Publications by authors named "Feiyang Na"

Background: Childhood obesity is a global public health issue, and the status of clinical practice guidelines (CPGs) as instruction manuals for the management of childhood obesity remains unclear. This study aims to identify and apprise the methodological and reporting quality of CPGs focused on childhood obesity and provide an overview of key recommendations.

Methods: Databases and websites reporting guidelines were searched from January, 2018 to September, 2023.

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Article Synopsis
  • Respiratory syncytial virus (RSV) is a major cause of serious respiratory infections in children under 5, highlighting the need for effective prevention methods.* -
  • This study conducted a systematic review comparing the efficacy and safety of monoclonal antibodies in protecting infants from RSV, analyzing data from randomized clinical trials.* -
  • Results showed that monoclonal antibodies like nirsevimab, palivizumab, and motavizumab significantly reduced RSV-related hospitalizations and infections compared to placebo, providing moderate to high-certainty evidence of their effectiveness.*
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Background: Cuproptosis is the most recently identified form of cell death, and copper homeostasis is an important cancer therapeutic target. However, the therapeutic benefits of cuproptosis-targeted treatment in BRCA remain undetermined. This study utilized LncRNAs linked to cuproptosis genes and immune checkpoint genes to generate a BRCA predictive signature.

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Background: Paediatric pleural tuberculosis (TB) is a paucibacillary disease, which increases the difficulty of examination. We aimed to assess the performance of pleural fluid adenosine deaminase (ADA) in the detection of paediatric pleural TB.

Methods: PubMed, Web of Science Core Collection, Embase and Cochrane Library databases were searched up to 20 December 2021.

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Human asthma is caused by interactions between a range of genetic and environmental factors. However, the specific pathogenesis of asthma remains controversial. This study explored the contribution of DNA methylation to asthma using computer learning methods.

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