Identifying the Main Components and Mechanisms of Action of Artemisia annua L. in the Treatment of Endometrial Cancer Using Network Pharmacology.

Artemisia annua L. (A. annua), a Traditional Chinese Medicine (TCM) that has been utilized in China for centuries, is known for its potential anticancer properties. However, the main components and mechanism of action of A. annua on endometrial carcinoma have not been reported. We used the TCMSP database to identify the active components of A. annua and their corresponding gene targets. We then obtained the gene targets specific to endometrial cancer from The Cancer Genome Atlas (TCGA) and GeneCards databases. The gene targets common to three databases were selected, and a "component-target" network was constructed. Protein-protein interaction (PPI) network analysis and ranking of the target proteins identified the key protein PTGS2 network analysis, and ranking of the target proteins identified the key protein PTGS2. We also screened the active components of A. annua and found that quercetin, kaempferol, luteolin, isorhamnetin, artemisin, and stigmasterol had the most targets. Molecular docking models were established for these six components with PTGS2, revealing strong binding activity for all of them. Finally, we conducted validation experiments to assess the effects of quercetin, an active component of A. annua, on endometrial cancer cells (HEC-1-A and Ishikawa cells). Our findings demonstrate that quercetin has the potential to inhibit both cell growth and migration, while also suppressing the expression of PTGS2.

Graphene oxide-based a network porous poly (trially isocyanurate-co-methacrylate) monolithic column for HPLC separation of aromatic molecular and lipopeptide antibiotics.

Graphene oxide (GO) was introduced into a monolithic column and a network porous poly (GO-co-TAIC-co-MMA) monolith was prepared by redox polymerization. The internal morphology and pore size distribution of the polymer were observed by scanning electron microscopy, and the nitrogen adsorption-desorption and mercury intrusion methods. After optimization, 8 kinds of aromatic compounds were effectively separated in 5 min, and the theoretical plates number of the monolithic column exceeded 33, 070 plates m-1. Five kinds of main ingredients were separated from the traditional Chinese medicine (Schisandra) ingredients and 26 peaks were successfully separated from the fermentation broth containing natural lipopeptide antibiotics. The addition of GO material enhanced the interaction between the compound and the monolithic column, increased the binding sites, improved the uniformity of the internal pore structure of the monolithic column, and improved the separation performance of the monolith. Methodologic validation of five ingredients in Schisandra showed that the correlation coefficients of the linear regressions were in the range of 0.9987-0.9997. The intra- and inter-day values of the relative standard deviation for precision were in the range of 0.6-4.1% and 1.1-4.8%, respectively. The values of accuracy (expressed as recovery) were in the range of 97.7-103.2%, 100.5-105.0%, 98.2-101.8%, 101.3-104.1%, and 101.2-103.3% for the 5 ingredients in order. In terms of the relative standard deviation of the retention time, the reproducibility of the monolithic column M1 was <3.7%. The monolithic column based on GO has great potential in chromatographic separation.

The Impact of the Declaration of the State of Emergency on the Spread of COVID-19: A Modeling Analysis.

When encountering the outbreak and early spreading of COVID-19, the Government of Japan imposed gradually upgraded restriction policies and declared the state of emergency in April 2020 for the first time. To evaluate the efficacy of the countering strategies in different periods, we constructed a SEIADR (susceptible-exposed-infected-asymptomatic-documented-recovered) model to simulate the cases and determined corresponding spreading coefficients. The effective reproduction number R t was obtained to evaluate the measures controlling the COVID-19 conducted by the Government of Japan during different stages. It was found that the strict containing strategies during the state of emergency period drastically inhibit the COVID-19 trend. R t was decreased to 1.1123 and 0.8911 in stages 4 and 5 (a state of emergency in April and May 2020) from 3.5736, 2.0126, 3.0672 in the previous three stages when the containing strategies were weak. The state of emergency was declared again in view of the second wave of massive infections in January 2021. We estimated the cumulative infected cases and additional days to contain the COVID-19 transmission for the second state of emergency using this model. R t was 1.028 which illustrated that the strategies were less effective than the previous state of emergency. Finally, the overall infected population was predicted using combined isolation and testing intensity; the effectiveness and the expected peak time were evaluated. If using the optimized control strategies in the current stage, the spread of COVID-19 in Japan could be controlled within 30 days. The total confirmed cases should reduce to less than 4.2 × 105 by April 2021. This model study suggested stricter isolating measures may be required to shorten the period of the state of emergency.