ABSTRACT
BACKGROUND: This study discusses the anti-inflammatory mechanism of Yiqi Huayu Jiedu decoction (YQHYJD) and studies the intervening effect of YQHYJD on the inflammatory cytokines in acute respiratory distress syndrome (ARDS) rats by inhibiting the TLR4/NLRP3 signal pathway. The aim of the probe is to provide evidence to support the identification of therapeutic targets in Chinese medicine treatment, which broadens the alternatives for the treatment of ARDS. METHOD: A lipopolysaccharide (LPS)-induced ARDS model group is established on rats by tail vein injection. A medicine group is established on ARDS rats by prophylactic administration using YQHYJD. Materials are collected, and tests are conducted according to experimental processes. RESULT: The rats in the medicine group gained weight compared with those in the ARDS model group. Pathological sections from the medicine group indicated improved condition in terms of pulmonary and interstitial edema in the lung tissues of rats compared with that from the ARDS model group. The percentage of neutrophil of the medicine group was significantly brought down compared with that of the ARDS model group (P < 0.001). Enzyme-linked immunosorbent assay (ELISA) was used to detect the changes in the level of inflammatory cytokines. It was observed that the levels of IL-1ß and IL-18 in serum of the medicine group significantly decreased (P < 0.001 and P < 0.01), the contents of TLR4 and NLRP3 in bronchoalveolar lavage fluid (BALF) of the medicine group decreased, and the contents of TLR4 and NLRP3 in lung tissue homogenate of the medicine group significantly decreased (P < 0.05, P < 0.001, P < 0.01, and P < 0.05). In further mass spectrum identification of the proteins from the same animal groups, it was observed that the expressions of inflammatory proteins TNFRSF1, LBP, and NOS2 of the medicine group were reduced. The differences were statistically significant. CONCLUSIONS: The pharmacological action of YQHYJD's anti-inflammatory mechanism is closely associated with the regulation of inflammatory cytokines TLR4, NLRP3, IL-1ß, IL-18, TNFRSF1, LBP, and NOS2 on the TLR4/NLRP3 signal pathway.
ABSTRACT
OBJECTIVE: Study the impact of local policies on near-future hospitalization and mortality rates. MATERIALS AND METHODS: We introduce a novel risk-stratified SIR-HCD model that introduces new variables to model the dynamics of low-contact (e.g., work from home) and high-contact (e.g., work on-site) subpopulations while sharing parameters to control their respective R0(t) over time. We test our model on data of daily reported hospitalizations and cumulative mortality of COVID-19 in Harris County, Texas, from May 1, 2020, until October 4, 2020, collected from multiple sources (USA FACTS, U.S. Bureau of Labor Statistics, Southeast Texas Regional Advisory Council COVID-19 report, TMC daily news, and Johns Hopkins University county-level mortality reporting). RESULTS: We evaluated our model's forecasting accuracy in Harris County, TX (the most populated county in the Greater Houston area) during Phase-I and Phase-II reopening. Not only does our model outperform other competing models, but it also supports counterfactual analysis to simulate the impact of future policies in a local setting, which is unique among existing approaches. DISCUSSION: Mortality and hospitalization rates are significantly impacted by local quarantine and reopening policies. Existing models do not directly account for the effect of these policies on infection, hospitalization, and death rates in an explicit and explainable manner. Our work is an attempt to improve prediction of these trends by incorporating this information into the model, thus supporting decision-making. CONCLUSION: Our work is a timely effort to attempt to model the dynamics of pandemics under the influence of local policies.