Publications by authors named "K Fraga"
Higher levels of plasmatic saturated fatty acid were significantly associated with liver fibrosis in HIV mono-infection: A case-control study.
Cristiane Fonseca de Almeida Wilza Arantes Ferreira Peres Paula Simplício da Silva Claudia Santos de Aguiar Cardoso Michelle Morata de Andrade Karla Yasmin Dias Fraga
Metabol Open
December 2024
Background: The relationship between plasmatic fatty acid (FA) composition and liver fibrosis remains scarce in people living with HIV/AIDS (PLWHA). We aimed to evaluate the association of plasmatic FAs and liver fibrosis in HIV mono-infected individuals.
Methods: This case-control study included PLWHA with liver fibrosis (cases) and randomly selected subjects without fibrosis (controls) from the PROSPEC-HIV study (NCT02542020).
Introduction: The needs of haemophilia carriers (HC) have been historically overlooked. It is now recognised that HC manifests bleeding symptoms, including haemarthrosis. The natural history of joint health in HC is not yet defined.
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- Female X-linked diseases are rare due to X chromosome inactivation, but Rett syndrome (RTT) is an exception caused by MECP2 mutations.
- In a study using mutant mice, researchers found sex differences in gene expression, with mutant females showing significantly more altered genes than males, even before symptoms appeared.
- The study highlights the importance of both cell type and interactions between different cell types in understanding RTT progression, suggesting potential avenues for treatment.
Article Synopsis
- Dominant X-linked diseases, like Rett syndrome (RTT), are rare because females have X chromosome inactivation, which usually protects against such mutations.
- RTT is a neurodevelopmental disorder that appears in girls after a period of normal development, leading to a regression of skills that researchers still don't fully understand.
- A study using single-nucleus RNA sequencing on a mouse model of RTT found significant sex differences in gene expression, revealing that mutant females had more affected genes than males, which could be vital for understanding disease progression and potential treatments.
Article Synopsis
- Advances in molecular modeling, particularly through AlphaFold-2 (AF2) from DeepMind, are revolutionizing structural biology by providing highly accurate protein structure predictions using AI.
- The study specifically tested AF2's ability to model small, monomeric proteins that were not part of its training data, using nine open-source NMR datasets.
- Results showed that AF2's predictions often matched or exceeded the fit of existing NMR structure models, highlighting its potential as a valuable tool for protein structure analysis and hypothesis generation in research.