Purpose This study aimed to investigate the molecular mechanisms of compound herba Sarcandrae aerosol, also known as the Fufang Zhongjiefeng (FFZJF) aerosol, in treating chronic pharyngitis (CP) using network pharmacology and in vivo experimental approaches. Methods Active compounds and putative targets of five herbs in FFZJF were identified from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Chemistry Database, and Swiss Target Prediction databases. The therapeutic targets of CP were obtained from OMIM, Durgbank, DisGeNT, and GAD databases. The active compounds-target networks were constructed using Cytoscape 3.6.1. The overlapping targets of FFZJF active compounds and CP targets were further analyzed using the String database to construct protein–protein interaction (PPI) network. KEGG pathway and Gene Ontology enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery. The predicted targets and pathways were validated in a group A β-hemolytic streptococcus-induced rat CP model. Results There were 45 active compounds identified from FFZJF and 11 potential protein targets identified for CP treatment. PPI network demonstrated that IL6, PTGS2, TLR-4, and TNF may serve as the key targets of FFZJF for the treatment of CP. The main functional pathways involving these key targets include cytokine secretion, inflammatory response, MyD88-dependent toll-like receptor signaling pathway, toll-like receptor signaling pathway, TNF signaling pathway, and NF-κB signaling pathway. In a rat CP model, the elevation of serum TNF-α, IL1β, and IL6 levels, as well as the upregulation of TLR-4, MyD88, NF-κB P65 in the pharyngeal mucosal tissues could be effectively reduced by FFZJF treatment in a dose-dependent manner. Conclusion Through a network pharmacology approach and animal study, we predicted and validated the active compounds of FFZJF and their potential targets for CP treatment. The results suggest that FFZJF can markedly alleviate GAS-induced chronic pharyngitis by modulating the TLR-4/MyD88/NF-κB signaling pathways.

No abstract

Background WW surveillance enables real time monitoring of SARS-CoV-2 burden in defined sewer catchment areas. Here, we assessed the occurrence of total, Delta and Omicron SARS-CoV-2 RNA in sewage from three tertiary-care hospitals in Calgary, Canada. Methods Nucleic acid was extracted from hospital (H) WW using the 4S-silica column method. H-1 and H-2 were assessed via a single autosampler whereas H-3 required three separate monitoring devices (a-c). SARS-CoV-2 RNA was quantified using two RT-qPCR approaches targeting the nucleocapsid gene; N1 and N200 assays, and the R203K/G204R and R203M mutations. Assays were positive if Cq< 40. Cross-correlation function analyses (CCF) was performed to determine the time-lagged relationships between WW signal and clinical cases. SARS-CoV-2 RNA abundance was compared to total hospitalized cases, nosocomial-acquired cases, and outbreaks. Statistical analyses were conducted using R. Results Ninety-six percent (188/196) of WW samples collected between Aug/21-Jan/22 were positive for SARS-CoV-2. Omicron rapidly supplanted Delta by mid-December and this correlated with lack of Delta-associated H-transmissions during a period of frequent outbreaks. The CCF analysis showed a positive autocorrelation between the RNA concentration and total cases, where the most dominant cross correlations occurred between -3 and 0 lags (weeks) (Cross-correlation values: 0.75, 0.579, 0.608, 0.528 and 0.746 for H-1, H-2, H-3a, H-3b and H-3c; respectively). VOC-specific assessments showed this positive association only to hold true for Omicron across all hospitals (cross-correlation occurred at lags -2 and 0, CFF value range between 0.648 -0.984). We observed a significant difference in median copies/ml SARS-CoV-2 N-1 between outbreak-free periods vs outbreaks for H-1 (46 [IQR: 11-150] vs 742 [IQR: 162-1176], P< 0.0001), H-2 (24 [IQR: 6-167] vs 214 [IQR: 57-560], P=0.009) and H-3c (2.32 [IQR: 0-19] vs 129 [IQR: 14-274], P=0.001). Conclusion WW surveillance is a powerful tool for early detection and monitoring of circulating SARS-CoV-2 VOCs. Total SARS-CoV-2 and VOC-specific WW signal correlated with hospitalized prevalent cases of COVID-19 and outbreak occurrence. Disclosures All Authors: No reported disclosures.

Background New tools capable of dynamic assessment of the varying burden of Clostridioides difficile infections are required to mitigate increased patient morbidity, mortality, and health costs. Wastewater (WW)-based epidemiology (WBE) is an emerging science, enabling comprehensive, inclusive, and unbiased assessment of populations, spatially and temporally. We sought to detect, quantify and track C. difficile across a range of scales using WBE. Methods WW collected from two hospitals; the Rockyview General Hospital (RGH; 600 beds) and Peter Lougheed Centre (PLC; 550 beds) both based in Calgary, were compared to that from a municipal WW Treatment Plant (WWTP) in Calgary, Canada. DNA was extracted from pellets collected after WW centrifugation. A multiplexed quantitative PCR assay was used to quantify the abundance of C. difficile 16S rRNA and toxin A (tcdA) genes. These were then assessed as raw values or as normalized ratios to three fecal biomarker genes: total bacterial 16S rRNA, human 18S rRNA, and Bacteroides HF183 16S rRNA. Kruskal-Wallis and Mann-Whitney tests were performed using RStudio and GraphPad Prism (version 9.3.1). Results Eight weekly samples collected from the RGH demonstrated significant changes in the levels of total C. difficile 16S rRNA gene and tcdA over time (P=0.0004 and P=0.0005, respectively, Kruskal-Wallis). Similar trends in total C. difficile and tcdA burden over time were observed when gene copies were normalized with the three fecal biomarker genes. Over a separate 13-week comparison, C. difficile and tcdA gene target abundance was greater in hospital WW (RGH and PLC) than in community-based samples from the WWTP (P=0.048 and P=0.012, respectively, Mann-Whitney). There was no significant difference in C. difficile and tcdA gene target abundance between RGH and PLC (P=0.896 and P=0.343, respectively, Mann-Whitney). Clostridioides difficile genes in wastewater measured by quantitative PCR. C. difficile 16S rRNA and tcdA gene abundance normalized as a ratio against total bacterial load (16S rRNA) varies over time and is markedly increased in hospitals relative to a municipal wastewater treatment plant in Calgary, Canada. Conclusion WW surveillance is a powerful tool that can monitor the burden the C. difficile across a range of scales in real-time. This tool could augment infection prevention and control and antimicrobial stewardship programs to better understand factors that contribute to colonization and infection. Disclosures Thomas J. Louie, MD, Artugen: Advisor/Consultant|Artugen: Grant/Research Support|Crestone: Advisor/Consultant|Crestone: Grant/Research Support|Finch Therapeutics: Advisor/Consultant|Finch Therapeutics: Grant/Research Support|Rebiotix: Advisor/Consultant|Rebiotix: Grant/Research Support|Seres Therapeutics: Advisor/Consultant|Seres Therapeutics: Grant/Research Support|summit plc: Advisor/Consultant|summit plc: Grant/Research Support|Vedanta Biosciences: Advisor/Consultant|Vedanta Biosciences: Grant/Research Support.