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The field of liquid biopsy has seen extensive growth in recent decades, making it one of the most promising areas in molecular diagnostics. Circulating cell-free DNA (ccfDNA) especially is used as an analyte in a growing number of diagnostic assays. These assays require specified preanalytical workflows delivering ccfDNA in qualities and quantities that facilitate correct and reliable results. As each step and component used in the preanalytical process has the potential to influence the assay sensitivity and other performance characteristics, it is key to find an unbiased experimental setup to test these factors in diagnostic or research laboratories. We defined one such setup by using blood from healthy subjects and commercially available products for blood collection, spike-in material, ccfDNA isolation, and qPCR assays. As the primary read-out, we calculated the probit model-based LOD95 (limit of detection of the 95 th percentile) from the qPCR assay results. In a proof of principle study we tested two different but widely used blood ccfDNA profile stabilization technologies in blood collection tubes, the Cell-Free DNA BCT and the PAXgene Blood ccfDNA Tube. We tested assays for three different EGFR gene mutations and one BRAF gene mutation. The study design revealed differences in performance between the two tested technologies for all four mutations. In conclusion, we successfully established a blueprint for a test procedure capable of verifying and validating a liquid biopsy workflow from blood collection to the analytical result.

Radiological exposure scenarios involving large numbers of people require a rapid and high-throughput method to identify the unexposed, and those exposed to low- and high-dose radiation. Those with high-dose exposure, e.g., >2 Gy and depending on host characteristics, may develop severe hematological acute radiation syndrome (HARS), requiring hospitalization and treatment. Previously, we identified a set of genes that discriminated these clinically relevant groups. In the current work, we examined the utility of gene expression changes to classify 1,000 split blood samples into HARS severity scores of H0, H1 and H2–4, with the latter indicating likely hospitalization. In several previous radiation dose experiments, we determined that these HARS categories corresponded, respectively, to doses of 0 Gy (unexposed), 0.5 Gy and 5 Gy. The main purpose of this work was to assess the rapidity of blood sample processing using targeted next-generation sequencing (NGS). Peripheral blood samples from two healthy donors were X-ray irradiated in vitro and incubated at 37°C for 24 h. A total of 1,000 samples were evaluated by laboratory personnel blinded to the radiation dose. Changes in gene expression of FDXR, DDB2, POU2AF1 and WNT3 were examined with qRT-PCR as positive controls. Targeted NGS (TREX) was used on all samples for the same four genes. Agreement using both methods was almost 78%. Using NGS, all 1,000 samples were processed within 30 h. Classification of the HARS severity categories corresponding to radiation dose had an overall agreement ranging between 90–97%. Depending on the end point, either a combination of all genes or FDXR alone (H0 HARS or unexposed) provided the best classification. Using this optimized automated methodology, we assessed 100× more samples approximately three times faster compared to standard cytogenetic studies. We showed that a small set of genes, rather than a complex constellation of genes, provided robust positive (97%) and negative (97%) predictive values for HARS categories and radiation doses of 0, 0.5 and 5 Gy. The findings of this study support the potential utility of early radiation-induced gene expression changes for high-throughput biodosimetry and rapid identification of irradiated persons in need of hospitalization.

Background Long-read sequencing technologies enable resolution of structural variants (SV) and long-range genome assembly, but require high molecular weight (HMW) DNA of both high quantity and quality to produce optimal sequencing results. New DNA extraction methods have been developed but these have not been assessed for use in routine testing. The interlaboratory study described here tested four commonly used methods: Fire Monkey, Nanobind, Puregene and Genomic-tip with a reference cell line containing known chromosomal alterations. Samples were assessed with commonly applied approaches for evaluating DNA purity and integrity as well as a method based on linkage using digital PCR. Sequencing performance was evaluated and the impact of extraction method on structural variant calling investigated. Results All methods generally produced samples of acceptable purity although yield varied considerably between laboratories. Library preparation and sequencing were successful for all four methods, with Fire Monkey extracts achieving the highest N50 values, Genomic Tip giving the highest sequencing yields and Nanobind, the highest proportion of ultra-long reads (> 100 kb). The dPCR assay with duplexes at 100 kb and 150 kb distances was predictive of ultra-long reads and provides a more quantitative read-out (% linkage) than pulse-field gel electrophoresis (PFGE) which varied in performance between instruments and gel dyes. Neither PFGE nor dPCR were predictive of the proportion of short reads (< 10 kb). Coverage was a key factor in the success of SV calling, but this was dependent on SV caller. Megabase scale SVs were challenging to analyse with SV callers and required confirmation based on coverage plots and mapping of junction sequences, and the findings of earlier studies were only partially confirmed. Conclusions This study highlights some of the challenges of HMW DNA extraction as well as the need for robust sample QC metrics to ensure optimal sequencing yield and read length which in turn influence the success of SV analysis. dPCR approaches for DNA integrity showed potential but require further development. As long-read methods are increasingly applied in routine settings such as clinical testing laboratories, cellular reference samples with well-characterised SVs are recommended as controls for the full long-read sequencing workflow.

In cancer patients, circulating cell-free DNA (ccfDNA) can contain tumor-derived DNA (ctDNA), which enables noninvasive diagnosis, real-time monitoring, and treatment susceptibility testing. However, ctDNA fractions are highly variable, which challenges downstream applications. Therefore, established preanalytical work flows in combination with costefficient and reproducible reference materials for ccfDNA analyses are crucial for analytical validity and subsequently for clinical decision-making. We describe the efforts of the Innovative Medicines Initiative consortium CANCER-ID (http:// www.cancer-id.eu) for comparing different technologies for ccfDNA purification, quantification, and characterization in a multicenter setting. To this end, in-house generated mononucleosomal DNA (mnDNA) from lung cancer cell lines carrying known TP53 mutations was spiked in pools of plasma from healthy donors generated from 2 different blood collection tubes (BCTs). ccfDNA extraction was performed at 15 partner sites according to their respective routine practice. Downstream analysis of ccfDNA with respect to recovery, integrity, and mutation analysis was performed centralized at 4 different sites. We demonstrate suitability of mnDNA as a surrogate for ccfDNA as a process quality control from nucleic acid extraction to mutation detection. Although automated extraction protocols and quantitative PCR-based quantification methods yielded the most consistent and precise results, some kits preferentially recovered spiked mnDNA over endogenous ccfDNA. Mutated TP53 fragments derived from mnDNA were consistently detected using both next-generation sequencing-based deep sequencing and droplet digital PCR independently of BCT. This comprehensive multicenter comparison of ccfDNA preanalytical and analytical work flows is an important contribution to establishing evidence-based guidelines for clinically feasible (pre)analytical work flows.

The aim of our investigation was to answer the question how corporate entrepreneurship can be implemented successfully by one approach solely.Therefore, we analysed various factors and challenges regarding their impacts on the process of implementing corporate entrepreneurship. It could be noted that the successful implementation depends on various factors arising from the internal and external environment. Because of these environmental factors various problems and challenges for the successful implementation of corporate entrepreneurship arise. These challenges may not only hinder the implementation but also make it impossible to succeed if the company does not respond accordingly. At this point, it should be emphasised that the identification of every single challenge or problem is not possible due to the diversity, complexity and dynamics of the environment. Yet the most significant challenges arise from the outdated and entrenched structures and visions of a company and from the outdated business objectives and processes. In particular by this, company members are encouraged to stick to routine standard behaviour. Thereby, entrepreneurial behaviour is suppressed and thus the implementation of corporate entrepreneurship is blocked.In general, the challenges of the company consist therefore in establishing a basis for entrepreneurial behaviour and following (re-)activate this behaviour. To meet this challenge, the company can make use of different approaches. Generally, these are intended to encourage individuals through motivational design measures for entrepreneurial behaviour. Regarding the intention of the company, different approaches should be taken into consideration. Each approach has a different focus and different arrangements, hence impacts on different areas. At this point it must be stated that the recommendations presented do not have a universal validity due to the fact that each company faces different challenges and problems. However, each approach and its arrangements have different impacts on various areas, individuals and units. Thus, each approach affects other approaches directly or indirectly. Moreover, the arrangement of one approach can be a prerequisite for other approaches.Therefore, we claim that corporate entrepreneurship cannot successfully be implemented by one approach solely. We evaluate that focusing on solely one approach and trying to implement corporate entrepreneurship by it might result in even more challenges and problems as it can be seen in an expansion of authorities without the necessary structural changes. The interrelations of the approaches must be taken into consideration when trying to implement corporate entrepreneurship.Therefore, we propose that for each approach, several other approaches are necessary in order to successfully implement corporate entrepreneurship.

The genes of the gibberellin (GA) biosynthesis pathway in Gibberella fujikuroi are organized in a gene cluster consisting of at least seven genes. Here we report the cloning and characterization of smt, a gene encoding a membrane transporter of the major facilitator superfamily I, which is located next to the GA gene cluster. Since pathway-specific transporters occur frequently in prokaryotic and fungal antibiotic and toxin clusters, smt was thought to be involved in GA secretion. The gene is expressed in mycelium grown under GA-production conditions, but not when the GA biosynthesis is repressed by high amounts of ammonium. To investigate the function of SMT, gene replacement experiments were performed. The smt-mutants did not show any reduction in the GA yield; and gibberellic acid or its precursors did not influence the gene expression. However, sugar alcohols, such as myo-inositol, sorbitol and mannitol, induced the expression of smt. The results demonstrate that the smt gene does not play an essential role in biosynthesis and secretion of GAs in G. fujikuroi, despite the location adjacent to the GA gene cluster.

How fisheries will be impacted by climate change is far from understood. While some fish populations may be able to escape global warming via range shifts, they cannot escape ocean acidification (OA), an inevitable consequence of the dissolution of anthropogenic carbon dioxide (CO2) emissions in marine waters. How ocean acidification affects population dynamics of commercially important fish species is critical for adapting management practices of exploited fish populations. Ocean acidification has been shown to impair fish larvae’s sensory abilities, affect the morphology of otoliths, cause tissue damage and cause behavioural changes. Here, we obtain first experimental mortality estimates for Atlantic cod larvae under OA and incorporate these effects into recruitment models. End-of-century levels of ocean acidification (~1100 μatm according to the IPCC RCP 8.5) resulted in a doubling of daily mortality rates compared to present-day CO2 concentrations during the first 25 days post hatching (dph), a critical phase for population recruitment. These results were consistent under different feeding regimes, stocking densities and in two cod populations (Western Baltic and Barents Sea stock). When mortality data were included into Ricker-type stock-recruitment models, recruitment was reduced to an average of 8 and 24% of current recruitment for the two populations, respectively. Our results highlight the importance of including vulnerable early life stages when addressing effects of climate change on fish stocks.

Outcome-guided behavior requires knowledge about the identity of future rewards. Previous work across species has shown that the dopaminergic midbrain responds to violations in expected reward identity and that the lateral orbitofrontal cortex (OFC) represents reward identity expectations. Here we used network-targeted transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) during a trans-reinforcer reversal learning task to test the hypothesis that outcome expectations in the lateral OFC contribute to the computation of identity prediction errors (iPE) in the midbrain. Network-targeted TMS aiming at lateral OFC reduced the global connectedness of the lateral OFC and impaired reward identity learning in the first block of trials. Critically, TMS disrupted neural representations of expected reward identity in the OFC and modulated iPE responses in the midbrain. These results support the idea that iPE signals in the dopaminergic midbrain are computed based on outcome expectations represented in the lateral OFC. Behaviour requires knowledge of cues and outcomes. Here the authors use neuromodulation of lateral orbitofrontal cortex and neuroimaging of error-related midbrain activity to reveal the neurocomputational mechanisms underlying reward identity learning.

Although effective rabies virus vaccines have been existing for decades, each year, rabies virus infections still cause around 50.000 fatalities worldwide. Most of these cases occur in developing countries, where these vaccines are not available. The reasons for this are the prohibitive high costs of cell culture or egg grown rabies virus vaccines and the lack of a functional cold chain in many regions in which rabies virus is endemic. Here, we describe the excellent temperature resistance of a non-replicating mRNA based rabies virus vaccine encoding the rabies virus glycoprotein (RABV-G). Prolonged storage of the vaccine from -80°C to up to +70°C for several months did not impact the protective capacity of the mRNA vaccine. Efficacy after storage was demonstrated by the induction of rabies specific virus neutralizing antibodies and protection in mice against lethal rabies infection. Moreover, storing the vaccine at oscillating temperatures between +4° and +56°C for 20 cycles in order to simulate interruptions of the cold chain during vaccine transport, did not affect the vaccine's immunogenicity and protective characteristics, indicating that maintenance of a cold chain is not essential for this vaccine.

Fisheries worldwide face uncertain futures as climate change manifests in environmental effects of hitherto unseen strengths. Developing climate-ready management strategies traditionally requires a good mechanistic understanding of stock response to climate change in order to build projection models for testing different exploitation levels. Unfortunately, model-based projections of fish stocks are severely limited by large uncertainties in the recruitment process, as the required stock-recruitment relationship is usually not well represented by data. An alternative is to shift focus to improving the decision-making process, as postulated by the decision-making under deep uncertainty (DMDU) framework. Robust Decision Making (RDM), a key DMDU concept, aims at identifying management decisions that are robust to a vast range of uncertain scenarios. Here we employ RDM to investigate the capability of North Sea cod to support a sustainable and economically viable fishery under future climate change. We projected the stock under 40,000 combinations of exploitation levels, emission scenarios and stock-recruitment parameterizations and found that model uncertainties and exploitation have similar importance for model outcomes. Our study revealed that no management strategy exists that is fully robust to the uncertainty in relation to model parameterization and future climate change. We instead propose a risk assessment that accounts for the trade-offs between stock conservation and profitability under deep uncertainty.