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The quality of human translation was long thought to be unattainable for computer translation systems. In this study, we present a deep-learning system, CUBBITT, which challenges this view. In a context-aware blind evaluation by human judges, CUBBITT significantly outperformed professional-agency English-to-Czech news translation in preserving text meaning (translation adequacy). While human translation is still rated as more fluent, CUBBITT is shown to be substantially more fluent than previous state-of-the-art systems. Moreover, most participants of a Translation Turing test struggle to distinguish CUBBITT translations from human translations. This work approaches the quality of human translation and even surpasses it in adequacy in certain circumstances.This suggests that deep learning may have the potential to replace humans in applications where conservation of meaning is the primary aim. The quality of human language translation has been thought to be unattainable by computer translation systems. Here the authors present CUBBITT, a deep learning system that outperforms professional human translators in retaining text meaning in English-to-Czech news translation, and validate the system on English-French and English-Polish language pairs.

Human-based modelling and simulations are becoming ubiquitous in biomedical science due to their ability to augment experimental and clinical investigations. Cardiac electrophysiology is one of the most advanced areas, with cardiac modelling and simulation being considered for virtual testing of pharmacological therapies and medical devices. Current models present inconsistencies with experimental data, which limit further progress. In this study, we present the design, development, calibration and independent validation of a human-based ventricular model (ToR-ORd) for simulations of electrophysiology and excitation-contraction coupling, from ionic to whole-organ dynamics, including the electrocardiogram. Validation based on substantial multiscale simulations supports the credibility of the ToR-ORd model under healthy and key disease conditions, as well as drug blockade. In addition, the process uncovers new theoretical insights into the biophysical properties of the L-type calcium current, which are critical for sodium and calcium dynamics. These insights enable the reformulation of L-type calcium current, as well as replacement of the hERG current model. Decades of intensive experimental and clinical research have revealed much about how the human heart works. Though incomplete, this knowledge has been used to construct computer models that represent the activity of this organ as a whole, and of its individual chambers (the atria and ventricles), tissues and cells. Such models have been used to better understand life-threatening irregular heartbeats; they are also beginning to be used to guide decisions about the treatment of patients and the development of new drugs by the pharmaceutical industry. Yet existing computer models of the electrical activity of the human heart are sometimes inconsistent with experimental data. This problem led Tomek et al. to try to create a new model that was consistent with established biophysical knowledge and experimental data for a wide range of conditions including disease and drug action. Tomek et al. designed a strategy that explicitly separated the construction and validation of a model that could recreate the electrical activity of the ventricles in a human heart. This model was able to integrate and explain a wide range of properties of both healthy and diseased hearts, including their response to different drugs. The development of the model also uncovered and resolved theoretical inconsistencies that have been present in almost all models of the heart from the last 25 years. Tomek et al. hope that their new human heart model will enable more basic, translational and clinical research into a range of heart diseases and accelerate the development of new therapies.

Background DNA replication plays an important role in mutagenesis, yet little is known about how it interacts with other mutagenic processes. Here, we use somatic mutation signatures—each representing a mutagenic process—derived from 3056 patients spanning 19 cancer types to quantify the strand asymmetry of mutational signatures around replication origins and between early and late replicating regions. Results We observe that most of the detected mutational signatures are significantly correlated with the timing or direction of DNA replication. The properties of these associations are distinct for different signatures and shed new light on several mutagenic processes. For example, our results suggest that oxidative damage to the nucleotide pool substantially contributes to the mutational landscape of esophageal adenocarcinoma. Conclusions Together, our results indicate an interaction between DNA replication, the associated damage repair, and most mutagenic processes.

Optical mapping is widely used in experimental cardiology, as it allows visualization of cardiac membrane potential and calcium transients. However, optical mapping measurements from a single heart or cell culture can produce several gigabytes of data, warranting automated computer analysis. Here we present COSMAS, a software toolkit for automated analysis of optical mapping recordings in cardiac preparations. COSMAS generates activation and conduction velocity maps, as well as visualizations of action potential and calcium transient duration, S1-S2 protocol analysis, and alternans mapping. The software is built around our recent ‘comb’ algorithm for segmentation of action potentials and calcium transients, offering excellent performance and high resistance to noise. A core feature of our software is that it is based on scripting as opposed to relying on a graphical user interface for user input. The central role of scripts in the analysis pipeline enables batch processing and promotes reproducibility and transparency in the interpretation of large cardiac data sets. Finally, the code is designed to be easily extended, allowing researchers to add functionality if needed. COSMAS is provided in two languages, Matlab and Python, and is distributed with a user guide and sample scripts, so that accessibility to researchers is maximized.

Sudden death after myocardial infarction (MI) is associated with electrophysiological heterogeneities and ionic current remodelling. Low ejection fraction (EF) is used in risk stratification, but its mechanistic links with pro-arrhythmic heterogeneities are unknown. We aim to provide mechanistic explanations of clinical phenotypes in acute and chronic MI, from ionic current remodelling to ECG and EF, using human electromechanical modelling and simulation to augment experimental and clinical investigations. A human ventricular electromechanical modelling and simulation framework is constructed and validated with rich experimental and clinical datasets, incorporating varying degrees of ionic current remodelling as reported in literature. In acute MI, T-wave inversion and Brugada phenocopy were explained by conduction abnormality and local action potential prolongation in the border zone. In chronic MI, upright tall T-waves highlight large repolarisation dispersion between the border and remote zones, which promoted ectopic propagation at fast pacing. Post-MI EF at resting heart rate was not sensitive to the extent of repolarisation heterogeneity and the risk of repolarisation abnormalities at fast pacing. T-wave and QT abnormalities are better indicators of repolarisation heterogeneities than EF in post-MI.

Plants engineer the rhizosphere to their advantage by secreting various nutrients and secondary metabolites. Coupling transcriptomic and metabolomic analyses of the pea (Pisum sativum) rhizosphere, a suite of bioreporters has been developed in Rhizobium leguminosarum bv viciae strain 3841, and these detect metabolites secreted by roots in space and time. Fourteen bacterial lux fusion bioreporters, specific for sugars, polyols, amino acids, organic acids, or flavonoids, have been validated in vitro and in vivo. Using different bacterial mutants (nodC and nifH), the process of colonization and symbiosis has been analyzed, revealing compounds important in the different steps of the rhizobium-legume association. Dicarboxylates and sucrose are the main carbon sources within the nodules; in ineffective (nifH) nodules, particularly low levels of sucrose were observed, suggesting that plant sanctions affect carbon supply to nodules. In contrast, high myo-inositol levels were observed prior to nodule formation and also in nifH senescent nodules. Amino acid biosensors showed different patterns: a g-aminobutyrate biosensor was active only inside nodules, whereas the phenylalanine bioreporter showed a high signal also in the rhizosphere. The bioreporters were further validated in vetch (Vicia hirsuta), producing similar results. In addition, vetch exhibited a local increase of nod gene-inducing flavonoids at sites where nodules developed subsequently. These bioreporters will be particularly helpful in understanding the dynamics of root exudation and the role of different molecules secreted into the rhizosphere.

Nucleos(t)ides are essential for DNA/RNA synthesis, energy metabolism, and signaling, yet their roles in placental development remain poorly understood. The placenta undergoes dynamic metabolic adaptations throughout gestation to support fetal growth. This study investigates gene expression shifts in nucleos(t)ide metabolism, transport, and adenosine signaling during placental development and in the pathological condition of spontaneous preterm birth (PTB). We analyzed gene expression in first-trimester ( n  = 10) and term ( n  = 10), and PTB ( n  = 10) human placentas, and in cytotrophoblast and syncytiotrophoblast stage in primary human trophoblasts ( n  = 3) and BeWo ( n  = 5) cells. For developmental context, rat placentas were examined at gestation days (GD) GD12, GD15, and GD20 ( n  = 5 per group) that correspond to early second trimester in the human placenta. We found that genes involved in nucleos(t)ide metabolism and adenosine signaling were dominantly upregulated from early gestation to term in the human placenta. PTB placentas revealed further elevation compared to the term placenta. Differentiation from cytotrophoblast to syncytiotrophoblast was accompanied by only minor changes. Pearson’s correlation analysis revealed strong gene-metabolite and gene-gene associations, highlighting an integrated metabolic network regulating placental function. Gene expression also differed among the tested GDs in the rat placenta. These findings demonstrate dynamic changes of nucleos(t)ide metabolism during healthy placental development and enhanced expression in PTB placentas, suggesting increasing needs for nucleos(t)ides during placental growth and metabolic shifts in the PTB placenta. Our data also indicate that nucleos(t)ide metabolism is preserved in both proliferative and differentiated states.

Natriuretic peptides are often elevated in congenital heart disease (CHD); however, the clinical impact on mortality is unclear. The aim of our study was to evaluate the prognostic value of N-terminal pro-brain natriuretic peptide (NT-proBNP) in the prediction of all-cause mortality in adults with different CHD. In this prospective longitudinal mortality study, we evaluated NT-proBNP in 1,242 blood samples from 646 outpatient adults with stable CHD (mean age 35 ± 12 years; 345 women). Patients were followed up for 6 ± 3 (1 to 10) years. The mortality rate was 5% (35 patients, mean age 40 ± 14 years, 17 women). Median NT-proBNP (pg/ml) was 220 in the whole cohort, 203 in survivors, and 1,548 in deceased patients. The best discrimination value for mortality prediction was 630 pg/ml with 74% sensitivity and 84% specificity. During the follow-up, the survival rate was 65% for those with median NT-proBNP ≥630 pg/ml and 94% for NT-proBNP <630 pg/ml; p <0.0001. There was only 1% mortality among 388 patients with at least 1 NT-proBNP value ≤220 pg/ml compared with 41% mortality among 54 patients with at least 1 NT-proBNP value >1,548 pg/ml. Even the first (baseline) measurements of NT-proBNP were strongly associated with a high risk of death (log10 NT-proBNP had hazard ratio 7, p <0.0001). In conclusion, NT-proBNP assessment is a useful and simple tool for the prediction of mortality in long-term follow-up of adults with CHD.

C-to-T transitions in CpG dinucleotides are the most prevalent mutations in human cancers and genetic diseases. These mutations have been attributed to deamination of 5-methylcytosine (5mC), an epigenetic modification found on CpGs. We recently linked CpG>TpG mutations to replication and hypothesized that errors introduced by polymerase ε (Pol ε) may represent an alternative source of mutations. Here we present a new method called polymerase error rate sequencing (PER-seq) to measure the error spectrum of DNA polymerases in isolation. We find that the most common human cancer-associated Pol ε mutant (P286R) produces an excess of CpG>TpG errors, phenocopying the mutation spectrum of tumors carrying this mutation and deficiencies in mismatch repair. Notably, we also discover that wild-type Pol ε has a sevenfold higher error rate when replicating 5mCpG compared to C in other contexts. Together, our results from PER-seq and human cancers demonstrate that replication errors are a major contributor to CpG>TpG mutagenesis in replicating cells, fundamentally changing our understanding of this important disease-causing mutational mechanism. A new method called polymerase error rate sequencing (PER-seq) can measure the nucleotide misincorporation rate of DNA polymerases. DNA polymerase ε mutants produce an excess of CpG

Journal Article

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