Publications by authors named "Mayk Caldas Ramos"

Impaired wound healing due to insufficient cell proliferation and angiogenesis is a significant physical and psychological burden to patients worldwide. Therapeutic delivery of exogenous growth factors (GFs) at high doses for wound repair is non-ideal as GFs have poor stability in proteolytic wound environments. Here, we present a two-stage strategy using bioactive sucralfate-based microneedle (SUC-MN) for delivering interleukin-4 (IL-4) to accelerate wound healing.

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Aqueous solubility is a valuable yet challenging property to predict. Computing solubility using first-principles methods requires accounting for the competing effects of entropy and enthalpy, resulting in long computations for relatively poor accuracy. Data-driven approaches, such as deep learning, offer improved accuracy and computational efficiency but typically lack uncertainty quantification.

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Article Synopsis
  • Large-language models like GPT-4 have sparked interest among scientists, especially in fields like chemistry and materials science.
  • A hackathon was organized to explore their potential applications, resulting in various projects such as predicting molecular properties and developing educational tools.
  • The rapid prototyping of ideas within the hackathon suggests that LLMs could significantly influence multiple scientific disciplines beyond just chemistry and materials science.
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