Transcriptomic Analysis Exploring the Molecular Mechanisms of Hanchuan Zupa Granules in Alleviating Asthma in Rat

Yin, Hai-Long; Fan, Yanbo; Mu, Dandan; Song, Fei; Tian, Fang; Yin, Qiang

doi:10.1155/2021/5584099

Cited by 3 publications

(1 citation statement)

References 54 publications

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“…In the EBI QuickGO database the term GO:0042287 is further described as ‘Binding to a major histocompatibility complex molecule; a set of molecules displayed on cell surfaces that are responsible for lymphocyte recognition and antigen presentation’. In the RNA-seq example, the selected biological process ‘macrophage activation’ (GO:0042116) was also mentioned in the context of Asthma [ 37 ]. Furthermore, the molecular function ‘antigen binding’ (GO:00003823) was found to be enriched in a study on early-stage lung carcinoma [ 38 ].…”

Section: Discussionmentioning

confidence: 99%

Augmentation of Transcriptomic Data for Improved Classification of Patients with Respiratory Diseases of Viral Origin

Kircher¹,

Chludzinski²,

Krepel³

et al. 2022

IJMS

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To better understand the molecular basis of respiratory diseases of viral origin, high-throughput gene-expression data are frequently taken by means of DNA microarray or RNA-seq technology. Such data can also be useful to classify infected individuals by molecular signatures in the form of machine-learning models with genes as predictor variables. Early diagnosis of patients by molecular signatures could also contribute to better treatments. An approach that has rarely been considered for machine-learning models in the context of transcriptomics is data augmentation. For other data types it has been shown that augmentation can improve classification accuracy and prevent overfitting. Here, we compare three strategies for data augmentation of DNA microarray and RNA-seq data from two selected studies on respiratory diseases of viral origin. The first study involves samples of patients with either viral or bacterial origin of the respiratory disease, the second study involves patients with either SARS-CoV-2 or another respiratory virus as disease origin. Specifically, we reanalyze these public datasets to study whether patient classification by transcriptomic signatures can be improved when adding artificial data for training of the machine-learning models. Our comparison reveals that augmentation of transcriptomic data can improve the classification accuracy and that fewer genes are necessary as explanatory variables in the final models. We also report genes from our signatures that overlap with signatures presented in the original publications of our example data. Due to strict selection criteria, the molecular role of these genes in the context of respiratory infectious diseases is underlined.

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Section: Discussionmentioning

confidence: 99%

Augmentation of Transcriptomic Data for Improved Classification of Patients with Respiratory Diseases of Viral Origin

Kircher¹,

Chludzinski²,

Krepel³

et al. 2022

IJMS

View full text Add to dashboard Cite

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Biosensor‐based active ingredient recognition system for screening potential small molecular Severe acute respiratory syndrome coronavirus 2 entry blockers targeting the spike protein from Rugosa rose

Yu,

Yi,

Jiang

et al. 2024

Biomedical Chromatography

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The traditional formulation Hanchuan zupa granules (HCZPs) have been widely used for controlling coronavirus disease 2019 (COVID‐19). However, its active components remain unknown. Here, HCZP components targeting the spike receptor‐binding domain (S‐RBD) of SARS‐CoV‐2 were investigated using a surface plasmon resonance (SPR) biosensor‐based active ingredient recognition system (SPR‐AIRS). Recombinant S‐RBD proteins were immobilized on the SPR chip by amine coupling for the prescreening of nine HCZP medicinal herbs. Ultra‐performance liquid chromatography‐tandem mass spectrometry (UPLC‐MS/MS) identified gallic acid (GA) and methyl gallate (MG) from Rosa rugosa as S‐RBD ligands, with KD values of 2.69 and 0.95 μM, respectively, as shown by SPR. Molecular dynamics indicated that GA formed hydrogen bonds with G496, N501, and Y505 of S‐RBD, and MG with G496 and Y505, inhibiting S‐RBD binding to angiotensin‐converting enzyme 2 (ACE2). SPR‐based competition analysis verified that both compounds blocked S‐RBD and ACE2 binding, and SPR demonstrated that GA and MG bound to ACE2 (KD = 5.10 and 4.05 μM, respectively), suggesting that they blocked the receptor and neutralized SARS‐CoV‐2. Infection with SARS‐CoV‐2 pseudovirus showed that GA and MG suppressed viral entry into 293T‐ACE2 cells. These S‐RBD inhibitors have potential for drug design, while the findings provide a reference on HCZP composition and its use for treating COVID‐19.

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Zi-Su-Zi decoction improves airway hyperresponsiveness in cough-variant asthma rat model through PI3K/AKT1/mTOR, JAK2/STAT3 and HIF-1α/NF-κB signaling pathways

Nguyen

Zhang

Pan

et al. 2023

Journal of Ethnopharmacology

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Transcriptomic Analysis Exploring the Molecular Mechanisms of Hanchuan Zupa Granules in Alleviating Asthma in Rat

Cited by 3 publications

References 54 publications

Augmentation of Transcriptomic Data for Improved Classification of Patients with Respiratory Diseases of Viral Origin

Augmentation of Transcriptomic Data for Improved Classification of Patients with Respiratory Diseases of Viral Origin

Biosensor‐based active ingredient recognition system for screening potential small molecular Severe acute respiratory syndrome coronavirus 2 entry blockers targeting the spike protein from Rugosa rose

Zi-Su-Zi decoction improves airway hyperresponsiveness in cough-variant asthma rat model through PI3K/AKT1/mTOR, JAK2/STAT3 and HIF-1α/NF-κB signaling pathways

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