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The Transition Radiation Detector (TRD) was designed and built to enhance the capabilities of the ALICE detector at the Large Hadron Collider (LHC). While aimed at providing electron identification and triggering, the TRD also contributes significantly to the track reconstruction and calibration in the central barrel of ALICE. In this paper the design, construction, operation, and performance of this detector are discussed. A pion rejection factor of up to 410 is achieved at a momentum of 1 GeV/c in p–Pb collisions and the resolution at high transverse momentum improves by about 40% when including the TRD information in track reconstruction. The triggering capability is demonstrated both for jet, light nuclei, and electron selection.
The Transition Radiation Detector (TRD) was designed and built to enhance the capabilities of the ALICE detector at the Large Hadron Collider (LHC). While aimed at providing electron identification and triggering, the TRD also contributes significantly to the track reconstruction and calibration in the central barrel of ALICE. In this paper the design, construction, operation, and performance of this detector are discussed. A pion rejection factor of up to 410 is achieved at a momentum of 1 GeV/c in p-Pb collisions and the resolution at high transverse momentum improves by about 40% when including the TRD information in track reconstruction. The triggering capability is demonstrated both for jet, light nuclei, and electron selection.
The Transition Radiation Detector (TRD) was designed and built to enhance the capabilities of the ALICE detector at the Large Hadron Collider (LHC). While aimed at providing electron identification and triggering, the TRD also contributes significantly to the track reconstruction and calibration in the central barrel of ALICE. In this paper the design, construction, operation, and performance of this detector are discussed. A pion rejection factor of up to 410 is achieved at a momentum of 1 GeV/c in p-Pb collisions and the resolution at high transverse momentum improves by about 40% when including the TRD information in track reconstruction. The triggering capability is demonstrated both for jet, light nuclei, and electron selection.
Objective: Pancreatic ductal adenocarcinoma (PDAC) still carries a dismal prognosis with an overall 5-year survival rate of 9%. Conventional combination chemotherapies are a clear advance in the treatment of PDAC; however, subtypes of the disease exist, which exhibit extensive resistance to such therapies. Genomic MYC amplifications represent a distinct subset of PDAC with an aggressive tumour biology. It is clear that hyperactivation of MYC generates dependencies that can be exploited therapeutically. The aim of the study was to find and to target MYC-associated dependencies.
Design: We analysed human PDAC gene expression datasets. Results were corroborated by the analysis of the small ubiquitin-like modifier (SUMO) pathway in a large PDAC cohort using immunohistochemistry. A SUMO inhibitor was used and characterised using human and murine two-dimensional, organoid and in vivo models of PDAC.
Results: We observed that MYC is connected to the SUMOylation machinery in PDAC. Components of the SUMO pathway characterise a PDAC subtype with a dismal prognosis and we provide evidence that hyperactivation of MYC is connected to an increased sensitivity to pharmacological SUMO inhibition.
Conclusion: SUMO inhibitor-based therapies should be further developed for an aggressive PDAC subtype.
Two methods for the fast, fragment-based combinatorial molecule assembly were developed. The software COLIBREE® (Combinatorial Library Breeding) generates candidate structures from scratch, based on stochastic optimization [1]. Result structures of a COLIBREE design run are based on a fixed scaffold and variable linkers and side-chains. Linkers representing virtual chemical reactions and side-chain building blocks obtained from pseudo-retrosynthetic dissection of large compound databases are exchanged during optimization. The process of molecule design employs a discrete version of Particle Swarm Optimization (PSO) [2]. Assembled compounds are scored according to their similarity to known reference ligands. Distance to reference molecules is computed in the space of the topological pharmacophore descriptor CATS [3]. In a case study, the approach was applied to the de novo design of potential peroxisome proliferator-activated receptor (PPAR gamma) selective agonists. In a second approach, we developed the formal grammar Reaction-MQL [4] for the in silico representation and application of chemical reactions. Chemical transformation schemes are defined by functional groups participating in known organic reactions. The substructures are specified by the linear Molecular Query Language (MQL) [5]. The developed software package contains a parser for Reaction-MQL-expressions and enables users to design, test and virtually apply chemical reactions. The program has already been used to create combinatorial libraries for virtual screening studies. It was also applied in fragmentation studies with different sets of retrosynthetic reactions and various compound libraries.
Poster presentation: Introduction The ability of neurons to emit different firing patterns is considered relevant for neuronal information processing. In dopaminergic neurons, prominent patterns include highly regular pacemakers with separate spikes and stereotyped intervals, processes with repetitive bursts and partial regularity, and irregular spike trains with nonstationary properties. In order to model and quantify these processes and the variability of their patterns with respect to pharmacological and cellular properties, we aim to describe the two dimensions of burstiness and regularity in a single model framework. Methods We present a stochastic spike train model in which the degree of burstiness and the regularity of the oscillation are described independently and with two simple parameters. In this model, a background oscillation with independent and normally distributed intervals gives rise to Poissonian spike packets with a Gaussian firing intensity. The variability of inter-burst intervals and the average number of spikes in each burst indicate regularity and burstiness, respectively. These parameters can be estimated by fitting the model to the autocorrelograms. This allows to assign every spike train a position in the two-dimensional space described by regularity and burstiness and thus, to investigate the dependence of the firing patterns on different experimental conditions. Finally, burst detection in single spike trains is possible within the model because the parameter estimates determine the appropriate bandwidth that should be used for burst identification. Results and Discussion We applied the model to a sample data set obtained from dopaminergic substantia nigra and ventral tegmental area neurons recorded extracellularly in vivo and studied differences between the firing activity of dopaminergic neurons in wildtype and K-ATP channel knock-out mice. The model is able to represent a variety of discharge patterns and to describe changes induced pharmacologically. It provides a simple and objective classification scheme for the observed spike trains into pacemaker, irregular and bursty processes. In addition to the simple classification, changes in the parameters can be studied quantitatively, also including the properties related to bursting behavior. Interestingly, the proposed algorithm for burst detection may be applicable also to spike trains with nonstationary firing rates if the remaining parameters are unaffected. Thus, the proposed model and its burst detection algorithm can be useful for the description and investigation of neuronal firing patterns and their variability with cellular and experimental conditions.
An integrative correlation of myopathology, phenotype and genotype in late onset Pompe disease
(2019)
Aims: Pompe disease is caused by pathogenic mutations in the alpha 1,4‐glucosidase (GAA) gene and in patients with late onset Pome disease (LOPD), genotype–phenotype correlations are unpredictable. Skeletal muscle pathology includes glycogen accumulation and altered autophagy of various degrees. A correlation of the muscle morphology with clinical features and the genetic background in GAA may contribute to the understanding of the phenotypic variability.
Methods: Muscle biopsies taken before enzyme replacement therapy were analysed from 53 patients with LOPD. On resin sections, glycogen accumulation, fibrosis, autophagic vacuoles and the degree of muscle damage (morphology‐score) were analysed and the results were compared with clinical findings. Additional autophagy markers microtubule‐associated protein 1A/1B‐light chain 3, p62 and Bcl2‐associated athanogene 3 were analysed on cryosections from 22 LOPD biopsies.
Results: The myopathology showed a high variability with, in most patients, a moderate glycogen accumulation and a low morphology‐score. High morphology‐scores were associated with increased fibrosis and autophagy highlighting the role of autophagy in severe stages of skeletal muscle damage. The morphology‐score did not correlate with the patient's age at biopsy, disease duration, nor with the residual GAA enzyme activity or creatine‐kinase levels. In 37 patients with LOPD, genetic analysis identified the most frequent mutation, c.‐32‐13T>G, in 95%, most commonly in combination with c.525delT (19%). No significant correlation was found between the different GAA genotypes and muscle morphology type.
Conclusions: Muscle morphology in LOPD patients shows a high variability with, in most cases, moderate pathology. Increased pathology is associated with more fibrosis and autophagy.
DNA methylation was shown previously to be a crucial mechanism responsible for transcriptional deregulation in the pathogenesis of classical Hodgkin lymphoma (cHL). To identify epigenetically inactivated miRNAs in cHL, we have analyzed the set of miRNAs downregulated in cHL cell lines using bisulfite pyrosequencing. We focused on miRNAs with promoter regions located within or <1000 bp from a CpG island. Most promising candidate miRNAs were further studied in primary Hodgkin and Reed-Sternberg (HRS) cells obtained by laser capture microdissection. Last, to evaluate the function of identified miRNAs, we performed a luciferase reporter assay to confirm miRNA: mRNA interactions and therefore established cHL cell lines with stable overexpression of selected miRNAs for proliferation tests. We found a significant reverse correlation between DNA methylation and expression levels of mir-339-3p, mir-148a-3p, mir-148a-5p and mir-193a-5 demonstrating epigenetic regulation of these miRNAs in cHL cell lines. Moreover, we demonstrated direct interaction between miR-148a-3p and IL15 and HOMER1 transcripts as well as between mir-148a-5p and SUB1 and SERPINH1 transcripts. Furthermore, mir-148a overexpression resulted in reduced cell proliferation in the KM-H2 cell line. In summary, we report that mir-148a is a novel tumor suppressor inactivated in cHL and that epigenetic silencing of miRNAs is a common phenomenon in cHL.
An iridium(III/IV/V) redox series featuring a terminal imido complex with triplet ground state
(2018)
The iridium(III/IV/V) imido redox series [Ir(NtBu){N(CHCHPtBu2)2}]0/+/2+ was synthesized and examined spectroscopically, magnetically, crystallographically and computationally. The monocationic iridium(IV) imide exhibits an electronic doublet ground state with considerable ‘imidyl’ character as a result of covalent Ir–NtBu bonding. Reduction gives the neutral imide [Ir(NtBu){N(CHCHPtBu2)2}] as the first example of an iridium complex with a triplet ground state. Its reactivity with respect to nitrene transfer to selected electrophiles (CO2) and nucleophiles (PMe3), respectively, is reported.