Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Más filtros












Base de datos
Intervalo de año de publicación
1.
Int J Chron Obstruct Pulmon Dis ; 19: 1819-1834, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-39140079

RESUMEN

Purpose: Sangbaipi decoction (SBPD), a traditional Chinese medicine (TCM) prescription, has been widely used to treat acute exacerbation of chronic obstructive pulmonary disease (AECOPD), while the underlying pharmacological mechanism remains unclear due to the complexity of composition. Methods: A TCM-active ingredient-drug target network of SBPD was constructed utilizing the TCM-Systems-Pharmacology database. AECOPD-relevant proteins were gathered from Gene Cards and the Online-Mendelian-Inheritance-in-Man database. Protein-protein interaction, GO and KEGG enrichment analyses of the targets from the intersection of SBPD and AECOPD targets were performed to identify the core signaling pathway, followed by molecular docking verification of its interaction with active ingredients. The network pharmacology results were checked using in-vivo experiments. To induce AECOPD, rats were exposure to combined tobacco smoke and lipopolysaccharide (LPS). Then rats underwent gavage with stigmasterol (SM) after successful modeling. The involvement of phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) signaling was investigated using its inhibitor, LY294002. Lung function and histopathology were examined. The levels of inflammatory cytokines in the lung and serum were assessed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), Western blot and/or Enzyme-linked immunosorbent assay (ELISA). Results: SM was recognized as an active ingredient of SBPD and stably bound to Akt1. SM improved lung function and histological abnormalities, concomitant with suppressed PI3K/Akt signaling, downregulated lung and serum Interleukin 6 (IL-6) and tumor necrosis factor-α (TNF-α) levels and serum transforming growth factor-ß (TGF-ß) levels and upregulated lung and serum Interleukin 10 (IL-10) levels in AECOPD rats. In AECOPD rats, LY294002 restored lung function, and it also improved lung histological abnormalities and inflammation, which was found to be potentiated by SM. Conclusion: SM targets PI3K/Akt signaling to reduce lung injury and inflammation in AECOPD rats.


Asunto(s)
Medicamentos Herbarios Chinos , Pulmón , Farmacología en Red , Fosfatidilinositol 3-Quinasa , Proteínas Proto-Oncogénicas c-akt , Enfermedad Pulmonar Obstructiva Crónica , Estigmasterol , Animales , Masculino , Ratas , Antiinflamatorios/farmacología , Cromonas/farmacología , Citocinas/metabolismo , Citocinas/sangre , Modelos Animales de Enfermedad , Progresión de la Enfermedad , Medicamentos Herbarios Chinos/farmacología , Mediadores de Inflamación/metabolismo , Lipopolisacáridos , Pulmón/efectos de los fármacos , Pulmón/patología , Pulmón/metabolismo , Pulmón/fisiopatología , Simulación del Acoplamiento Molecular , Fosfatidilinositol 3-Quinasa/metabolismo , Fosfatidilinositol 3-Quinasas/metabolismo , Inhibidores de las Quinasa Fosfoinosítidos-3/farmacología , Mapas de Interacción de Proteínas , Proteínas Proto-Oncogénicas c-akt/metabolismo , Enfermedad Pulmonar Obstructiva Crónica/tratamiento farmacológico , Enfermedad Pulmonar Obstructiva Crónica/fisiopatología , Enfermedad Pulmonar Obstructiva Crónica/metabolismo , Ratas Sprague-Dawley , Reproducibilidad de los Resultados , Transducción de Señal/efectos de los fármacos , Estigmasterol/farmacología
2.
Biomimetics (Basel) ; 8(2)2023 Jun 17.
Artículo en Inglés | MEDLINE | ID: mdl-37366861

RESUMEN

Restructuring Particle Swarm Optimization (RPSO) algorithm has been developed as an intelligent approach based on the linear system theory of particle swarm optimization (PSO). It streamlines the flow of the PSO algorithm, specifically targeting continuous optimization problems. In order to adapt RPSO for solving discrete optimization problems, this paper proposes the binary Restructuring Particle Swarm Optimization (BRPSO) algorithm. Unlike other binary metaheuristic algorithms, BRPSO does not utilize the transfer function. The particle updating process in BRPSO relies solely on comparison results between values derived from the position updating formula and a random number. Additionally, a novel perturbation term is incorporated into the position updating formula of BRPSO. Notably, BRPSO requires fewer parameters and exhibits high exploration capability during the early stages. To evaluate the efficacy of BRPSO, comprehensive experiments are conducted by comparing it against four peer algorithms in the context of feature selection problems. The experimental results highlight the competitive nature of BRPSO in terms of both classification accuracy and the number of selected features.

SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA
...