Impact of the COVID-19 lockdown on typical ambient air pollutants: Cyclical response to anthropogenic emission reduction.

Preliminary studies have confirmed that ambient air pollutant concentrations are significantly influenced by the COVID-19 lockdown measures, but little attention focus on the long term impacts of human countermeasures in cities all over the world during the period. Still, fewer have addressed their other essential properties, especially the cyclical response to concentration reduction. This paper aims to fill the gaps with combined methods of abrupt change test and wavelet analysis, research areas were made of five cities, Wuhan, Changchun, Shanghai, Shenzhen and Chengdu, in China. Abrupt changes in contaminant concentrations commonly occurred in the year prior to the outbreak. The lockdown has almost no effect on the short cycle below 30 d (days) for both pollutants, and a negligible impact on the cycle above 30 d. PM2.5 (fine particulate matter) has a stable short-cycle nature, which is greatly influenced by anthropogenic emissions. The analysis revealed that the sensitivity of PM2.5 to climate is increased along with the concentrations of PM2.5 were decreasing by the times when above the threshold (30-50 µg m-3), and which could lead to PM2.5 advancement relative to the ozone phase over a period of 60 d after the epidemic. These results suggest that the epidemic may have had an impact earlier than when it was known. And significant reductions in anthropogenic emissions have little impact on the cyclic nature of pollutants, but may alter the inter-pollutant phase differences during the study period.

Protease-Responsive Peptide-Conjugated Mitochondrial-Targeting AIEgens for Selective Imaging and Inhibition of SARS-CoV-2-Infected Cells.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a serious threat to human health and lacks an effective treatment. There is an urgent need for both real-time tracking and precise treatment of the SARS-CoV-2-infected cells to mitigate and ultimately prevent viral transmission. However, selective triggering and tracking of the therapeutic process in the infected cells remains challenging. Here, we report a main protease (Mpro)-responsive, mitochondrial-targeting, and modular-peptide-conjugated probe (PSGMR) for selective imaging and inhibition of SARS-CoV-2-infected cells via enzyme-instructed self-assembly and aggregation-induced emission (AIE) effect. The amphiphilic PSGMR was constructed with tunable structure and responsive efficiency and validated with recombinant proteins, cells transfected with Mpro plasmid or infected by SARS-CoV-2, and a Mpro inhibitor. By rational construction of AIE luminogen (AIEgen) with modular peptides and Mpro, we verified that the cleavage of PSGMR yielded gradual aggregation with bright fluorescence and enhanced cytotoxicity to induce mitochondrial interference of the infected cells. This strategy may have value for selective detection and treatment of SARS-CoV-2-infected cells.

A Charge-Switchable Zwitterionic Peptide for Rapid Detection of SARS-CoV-2 Main Protease.

The transmission of SARS-CoV-2 coronavirus has led to the COVID-19 pandemic. Nucleic acid testing while specific has limitations for mass surveillance. One alternative is the main protease (Mpro ) due to its functional importance in mediating the viral life cycle. Here, we describe a combination of modular substrate and gold colloids to detect Mpro via visual readout. The strategy involves zwitterionic peptide that carries opposite charges at the C-/N-terminus to exploit the specific recognition by Mpro . Autolytic cleavage releases a positively charged moiety that assembles the nanoparticles with rapid color changes (t<10 min). We determine a limit of detection for Mpro in breath condensate matrices <10 nM. We further assayed ten COVID-negative subjects and found no false-positive result. In the light of simplicity, our test for viral protease is not limited to an equipped laboratory, but also is amenable to integrating as portable point-of-care devices including those on face-coverings.

ACE2 Correlated With Immune Infiltration Serves As A Novel Prognostic Biomarker In Clear Cell Renal Cell Carcinoma: Implication For COVID-19.

The current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global infection, and is seriously threatening human life, especially cancer patients. Thus, we sought to determine the clinical roles of ACE2 (the cell entry receptor of SARS-CoV-2) in ccRCC (clear cell renal cell carcinoma). TCGA, GEO and TIP datasets, and immunohistochemistry and western blot results were used to determine the prognostic and clinicopathological characteristics of ACE2. ACE2 expression was down-regulated in ccRCC tissues and cell lines. The multivariate Cox regression analysis results indicated that increased ACE2 expression was independent predictor of longer OS (HR: 0.8259, 95%CI: 0.7734-0.8819, P<0.0001) and RFS (HR: 0.8023, 95%CI: 0.7375-0.8729, P<0.0001) in ccRCC patients. Lower ACE2 expression was also associated with advanced tumor stage, higher histological grade and pathological stage, and metastasis. Besides, ACE2 expression was significantly positively and negatively correlated with CD4 Naïve infiltration and CD4 Memory infiltration, respectively. Moreover, higher CD4 Naïve and lower CD4 Memory infiltration levels were associated with better pathological features and longer OS and RFS. Furthermore, high ACE2 expression group in decreased CD4 Naïve, enriched CD4 Naïve and enriched CD4 memory cohort had favorable prognosis. These findings identified that AEC2 was significantly reduced in ccRCC, and decreased ACE2 was related to worse pathological features and poor prognosis. Low ACE2 expression in ccRCC may partially affect the prognosis due to altered immune cells infiltration levels.

Mapping Aerosolized Saliva on Face Coverings for Biosensing Applications.

Facemasks in congregate settings prevent the transmission of SARS-CoV-2 and help control the ongoing COVID-19 global pandemic because face coverings can arrest transmission of respiratory droplets. While many groups have studied face coverings as personal protective equipment, these respiratory droplets can also serve as a diagnostic fluid to report on health state; surprisingly, studies of face coverings from this perspective are quite limited. Here, we determined the concentration and distribution of aerosolized saliva (via α-amylase levels) captured on various face coverings. Our results showed that α-amylase accumulated on face coverings in a time-dependent way albeit at different levels, e.g., neck gaiters and surgical masks captured about 3-fold more α-amylase than cloth masks and N95 respirators. In addition, the saliva aerosols were primarily detected on the inner layer of multilayered face coverings. We also found that the distribution of salivary droplets on the mask correlated with the morphologies of face coverings as well as their coherence to the face curvature. These findings motivated us to extend this work and build multifunctional sensing strips capable of detecting biomarkers in situ to create "smart" masks. The work highlights that face coverings are promising platforms for biofluid collection and colorimetric biosensing, which bode well for developing surveillance tools for airborne diseases.