Publications by authors named "A Yepes"

In this work, we developed potential multifunctional agents to combat Alzheimer's disease. According to our strategy, fragments of tacrine and donepezil were merged in a unique hybrid structure. After successfully synthesizing the compounds, they were evaluated for their dual AChE/BuChE inhibitor potential and neuroprotector response using a glutamate-induced excitotoxicity model.

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Background: Human herpesvirus 6B (HHV-6B) frequently reactivates following allogeneic stem cell transplant (alloHCT). Consensus guidelines note that haploidentical alloHCT may represent a high-risk population for which there is little evidence; this warrants further investigation.

Methods: In this single-center retrospective study, we evaluated 188 consecutive adult patients receiving haploidentical alloHCT between 11/2014 and 11/2020 and compared outcomes between patients with HHV-6B reactivation receiving targeted antiviral therapy and those who were clinically observed.

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Teaching medical rounds in intensive care units (ICUs) are essential for resident education. However, the ICU's high workload can hinder these rounds. We propose a new approach that is based on the constructivist theory of learning communities.

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Article Synopsis
  • Shock is a critical condition that can lead to organ failure if not recognized and treated quickly, especially in the ICU where it's frequently seen.
  • A review introduces an ultrasound-based protocol to assess hemodynamics in shock, categorizing it by cardiac index and identifying its different causes like obstructive, hypovolemic, cardiogenic, and distributive shock.
  • Utilizing critical care ultrasound helps clinicians not only diagnose the type of shock but also tailor the treatment effectively while monitoring patient progress, improving overall outcomes.
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In fully supervised learning-based medical image classification, the robustness of a trained model is influenced by its exposure to the range of candidate disease classes. Generalized Zero Shot Learning (GZSL) aims to correctly predict seen and novel unseen classes. Current GZSL approaches have focused mostly on the single-label case.

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