Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data.

Fine particulate matter (PM2.5) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model simulations. We developed a four-dimensional spatiotemporal deep forest (4D-STDF) model to estimate daily PM2.5 chemical composition at a spatial resolution of 1 km in China since 2000 by integrating measurements of PM2.5 species from a high-density observation network, satellite PM2.5 retrievals, atmospheric reanalyses, and model simulations. Cross-validation results illustrate the reliability of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) estimates, with high coefficients of determination (CV-R2) with ground-based observations of 0.74, 0.75, 0.71, and 0.66, and average root-mean-square errors (RMSE) of 6.0, 6.6, 4.3, and 2.3 µg/m3, respectively. The three components of secondary inorganic aerosols (SIAs) account for 21% (SO42-), 20% (NO3-), and 14% (NH4+) of the total PM2.5 mass in eastern China; we observed significant reductions in the mass of inorganic components by 40-43% between 2013 and 2020, slowing down since 2018. Comparatively, the ratio of SIA to PM2.5 increased by 7% across eastern China except in Beijing and nearby areas, accelerating in recent years. SO42- has been the dominant SIA component in eastern China, although it was surpassed by NO3- in some areas, e.g., Beijing-Tianjin-Hebei region since 2016. SIA, accounting for nearly half (∼46%) of the PM2.5 mass, drove the explosive formation of winter haze episodes in the North China Plain. A sharp decline in SIA concentrations and an increase in SIA-to-PM2.5 ratios during the COVID-19 lockdown were also revealed, reflecting the enhanced atmospheric oxidation capacity and formation of secondary particles.

Estrogen hormone is an essential sex factor inhibiting inflammation and immune response in COVID-19.

Although vaccines have been evaluated and approved for SARS-CoV-2 infection prevention, there remains a lack of effective treatments to reduce the mortality of COVID-19 patients already infected with SARS-CoV-2. The global data on COVID-19 showed that men have a higher mortality rate than women. We further observed that the proportion of mortality of females increases starting from around the age of 55 significantly. Thus, sex is an essential factor associated with COVID-19 mortality, and sex related genetic factors could be interesting mechanisms and targets for COVID-19 treatment. However, the associated sex factors and signaling pathways remain unclear. Here, we propose to uncover the potential sex associated factors using systematic and integrative network analysis. The unique results indicated that estrogens, e.g., estrone and estriol, (1) interacting with ESR1/2 receptors, (2) can inhibit SARS-CoV-2 caused inflammation and immune response signaling in host cells; and (3) estrogens are associated with the distinct fatality rates between male and female COVID-19 patients. Specifically, a high level of estradiol protects young female COVID-19 patients, and estrogens drop to an extremely low level in females after about 55 years of age causing the increased fatality rate of women. In conclusion, estrogen, interacting with ESR1/2 receptors, is an essential sex factor that protects COVID-19 patients from death by inhibiting inflammation and immune response caused by SARS-CoV-2 infection. Moreover, medications boosting the down-stream signaling of ESR1/ESR2, or inhibiting the inflammation and immune-associated targets on the signaling network can be potentially effective or synergistic combined with other existing drugs for COVID-19 treatment.

Computational analysis to repurpose drugs for COVID-19 based on transcriptional response of host cells to SARS-CoV-2.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) pandemic has infected over 10 million people globally with a relatively high mortality rate. There are many therapeutics undergoing clinical trials, but there is no effective vaccine or therapy for treatment thus far. After affected by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), molecular signaling pathways of host cells play critical roles during the life cycle of SARS-CoV-2. Thus, it is significant to identify the involved molecular signaling pathways within the host cells. Drugs targeting these molecular signaling pathways could be potentially effective for COVID-19 treatment. METHODS: In this study, we developed a novel integrative analysis approach to identify the related molecular signaling pathways within host cells, and repurposed drugs as potentially effective treatments for COVID-19, based on the transcriptional response of host cells. RESULTS: We identified activated signaling pathways associated with the infection caused SARS-CoV-2 in human lung epithelial cells through integrative analysis. Then, the activated gene ontologies (GOs) and super GOs were identified. Signaling pathways and GOs such as MAPK, JNK, STAT, ERK, JAK-STAT, IRF7-NFkB signaling, and MYD88/CXCR6 immune signaling were particularly activated. Based on the identified signaling pathways and GOs, a set of potentially effective drugs were repurposed by integrating the drug-target and reverse gene expression data resources. In addition to many drugs being evaluated in clinical trials, the dexamethasone was top-ranked in the prediction, which was the first reported drug to be able to significantly reduce the death rate of COVID-19 patients receiving respiratory support. CONCLUSIONS: The integrative genomics data analysis and results can be helpful to understand the associated molecular signaling pathways within host cells, and facilitate the discovery of effective drugs for COVID-19 treatment.

[Moxibustion therapy in prevention and treatment of coronavirus disease 2019 (COVID-19): construction and application of non-contact diagnosis and treatment mode].

OBJECTIVE: To establish and promote the non-contact doctor-patient interactive diagnosis and treatment mode based on mobile internet for the treatment of coronavirus disease 2019 (COVID-19) with moxibustion therapy, and to observe the feasibility and effectiveness of the model in the pandemic. METHODS: A total of 43 first-line medical staff and 149 suspected and confirmed cases with COVID-19 [18 cases in medical observation period, 17 cases of mild type (cold dampness and stagnation in the lung), 24 cases of ordinary type (cold-dampness accumulated in the lung) and 90 cases in recovery period (qi deficiency of spleen and lung)] were included. A non-contact doctor-patient interactive diagnosis and treatment platform was established for the treatment of COVID-19 with indirect moxibustion plaster based on mobile internet. By the platform, the patients were instructed to use indirect moxibustion plaster in treatment. For the first-line medical staff and patients in the medical observation period, Zusanli (ST 36), Qihai (CV 6) and Zhongwan (CV 12) were selected. For the mild cases (cold dampness and stagnation in the lung) and the cases of ordinary type (cold-dampness accumulated in the lung), Hegu (LI 4), Taichong (LR 3), Zusanli (ST 36) and Guanyuan (CV 4) were selected. In the recovery period (qi deficiency of spleen and lung), Dazhui (GV 14), Feishu (BL 13), Geshu (BL 17), Zusanli (ST 36) and Kongzui (LU 6) were used. The treatment was given once daily for 40 min each time. The intervention lasted for 10 days. After intervention, the infection rate and the improvement in the symptoms and psychological status of COVID-19 were observed in clinical first-line medical staff and COVID-19 patients. RESULTS: In 10 days of intervention with indirect moxibustion plaster, there was "zero" infection among medical staff. Of 43 first-line physicians and nurses, 33 cases had some physical symptoms and psychological discomforts, mainly as low back pain, poor sleep and anxiety. After treatment, regarding the improvements in the symptoms and psychological discomforts, the effective rate was 78.8% (26/33) and the curative rate was 36.4% (12/33). Regarding the improvements in psychological discomforts, the effective rate was 58.3% (14/24) and the curative rate was 37.5 (9/24). Of 149 patients, 133 cases had the symptoms and psychological discomforts. After treatment, regarding the improvements in the symptoms and psychological discomforts, the effective rate was 81.2% (108/133) and the curative rate was 34.6% (46/133). Regarding the improvements in psychological discomforts, the effective rate was 76.5% (52/68) and the curative rate was 57.4 % (39/68). CONCLUSION: It is feasible to apply the indirect moxibustion plaster technique based on mobile internet to the treatment COVID-19. This mode not only relieves the symptoms such as cough and fatigue, improves psychological state, but also possibly prevents the first-line medical staff from COVID-19.