Nukleophile Kupfer-Vermittelte Radiofluorierung von L-Tryptophan-Derivaten

$^{18}$F-Labeled aromatic amino acids became more and more important for molecular imgaging withPositron Emission Tomography (PET). Several examples have emerged showing higherspecificity in imaging disorders in neurological processes or tumors. The essential amino acidtryptophan is an important precursor in the serotonergic system and the kynurenine pathway, reported to be of significance in the metabolism of some tumors. Therefore, $^{18}$F-labeled derivatives of tryptophan are of major interest for the investigation of neurological andoncological behavior via PET. In this work, new [$^{18}$F]fluorotryptophan derivatives were synthesized by a novel copper-mediated radiofluorination method which was also amenable to automation. In an initial step, the reactivity of the different substitution positions in the indole motif was examined using the copper-mediated radiofluorination. The highest reactivity was found in position 6; therefore, an appropriate precursor for the radiosynthesis of 6-[$^{18}$F]fluoro-Ltryptophan(6-[$^{18}$F]FTrp) was synthesized in a 6-step synthesis with 40 % overall yield. Using this precursor, the radiosynthesis was improved by using less concentrated base, a different drying method, other solvents and a new acidic hydrolysis. The overall radiochemical yield was 16 % within 110 min, an enantiomeric excess (e.e.) of 89 % and a molar radioactivity up to 240 GBq/$\mu$mol. In a next step, a new designed appropriate precursor for 5-[$^{18}$F]fluoro-L-tryptophan(5-[$^{18}$F]FTrp) was synthesized using protecting groups which are easier to hydrolyze. Furthermore, the copper-mediated radiofluorination was modified by using different alcoholic solvents. After studying several parameters of the new alcohol-enhanced method, the radiosynthesis of 5-[$^{18}$F]FTrp gave a radiochemical yield of 53 % in 105 min, an e.e. of >99 % and a molar radioactivity of up to 180 GBq/$\mu$mol. As last derivative, a precursor for 4-[$^{18}$F]fluoro-L-tryptophan (4-[$^{18}$F]FTrp) was synthesized and radiofluorinated using the same parameters as for 5-[$^{18}$F]FTrp. It was obtained in a RCY of 39 % whithin 104 min, an e.e. of >99 % and a molar radioactivity up to 95 GBq/$\mu$mol. The radiosyntheses of all three [$^{18}$F]FTrp derivatives were amenable to automation. They were thus produced in quantities sufficient for $\textit{in vivo}$ animal-PET studies in rats. Every [$^{18}$F]fluorotryptophan derivative showed a different $\textit{in vivo}$ behavior. In summary, a practical radiosynthesis for three $^{18}$F-labeled tryptophan-derivatives was established giving sufficient radiochemical yields and purities for $\textit{in vivo}$ investigations and the procedure shows adaptility for automation

Evidence of active oviposition avoidance to systemically applied imidacloprid in the Colorado potato beetle

Agricultural pests can develop behavioral resistance to insecticides by choosing to feed or oviposit on insecticide-free hosts. As young larvae have relatively low mobility, oviposition preferences from female adults may play a critical role in shaping the evolutionary trajectory of pest populations. While oviposition avoidance of insecticide-treated hosts was found in different agriculture pests, it remains unclear whether female adults actively choose to occupy insecticide-free hosts. To address this question, we investigated feeding and oviposition preferences between imidacloprid-treated and imidacloprid-free plants in the Colorado potato beetle, Leptinotarsa decemlineata Say, a major potato pest. We performed behavioral choice assays on two strains that differed in both fecundity and insecticide resistance. We found that one strain preferred to feed on the insecticide-free plants and that this preference is not innate. Meanwhile, the other strain chose plants for feeding and oviposition randomly. Further analyses of the moving patterns of the beetles suggested that the oviposition preference in the first strain is likely due to active learning

An inter-laboratory comparison demonstrates that [1H]-NMR metabolite fingerprinting is a robust technique for collaborative plant metabolomic data collection

In any metabolomics experiment, robustness and reproducibility of data collection is of vital importance. These become more important in collaborative studies where data is to be collected on multiple instruments. With minimisation of variance in sample preparation and instrument performance it is possible to elucidate even subtle differences in metabolite fingerprints due to genotype or biological treatment. In this paper we report on an inter laboratory comparison of plant derived samples by [1H]-NMR spectroscopy across five different sites and within those sites utilising instruments with different probes and magnetic field strengths of 9.4 T (400 MHz), 11.7 T (500 MHz) and 14.1 T (600 MHz). Whilst the focus of the study is on consistent data collection across laboratories, aspects of sample stability and the requirement for sample rotation within the NMR magnet are also discussed. Comparability of the datasets from participating laboratories was exceptionally good and the data were amenable to comparative analysis by multivariate statistics. Field strength differences can be adjusted for in the data pre-processing and multivariate analysis demonstrating that [1H]-NMR fingerprinting is the ideal technique for large scale plant metabolomics data collection requiring the participation of multiple laboratories

Competition-based model of pheromone component ratio detection in the moth

For some moth species, especially those closely interrelated and sympatric, recognizing a specific pheromone component concentration ratio is essential for males to successfully locate conspecific females. We propose and determine the properties of a minimalist competition-based feed-forward neuronal model capable of detecting a certain ratio of pheromone components independently of overall concentration. This model represents an elementary recognition unit for the ratio of binary mixtures which we propose is entirely contained in the macroglomerular complex (MGC) of the male moth. A set of such units, along with projection neurons (PNs), can provide the input to higher brain centres. We found that (1) accuracy is mainly achieved by maintaining a certain ratio of connection strengths between olfactory receptor neurons (ORN) and local neurons (LN), much less by properties of the interconnections between the competing LNs proper. An exception to this rule is that it is beneficial if connections between generalist LNs (i.e. excited by either pheromone component) and specialist LNs (i.e. excited by one component only) have the same strength as the reciprocal specialist to generalist connections. (2) successful ratio recognition is achieved using latency-to-first-spike in the LN populations which, in contrast to expectations with a population rate code, leads to a broadening of responses for higher overall concentrations consistent with experimental observations. (3) when longer durations of the competition between LNs were observed it did not lead to higher recognition accuracy

A new procyanidin B from Campylospermum zenkeri (Ochnaceae) and antiplasmodial activity of two derivatives of (±)-serotobenine

Phytochemical investigation of the stem bark of Campylospermum zenkeri led to the isolation of five known compounds: (Z,Z)-9,12-octadecadienoic acid (1), serotobenine (2), agathisflavone (3), lophirone A (4) and lophirone F (5), together with a new derivative of procyanidin B, a catechin dimer named zenkerinol (6). Serotobenine (2) is structurally related to decursivine which shows moderate activity against D6 and W2 strains of Plasmodium falciparum. For a better understanding of structure-activity relationships, three new semi-synthetic derivatives of serotobenine (2) have been prepared. These are: serotobenine monopropionate (2a), serotobenine monopivalate (2b) and serotobenine cyclohexyl ether (2c) respectively. Two of them (2a) and (2b), were evaluated for their antiplasmodial activity against P. falciparum 3D7 strain in a parasite lactate-dehydrogenase (pLDH) assay. Compound 2b was more active than compound 2a based on their IC50 values (36.6 and 123 μM, respectively)

Scalable high-repetition-rate sub-half-cycle terahertz pulses from spatially indirect interband transitions

Intense phase-locked terahertz (THz) pulses are the bedrock of THz lightwave electronics, where the carrier field creates a transient bias to control electrons on sub-cycle time scales. Key applications such as THz scanning tunnelling microscopy or electronic devices operating at optical clock rates call for ultimately short, almost unipolar waveforms, at megahertz (MHz) repetition rates. Here, we present a flexible and scalable scheme for the generation of strong phase-locked THz pulses based on shift currents in type-II-aligned epitaxial semiconductor heterostructures. The measured THz waveforms exhibit only 0.45 optical cycles at their centre frequency within the full width at half maximum of the intensity envelope, peak fields above 1.1 kV cm−1 and spectral components up to the mid-infrared, at a repetition rate of 4 MHz. The only positive half-cycle of this waveform exceeds all negative half-cycles by almost four times, which is unexpected from shift currents alone. Our detailed analysis reveals that local charging dynamics induces the pronounced positive THz-emission peak as electrons and holes approach charge neutrality after separation by the optical pump pulse, also enabling ultrabroadband operation. Our unipolar emitters mark a milestone for flexibly scalable, next-generation high-repetition-rate sources of intense and strongly asymmetric electric field transients

Subcellular localization of PD‐L1 and cell‐cycle‐dependent expression of nuclear PD‐L1 variants: implications for head and neck cancer cell functions and therapeutic efficacy

The programmed cell death 1 ligand 1 (PD-L1)/programmed cell death protein 1 (PD-1) axis is primarily associated with immunosuppression in cytotoxic T lymphocytes (CTLs). However, mounting evidence is supporting the thesis that PD-L1 not only functions as a ligand but mediates additional cellular functions in tumor cells. Moreover, it has been demonstrated that PD-L1 is not exclusively localized at the cellular membrane. Subcellular fractionation revealed the presence of PD-L1 in various cellular compartments of six well-characterized head and neck cancer (HNC) cell lines, including the nucleus. Via Western blotting, we detected PD-L1 in its well-known glycosylated/deglycosylated state at 40–55 kDa. In addition, we detected previously unknown PD-L1 variants with a molecular weight at approximately 70 and > 150 kDa exclusively in nuclear protein fractions. These in vitro findings were confirmed with primary tumor samples from head and neck squamous cell carcinoma (HNSCC) patients. Furthermore, we demonstrated that nuclear PD-L1 variant expression is cell-cycle-dependent. Immunofluorescence staining of PD-L1 in different cell cycle phases of synchronized HNC cells supported these observations. Mechanisms of nuclear PD-L1 trafficking remain less understood; however, proximity ligation assays showed a cell-cycle-dependent interaction of the cytoskeletal protein vimentin with PD-L1, whereas vimentin could serve as a potential shuttle for nuclear PD-L1 transportation. Mass spectrometry after PD-L1 co-immunoprecipitation, followed by gene ontology analysis, indicated interaction of nuclear PD-L1 with proteins involved in DNA remodeling and messenger RNA (mRNA) splicing. Our results in HNC cells suggest a highly complex regulation of PD-L1 and multiple tumor cell-intrinsic functions, independent of immune regulation. These observations bear significant implications for the therapeutic efficacy of immune checkpoint inhibition

Genomic correlates of glatiramer acetate adverse cardiovascular effects lead to a novel locus mediating coronary risk

Glatiramer acetate is used therapeutically in multiple sclerosis but also known for adverse effects including elevated coronary artery disease (CAD) risk. The mechanisms underlying the cardiovascular side effects of the medication are unclear. Here, we made use of the chromosomal variation in the genes that are known to be affected by glatiramer treatment. Focusing on genes and gene products reported by drug-gene interaction database to interact with glatiramer acetate we explored a large meta-analysis on CAD genome-wide association studies aiming firstly, to investigate whether variants in these genes also affect cardiovascular risk and secondly, to identify new CAD risk genes. We traced association signals in a 200-kb region around genomic positions of genes interacting with glatiramer in up to 60 801 CAD cases and 123 504 controls. We validated the identified association in additional 21 934 CAD cases and 76 087 controls. We identified three new CAD risk alleles within the TGFB1 region on chromosome 19 that independently affect CAD risk. The lead SNP rs12459996 was genome-wide significantly associated with CAD in the extended meta-analysis (odds ratio 1.09, p = 1.58×10-12). The other two SNPs at the locus were not in linkage disequilibrium with the lead SNP and by a conditional analysis showed p-values of 4.05 × 10-10 and 2.21 × 10-6. Thus, studying genes reported to interact with glatiramer acetate we identified genetic variants that concordantly with the drug increase the risk of CAD. Of these, TGFB1 displayed signal for association. Indeed, the gene has been associated with CAD previously in both in vivo and in vitro studies. Here we establish genome-wide significant association with CAD in large human samples.This work was supported by grants from the Fondation Leducq (CADgenomics: Understanding CAD Genes, 12CVD02), the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (e:AtheroSysMed, grant 01ZX1313A-2014 and SysInflame, grant 01ZX1306A), and the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no HEALTH-F2-2013-601456 (CVgenes-at-target). Further grants were received from the DFG as part of the Sonderforschungsbereich CRC 1123 (B2). T.K. was supported by a DZHK Rotation Grant. I.B. was supported by the Deutsche Forschungsgemeinschaft (DFG) cluster of excellence ‘Inflammation at Interfaces’. F.W.A. is supported by a Dekker scholarship-Junior Staff Member 2014T001 - Netherlands Heart Foundation and UCL Hospitals NIHR Biomedical Research Centre

Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research

No abstract available

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations