CMOS-based cryogenic control of silicon quantum circuits.

The most promising quantum algorithms require quantum processors that host millions of quantum bits when targeting practical applications1. A key challenge towards large-scale quantum computation is the interconnect complexity. In current solid-state qubit implementations, an important interconnect bottleneck appears between the quantum chip in a dilution refrigerator and the room-temperature electronics. Advanced lithography supports the fabrication of both control electronics and qubits in silicon using technology compatible with complementary metal oxide semiconductors (CMOS)2. When the electronics are designed to operate at cryogenic temperatures, they can ultimately be integrated with the qubits on the same die or package, overcoming the 'wiring bottleneck'3-6. Here we report a cryogenic CMOS control chip operating at 3 kelvin, which outputs tailored microwave bursts to drive silicon quantum bits cooled to 20 millikelvin. We first benchmark the control chip and find an electrical performance consistent with qubit operations of 99.99 per cent fidelity, assuming ideal qubits. Next, we use it to coherently control actual qubits encoded in the spin of single electrons confined in silicon quantum dots7-9 and find that the cryogenic control chip achieves the same fidelity as commercial instruments at room temperature. Furthermore, we demonstrate the capabilities of the control chip by programming a number of benchmarking protocols, as well as the Deutsch-Josza algorithm10, on a two-qubit quantum processor. These results open up the way towards a fully integrated, scalable silicon-based quantum computer.

Transient left ventricular outflow tract obstruction with systolic anterior motion of the mitral valve: A stunning cause.

Left ventricular outflow tract obstruction (LVOTO) and systolic anterior motion (SAM) of the mitral valve may have various etiologies, of which hypertrophic cardiomyopathy is the most common. More rarely, an acute coronary syndrome, myocardial stunning, and takotsubo cardiomyopathy may give rise to LVOTO and SAM. Here, we present a 70-year-old female patient with a non-ST-elevation acute coronary syndrome treated with percutaneous coronary intervention. Echocardiography the day after, because of dyspnea and hypotension, revealed apical akinesia, LVOTO, and SAM, which proved completely reversible after treatment with a ß-blocker and a 2-month follow-up period. It was concluded that postischemic apical stunning had caused LVOTO and SAM.

DNA enrichment approaches to identify unauthorized genetically modified organisms (GMOs).

With the increased global production of different genetically modified (GM) plant varieties, chances increase that unauthorized GM organisms (UGMOs) may enter the food chain. At the same time, the detection of UGMOs is a challenging task because of the limited sequence information that will generally be available. PCR-based methods are available to detect and quantify known UGMOs in specific cases. If this approach is not feasible, DNA enrichment of the unknown adjacent sequences of known GMO elements is one way to detect the presence of UGMOs in a food or feed product. These enrichment approaches are also known as chromosome walking or gene walking (GW). In recent years, enrichment approaches have been coupled with next generation sequencing (NGS) analysis and implemented in, amongst others, the medical and microbiological fields. The present review will provide an overview of these approaches and an evaluation of their applicability in the identification of UGMOs in complex food or feed samples.

Tuber proteome comparison of five potato varieties by principal component analysis.

BACKGROUND: Data analysis of omics data should be performed by multivariate analysis such as principal component analysis (PCA). The way data are clustered in PCA is of major importance to develop some classification systems based on multivariate analysis, such as soft independent modeling of class analogy (SIMCA). In a previous study a one-class classifier based on SIMCA was built using microarray data from a set of potatoes. The PCA grouped the transcriptomic data according to varieties. The present work aimed to use PCA to verify the clustering of the proteomic profiles for the same potato varieties. RESULTS: Proteomic profiles of five potato varieties (Biogold, Fontane, Innovator, Lady Rosetta and Maris Piper) were evaluated by two-dimensional gel electrophoresis (2-DE) performed on two immobilized pH gradient (IPG) strip lengths, 13 and 24 cm, both under pH range 4-7. For each strip length, two gels were prepared from each variety; in total there were ten gels per analysis. For 13 cm strips, 199-320 spots were detected per gel, and for 24 cm strips, 365-684 spots. CONCLUSION: All four PCAs performed with these datasets presented clear grouping of samples according to the varieties. The data presented here showed that PCA was applicable for proteomic analysis of potato and was able to separate the samples by varieties. © 2016 Society of Chemical Industry.

Detecting authorized and unauthorized genetically modified organisms containing vip3A by real-time PCR and next-generation sequencing.

The growing number of biotech crops with novel genetic elements increasingly complicates the detection of genetically modified organisms (GMOs) in food and feed samples using conventional screening methods. Unauthorized GMOs (UGMOs) in food and feed are currently identified through combining GMO element screening with sequencing the DNA flanking these elements. In this study, a specific and sensitive qPCR assay was developed for vip3A element detection based on the vip3Aa20 coding sequences of the recently marketed MIR162 maize and COT102 cotton. Furthermore, SiteFinding-PCR in combination with Sanger, Illumina or Pacific BioSciences (PacBio) sequencing was performed targeting the flanking DNA of the vip3Aa20 element in MIR162. De novo assembly and Basic Local Alignment Search Tool searches were used to mimic UGMO identification. PacBio data resulted in relatively long contigs in the upstream (1,326 nucleotides (nt); 95 % identity) and downstream (1,135 nt; 92 % identity) regions, whereas Illumina data resulted in two smaller contigs of 858 and 1,038 nt with higher sequence identity (>99 % identity). Both approaches outperformed Sanger sequencing, underlining the potential for next-generation sequencing in UGMO identification.

A high-throughput method for GMO multi-detection using a microfluidic dynamic array.

The ever-increasing production of genetically modified crops generates a demand for high-throughput DNA-based methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis by DNA based methods, which is the use of a microfluidic dynamic array as a high throughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.

Safety assessment of plant varieties using transcriptomics profiling and a one-class classifier.

An important part of the current hazard identification of novel plant varieties is comparative targeted analysis of the novel and reference varieties. Comparative analysis will become much more informative with unbiased analytical approaches, e.g. omics profiling. Data analysis estimating the similarity of new varieties to a reference baseline class of known safe varieties would subsequently greatly facilitate hazard identification. Further biological and eventually toxicological analysis would then only be necessary for varieties that fall outside this reference class. For this purpose, a one-class classifier tool was explored to assess and classify transcriptome profiles of potato (Solanum tuberosum) varieties in a model study. Profiles of six different varieties, two locations of growth, two year of harvest and including biological and technical replication were used to build the model. Two scenarios were applied representing evaluation of a 'different' variety and a 'similar' variety. Within the model higher class distances resulted for the 'different' test set compared with the 'similar' test set. The present study may contribute to a more global hazard identification of novel plant varieties.

Development of a multiplex DNA-based traceability tool for crop plant materials.

The authenticity of food is of increasing importance for producers, retailers and consumers. All groups benefit from the correct labelling of the contents of food products. Producers and retailers want to guarantee the origin of their products and check for adulteration with cheaper or inferior ingredients. Consumers are also more demanding about the origin of their food for various socioeconomic reasons. In contrast to this increasing demand, correct labelling has become much more complex because of global transportation networks of raw materials and processed food products. Within the European integrated research project 'Tracing the origin of food' (TRACE), a DNA-based multiplex detection tool was developed-the padlock probe ligation and microarray detection (PPLMD) tool. In this paper, this method is extended to a 15-plex traceability tool with a focus on products of commercial importance such as the emmer wheat Farro della Garfagnana (FdG) and Basmati rice. The specificity of 14 plant-related padlock probes was determined and initially validated in mixtures comprising seven or nine plant species/varieties. One nucleotide difference in target sequence was sufficient for the distinction between the presence or absence of a specific target. At least 5% FdG or Basmati rice was detected in mixtures with cheaper bread wheat or non-fragrant rice, respectively. The results suggested that even lower levels of (un-)intentional adulteration could be detected. PPLMD has been shown to be a useful tool for the detection of fraudulent/intentional admixtures in premium foods and is ready for the monitoring of correct labelling of premium foods worldwide.

Development and validation of real-time PCR screening methods for detection of cry1A.105 and cry2Ab2 genes in genetically modified organisms.

Primers and probes were developed for the element-specific detection of cry1A.105 and cry2Ab2 genes, based on their DNA sequence as present in GM maize MON89034. Cry genes are present in many genetically modified (GM) plants and they are important targets for developing GMO element-specific detection methods. Element-specific methods can be of use to screen for the presence of GMOs in food and feed supply chains. Moreover, a combination of GMO elements may indicate the potential presence of unapproved GMOs (UGMs). Primer-probe combinations were evaluated in terms of specificity, efficiency and limit of detection. Except for specificity, the complete experiment was performed in 9 PCR runs, on 9 different days and by testing 8 DNA concentrations. The results showed a high specificity and efficiency for cry1A.105 and cry2Ab2 detection. The limit of detection was between 0.05 and 0.01 ng DNA per PCR reaction for both assays. These data confirm the applicability of these new primer-probe combinations for element detection that can contribute to the screening for GM and UGM crops in food and feed samples.

Extinction risk controlled by interaction of long-term and short-term climate change.

Assessing extinction risk from climate drivers is a major goal of conservation science. Few studies, however, include a long-term perspective of climate change. Without explicit integration, such long-term temperature trends and their interactions with short-term climate change may be so dominant that they blur or even reverse the apparent direct relationship between climate change and extinction. Here we evaluate how observed genus-level extinctions of arthropods, bivalves, cnidarians, echinoderms, foraminifera, gastropods, mammals and reptiles in the geological past can be predicted from the interaction of long-term temperature trends with short-term climate change. We compare synergistic palaeoclimate interaction (a short-term change on top of a long-term trend in the same direction) to antagonistic palaeoclimate interaction such as long-term cooling followed by short-term warming. Synergistic palaeoclimate interaction increases extinction risk by up to 40%. The memory of palaeoclimate interaction including the climate history experienced by ancestral lineages can be up to 60 Myr long. The effect size of palaeoclimate interaction is similar to other key factors such as geographic range, abundance or clade membership. Insights arising from this previously unknown driver of extinction risk might attenuate recent predictions of climate-change-induced biodiversity loss.

Comparison of two GM maize varieties with a near-isogenic non-GM variety using transcriptomics, proteomics and metabolomics.

The aim of this study was to evaluate the use of four nontargeted analytical methodologies in the detection of unintended effects that could be derived during genetic manipulation of crops. Three profiling technologies were used to compare the transcriptome, proteome and metabolome of two transgenic maize lines with the respective control line. By comparing the profiles of the two transgenic lines grown in the same location over three growing seasons, we could determine the extent of environmental variation, while the comparison with the control maize line allowed the investigation of effects caused by a difference in genotype. The effect of growing conditions as an additional environmental effect was also evaluated by comparing the Bt-maize line with the control line from plants grown in three different locations in one growing season. The environment was shown to play an important effect in the protein, gene expression and metabolite levels of the maize samples tested where 5 proteins, 65 genes and 15 metabolites were found to be differentially expressed. A distinct separation between the three growing seasons was also found for all the samples grown in one location. Together, these environmental factors caused more variation in the different transcript/protein/metabolite profiles than the different genotypes.

Molecular Characterization and Event-Specific Real-Time PCR Detection of Two Dissimilar Groups of Genetically Modified Petunia (Petunia x hybrida) Sold on the Market.

Petunia plants with unusual orange flowers were noticed on the European market and confirmed to be genetically modified (GM) by the Finnish authorities in spring 2017. Later in 2017, inspections and controls performed by several official laboratories of national competent authorities in the European Union detected several GM petunia varieties with orange flowers, but also another group of unusually colored flowers. In the latter group, a so far undetected gene coding for a flavonoid 3'5' hydroxylase (F3'5'H) responsible for the purple color was identified by German and Dutch authorities, suggesting that the petunias found on the markets contain different genetic constructs. Here, a strategy is described for the identification of GM petunia varieties. It is based on an initial GMO screening for known elements using (real-time) PCR and subsequent identification of the insertion sites by a gene walking-like approach called ALF (amplification of linearly-enriched fragments) in combination with Sanger and MinION sequencing. The results indicate that the positively identified GM petunias can be traced back to two dissimilar GM events used for breeding of the different varieties. The test results also confirm that the transgenic petunia event RL01-17 used in the first German field trial in 1991 is not the origin of the GM petunias sold on the market. On basis of the obtained sequence data, event-specific real-time PCR confirmatory methods were developed and validated. These methods are applicable for the rapid detection and identification of GM petunias in routine analysis. In addition, a decision support system was developed for revealing the most likely origin of the GM petunia.

Toward on-site food authentication using nanopore sequencing.

•MinION DNA metabarcoding is a promising tool for species identification in food.•MinION and Illumina MiSeq sequencing platforms perform equally accurate.•Species identification with MinION sequencing requires dedicated bioinformatics.

Omics analyses of potato plant materials using an improved one-class classification tool to identify aberrant compositional profiles in risk assessment procedures.

The objective of this study was to quantitatively assess potato omics profiles of new varieties for meaningful differences from analogous profiles of commercial varieties through the SIMCA one-class classification model. Analytical profiles of nine commercial potato varieties, eleven experimental potato varieties, one GM potato variety that had acquired Phytophtora resistance based on a single insert with potato-derived DNA sequences, and its non-GM commercial counterpart were generated. The ten conventional varieties were used to construct the one-class model. Omics profiles from experimental non-GM and GM varieties were assessed using the one-class SIMCA models. No potential unintended effects were identified in the case of the GM variety. The model showed that varieties that were genetically more distant from the commercial varieties were recognized as aberrant, highlighting its potential in determining whether additional evaluation is required for the risk assessment of materials produced from any breeding technique, including genetic modification.

Use of omics analytical methods in the study of genetically modified maize varieties tested in 90 days feeding trials.

Genetically modified (GM) maize and their non-modified counterparts were compared using MON810 varieties, the only GMO event cultivated in Europe. The differences in grain samples were analysed by omics profiles, including transcriptomics, proteomics and metabolomics. Other cultivated maize varieties were analysed as a reference for the variability that will exist between cultivated varieties. The observed differences between modified and non-modified maize varieties do not exceed typical differences between non-modified varieties. The use of these advanced analytical approaches to analyse novel plant materials as compared to the results from animal feeding trials with whole foods is assessed. No indications were observed for changes in the GM varieties that warrant further investigations. Furthermore, it was shown that such indications will be obtained if maize samples of inferior quality are analysed similarly. Omics data provide detailed analytical information of the plant material, which facilitates a risk assessment procedure of new (GM) plant varieties.

Optimised padlock probe ligation and microarray detection of multiple (non-authorised) GMOs in a single reaction.

BACKGROUND: To maintain EU GMO regulations, producers of new GM crop varieties need to supply an event-specific method for the new variety. As a result methods are nowadays available for EU-authorised genetically modified organisms (GMOs), but only to a limited extent for EU-non-authorised GMOs (NAGs). In the last decade the diversity of genetically modified (GM) ingredients in food and feed has increased significantly. As a result of this increase GMO laboratories currently need to apply many different methods to establish to potential presence of NAGs in raw materials and complex derived products. RESULTS: In this paper we present an innovative method for detecting (approved) GMOs as well as the potential presence of NAGs in complex DNA samples containing different crop species. An optimised protocol has been developed for padlock probe ligation in combination with microarray detection (PPLMD) that can easily be scaled up. Linear padlock probes targeted against GMO-events, -elements and -species have been developed that can hybridise to their genomic target DNA and are visualised using microarray hybridisation.In a tenplex PPLMD experiment, different genomic targets in Roundup-Ready soya, MON1445 cotton and Bt176 maize were detected down to at least 1%. In single experiments, the targets were detected down to 0.1%, i.e. comparable to standard qPCR. CONCLUSION: Compared to currently available methods this is a significant step forward towards multiplex detection in complex raw materials and derived products. It is shown that the PPLMD approach is suitable for large-scale detection of GMOs in real-life samples and provides the possibility to detect and/or identify NAGs that would otherwise remain undetected.

Evaluation of global left ventricular function and mechanical dyssynchrony in patients with an asymptomatic left bundle branch block: a real-time 3D echocardiography study.

BACKGROUND: A left bundle branch block (LBBB) affects both global left ventricular (LV) function and mechanical dyssynchrony. The aim was to evaluate global LV function and mechanical dyssynchrony with real-time 3D echocardiography (RT3DE), in asymptomatic LBBB patients, healthy volunteers and patients with symptomatic heart failure (HF) and a LBBB. Furthermore, the relation between presence or absence of symptoms of HF and mechanical dyssynchrony was investigated. METHODS: RT3DE was performed in 61 consecutive patients: 16 healthy volunteers, 22 patients with an asymptomatic LBBB and 23 patients with symptomatic HF and a LBBB. Global LV function and the systolic dyssynchrony index (SDI) were measured. RESULTS: In healthy volunteers, mean LV ejection fraction was 54 +/- 5%, in asymptomatic LBBB patients 50 +/- 9%, and in HF patients 29 +/- 9%. SDI was 5.6 +/- 3.6%, 7.3 +/- 3.2% and 12.8 +/- 4.8% for healthy volunteers, asymptomatic LBBB patients and HF patients respectively. SDI differed significantly between HF patients and both other groups. A cut-off value for SDI for presence of symptoms of HF was 10.8%. CONCLUSION: Asymptomatic LBBB patients have more depressed global LV function than healthy volunteers have; patients with symptoms of HF and a LBBB have severe global LV dysfunction. Asymptomatic LBBB patients have an intermediate mechanical dyssynchrony; HF patients with a LBBB have the most severe mechanical dyssynchrony. A substantial amount of mechanical dyssynchrony might be accompanied by the presence of symptoms of HF.