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Sonstige beteiligte Institutionen
- Agricultural Center, BASF SE, 67117 Limburgerhof, Germany (1)
- Center of Excellence for Science and Technology - Integration of Mediterranean region (STIM), Faculty of Science, University of Split, Poljička cesta 35, 2100 Split, Croatia (1)
- Departamento de Química, Facultad de Ciencias, Universidad Autónoma de Madrid, 28049 Madrid, Spain (1)
- Department of Chemistry, Humboldt Universität zu Berlin, Brook-Taylor-Strasse 2, 12489 Berlin, Germany (1)
- Institute of Organic Chemistry and Center for Molecular Biosciences Innsbruck, CMBI, Leopold-Franzens University Innsbruck, Austria (1)
- Istituto di Chimica dei Composti Organometallici (ICCOM–CNR), Area della Ricerca del CNR, Via Moruzzi 1, I-56124 Pisa, Italy. (1)
SLC2A3 encodes the predominantly neuronal glucose transporter 3 (GLUT3), which facilitates diffusion of glucose across plasma membranes. The human brain depends on a steady glucose supply for ATP generation, which consequently fuels critical biochemical processes, such as axonal transport and neurotransmitter release. Besides its role in the central nervous system, GLUT3 is also expressed in nonneural organs, such as the heart and white blood cells, where it is equally involved in energy metabolism. In cancer cells, GLUT3 overexpression contributes to the Warburg effect by answering the cell's increased glycolytic demands. The SLC2A3 gene locus at chromosome 12p13.31 is unstable and prone to non‐allelic homologous recombination events, generating multiple copy number variants (CNVs) of SLC2A3 which account for alterations in SLC2A3 expression. Recent associations of SLC2A3 CNVs with different clinical phenotypes warrant investigation of the potential influence of these structural variants on pathomechanisms of neuropsychiatric, cardiovascular, and immune diseases. In this review, we accumulate and discuss the evidence how SLC2A3 gene dosage may exert diverse protective or detrimental effects depending on the pathological condition. Cellular states which lead to increased energetic demand, such as organ development, proliferation, and cellular degeneration, appear particularly susceptible to alterations in SLC2A3 copy number. We conclude that better understanding of the impact of SLC2A3 variation on disease etiology may potentially provide novel therapeutic approaches specifically targeting this GLUT.
In the last few years, monoclonal antibodies (mAbs) such as elotuzumab and daratutumab have brought the treatment of multiple myeloma (MM) into the new era of immunotherapy. More recently, chimeric antigen receptor (CAR) modified T cell, a novel cellular immunotherapy, has been developed for treatment of relapsed/refractory (RR) MM, and early phase clinical trials have shown promising efficacy of CAR T cell therapy. Many patients with end stage RRMM regard CAR T cell therapy as their “last chance” and a “hope of cure”. However, severe adverse events (AEs) and even toxic death related to CAR T cell therapy have been observed. The management of AEs related to CAR T cell therapy represents a new challenge, as the pathophysiology is not fully understood and there is still no well-established standard of management. With regard to CAR T cell associated toxicities in MM, in this review, we will provide an overview of experience from clinical trials, pathophysiology, and management strategies.
Excitation energy transport in DNA modelled by multi-chromophoric field-induced surface hopping
(2020)
Absorption of ultraviolet light is known as a major source of carcinogenic mutations of DNA. The underlying processes of excitation energy dissipation are yet not fully understood. In this work we provide a new and generally applicable route for studying the excitation energy transport in multi-chromophoric complexes at an atomistic level. The surface-hopping approach in the frame of the extended Frenkel exciton model combined with QM/MM techniques allowed us to simulate the photodynamics of the alternating (dAdT)10 : (dAdT)10 double-stranded DNA. In accordance with recent experiments, we find that the excited state decay is multiexponential, involving a long and a short component which are due to two distinct mechanisms: formation of long-lived delocalized excitonic and charge transfer states vs. ultrafast decaying localized states resembling those of the bare nucleobases. Our simulations explain all stages of the ultrafast photodynamics including initial photoexcitation, dynamical evolution out of the Franck-Condon region, excimer formation and nonradiative relaxation to the ground state.
The predicted 80 open reading frames (ORFs) of herpes simplex virus 1 (HSV-1) have been intensively studied for decades. Here, we unravel the complete viral transcriptome and translatome during lytic infection with base-pair resolution by computational integration of multi-omics data. We identify a total of 201 transcripts and 284 ORFs including all known and 46 novel large ORFs. This includes a so far unknown ORF in the locus deleted in the FDA-approved oncolytic virus Imlygic. Multiple transcript isoforms expressed from individual gene loci explain translation of the vast majority of ORFs as well as N-terminal extensions (NTEs) and truncations. We show that NTEs with non-canonical start codons govern the subcellular protein localization and packaging of key viral regulators and structural proteins. We extend the current nomenclature to include all viral gene products and provide a genome browser that visualizes all the obtained data from whole genome to single-nucleotide resolution. Here, using computational integration of multi-omics data, the authors provide a detailed transcriptome and translatome of herpes simplex virus 1 (HSV-1), including previously unidentified ORFs and N-terminal extensions. The study also provides a HSV-1 genome browser and should be a valuable resource for further research.
We investigated the influence of social status on behavior in a modified dictator game (DG). Since the DG contains an inherent dominance gradient, we examined the relationship between dictator decisions and recipient status, which was operationalized by three social identities and an artificial intelligence (AI). Additionally, we examined the predictive value of social dominance orientation (SDO) on the behavior of dictators toward the different social and non-social hierarchical recipients. A multilevel model analysis showed that recipients with the same status as the dictator benefited the most and the artificial intelligence the least. Furthermore, SDO, regardless of social status, predicted behavior toward recipients in such a way that higher dominance was associated with lower dictator offers. In summary, participants treated other persons of higher and lower status equally, those of equal status better and, above all, an algorithm worst. The large proportion of female participants and the limited variance of SDO should be taken into account with regard to the results of individual differences in SDO.
Reduced function of the serotonin transporter (SERT) is associated with increased susceptibility to anxiety and depression and with type-2 diabetes, which is especially true in older women. Preference for a “Western diet” (WD), enriched with saturated fat, cholesterol, and sugars, may aggravate these conditions. In previous studies, decreased glucose tolerance, central and peripheral inflammation, dyslipidemia, emotional, cognitive, and social abnormalities were reported in WD-fed young female mice. We investigated the metabolic, molecular, and behavioral changes associated with a 3-week-long dietary regime of either the WD or control diet in 12-month-old female mice with three different Sert genotypes: homozygous (Slc6a4) gene knockout (Sert\(^{−/−}\): KO), heterozygous (Sert\(^{+/−}\): HET), or wild-type mice (Sert\(^{+/+}\): WT). In the WT-WD and KO-WD groups, but not in HET-WD-fed mice, most of changes induced by the WD paralleled those found in the younger mice, including brain overexpression of inflammatory marker Toll-like receptor 4 (Tlr4) and impaired hippocampus-dependent performance in the marble test. However, the 12-month-old female mice became obese. Control diet KO mice exhibited impaired hippocampal-dependent behaviors, increased brain expression of the serotonin receptors Htr2c and Htr1b, as well as increased Tlr4 and mitochondrial regulator, peroxisome proliferator-activated receptor gamma-coactivator-1a (Ppargc1a). Paradoxically, these, and other changes, were reversed in KO-WD mutants, suggesting a complex interplay between Sert deficiency and metabolic factors as well as potential compensatory molecular mechanisms that might be disrupted by the WD exposure. Most, but not all, of the changes in gene expression in the brain and liver of KO mice were not exhibited by the HET mice fed with either diet. Some of the WD-induced changes were similar in the KO-WD and HET-WD-fed mice, but the latter displayed a “rescued” phenotype in terms of diet-induced abnormalities in glucose tolerance, neuroinflammation, and hippocampus-dependent performance. Thus, complete versus partial Sert inactivation in aged mice results in distinct metabolic, molecular, and behavioral consequences in response to the WD. Our findings show that Sert\(^{+/−}\) mice are resilient to certain environmental challenges and support the concept of heterosis as evolutionary adaptive mechanism.
The effect of non-personalised tips on the continued use of self-monitoring mHealth applications
(2020)
Chronic tinnitus, the perception of a phantom sound in the absence of corresponding stimulus, is a condition known to affect patients' quality of life. Recent advances in mHealth have enabled patients to maintain a ‘disease journal’ of ecologically-valid momentary assessments, improving patients' own awareness of their disease while also providing clinicians valuable data for research. In this study, we investigate the effect of non-personalised tips on patients' perception of tinnitus, and on their continued use of the application. The data collected from the study involved three groups of patients that used the app for 16 weeks. Groups A & Y were exposed to feedback from the start of the study, while group B only received tips for the second half of the study. Groups A and Y were run by different supervisors and also differed in the number of hospital visits during the study. Users of Group A and B underwent assessment at baseline, mid-study, post-study and follow-up, while users of group Y were only assessed at baseline and post-study. It is seen that the users in group B use the app for longer, and also more often during the day. The answers of the users to the Ecological Momentary Assessments are seen to form clusters where the degree to which the tinnitus distress depends on tinnitus loudness varies. Additionally, cluster-level models were able to predict new unseen data with better accuracy than a single global model. This strengthens the argument that the discovered clusters really do reflect underlying patterns in disease expression.
Macrophages are key players of the innate immune system that can roughly be divided into the pro-inflammatory M1 type and the anti-inflammatory, pro-healing M2 type. While a transient initial pro-inflammatory state is helpful, a prolonged inflammation deteriorates a proper healing and subsequent regeneration. One promising strategy to drive macrophage polarization by biomaterials is precise control over biomaterial geometry. For regenerative approaches, it is of particular interest to identify geometrical parameters that direct human macrophage polarization. For this purpose, we advanced melt electrowriting (MEW) towards the fabrication of fibrous scaffolds with box-shaped pores and precise inter-fiber spacing from 100 μm down to only 40 μm. These scaffolds facilitate primary human macrophage elongation accompanied by differentiation towards the M2 type, which was most pronounced for the smallest pore size of 40 μm. These new findings can be important in helping to design new biomaterials with an enhanced positive impact on tissue regeneration.
Comparison of moving and fixed basis sets for nonadiabatic quantum dynamics at conical intersections
(2020)
We assess the performance of two different types of basis sets for nonadiabatic quantum dynamics at conical intersections. The basis sets of both types are generated using Ehrenfest trajectories of nuclear coherent states. These trajectories can either serve as a moving (time-dependent) basis or be employed to sample a fixed (time-independent) basis. We demonstrate on the example of two-state two-dimensional and three-state five-dimensional models that both basis set types can yield highly accurate results for population transfer at intersections, as compared with reference quantum dynamics. The details of wave packet evolutions are discussed for the case of the two-dimensional model. The fixed basis is found to be superior to the moving one in reproducing nonlocal spreading and maintaining correct shape of the wave packet upon time evolution. Moreover, for the models considered, the fixed basis set outperforms the moving one in terms of computational efficiency.
Comparison of moving and fixed basis sets for nonadiabatic quantum dynamics at conical intersections
(2020)
We assess the performance of two different types of basis sets for nonadiabatic quantum dynamics at conical intersections. The basis sets of both types are generated using Ehrenfest trajectories of nuclear coherent states. These trajectories can either serve as a moving (time-dependent) basis or be employed to sample a fixed (time-independent) basis. We demonstrate on the example of two-state two-dimensional and three-state five-dimensional models that both basis set types can yield highly accurate results for population transfer at intersections, as compared with reference quantum dynamics. The details of wave packet evolutions are discussed for the case of the two-dimensional model. The fixed basis is found to be superior to the moving one in reproducing true nonlocal spreading and maintaining correct shape of the wave packet upon time evolution. Moreover, for the models considered, the fixed basis set outperforms the moving one in terms of computational efficiency.
Autonomous cars and artificial intelligence that beats humans in Jeopardy or Go are glamorous examples of the so-called Second Machine Age that involves the automation of cognitive tasks [Brynjolfsson and McAfee, 2014]. However, the larger impact in terms of increasing the efficiency of industry and the productivity of society might come from computers that improve or take over business decisions by using large amounts of available data. This impact may even exceed that of the First Machine Age, the industrial revolution that started with James Watt’s invention of an efficient steam engine in the late eighteenth century. Indeed, the prevalent phrase that calls data “the new oil” indicates the growing awareness of data’s importance. However, many companies, especially those in the manufacturing and traditional service industries, still struggle to increase productivity using the vast amounts of
data [for Economic Co-operation and Development, 2018].
One reason for this struggle is that companies stick with a traditional way of using data for decision support in operations management that is not well suited to automated decision-making. In traditional inventory and capacity management, some data – typically just historical demand data – is used to estimate a model that makes predictions about uncertain planning parameters, such as customer demand. The planner then has two tasks: to adjust the prediction with respect to additional information that was not part of the data but still might influence demand and to take the remaining uncertainty into account and determine a safety buffer based on the underage and overage costs. In the best case, the planner determines the safety buffer based on an optimization model that takes the costs and the distribution of historical forecast errors into account; however, these decisions are usually based on a planner’s experience and intuition, rather than on solid data analysis.
This two-step approach is referred to as separated estimation and optimization (SEO). With SEO, using more data and better models for making the predictions would improve only the first step, which would still improve decisions but would not automize (and, hence, revolutionize) decision-making. Using SEO is like using a stronger horse to pull the plow: one still has to walk behind.
The real potential for increasing productivity lies in moving from predictive to prescriptive approaches, that is, from the two-step SEO approach, which uses predictive models in the estimation step, to a prescriptive approach, which integrates the optimization problem with the estimation of a model that then provides a direct functional relationship between the data and the decision. Following Akcay et al. [2011], we refer to this integrated approach as joint estimation-optimization (JEO). JEO approaches prescribe decisions, so they can automate the decision-making process. Just as the steam engine replaced manual work, JEO approaches replace cognitive work.
The overarching objective of this dissertation is to analyze, develop, and evaluate new ways for how data can be used in making planning decisions in operations management to unlock the potential for increasing productivity. In doing so, the thesis comprises five self-contained research articles that forge the bridge from predictive to prescriptive approaches. While the first article focuses on how sensitive data like condition data from machinery can be used to make predictions of spare-parts demand, the remaining articles introduce, analyze, and discuss prescriptive approaches to inventory and capacity management.
All five articles consider approach that use machine learning and data in innovative ways to improve current approaches to solving inventory or capacity management problems. The articles show that, by moving from predictive to prescriptive approaches, we can improve data-driven operations management in two ways: by making decisions more accurate and by automating decision-making. Thus, this dissertation provides examples of how digitization and the Second Machine Age can change decision-making in companies to increase efficiency and productivity.
Here, we assessed whether 36 single nucleotide polymorphisms (SNPs) within the TNFSF4 and MAPKAPK2 loci influence the risk of developing invasive aspergillosis (IA). We conducted a two-stage case control study including 911 high-risk patients diagnosed with hematological malignancies that were ascertained through the aspBIOmics consortium. The meta-analysis of the discovery and replication populations revealed that carriers of the TNFSF4\(_{rs7526628T/T}\) genotype had a significantly increased risk of developing IA (p = 0.00022). We also found that carriers of the TNFSF4\(_{rs7526628T}\) allele showed decreased serum levels of TNFSF14 protein (p = 0.0027), and that their macrophages had a decreased fungicidal activity (p = 0.048). In addition, we observed that each copy of the MAPKAPK2\(_{rs12137965G}\) allele increased the risk of IA by 60% (p = 0.0017), whereas each copy of the MAPKAPK2\(_{rs17013271T}\) allele was estimated to decrease the risk of developing the disease (p = 0.0029). Mechanistically, we found that carriers of the risk MAPKAPK2\(_{rs12137965G}\) allele showed increased numbers of CD38+IgM-IgD- plasmablasts in blood (p = 0.00086), whereas those harboring two copies of the allele had decreased serum concentrations of thymic stromal lymphopoietin (p = 0.00097). Finally, we also found that carriers of the protective MAPKAPK2\(_{rs17013271T}\) allele had decreased numbers of CD27-IgM-IgD- B cells (p = 0.00087) and significantly lower numbers of CD14+ and CD14+CD16- cells (p = 0.00018 and 0.00023). Altogether, these results suggest a role of the TNFSF4 and MAPKAPK2 genes in determining IA risk.
Five compounds containing boron–boron multiple bonds are shown to undergo hydrophosphination reactions with diphenylphosphine in the absence of a catalyst. With diborenes, the products obtained are highly dependent on the substitution pattern at the boron atoms, with both 1,1- and 1,2- hydrophosphinations observed. With a symmetrical diboryne, 1,2-hydrophosphination yields a hydro(phosphino)diborene. The different mechanistic pathways for the hydrophosphination of diborenes are rationalised with the aid of density functional theory calculations.
RNA aptamers form compact tertiary structures and bind their ligands in specific binding sites. Fluorescence-based strategies reveal information on structure and dynamics of RNA aptamers. Here we report the incorporation of the universal emissive nucleobase analog 4-cyanoindole into the fluorogenic RNA aptamer Chili, and its application as a donor for supramolecular FRET to bound ligands DMHBI+ or DMHBO+. The photophysical properties of the new nucleobase-ligand-FRET pair revealed structural restraints for the overall RNA aptamer organization and identified nucleotide positions suitable for FRET-based readout of ligand binding. This strategy is generally suitable for binding site mapping and may also be applied for responsive aptamer devices.
Die Reaktion zwischen Aryl‐ und Amino(dihydro)boranen und Dibora[2]ferrocenophan 1 führt zur Bildung von 1,3‐trans‐Dihydrotriboranen durch formale Hydrierung und Insertion eines Borylens in die B=B Doppelbindung. Die Aryltriboran‐Derivate unterliegen einer reversiblen Photoisomerisierung zugunsten eines cis‐1,2‐μ‐H‐3‐Hydrotriborans, während eine Hydridabstraktion zu kationischen Triboranen führt, welche die ersten doppelt basenstabilisierten B\(_3\)H\(_4\)\(^+\)‐Analoga darstellen.
The reaction of aryl‐ and amino(dihydro)boranes with dibora[2]ferrocenophane 1 leads to the formation 1,3‐trans ‐dihydrotriboranes by formal hydrogenation and insertion of a borylene unit into the B=B bond. The aryltriborane derivatives undergo reversible photoisomerization to the cis ‐1,2‐μ‐H‐3‐hydrotriboranes, while hydride abstraction affords cationic triboranes, which represent the first doubly base‐stabilized B3H4\(^+\) analogues.
Whereas the reduction of N-heterocyclic carbene (NHC)-stabilised cymantrenyldibromoboranes, (NHC)BBr\(_2\)Cym, in benzene results in formation of the corresponding diborenes (NHC)\(_2\)B\(_2\)Cym\(_2\), a change of solvent to THF yields a borylene of the form (NHC)\(_2\)BCym, stabilised through its boratafulvene resonance form.
Identification of articular cartilage progenitor cells (ACPCs) has opened up new opportunities for cartilage repair. These cells may be used as alternatives for or in combination with mesenchymal stromal cells (MSCs) in cartilage engineering. However, their potential needs to be further investigated, since only a few studies have compared ACPCs and MSCs when cultured in hydrogels. Therefore, in this study, we compared chondrogenic differentiation of equine ACPCs and MSCs in agarose constructs as monocultures and as zonally layered co-cultures under both normoxic and hypoxic conditions. ACPCs and MSCs exhibited distinctly differential production of the cartilaginous extracellular matrix (ECM). For ACPC constructs, markedly higher glycosaminoglycan (GAG) contents were determined by histological and quantitative biochemical evaluation, both in normoxia and hypoxia. Differential GAG production was also reflected in layered co-culture constructs. For both cell types, similar staining for type II collagen was detected. However, distinctly weaker staining for undesired type I collagen was observed in the ACPC constructs. For ACPCs, only very low alkaline phosphatase (ALP) activity, a marker of terminal differentiation, was determined, in stark contrast to what was found for MSCs. This study underscores the potential of ACPCs as a promising cell source for cartilage engineering.
Nearly all classes of coding and non-coding RNA undergo post-transcriptional modification including RNA methylation. Methylated nucleotides belong to the evolutionarily most conserved features of tRNA and rRNA.1,2 Many contemporary methyltransferases use the universal cofactor S-adenosylmethionine (SAM) as methyl group donor. This and other nucleotide-derived cofactors are considered as evolutionary leftovers from an RNA World, in which ribozymes may have catalysed essential metabolic reactions beyond self-replication.3 Chemically diverse ribozymes seem to have been lost in Nature, but may be reconstructed in the laboratory by in vitro selection. Here, we report a methyltransferase ribozyme that catalyses the site-specific installation of 1-methyladenosine (m1A) in a substrate RNA, utilizing O6-methylguanine (m6G) as a small-molecule cofactor. The ribozyme shows a broad RNA sequence scope, as exemplified by site-specific adenosine methylation in tRNAs. This finding provides fundamental insights into RNA’s catalytic abilities, serves a synthetic tool to install m1A in RNA, and may pave the way to in vitro evolution of other methyltransferase and demethylase ribozymes.
Deoxyribozymes (DNAzymes) are small, synthetic, single-stranded DNAs capable of catalysing chemical reactions, including RNA ligation. Herein, we report a novel class of RNA ligase deoxyribozymes that utilize 5’-adenylated RNA (5’-AppRNA) as the donor substrate, mimicking the activated intermediates of protein-catalyzed RNA ligation. Four new DNAzymes were identified by in vitro selection from an N40 random DNA library and were shown to catalyze the intermolecular linear RNA-RNA ligation via the formation of a native 3’-5’-phosphodiester linkage. The catalytic activity is distinct from previously described RNA-ligating deoxyribozymes. Kinetic analyses revealed the optimal incubation conditions for high ligation yields and demonstrated a broad RNA substrate scope. Together with the smooth synthetic accessibility of 5’-adenylated RNAs, the new DNA enzymes are promising tools for the protein-free synthesis of long RNAs, for example containing precious modified nucleotides or fluorescent labels for biochemical and biophysical investigations.