methanoculleus bourgensis was found to be abundant in three mesophilic biogas plants studied and slightly less abundant in a thermophilic biogas plant, whereas Defluviitoga tunisiensis was only prominent in the thermophilic system. Moreover, several of the analyzed species were clearly detectable in the mesophilic biogas plants, but appeared to be only moderately abundant. Among the species for which genome sequence information was publicly available prior to this study, only the species Amphibacillus xylanus, Clostridium clariflavum, and Lactobacillus acidophilus are of importance for the biogas microbiomes analyzed, but did not reach the level of abundance as determined for M. bourgensis and D. tunisiensis. Conclusions: Isolation of key anaerobic digestion microorganisms and their functional interpretation was achieved by application of elaborated cultivation techniques and subsequent genome analyses. New isolates and their genome information extend the repository covering anaerobic digestion community members. © 2017 The Author(s)

MyCTC chip: microfluidic-based drug screen with patient-derived tumour cells from liquid biopsies

Cancer patients with advanced disease are characterized by intrinsic challenges in predicting drug response patterns, often leading to ineffective treatment. Current clinical practice for treatment decision-making is commonly based on primary or secondary tumour biopsies, yet when disease progression accelerates, tissue biopsies are not performed on a regular basis. It is in this context that liquid biopsies may offer a unique window to uncover key vulnerabilities, providing valuable information about previously underappreciated treatment opportunities. Here, we present MyCTC chip, a novel microfluidic device enabling the isolation, culture and drug susceptibility testing of cancer cells derived from liquid biopsies. Cancer cell capture is achieved through a label-free, antigen-agnostic enrichment method, and it is followed by cultivation in dedicated conditions, allowing on-chip expansion of captured cells. Upon growth, cancer cells are then transferred to drug screen chambers located within the same device, where multiple compounds can be tested simultaneously. We demonstrate MyCTC chip performance by means of spike-in experiments with patient-derived breast circulating tumour cells, enabling >95% capture rates, as well as prospective processing of blood from breast cancer patients and ascites fluid from patients with ovarian, tubal and endometrial cancer, where sensitivity to specific chemotherapeutic agents was identified. Together, we provide evidence that MyCTC chip may be used to identify personalized drug response patterns in patients with advanced metastatic disease and with limited treatment opportunities