Publications by authors named "R B Adkins"

Article Synopsis
  • The study analyzes how a boundary between a passive fluid and an active fluid made of microtubules behaves, especially under turbulence-like conditions.
  • It finds that strong active flows cause the boundary to have pronounced asymmetries and local vortices, which disrupts spatial symmetry and leads to significant fluctuations at the interface.
  • As the activity level increases, the interface deforms more dramatically, eventually folding in on itself and creating a foam-like structure with passive droplets embedded within the active fluid.
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Objective: To use online screening and virtual patient education tools to improve the provision of hereditary cancer risk assessment.

Methods: We conducted a prospective, single-arm study in which clinicians at five U.S.

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Modulation of neurotransmission is key for organismal responses to varying physiological contexts such as during infection, injury, or other stresses, as well as in learning and memory and for sensory adaptation. Roles for cell autonomous neuromodulatory mechanisms in these processes have been well described. The importance of cell non-autonomous pathways for inter-tissue signaling, such as gut-to-brain or glia-to-neuron, has emerged more recently, but the cellular mechanisms mediating such regulation remain comparatively unexplored.

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RNA transcripts are potential therapeutic targets, yet bacterial transcripts have uncharacterized biodiversity. We developed an algorithm for transcript prediction called tp.py using it to predict transcripts (mRNA and other RNAs) in K12 and E2348/69 strains (Bacteria:gamma-Proteobacteria), strains Scott A and RO15 (Bacteria:Firmicute), strains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), and (Archaea:Halobacteria).

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Transcripts are potential therapeutic targets, yet bacterial transcripts remain biological dark matter with uncharacterized biodiversity. We developed and applied an algorithm to predict transcripts for Escherichia coli K12 and E2348/69 strains (Bacteria:gamma-Proteobacteria) with newly generated ONT direct RNA sequencing data while predicting transcripts for Listeria monocytogenes strains Scott A and RO15 (Bacteria:Firmicute), Pseudomonas aeruginosa strains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), and Haloferax volcanii (Archaea:Halobacteria) using publicly available data. From >5 million E.

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