Performance evaluation of three DNA sample tracking tools in a whole exome sequencing workflow

Next-generation sequencing applications are becoming the building blocks for clinical diagnostics. These experiments require numerous wet- and drylab steps, each one increasing the probability of a sample swap and/or contamination. Therefore, an identity confirmation at the end of the process is required to ensure the right data is used for each patient. We tested three commercially available, SNP bases sample tracking kits in a diagnostic workflow to evaluate their performance. The coverage uniformity, on-target specificity, sample identification and genotyping performance were determined to measure the reliability and estimate the cost-effectiveness of each kit. Our findings showed that the kit from Swift did not perform up to standards as only 20 out of the 46 samples were correctly genotyped. The kit provided by Nimagen identified all but one sample and the kit from pxlence unambiguously identified all samples, making it the most reliable and robust kit of this evaluation. The kit from Nimagen showed poor on-target rates, resulting in deeper sequencing needs and higher sequencing costs compared to the other two kits.

Default change nudges Covid-19 vaccine uptake: a randomized controlled trial

Although vaccination against SARS-CoV-2 is considered the central strategy against the pandemic, uptake lags behind target rates. To explore whether this rate could be enhanced by a nudging strategy that exploits the status quo bias, we conducted a randomized controlled study in northern Italy comparing vaccination acceptance among 2,000 adults aged 50-59 who were either invited to set an appointment (opt-in group) or assigned an individual appointment (opt-out group). Results indicate an increase in vaccination rate for the opt-out group compared to the opt-in group of 3.2 percentage points — a 32% relative increase. This suggests that a significant portion of those who remain unvaccinated may not hold strong beliefs against vaccination, but rather tend to inaction and may therefore be nudged toward vaccination with a reduction of action required.

Development of the concept of system management of the reproduction of personal potential as an element of ensuring the sustainable development of rural territories

This article is devoted to the concept of systemic management of personal potential reproduction as an element of ensuring sustainable development of rural areas. The concept contains structural and substantive elements substantiated by us: 1) the relevance of the formation; 2) key difficulties; 3) purpose; 4) the task; 5) expected results; 6) benefits; 7) performance criteria. The scientific significance of the development lies in determining the main components of the concept, practical - in achieving a balanced rate of reproduction of personnel potential, as a result of which the profitability and labor productivity in the industry will increase. Also, the article defines the structure of the management system for the reproduction of personal potential in agriculture. The scientific significance of the development consists in a well-grounded and structured by us set of interrelated system components, the identification of which simplifies the process of reproduction management. Applying the methodology developed by us for assessing the impact of internal and external factors on the rate of reproduction of personal potential in the industry, the structure of the system specifies the subjects that can regulate the influence of these factors, using the tools of which it is possible to achieve the target rates of balanced reproduction (for the industry, agricultural organizations and their employees).

Predicting primer and panel off-target rate in QIAseq targeted DNA panels using convolutional neural networks

In QIAseq targeted DNA panels, synthetic primers (short single-strand DNA sequences) are used for target enrichment via complementary DNA binding. Off-target priming could occur in this process when a primer binds to some loci where the DNA sequences are identical or very similar to the target template. These off-target DNA segments go through the rest of the workflow, wasting sequencing resources in unwanted regions. Off-target cannot be avoided if some segments of the target region are repetitive throughout the genome, nor can it be quantified until after sequencing. But if off-target rates can be prospectively predicted, scientists can make informed decisions about investment on high off-target panels.We developed pordle (predicting off-target rate with deep learning and epcr07), a convolutional neural network (CNN) model to predict off-target binding events of a given primer. The neural network was trained using 10 QIAseq DNA panels with 29,274 unique primers and then tested on an independent QIAseq panel with 7,576 primers. The model predicted a 10.5% off-target rate for the test panel, a -0.1% bias from the true value of 10.6%. The model successfully selected the better primer (in terms of off-target rate) for 89.2% of 3,835 pairs of close-by primers in the test panel whose off-target rates differ by at least 10%. The order-preserving property may help panel developers select the optimal primer from a group of candidates, which is a common task in panel design.

Investigating diachronic trends in phonological inventories using BDPROTO

Here we present an expanded version of bdproto, a database comprising phonological inventory data from 257 ancient and reconstructed languages. These data were extracted from historical linguistic reconstructions and brought together into a single unified, normalized, accessible, and Unicode-compliant language resource. This dataset is publicly available and we aim to engage language scientists doing research on language change and language evolution. Furthermore, we identify a hitherto undiscussed temporal bias that complicates the simple comparison of ancient and reconstructed languages with present-day languages. Due to the sparsity of the data and the absence of statistical and computational methods that can adequately handle this bias, we instead directly target rates of change within and across families, thereby providing a case study to highlight bdproto’s research viability; using phylogenetic comparative methods and high-resolution language family trees, we investigate whether consonantal and vocalic systems differ in their rates of change over the last 10,000 years. In light of the compilation of bdproto and the findings of our case study, we discuss the challenges involved in comparing the sound systems of reconstructed languages with modern day languages.

On Performance Analysis of Underlay Cognitive Radio-Aware Hybrid OMA/NOMA Networks with Imperfect CSI

This study considers the outage and throughput performance of downlink in the secondary network of cognitive radio assisted non-orthogonal multiple access (NOMA) systems. Both orthogonal multiple access (OMA) mode and NOMA mode are investigated with respect to status of decoding operation of each user. Depending on the transmit signal-to-noise ratio (SNR) at the primary source and interference constraint from the primary network, the closed-form expressions of the outage probability for two users are obtained and compared in terms of performance. To obtain further insights, an asymptotic analysis of the outage probability in the high SNR regime is presented. Optimal throughput also provides insight in the computation of the power allocation factor. Furthermore, power allocation factor, target rates, and transmit SNR are evaluated to obtain reasonable outage performance. Monte Carlo simulations are conducted to confirm the analytical results.