ABSTRACT
Depression is a prevalent mental disorder. However, clinical treatment options primarily based on chemical drugs have demonstrated varying degrees of adverse reactions and drug resistance, including somnolence, nausea, and cognitive impairment. Therefore, the development of novel antidepressant medications that effectively reduce suffering and side effects has become a prominent area of research. Polysaccharides are bioactive compounds extracted from natural plants that possess diverse pharmacological activities and medicinal values. It has been discovered that polysaccharides can effectively mitigate depression symptoms. This paper provides an overview of the pharmacological action and mechanisms, intervention approaches, and experimental models regarding the antidepressant effects of polysaccharides derived from various natural sources. Additionally, we summarize the roles and potential mechanisms through which these polysaccharides prevent depression by regulating neurotransmitters, HPA axis, neurotrophic factors, neuroinflammation, oxidative stress, tryptophan metabolism, and gut microbiota. Natural plant polysaccharides hold promise as adjunctive antidepressants for prevention, reduction, and treatment of depression by exerting their therapeutic effects through multiple pathways and targets. Therefore, this review aims to provide scientific evidence for developing polysaccharide resources as effective antidepressant drugs.
ABSTRACT
Non-coding RNAs (ncRNAs) are a class of RNA molecules that do not have the potential to encode proteins. Meanwhile, they can occupy a significant portion of the human genome and participate in gene expression regulation through various mechanisms. Gestational diabetes mellitus (GDM) is a pathologic condition of carbohydrate intolerance that begins or is first detected during pregnancy, making it one of the most common pregnancy complications. Although the exact pathogenesis of GDM remains unclear, several recent studies have shown that ncRNAs play a crucial regulatory role in GDM. Herein, we present a comprehensive review on the multiple mechanisms of ncRNAs in GDM along with their potential role as biomarkers. In addition, we investigate the contribution of deep learning-based models in discovering disease-specific ncRNA biomarkers and elucidate the underlying mechanisms of ncRNA. This might assist community-wide efforts to obtain insights into the regulatory mechanisms of ncRNAs in disease and guide a novel approach for early diagnosis and treatment of disease.