How much urban air quality is affected by local emissions: A unique case study from a megacity in the Pearl River Delta, China

In March 2022, the resurgence of COVID-19 cases in Shenzhen, a megacity in the Pearl River Delta (PRD) region of China, led to unusual restrictions on anthropogenic activities within a single city, in contrast to the restrictions COVID-19 caused on a national scale at the beginning of 2020. In this unique event, we found that only under unfavorable meteorological conditions did substantial urban local emission reductions have an impact on air pollutant changes (−42.4%–6.6%), whereas the deweathered changes were very small (−8.3%–3.4%) under favorable meteorological conditions. Primary anthropogenic pollutants, such as NO2, toluene, BC, and primary organic aerosol (POA), responded most considerably to emission reductions from early morning to noon during unfavorable meteorological days;for secondary organic aerosol (SOA), regulating the daytime total oxidant (Ox = O3 + NO2) was found to be more effective than controlling its precursors within the city scale, whereas secondary nitrate displayed the opposite trend. Since Ox changed little during the urban lockdown despite the remarkable decrease in precursors, it is emphasized that regionally coordinated control of VOCs and NOx is necessary to effectively reduce Ox levels. In addition, Shenzhen's NOx emission reduction efforts should be sustained in order to control PM2.5 and O3 pollution synergistically for long-term attainment.

Decisive role of ozone formation control in winter PM2.5 mitigation in Shenzhen, China.

During the COVID-19 lockdown, atmospheric PM2.5 in the Pearl River Delta (PRD) showed the highest reduction in China, but the reasons, being a critical question for future air quality policy design, are not yet clear. In this study, we analyzed the relationships among gaseous precursors, secondary aerosols and atmospheric oxidation capacity in Shenzhen, a megacity in the PRD, during the lockdown period in 2020 and the same period in 2021. The comprehensive observational datasets showed large lockdown declines in all primary and secondary pollutants (including O3). We found that, however, the daytime concentrations of secondary aerosols during the lockdown period and normal period were rather similar when the corresponding odd oxygen (Ox≡O3+NO2, an indicator of photochemical processing avoiding the titration effect of O3 by freshly emitted NO) were at similar levels. Therefore, reduced Ox, rather than the large reduction in precursors, was a direct driver to achieve the decline in secondary aerosols. Moreover, Ox was also found to determine the spatial distribution of intercity PM2.5 levels in winter PRD. Thus, an effective strategy for winter PM2.5 mitigation should emphasize on control of winter O3 formation in the PRD and other regions with similar conditions.

Ni2+ Catalyzed Cleavage of TrpLE-Fused Small Transmembrane Peptides.

In addition to a membrane anchor, the transmembrane domain (TMD) of single-pass transmembrane proteins (SPTMPs) recently has shown essential roles in the cross-membrane activity or receptor assembly/clustering. However, these small TMD peptides are generally hydrophobic and dynamic, difficult to be expressed and purified. Here, we have integrated the power of TrpLE fusion protein and a sequence-specific nickel-assisted cleavage (SNAC)-tag to produce small TMD peptides in a highly efficient way under mild conditions, which uses Ni2+ as the cleavage reagent, avoiding the usage of toxic cyanogen bromide (CNBr). Furthermore, this method simplifies the downstream protein purification and reconstitution. Two representative TMDs, including the Spike-TMD from severe acute respiratory syndrome coronavirus 2 (SARS2), were successfully produced with high-quality nuclear magnetic resonance (NMR) spectra. Therefore, our study provides a more efficient and practical approach for general structural characterization of the small TM proteins.

Effect of COVID-19 on hospital visits in Ningbo, China: an interrupted time-series analysis.

OBJECTIVE: Unprecedented rigorous public health measures were implemented during the coronavirus disease 2019 (COVID-19) epidemic, but it is still unclear how the intervention influenced hospital visits for different types of diseases. We aimed to evaluate the impact of the intervention on hospital visits in Yinzhou District, Ningbo, Zhejiang province, China. METHODS: We conducted an interrupted time-series analysis from 1 January 2017 to 6 September 2020 based on the Yinzhou Health Information System in Ningbo, Zhejiang province. The beginning of the intervention was on 23 January 2020, and thus, there were 160 weeks before the intervention and 32 weeks after the implementation of the intervention. Level changes between expected and observed hospital visits in the post-intervention period were estimated using quasi-Poisson regression models. RESULTS: Compared with the expected level, there was an estimated decrease of -22.60% (95% confidence interval (CI): -27.53%, -17.36%) in the observed total hospital visits following the intervention. Observed hospital visits for diseases of the respiratory system were found to be decreased dramatically (-62.25%; 95% CI: -65.62%, -58.60%). However, observed hospital visits for certain diseases were estimated to be increased, including diseases of the nervous system (+11.17%; 95% CI: +3.21%, +19.74%); diseases of pregnancy, childbirth and the puerperium (+27.01%; 95% CI: +17.89%, +36.85%); certain conditions originating in the perinatal period (+45.05%; 95% CI: +30.24%, +61.56%); and congenital malformation deformations and chromosomal abnormalities (+35.50%; 95% CI: +21.24%, +51.45%). CONCLUSIONS: Our findings provided scientific evidence that cause-specific hospital visits evolve differently following the intervention during the COVID-19 epidemic.

SARS-CoV-2 spike protein dictates syncytium-mediated lymphocyte elimination.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is highly contagious and causes lymphocytopenia, but the underlying mechanisms are poorly understood. We demonstrate here that heterotypic cell-in-cell structures with lymphocytes inside multinucleate syncytia are prevalent in the lung tissues of coronavirus disease 2019 (COVID-19) patients. These unique cellular structures are a direct result of SARS-CoV-2 infection, as the expression of the SARS-CoV-2 spike glycoprotein is sufficient to induce a rapid (~45.1 nm/s) membrane fusion to produce syncytium, which could readily internalize multiple lines of lymphocytes to form typical cell-in-cell structures, remarkably leading to the death of internalized cells. This membrane fusion is dictated by a bi-arginine motif within the polybasic S1/S2 cleavage site, which is frequently present in the surface glycoprotein of most highly contagious viruses. Moreover, candidate anti-viral drugs could efficiently inhibit spike glycoprotein processing, membrane fusion, and cell-in-cell formation. Together, we delineate a molecular and cellular rationale for SARS-CoV-2 pathogenesis and identify novel targets for COVID-19 therapy.

Clinical features predicting mortality risk in older patients with COVID-19.

BACKGROUND: Since December 2019, the cumulative number of coronavirus disease 2019 (COVID-19) deaths worldwide has reached 1,013,100 and continues to increase as of writing. Of these deaths, more than 90% are people aged 60 and older. Therefore, there is a need for an easy-to-use clinically predictive tool for predicting mortality risk in older individuals with COVID-19. OBJECTIVE: To explore an easy-to-use clinically predictive tool that may be utilized in predicting mortality risk in older patients with COVID-19. METHODS: A retrospective analysis of 118 older patients with COVID-19 admitted to the Union Dongxihu Hospital, Huazhong University of Science and Technology, Wuhan, China from 12 January to 26 February 2020. The main results of epidemiological, demographic, clinical and laboratory tests on admission were collected and compared between dying and discharged patients. RESULTS: No difference in major symptoms was observed between dying and discharged patients. Among the results of laboratory tests, neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase, albumin, urea nitrogen and D-dimer (NLAUD) show greater differences and have better regression coefficients (ß) when using hierarchical comparisons in a multivariate logistic regression model. Predictors of mortality based on better regression coefficients (ß) included NLR (OR = 31.2, 95% CI 6.7-144.5, p < .0001), lactate dehydrogenase (OR = 73.4, 95% CI 11.8-456.8, p < .0001), albumin (OR < 0.1, 95% CI <0.1-0.2, p < .0001), urea nitrogen (OR = 12.0, 95% CI 3.0-48.4, p = .0005), and D-dimer (OR = 13.6, 95% CI 3.4-54.9, p = .0003). According to the above indicators, a predictive NLAUD score was calculated on the basis of a multivariate logistic regression model to predict mortality. This model showed a sensitivity of 0.889, specificity of 0.984 and a better predictive ability than CURB-65 (AUROC = 0.955 vs. 0.703, p < .001). Bootstrap validation generated the similar sensitivity and specificity. CONCLUSIONS: We designed an easy-to-use clinically predictive tool for early identification and stratified treatment of older patients with severe COVID-19.