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Enregistrement W4411962979 · doi:10.3389/fphar.2025.1630486

Editorial: Use of bioactives for treatment of respiratory diseases

2025· editorial· en· W4411962979 sur OpenAlexaff
Alan Aguiar Lopes, Akinori Cardozo Nagato, Frank Silva Bezerra, Samuel Santos Valença, Sabina A Antoniu

Notice bibliographique

RevueFrontiers in Pharmacology · 2025
Typeeditorial
Langueen
DomaineMedicine
ThématiqueHerbal Medicine Research Studies
Établissements canadiensConcordia University
Organismes subventionnairesnon disponible
Mots-clésMedicineIntensive care medicineTraditional medicinePharmacologyDermatology

Résumé

récupéré en direct d'OpenAlex

In this Research Topic, eight articles were published including a review paper, a study case study, and research papers.Initially, the review paper of Hufnagel et al. discusses the role of caffeoylquinic acids (DCQAs) in respiratory diseases. This article presents up-to-date information about the pharmacological properties of those molecules. Those properties translate into their pharmacodynamics, antioxidant, and anti-inflammatory activity. This article also reviews the mechanisms of action of the DCQAs including NF-κB and Nrf2 pathways and reduction of oxidative stress. This review paper presents a compounds that are worth further to investigate as antitussive agents.As a study case, the study of Wang et al. investigated the interrelation between the protective effect of aspirin to community-acquired pneumonia (CAP) in patients requiring ICU stay. Analyzing the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, the authors observed the relationship between aspirin and reduced 28-day mortality. The dose of 81mg/day of aspirin showed less negative effect over the patients than 325 mg/day because the patients treated with the latter dose of aspirin stayed longer in intensive care unit (ICU).In terms of original papers, there are three original papers that investigated the effect of BM on respiratory diseases using pharmacologic network (PN). First, the study of Feng et al. investigated the mechanism of aloin to treat the combined allergic rhinitis and asthma syndrome (CARAS). This research employed PN with molecular docking, molecular dynamics and experimental approach to investigate the main molecular targets of aloin and the anti-inflammatory effect of this bioactive molecule on ovalbulmin-induced CARAS in mice. As a result, aloin modulated CARAS by inhibiting inflammation and downregulating MAPK signaling-related proteins.Second, Xie et al. investigated the mechanism of action of Qibai Pingfei Capsule (QBPF) applying PN and metabolomics. This study identified 16 of 96 metabolites were reversed in the murine COPD model after the treatment with QBPF. Additionally, eighteen compounds of QBPF including fumarine and kaempferol presented strong affinity to prostagladinendoperoxide synthase 2 (PTGS2). Since PTGS2 is a marker of ferroptosis and it is inhibited by QBPF, the result of this study indicates the ferroptosis is involved with COPD pathogenesis.Third, Qin et al. studied the treatment of asthmatic mice with Bushenyiqi decoction (BYD) employing PN. The mechanism of action and pharmacological effects of BYD in asthma remain unclear; although, the authors employed PN to obtain an initial theoretical relationship between BYD and asthma-related genes. Furthermore, the researchers experimentally analyzed that relationship applying physiological, immunological, and histological assessments in allergic asthma mice. The PN analysis showed the phosphatidylinositol3 kinase-RAC-α serine/threonine-protein kinase (PI3K/AKT) signaling pathway as a part of the mechanism of action of BYD for asthma treatment. In the experimental study, results indicated the BYD controls the airway inflammation and boost the airway responsiveness. In addition, their results show the anti-inflammatory effects of BYD because to quercetin, kaempferol, and luteolin, its bioactive molecules.Concerning about pulmonary fibrosis, the study of Tsai et al. focused on studying the properties of imperatonin on pulmonary fibroblasts. Analyzing the effects of imperatonin on bleomycin-exposed mice, the zymosan-induced upregulation of connective tissue growth factor (CTGF), α-smooth muscle actin (α-SMA), and collagen protein was diminished. Moreover, imperatonin presented a preventive effect on bleomycin-induced pulmonary fibrosis.Regarding the asthma-chronic obstructive pulmonary disease overlap (ACO), the research of João et al. analyzed plant-derived peptides in a murine model of ACO. This In vivo study explored the effects of those peptides on ACO on physiological, immunological, and biochemical markers such as airway resistance, cytokine expression, and oxidative stress, respectively. Those peptides presented similar effects as corticosteroids in reversing the ACO responses including the effect of the peptides on regulating the hyperresponsiveness, inflammation, remodeling, and oxidative stress markers.Finally, the paper of Chernov et al. describes the effect of nonpeptide compound TAK-779, an antagonist of CCR5/CXCR3, for the treatment of acute respiratory distress syndrome (ARDS). ARSD has been described as the main causes of high mortality in patients with COVID-19. Employing the in-house produced method of the unilateral diffuse alveolar damage (DAD) in ICR mice, the authors observed the upregulation of two C-C chemokine receptor 5 (CCR5) ligands, macrophage inflammatory proteins (MIPs) MIP-1α/CCL3 and MIP-1β/CCL4. However, the single administration of TAK-779 showed a reduction of cellular infiltration in the lung tissue as well as the decreases of inflammatory markers in animals with DAD. Those results open the possibility of use of CCR5 inhibitors for the treatment of virus-induced hyperinflammation syndromes, including COVID-19.In summary, this research topic has shown the importance of the bioactive molecules for the treatment of respiratory diseases as well as the mechanisms of these molecules, and the different types of studies in animals and patients. However, more studies including clinical trials are necessary to elucidate and confirm this kind of properties in our research literature.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,035
Tête enseignante GPT0,408
Écart entre enseignants0,373 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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