The grand challenge in the development of atomically dispersed metallic catalysts is their low metal-atom loading density, uncontrollable localization and ambiguous interactions with supports, posing difficulty in maximizing their catalytic performance. Here, we achieve an interface catalyst consisting of atomic cobalt array covalently bound to distorted 1T MoS2 nanosheets (SA Co-D 1T MoS2). The phase of MoS2 transforming from 2H to D-1T, induced by strain from lattice mismatch and formation of Co-S covalent bond between Co and MoS2 during the assembly, is found to be essential to form the highly active single-atom array catalyst. SA Co-D 1T MoS2 achieves Pt-like activity toward HER and high long-term stability. Active-site blocking experiment together with density functional theory (DFT) calculations reveal that the superior catalytic behaviour is associated with an ensemble effect via the synergy of Co adatom and S of the D-1T MoS2 support by tuning hydrogen binding mode at the interface.

The 5= cap structures of eukaryotic mRNAs are important for RNA stability and protein translation. T he 5= ends of eukaryotic cellular mRNAs and most viral mRNAs possess a cap structure, which plays important roles in mRNA splicing, intracellular RNA transport, RNA stability, and translation initiation (1). Host and viral RNA molecules lacking the 5= cap structure are rapidly degraded in the cytoplasm (2). The cap-0 structure of mRNA is cotranscriptionally formed through sequential enzymatic reactions, including RNA triphosphatase (TPase), RNA guanylyltransferase (GTase), and RNA (guanine-N7)-methyltransferase (N7-MTase) (1). In higher eukaryotes and some viruses, cap-0 structure m7GpppN-RNA is further methylated at the ribose 2=-O position of the nascent mRNA by a ribose 2=-O-methyltransferase (2=-O-MTase) to form a cap-1 structure (m7GpppNm) and cap-2 structure (m7GpppNmNm). Both N7-MTase and 2=-O-MTase can catalyze the transfer of the methyl group from the methyl donor S-adenosyl-L-methionine (SAM or AdoMet) to RNA substrate and generate S-adenosyl-L-homocysteine (SAH or AdoHcy) as a by-product. The functions of viral RNA cap structure include the following: (i) the guanosine cap core structure protects the 5=-triphosphate from activating the host innate immune response (3, 4); (ii) the N7 methylation is essential for viral replication through the enhancement of viral RNA translation (5); and (iii) the 2=-O methylation functions to

RNA interference (RNAi) is originally regarded as a mechanism of eukaryotic posttranscriptional gene regulation mediated by small interfering RNA (siRNA)-induced sequence-specific RNA degradation (1). It is also well known to exert as an important antiviral defense mechanism in a wide range of organisms, from plants to invertebrates (2). During the virus infection, the virus-derived long double-stranded RNA (dsRNA) is cleaved by RNAIII-like endonuclease (named Dicer) into approximately 21-to 23-nucleotide (nt) siRNA, which is incorporated into the RNA-induced silencing complex (RISC) and activates the antiviral RNAi for viral RNA degradation. In mammalian cells, although the activation of RNAi by synthetic siRNA or short hairpin RNA (shRNA) is widely used as a tool for gene knockdown and antiviral treatment, the RNAi-mediated antiviral mechanism has been debated for a long time (3), because the interferon (IFN) response of the innate immune system is well known as the dominant antiviral mechanism (4). However, more and more evidence has provided strong support for the existence of a natural RNAi-mediated antiviral response in mammals (5). Moreover, recent studies showed that in undifferentiated cells and immature mice, the RNAi-mediated antiviral response is essential (6-8).To overcome the RNAi-mediated antiviral defense, viruses have evolved to encode a viral suppressor of RNA silencing (VSR) (9, 10). For example, in plant viruses, rice hoja blancavirus NS3, tombusvirus P19, and tomato aspermy virus 2b bind to long dsRNA or siRNA to block RNAi (11-13). Turnip crinkle virus P38 and cauliflower mosaic virus P6 disrupt the components of RNAi machinery (14,15). In insect viruses, flock house virus (FHV) B2 blocks RNAi by dsRNA binding (16,17), and Wuhan nodavirus (WhNV) B2 was identified as a VSR by targeting both dsRNAs and 19). Although the majority of VSRs have been identified in plant and invertebrate viruses, several mammalian viruses were shown to encode VSRs. For instance, Ebola virus VP35, influenza A virus NS1, vaccinia virus E3L, and Nodamura virus (NoV) B2 act as VSRs by binding dsRNA (20-23). Hepatitis C virus core and HIV-1 Tat block RNAi by inhibiting the activity of

Theoretical and eddy covariance studies demonstrate that aerosol-loading stimulates canopy photosynthesis, but field evidence for the aerosol effect on tree growth is limited. Here, we measured in situ daily stem growth rates of aspen trees under a wide range of aerosol-loading in China. The results showed that daily stem growth rates were positively correlated with aerosol-loading, even at exceptionally high aerosol levels. Using structural equation modeling analysis, we showed that variations in stem growth rates can be largely attributed to two environmental variables covarying with aerosol loading: diffuse fraction of radiation and vapor pressure deficit (VPD). Furthermore, we found that these two factors influence stem growth by influencing photosynthesis from different parts of canopy. Using field observations and a mechanistic photosynthesis model, we demonstrate that photosynthetic rates of both sun and shade leaves increased under high aerosol-loading conditions but for different reasons. For sun leaves, the photosynthetic increase was primarily attributed to the concurrent lower VPD; for shade leaves, the positive aerosol effect was tightly connected with increased diffuse light. Overall, our study provides the first field evidence of increased tree growth under high aerosol loading. We highlight the importance of understanding biophysical mechanisms of aerosol-meteorology interactions, and incorporating the different pathways of aerosol effects into earth system models to improve the prediction of large-scale aerosol impacts, and the associated vegetation-mediated climate feedbacks.