Besides the dog, the fecal carriage of K. pneumoniae was also detected in a pet turtle. This turtle isolate was resistant to multiple antimicrobials, including carbapenems. Possible transmission of drug-resistant K. pneumoniae through human-pet bonds warrants our attention.Glaesserella parasuis (G. parasuis) is an important pathogenic bacterium that can cause Glässer’s disease, and it has resulted in tremendous economic losses to the global swine industry. The intensive pulmonary inflammatory response caused by G. parasuis infection is the main cause of lung injury and death in pigs. However, the exact mechanism by which it causes severe pulmonary inflammation is not fully understood yet. In this study, severe pneumonia was observed in piglets infected with G. parasuis; and an infection cell model was established using porcine alveolar macrophages cell line 3D4/21, which was determined to be susceptible to G. parasuis infection in vitro. G. parasuis infection of 3D4/21 cells induced upregulation of proinflammatory cytokines TNF-α, IL-1β, IL-18 and production of intracellular reactive oxygen species (ROS). The expression of IL-1β related to activation of the NLRP3 inflammasome signaling pathway, which had not been shown before in G. parasuis infection. Furthermore, it was first found that release of intracellular ROS, which was mediated by NADPH oxidase in 3D4/21 cells, was found crucial for the activation of the NLRP3 signaling pathway and promoted the expression of proinflammatory cytokines, such as TNF-α and IL-1. In general, this study explored the specific mechanism of severe pulmonary inflammation caused by G. parasuis infection, and provides a foundation for further elucidating the pathogenic mechanism of G. parasuis.

Xuebijing (XBJ) is a traditional Chinese patent medicine for sepsis. However, the mechanism of action (MoA) of XBJ on sepsis remain unclear.

Elucidate the MoA of XBJ for treating sepsis based on network pharmacology.

Integrate computational prediction, experimental validation and literature reported clinical results analysis based on network pharmacology.

Computationally, representative compounds of XBJ were characterized by LC-MS/MS and the target profiles of each compound were identified using network-based method. Compounds from XBJ were compared with FDA approved drugs or experimental agents for sepsis by hierarchical clustering of target profile. Key biological functional modules of XBJ for treating sepsis were identified by enrichment analysis. Differential expressed analysis for each biological functional module was conducted from sepsis related public omics datasets. Herb-biological functional module network was constructed to reveal part of the traditional combinatorial rules of herbs for modature reported clinical results, XBJ was found to exert anti-inflammatory effect through regulating the NF-kappa B signaling pathway.

The network pharmacology framework integrating computational prediction, experimental validation and literature reported clinical results analysis provides a novel approach for analyzing MoA of XBJ for treating sepsis.

The network pharmacology framework integrating computational prediction, experimental validation and literature reported clinical results analysis provides a novel approach for analyzing MoA of XBJ for treating sepsis.

Paridis Rhizoma (PR) is a famous traditional herbal medicine. Apart from two officially recorded species, viz. Paris polyphylla Smith var. yunnanensis (Franch.) Hand. – Mazz. (PPY) and P. polyphylla Smith var. chinensis (Franch.) Hara (PPC), there are still many other species used as folk medicine. It is necessary to understand the metabolic differences among Paris species.

To establish a strategy that can discover species-specific steroidal saponin markers to distinguish closely-related Paris herbs for quality and safety control.

A new strategy of molecular-networking-guided discovery of species-specific markers was proposed. Firstly, the ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) was applied to obtain the MS and MS/MS data of all samples. Then, molecular networking (MN) was created using MS/MS data to prescreen the steroidal saponins for subsequent analysis. DT2216 concentration Next, the principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA) models were established to discover potential markers. Finally, the verification, identification and distribution of chemical markers were performed.

A total of 126 steroidal saponins were screened out from five species using MN. Five species were classified successfully by OPLS-DA model, and 18 species-specific markers were discovered combining the variable importance in the projection (VIP) value, P value (one-way ANOVA) and their relative abundance. These markers could predict the species of Paris herbs correctly.

These results revealed that this new strategy could be an efficient way for chemical discrimination of medicinal herbs with close genetic relationship.

These results revealed that this new strategy could be an efficient way for chemical discrimination of medicinal herbs with close genetic relationship.

Qingfei Paidu Tang (QPT), a formula of traditional Chinese medicine, which was suggested to be able to ease symptoms in patients with Coronavirus Disease 2019 (COVID-19), has been recommended by clinical guidelines and widely used to treat COVID-19 in China. However, whether it decreases mortality remains unknown.

We aimed to explore the association between QPT use and in-hospital mortality among patients hospitalized for COVID-19.

A retrospective study based on a real-world database was conducted.

We identified patients consecutively hospitalized with COVID-19 in 15 hospitals from a national retrospective registry in China, from January through May 2020. Data on patients’ characteristics, treatments, and outcomes were extracted from the electronic medical records. The association of QPT use with COVID-19 related mortality was evaluated using Cox proportional hazards models based on propensity score analysis.

Of the 8939 patients included, 28.7% received QPT. The COVID-19 related mortality was 1.2% (95% confidence interval [CI] 0.