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Introduction: DNA strand displacement reactions are emerging as a promising biocomputing tool. The minimum spanning tree problem is fundamental in graph theory. This paper explores the use of DNA strand displacement reaction networks for addressing the minimum spanning tree problem. We also present a computing model that is based on DNA strand displacement reactions.
Method: The model effectively solves the minimum spanning tree problem by intelligently integrating the three reaction modules of weighted, threshold, and sum. Thus, initially, we encoded the edges in the graph using distinct DNA sequences and effectively assigned the edges their respective weights. Afterwards, the threshold module applied a filter to the weighted edges based on the fluorescence intensity. Ultimately, the sum module gathered the filtered edges to calculate the overall weight of the minimum spanning tree. In order to verify the effectiveness of the proposed method, we conducted simulation experiments using visual DSD software.
Result: The results of the simulations showed the viability and precision of this DNA computing model in resolving intricate problems.
Conclusion: Furthermore, this study not only confirms the capability of DNA computing in solving problems related to graph theory, but also offers significant theoretical backing and experimental foundation for the future advancement of DNA-based computer systems and biocomputing applications.
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http://dx.doi.org/10.2174/0113862073360358250128094601 | DOI Listing |
J R Soc Interface
September 2025
Department of Bioengineering, Imperial College London, London, UK.
Insects and plants have been locked in an evolutionary arms race spanning 350 million years. Insects evolved specialized tools to cut into plant tissue, and plants, to counter these attacks, developed diverse defence strategies. Much previous worked has focused on chemical defences.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
College of Agriculture and Biological Science, Dali University, Dali 671000, China.
The E76K mutation in protein tyrosine phosphatase (PTP) SHP2 is a recurrent driver of developmental disorders and cancers, yet the mechanism by which this single-site substitution promotes persistent activation remains elusive. Here, we combine path-based conformational sampling, unbiased molecular dynamics (MD) simulations, Markov state models (MSMs), and neural relational inference (NRI) to elucidate how E76K reshapes the activation landscape and regulatory architecture of SHP2. Using a minimum-action trajectory derived from experimentally determined closed and open structures, we generated representative transition intermediates to guide the unbiased MD simulations.
View Article and Find Full Text PDFmSphere
September 2025
Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
The ferret model is widely used to study influenza A viruses (IAVs) isolated from multiple avian and mammalian species, as IAVs typically replicate in the respiratory tract of ferrets without the need for prior host adaptation. During standard IAV risk assessments, tissues are routinely collected from ferrets at a fixed time point post-inoculation to assess the capacity for systemic spread. Here, we describe a data set of virus titers in tissues collected from both respiratory tract and extrapulmonary sites 3 days post-inoculation from over 300 ferrets inoculated with more than 100 unique IAVs (inclusive of H1, H2, H3, H5, H7, and H9 IAV subtypes, both mammalian and zoonotic origin).
View Article and Find Full Text PDFThe architecture of an ant colony's nest entrance modulates the regulation of activity in and out of the nest. This study considers how the architecture of nests of the desert harvester ant facilitates the regulation of foraging activity in an arid environment. Colonies must spend water, in water lost to evaporation when outside the nest, to obtain food and water.
View Article and Find Full Text PDFAIDS Patient Care STDS
September 2025
Department of Medicine and Dentistry, University of Rochester, Rochester, New York, USA.
Structural inequities significantly shape disparities across the HIV care continuum, yet few validated tools exist to quantify HIV-specific structural vulnerability at the population level in the United States. This study introduces and validates the HIV-Specific Social and Structural Determinants of Health Index (HIV-SSDI), a multi-dimensional, state-level index designed to capture structural disadvantage relevant to HIV prevention and care. Using publicly available state-level index (2008-2023) spanning nine structural domains, we developed the HIV-SSDI through exploratory factor analysis with three extraction methods: principal component analysis, maximum likelihood, and minimum residual.
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