ROS-responsive polymer nanoparticles with enhanced loading of dexamethasone effectively modulate the lung injury microenvironment.

The acute lung injury (ALI) is an inflammatory disorder associated with cytokine storm, which activates various reactive oxygen species (ROS) signaling pathways and causes severe complications in patients as currently seen in coronavirus disease 2019 (COVID-19). There is an urgent need for medication of the inflammatory lung environment and effective delivery of drugs to lung to reduce the burden of high doses of medications and attenuate inflammatory cells and pathways. Herein, we prepared dexamethasone-loaded ROS-responsive polymer nanoparticles (PFTU@DEX NPs) by a modified emulsion approach, which achieved high loading content of DEX (11.61 %). DEX was released faster from the PFTU@DEX NPs in a ROS environment, which could scavenge excessive ROS efficiently both in vitro and in vivo. The PFTU NPs and PFTU@DEX NPs showed no hemolysis and cytotoxicity. Free DEX, PFTU NPs and PFTU@DEX NPs shifted M1 macrophages to M2 macrophages in RAW264.7 cells, and showed anti-inflammatory modulation to A549 cells in vitro. The PFTU@DEX NPs treatment significantly reduced the increased total protein concentration in BALF of ALI mice. The delivery of PFTU@DEX NPs decreased the proportion of neutrophils significantly, mitigated the cell apoptosis remarkably compared to the other groups, reduced M1 macrophages and increased M2 macrophages in vivo. Moreover, the PFTU@DEX NPs had the strongest ability to suppress the expression of NLRP3, Caspase1, and IL-1ß. Therefore, the PFTU@DEX NPs could efficiently suppress inflammatory cells, ROS signaling pathways, and cell apoptosis to ameliorate LPS-induced ALI. STATEMENT OF SIGNIFICANCE: The acute lung injury (ALI) is an inflammatory disorder associated with cytokine storm, which activates various reactive oxygen species (ROS) signaling pathways and causes severe complications in patients. There is an urgent need for medication of the inflammatory lung environment and effective delivery of drugs to modulate the inflammatory disorder and suppress the expression of ROS and inflammatory cytokines. The inhaled PFTU@DEX NPs prepared through a modified nanoemulsification method suppressed the activation of NLRP3, induced the polarization of macrophage phenotype from M1 to M2, and thereby reduced the neutrophil infiltration, inhibited the release of proteins and inflammatory mediators, and thus decreased the acute lung injury in vivo.

Clinical Symptom Differences Between Mild and Severe COVID-19 Patients in China: A Meta-Analysis.

Objective: The prognosis of mild and severe patients has prominent differences during the prevalence of COVID-19, and it will be significant to identify patients' potential risk of progressing to severe cases according to their first clinical presentations. Therefore, we aim to review the clinical symptoms of the COVID-19 epidemic systematically. Methods:We searched PubMed, Embase, Web of Science, and CNKI (Chinese Database) for studies about the clinical features of COVID-19 in China from March 18 to April 18. Then we used REVMAN to conduct a meta-analysis. Results: After screening, 20 articles including 3,326 COVID-19 confirmed cases were selected from 142 articles we retrieved at the beginning of our research. We divided all the cases into a severe group (including severe and critically severe patients) and a mild group according to the "Diagnosis and Treatment Protocol for Novel Coronavirus Infection-Induced Pneumonia" version 4 (trial). Of all the initial symptoms (including fever, cough, abdominal pain, anorexia, chest tightness, diarrhea, dyspnea, expectoration, fatigue, headache, hemoptysis, myalgia, nausea or vomiting, and pharyngalgia) we studied, we found that cough (odds ratio [OR] = 1.4, 95% confidence interval [CI]: 1.2-1.7; p < 0.001), fever (OR = 1.5, 95% CI: 1.2-1.9; p < 0.001), dyspnea (OR = 6.2, 95% CI: 3.6-10.6; p < 0.001), diarrhea (OR = 2.6, 95% CI: 1.3-4.9; p < 0.001), fatigue (OR = 2.1, 95% CI: 1.3-3.3; p < 0.01), expectoration (OR = 1.7, 95% CI: 1.2-2.6; p < 0.01), myalgia (OR = 1.6, 95% CI: 0.8-3.1; p < 0.001), hemoptysis (OR = 4.0, 95% CI: 1.5-11.3; p < 0.001), abdominal pain (OR = 7.5, 95% CI: 2.4-23.4; p < 0.001), and anorexia (OR = 2.8, 95% CI: 1.5-5.1; p < 0.001) had a different distribution in two groups and were statistically significant (p < 0.05). Conclusion:COVID-19 patients whose initial manifestation is dyspnea, hemoptysis, anorexia, diarrhea, or fatigue, especially abdominal pain should be closely monitored to prevent disease deterioration.

A Risk Prediction Model for Evaluating the Disease Progression of COVID-19 Pneumonia.

Background and Objective: The epidemic of coronavirus disease 2019 (COVID-19) pneumonia caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) has expanded from China throughout the world. This study aims to estimate the risk of disease progression of patients who have been confirmed with COVID-19. Methods: Meta-analysis was performed in existing literatures to identify risk factors associated with COVID-19 pneumonia progression. Patients with COVID-19 pneumonia were admitted to hospitals in Wuhan or Hangzhou were retrospectively enrolled. The risk prediction model and nomogram were developed from Wuhan cohort through logistic regression algorithm, and then validated in Hangzhou and Yinchuan cohorts. Results: A total of 270 patients admitted to hospital between Dec 30, 2019, and Mar 30, 2020, were retrospectively enrolled (Table 1). The development cohort (Wuhan cohort) included 87 (43%) men and 115 (57%) women, and the median age was 53 years old. Hangzhou validation cohort included 20 (48%) men and 22 (52%) women, and the median age was 59 years old. Yinchuan validation cohort included 12 (46%) men and 14 (54%) women, and the median age was 44 years old. The meta-analysis along with univariate logistic analysis in development cohort have shown that age, fever, diabetes, hypertension, CREA, BUN, CK, LDH, and neutrophil count were significantly associated with disease progression of COVID-19 pneumonia. The model and nomogram derived from development cohort show good performance in both development and validation cohorts. Conclusion: The severe COVID-19 pneumonia is associated with various types of risk factors including age, fever, comorbidities, and some laboratory examination indexes. The model integrated with these factors can help to evaluate the disease progression of COVID-19 pneumonia.

Immune-Inflammatory Parameters in COVID-19 Cases: A Systematic Review and Meta-Analysis.

Background: The recent outbreak of coronavirus disease 2019 (COVID-19) has been rapidly spreading on a global scale and poses a great threat to human health. Acute respiratory distress syndrome, characterized by a rapid onset of generalized inflammation, is the leading cause of mortality in patients with COVID-19. We thus aimed to explore the effect of risk factors on the severity of the disease, focusing on immune-inflammatory parameters, which represent the immune status of patients. Methods: A comprehensive systematic search for relevant studies published up to April 2020 was performed by using the PubMed, Web of Science, EMBASE, and China National Knowledge Internet (CNKI) databases. After extracting all available data of immune-inflammatory indicators, we statistically analyzed the risk factors of severe and non-severe COVID-19 patients with a meta-analysis. Results: A total of 4,911 patients from 29 studies were included in the final meta-analysis. The results demonstrated that severe patients tend to present with increased white blood cell (WBC) and neutrophil counts, neutrophil-lymphocyte ratio (NLR), procalcitonin (PCT), C-reaction protein (CRP), erythrocyte sedimentation rate (ESR), and Interleukin-6 (IL-6) and a decreased number of total lymphocyte and lymphocyte subtypes, such as CD4+ T lymphocyte and CD8+ T lymphocyte, compared to the non-severe patients. In addition, the WBC count>10 × 109/L, lymphocyte count<1 × 109/L, PCT>0.5 ng/mL, and CRP>10 mg/L were risk factors for disease progression in patients with COVID-19 (WBC count>10 × 109/L: OR = 2.92, 95% CI: 1.96-4.35; lymphocyte count<1 × 109/L: OR = 4.97, 95% CI: 3.53-6.99; PCT>0.5 ng/mL: OR = 6.33, 95% CI: 3.97-10.10; CRP>10 mg/L: OR = 3.51, 95% CI: 2.38-5.16). Furthermore, we found that NLR, as a novel marker of systemic inflammatory response, can also help predict clinical severity in patients with COVID-19 (OR = 2.50, 95% CI: 2.04-3.06). Conclusions: Immune-inflammatory parameters, such as WBC, lymphocyte, PCT, CRP, and NLR, could imply the progression of COVID-19. NLR has taken both the levels of neutrophil and lymphocyte into account, indicating a more complete, accurate, and reliable inspection efficiency; surveillance of NLR may help clinicians identify high-risk COVID-19 patients at an early stage.