Force-induced rupture of a DNA duplex

The rupture of double-stranded DNA under stress is a key process in biophysics and nanotechnology. In this article we consider the shear-induced rupture of short DNA duplexes, a system that has been given new importance by recently designed force sensors and nanotechnological devices. We argue that rupture must be understood as an activated process, where the duplex state is metastable and the strands will separate in a finite time that depends on the duplex length and the force applied. Thus, the critical shearing force required to rupture a duplex within a given experiment depends strongly on the time scale of observation. We use simple models of DNA to demonstrate that this approach naturally captures the experimentally observed dependence of the critical force on duplex length for a given observation time. In particular, the critical force is zero for the shortest duplexes, before rising sharply and then plateauing in the long length limit. The prevailing approach, based on identifying when the presence of each additional base pair within the duplex is thermodynamically unfavorable rather than allowing for metastability, does not predict a time-scale-dependent critical force and does not naturally incorporate a critical force of zero for the shortest duplexes. Additionally, motivated by a recently proposed force sensor, we investigate application of stress to a duplex in a mixed mode that interpolates between shearing and unzipping. As with pure shearing, the critical force depends on the time scale of observation; at a fixed time scale and duplex length, the critical force exhibits a sigmoidal dependence on the fraction of the duplex that is subject to shearing.Comment: 10 pages, 6 figure

Inference of hidden structures in complex physical systems by multi-scale clustering

We survey the application of a relatively new branch of statistical physics--"community detection"-- to data mining. In particular, we focus on the diagnosis of materials and automated image segmentation. Community detection describes the quest of partitioning a complex system involving many elements into optimally decoupled subsets or communities of such elements. We review a multiresolution variant which is used to ascertain structures at different spatial and temporal scales. Significant patterns are obtained by examining the correlations between different independent solvers. Similar to other combinatorial optimization problems in the NP complexity class, community detection exhibits several phases. Typically, illuminating orders are revealed by choosing parameters that lead to extremal information theory correlations.Comment: 25 pages, 16 Figures; a review of earlier work

Introducing improved structural properties and salt dependence into a coarse-grained model of DNA

We introduce an extended version of oxDNA, a coarse-grained model of deoxyribonucleic acid (DNA) designed to capture the thermodynamic, structural, and mechanical properties of single- and double-stranded DNA. By including explicit major and minor grooves and by slightly modifying the coaxial stacking and backbone-backbone interactions, we improve the ability of the model to treat large (kilobase-pair) structures, such as DNA origami, which are sensitive to these geometric features. Further, we extend the model, which was previously parameterised to just one salt concentration ([Na +] = 0.5M), so that it can be used for a range of salt concentrations including those corresponding to physiological conditions. Finally, we use new experimental data to parameterise the oxDNA potential so that consecutive adenine bases stack with a different strength to consecutive thymine bases, a feature which allows a more accurate treatment of systems where the flexibility of single-stranded regions is important. We illustrate the new possibilities opened up by the updated model, oxDNA2, by presenting results from simulations of the structure of large DNA objects and by using the model to investigate some salt-dependent properties of DNA

Evaluation of specificity and sensitivity of gastric aspirate shake test to predict surfactant deficiency in Iranian premature infants

Introduction Respiratory failure secondary to pulmonary surfactant deficiency is an important cause of severe respiratory distress in term and preterm infants. The aim of this study was to evaluate the specificity and sensitivity of gastric aspirate shake test (GAST) to predict surfactant deficiency in newly born premature infants in Arash Hospital (Iran) during 2012-13. Methods In this case-control study, the case group comprised 69 premature infants (gestational age < 37 weeks) who were admitted to the neonatal intensive care unit due to respiratory distress. The control group included 50 healthy infants.GAST test was done. The subjects were finally categorized as healthy or surfactant-deficient based on clinical and radiological assessments. Results Using statistical methods the sensitivity, specificity, and positive and negative predictive values of GAST were 60, 75, 15, and 52, respectively. There was a significant difference between respiratory distress syndrome (RDS) scores and receiving surfactant in neonates with gestational age below 34 weeks. Moreover, there were significant differences between GAST results and both radiological findings of RDS and receiving oxygen in premature infants (gestational age < 34 weeks). Negative GAST results were more prevalent in neonates who were born to mothers with hypothyroidism, preeclampsia, diabetes mellitus, and premature rupture of membranes. However, this difference was not significant. Conclusion According to our findings, the application of GAST on gastric aspirate secretions is not a useful method to predict surfactant deficiency. Therefore, decisions for RDS management must be made based on clinical and radiological findings. © 2015 International Society for the Study of Hypertension in Pregnancy Published by Elsevier B.V. All rights reserved

Transferability of cathodal tDCS effects from the primary motor to the prefrontal cortex: A multimodal TMS-EEG study

Neurophysiological effects of transcranial direct current stimulation (tDCS) have been extensively studied over the primary motor cortex (M1). Much less is however known about its effects over non-motor areas, such as the prefrontal cortex (PFC), which is the neuronal foundation for many high-level cognitive functions and involved in neuropsychiatric disorders. In this study, we, therefore, explored the transferability of cathodal tDCS effects over M1 to the PFC. Eighteen healthy human participants (11 males and 8 females) were involved in eight randomized sessions per participant, in which four cathodal tDCS dosages, low, medium, and high, as well as sham stimulation, were applied over the left M1 and left PFC. After-effects of tDCS were evaluated via transcranial magnetic stimulation (TMS)-electroencephalography (EEG), and TMS-elicited motor evoked potentials (MEP), for the outcome parameters TMS-evoked potentials (TEP), TMS-evoked oscillations, and MEP amplitude alterations. TEPs were studied both at the regional and global scalp levels. The results indicate a regional dosage-dependent nonlinear neurophysiological effect of M1 tDCS, which is not one-to-one transferable to PFC tDCS. Low and high dosages of M1 tDCS reduced early positive TEP peaks (P30, P60), and MEP amplitudes, while an enhancement was observed for medium dosage M1 tDCS (P30). In contrast, prefrontal low, medium and high dosage tDCS uniformly reduced the early positive TEP peak amplitudes. Furthermore, for both cortical areas, regional tDCS-induced modulatory effects were not observed for late TEP peaks, nor TMS-evoked oscillations. However, at the global scalp level, widespread effects of tDCS were observed for both, TMS-evoked potentials and oscillations. This study provides the first direct physiological comparison of tDCS effects applied over different brain areas and therefore delivers crucial information for future tDCS applications