CellDynaMo–stochastic reaction-diffusion-dynamics model: Application to search-and-capture process of mitotic spindle assembly

We introduce a Stochastic Reaction-Diffusion-Dynamics Model (SRDDM) for simulations of cellular mechanochemical processes with high spatial and temporal resolution. The SRDDM is mapped into the CellDynaMo package, which couples the spatially inhomogeneous reaction-diffusion master equation to account for biochemical reactions and molecular transport within the Langevin Dynamics (LD) framework to describe dynamic mechanical processes. This computational infrastructure allows the simulation of hours of molecular machine dynamics in reasonable wall-clock time. We apply SRDDM to test performance of the Search-and-Capture of mitotic spindle assembly by simulating, in three spatial dimensions, dynamic instability of elastic microtubules anchored in two centrosomes, movement and deformations of geometrically realistic centromeres with flexible kinetochores and chromosome arms. Furthermore, the SRDDM describes the mechanics and kinetics of Ndc80 linkers mediating transient attachments of microtubules to the chromosomal kinetochores. The rates of these attachments and detachments depend upon phosphorylation states of the Ndc80 linkers, which are regulated in the model by explicitly accounting for the reactions of Aurora A and B kinase enzymes undergoing restricted diffusion. We find that there is an optimal rate of microtubule-kinetochore detachments which maximizes the accuracy of the chromosome connections, that adding chromosome arms to kinetochores improve the accuracy by slowing down chromosome movements, that Aurora A and kinetochore deformations have a small positive effect on the attachment accuracy, and that thermal fluctuations of the microtubules increase the rates of kinetochore capture and also improve the accuracy of spindle assembly.     

Influence of Polymer Aggregation and Liquid Immiscibility on Morphology Tuning by Varying Composition in PffBT4T‐2DT/Nonfullerene Organic Solar Cells

The temperature‐dependent aggregation behavior of PffBT4T polymers used in organic solar cells plays a critical role in the formation of a favorable morphology in fullerene‐based devices. However, there is little investigation into the impact of donor/acceptor ratio on morphology tuning, especially for nonfullerene acceptors (NFAs). Herein, the influence of composition on morphology is reported for blends of PffBT4T‐2DT with two NFAs, O‐IDTBR and O‐IDFBR. The monotectic phase behavior inferred from differential scanning calorimetry provides qualitative insight into the interplay between solid–liquid and liquid–liquid demixing. Transient absorption spectroscopy suggests that geminate recombination dominates charge decay and that the decay rate is insensitive to composition, corroborated by negligible changes in open‐circuit voltage. Exciton lifetimes are also insensitive to composition, which is attributed to the signal being dominated by acceptor excitons which are formed and decay in domains of similar size and purity irrespective of composition. A hierarchical morphology is observed, where the composition dependence of size scales and scattering intensity from resonant soft X‐ray scattering (R‐SoXS) is dominated by variations in volume fractions of polymer/polymer‐rich domains. Results suggest an optimal morphology where polymer crystallite size and connectivity are balanced, ensuring a high probability of hole extraction via such domains.     

Cryptic diversity and unexpected evolutionary patterns in the meadow lizard,Darevskia praticola (Eversmann, 1834)

Darevskia praticola differs from the other species of the genus in having a large but disjunct distribution, covering the Balkan and the Caucasus regions. Furthermore, most Darevskia species occupy saxicolous habitats, whereas D. praticola inhabits meadows and forest environments. Here we determine the phylogeographic and phylogenetic relationships of Darevskia praticola sensu lato and evaluate the current, morphology-based taxonomy. We sequenced two mtDNA genes (Cyt-b and ND4) and two nuclear loci (MC1R and RELN) for samples collected across the species range. Because our sequences amplified with the Cyt-b primers appear to represent a nuclear pseudogene we excluded this marker from the final analysis. Our results support monophyly of D. praticola and show its division into three clades. The first divergence, dated to the Late Pliocene, is between the Balkans and the Caucasus. The Caucasus lineage is further subdivided in a western Greater Caucasus and a Transcaucasia clade, likely due to subsequent differentiation during the Pleistocene. Our findings do not support the current taxonomic arrangement within D. praticola. The main geographic divergence likely happened due to a vicariance event associated with Plio-Pleistocene climatic and vegetation oscillations.     

Revealing the True Incidence of Pandemic A(H1N1)pdm09 Influenza in Finland during the First Two Seasons — An Analysis Based on a Dynamic Transmission Model

The threat of the new pandemic influenza A(H1N1)pdm09 imposed a heavy burden on the public health system in Finland in 2009-2010. An extensive vaccination campaign was set up in the middle of the first pandemic season. However, the true number of infected individuals remains uncertain as the surveillance missed a large portion of mild infections. We constructed a transmission model to simulate the spread of influenza in the Finnish population. We used the model to analyse the two first years (2009-2011) of A(H1N1)pdm09 in Finland. Using data from the national surveillance of influenza and data on close person-to-person (social) contacts in the population, we estimated that 6% (90% credible interval 5.1 – 6.7%) of the population was infected with A(H1N1)pdm09 in the first pandemic season (2009/2010) and an additional 3% (2.5 – 3.5%) in the second season (2010/2011). Vaccination had a substantial impact in mitigating the second season. The dynamic approach allowed us to discover how the proportion of detected cases changed over the course of the epidemic. The role of time-varying reproduction number, capturing the effects of weather and changes in behaviour, was important in shaping the epidemic.     

Pathway-Based Genomics Prediction using Generalized Elastic Net

We present a novel regularization scheme called The Generalized Elastic Net (GELnet) that incorporates gene pathway information into feature selection. The proposed formulation is applicable to a wide variety of problems in which the interpretation of predictive features using known molecular interactions is desired. The method naturally steers solutions toward sets of mechanistically interlinked genes. Using experiments on synthetic data, we demonstrate that pathway-guided results maintain, and often improve, the accuracy of predictors even in cases where the full gene network is unknown. We apply the method to predict the drug response of breast cancer cell lines. GELnet is able to reveal genetic determinants of sensitivity and resistance for several compounds. In particular, for an EGFR/HER2 inhibitor, it finds a possible trans-differentiation resistance mechanism missed by the corresponding pathway agnostic approach.     

Sequentially Deposited versus Conventional Nonfullerene Organic Solar Cells: Interfacial Trap States,Vertical Stratification,and Exciton Dissociation

Bulk heterojunction (BHJ) nonfullerene organic solar cells prepared from sequentially deposited donor and acceptor layers (sq‐BHJ) have recently been shown to be highly efficient, environmentally friendly, and compatible with large area and roll‐to‐roll fabrication. However, the related photophysics at donor‐acceptor interface and the vertical heterogeneity of donor‐acceptor distribution, critical for exciton dissociation and device performance, have been largely unexplored. Herein, steady‐state and time‐resolved optical and electrical techniques are employed to characterize the interfacial trap states. Correlating with the luminescent efficiency of interfacial states and its nonradiative recombination, interfacial trap states are characterized to be about 40% more populated in the sq‐BHJ devices than the as‐cast BHJ (c‐BHJ), which probably limits the device voltage output. Cross‐sectional energy‐dispersive X‐ray spectroscopy and ultraviolet photoemission spectroscopy depth profiling directly visualize the donor–acceptor vertical stratification with a precision of 1–2 nm. From the proposed “needle” model, the high exciton dissociation efficiency is rationalized. This study highlights the promise of sequential deposition to fabricate efficient solar cells, and points toward improving the voltage output and overall device performance via eliminating interfacial trap states.     

Optical coherence tomography to detect acute esophageal radiation‐induced damage in mice: A validation study

Radiation therapy for patients with non‐small‐cell lung cancer is hampered by acute radiation‐induced toxicity in the esophagus. This study aims to validate that optical coherence tomography (OCT), a minimally invasive imaging technique with high resolution (~10 μm), is able to visualize and monitor acute radiation‐induced esophageal damage (ARIED) in mice. We compare our findings with histopathology as the gold standard. Irradiated mice receive a single dose of 40 Gy at proximal and distal spots of the esophagus of 10.0 mm in diameter. We scan mice using OCT at two, three, and seven days post‐irradiation. In OCT analysis, we define ARIED as a presence of distorted esophageal layering, change in backscattering signal properties, or change in the esophageal wall thickness. The average esophageal wall thickness is 0.53 mm larger on OCT when ARIED is present based on histopathology. The overall sensitivity and specificity of OCT to detect ARIED compared to histopathology are 94% and 47%, respectively. However, the overall sensitivity of OCT to assess ARIED is 100% seven days post‐irradiation. We validate the capability of OCT to detect ARIED induced by high doses in mice. Nevertheless, clinical studies are required to assess the potential role of OCT to visualize ARIED in humans.      

Evolution of the genetic code: partial optimization of a random code for robustness to translation error in a rugged fitness landscape

Background  

The standard genetic code table has a distinctly non-random structure, with similar amino acids often encoded by codons series that differ by a single nucleotide substitution, typically, in the third or the first position of the codon. It has been repeatedly argued that this structure of the code results from selective optimization for robustness to translation errors such that translational misreading has the minimal adverse effect. Indeed, it has been shown in several studies that the standard code is more robust than a substantial majority of random codes. However, it remains unclear how much evolution the standard code underwent, what is the level of optimization, and what is the likely starting point.