Characterization of DNA\u27s from several Neurospora species

Characterization of DNA\u27s from several Neurospora specie

Validation of a Novel Sensing Approach for Continuous Pavement Monitoring Using Full-Scale APT Testing

The objective of this paper is to present a novel approach for the continuous monitoring of pavement condition through the use of combined piezoelectric sensing and novel condition-based interpretation methods. The performance of the developed approach is validated for the detection of bottom-up fatigue cracking through full-scale accelerated pavement testing (APT). The innovative piezoelectric sensors are installed at the bottom of a thin 102 mm (4 in.) asphalt layer. The structure is then loaded until failure (up to 1 million loading cycles in this study). The condition-based approach, used in this work, does not rely on stain measurements and allows users to bypass the need for any structural or finite-element models. Instead, the data compression approach relies on variations in strain energy harvested by smart sensors to track changes in material and structural conditions. Falling weight deflectometer (FWD) measurements and visual inspections were used to validate the observations from the sensing system. The results in this paper present a first large-scale validation in pavement structures for a piezopowered sensing system combined with a new response-only based approach for data reduction and interpretation. The proposed data analysis method has demonstrated a very early detection capability compared to classical inspection methods, which unveils a huge potential for improved pavement monitoring

Spin order dependent skyrmion stabilization in MnFeCoGe hexagonal magnets

Topological magnetic skyrmions in centrosymmetric systems exhibit a higher degrees of freedom in their helicity, hence possess a great potential in the advanced spintronics including skyrmion based quantum computation. However, the centrosymmetric magnets also display non-topological trivial bubbles along with the topological skyrmions. Hence it is utmost priority to investigate the impact of different magnetic ground states and their underlying interactions on the stabilization of magnetic skyrmions in cetrosymmetric magnets. Here, we present a combined theoretical and experimental study on the role of non-collinear magnetic ground state on the skyrmion stabilization in a series of exchange frustrated non-collinear ferromagnetic system MnFe1-xCoxGe. With the help of neutron diffraction (ND) and Lorentz transmission electron microscopy (LTEM) studies, we show that hexagonal skyrmions lattice emerges as a stable field driven state only when the underlying magnetic ground state is collinear with easy-axis anisotropy. In contrast, non-topological type-II bubbles are found to be stable state in the case of non-collinear magnetic ordering with partial in-plane anisotropy. Furthermore, we also find that the skyrmions transform to the non-topological bubbles when the system undergoes a spin reorientation transition from the easy-axis to easy-cone ferromagnetic phase. Our results categorically establish the significant role of in-plane magnetic moment/anisotropy that hinders the stability of skyrmion both in the case of collinear and non-collinear magnets. Thus, the present study offers a wide range of opportunities to manipulate the stability of dipolar skyrmions by changing the intrinsic characteristics of the materials.Comment: 18 pages, 4 figure

An effective all-atom potential for proteins

We describe and test an implicit solvent all-atom potential for simulations of protein folding and aggregation. The potential is developed through studies of structural and thermodynamic properties of 17 peptides with diverse secondary structure. Results obtained using the final form of the potential are presented for all these peptides. The same model, with unchanged parameters, is furthermore applied to a heterodimeric coiled-coil system, a mixed alpha/beta protein and a three-helix-bundle protein, with very good results. The computational efficiency of the potential makes it possible to investigate the free-energy landscape of these 49--67-residue systems with high statistical accuracy, using only modest computational resources by today's standards

Structure and evolutionary origin of Ca2+-dependent herring type II antifreeze protein

10.1371/journal.pone.0000548PLoS ONE26

Deciphering the Preference and Predicting the Viability of Circular Permutations in Proteins

Circular permutation (CP) refers to situations in which the termini of a protein are relocated to other positions in the structure. CP occurs naturally and has been artificially created to study protein function, stability and folding. Recently CP is increasingly applied to engineer enzyme structure and function, and to create bifunctional fusion proteins unachievable by tandem fusion. CP is a complicated and expensive technique. An intrinsic difficulty in its application lies in the fact that not every position in a protein is amenable for creating a viable permutant. To examine the preferences of CP and develop CP viability prediction methods, we carried out comprehensive analyses of the sequence, structural, and dynamical properties of known CP sites using a variety of statistics and simulation methods, such as the bootstrap aggregating, permutation test and molecular dynamics simulations. CP particularly favors Gly, Pro, Asp and Asn. Positions preferred by CP lie within coils, loops, turns, and at residues that are exposed to solvent, weakly hydrogen-bonded, environmentally unpacked, or flexible. Disfavored positions include Cys, bulky hydrophobic residues, and residues located within helices or near the protein's core. These results fostered the development of an effective viable CP site prediction system, which combined four machine learning methods, e.g., artificial neural networks, the support vector machine, a random forest, and a hierarchical feature integration procedure developed in this work. As assessed by using the hydrofolate reductase dataset as the independent evaluation dataset, this prediction system achieved an AUC of 0.9. Large-scale predictions have been performed for nine thousand representative protein structures; several new potential applications of CP were thus identified. Many unreported preferences of CP are revealed in this study. The developed system is the best CP viability prediction method currently available. This work will facilitate the application of CP in research and biotechnology

Identifying contextual determinants of problems in tuberculosis care provision in South Africa: a theory-generating case study

Background: Despite progress towards End TB Strategy targets for reducing tuberculosis (TB) incidence and deaths by 2035, South Africa remains among the top ten high-burden tuberculosis countries globally. A large challenge lies in how policies to improve detection, diagnosis and treatment completion interact with social and structural drivers of TB. Detailed understanding and theoretical development of the contextual determinants of problems in TB care is required for developing effective interventions. This article reports findings from the pre-implementation phase of a study of TB care in South Africa, contributing to HeAlth System StrEngThening in Sub-Saharan Africa (ASSET)—a five-year research programme developing and evaluating health system strengthening interventions in sub-Saharan Africa. The study aimed to develop hypothetical propositions regarding contextual determinants of problems in TB care to inform intervention development to reduce TB deaths and incidence whilst ensuring the delivery of quality integrated, person-centred care. Methods Theory-building case study design using the Context and Implementation of Complex Interventions (CICI) framework to identify contextual determinants of problems in TB care. Between February and November 2019, we used mixed methods in six public-sector primary healthcare facilities and one public-sector hospital serving impoverished urban and rural communities in the Amajuba District of KwaZulu-Natal Province, South Africa. Qualitative data included stakeholder interviews, observations and documentary analysis. Quantitative data included routine data on sputum testing and TB deaths. Data were inductively analysed and mapped onto the seven CICI contextual domains. Results: Delayed diagnosis was caused by interactions between fragmented healthcare provision; limited resources; verticalised care; poor TB screening, sputum collection and record-keeping. One nurse responsible for TB care, with limited integration of TB with other conditions, and policy focused on treatment adherence contributed to staff stress and limited consideration of patients’ psychosocial needs. Patients were lost to follow up due to discontinuity of information, poverty, employment restrictions and limited support for treatment side-effects. Infection control measures appeared to be compromised by efforts to integrate care. Conclusions: Delayed diagnosis, limited psychosocial support for patients and staff, patients lost to follow-up and inadequate infection control are caused by an interaction between multiple interacting contextual determinants. TB policy needs to resolve tensions between treating TB as epidemic and individually-experienced social problem, supporting interventions which strengthen case detection, infection control and treatment, and also promote person-centred support for healthcare professionals and patients