STING (also known as MITA) mediates the innate antiviral signaling and ubiquitination of STING is key to its function. However, the deubiquitination process of STING is unclear. Here we report that USP18 recruits USP20 to deconjugate K48-linked ubiquitination chains from STING and promotes the stability of STING and the expression of type I IFNs and proinflammatory cytokines after DNA virus infection. USP18 deficiency or knockdown of USP20 resulted in enhanced K48-linked ubiquitination and accelerated degradation of STING, and impaired activation of IRF3 and NF-κB as well as induction of downstream genes after infection with DNA virus HSV-1 or transfection of various DNA ligands. In addition, Usp18 mice were more susceptible to HSV-1 infection compared with the wild-type littermates. USP18 did not deubiquitinate STING in vitro but facilitated USP20 to catalyze deubiquitination of STING in a manner independent of the enzymatic activity of USP18. In addition, reconstitution of STING into Usp18 MEFs restored HSV-1-induced expression of downstream genes and cellular antiviral responses. Our findings thus uncover previously uncharacterized roles of USP18 and USP20 in mediating virus-triggered signaling and contribute to the understanding of the complicated regulatory system of the innate antiviral responses.
Great efforts have been devoted to seek novel approaches for the construction of efficient deep-blue fluorescent materials, one of the most important prerequisites for the commercialization of OLEDs. Here we report a new way to utilize polyphenylbenzene as a platform to yield a series of efficient deep-blue emitters. Non-doped multilayer electroluminescence (EL) devices using these new luminogens as emitting layers are fabricated. Maximum current efficiency (CE) of 2.0 cd A -1 is achieved and the Commission Internationale de l'Éclairage (CIE) coordinates can stay at (0.15, 0.08), close to the saturated deep-blue (0.14, 0.08). Through rational design of the device structure, blue-violet emission with the CIE coordinates of (0.15, 0.06) can be realized. Furthermore, 10-based doped devices show deep-blue emission with improved CE as high as 4.51 cd A -1 , and the external quantum efficiency (EQE) of 3.98%, which are among the best EL performance for deep-blue emission.
Over the past 3 months, coronavirus disease 2019 (COVID-19) has emerged across China and developed into a worldwide outbreak [1]. The disease has caused varying degrees of illness. The proportion of patients with COVID-19 with non-severe illness was 84.3% on admission, and severe cases accounted for 15.7% [2]. Most of the non-severe pneumonia patients would gradually alleviate and be cured with treatment, while others would rapidly progress to severe illness, which has a poor prognosis [3, 4]. As recently reported, the cumulative risk of the composite end-point was 3.6% in all COVID-19 patients, and the cumulative risk was 20.6% for severe illness [2]. However, it is still unknown whether early identification and intervention for non-severe patients with COVID-19 could prevent progression into severe disease. According to the experience of treating other diseases, there might be a large promoting effect of treatment. In this paper, we aim to build a predictive model for identifying high-risk non-severe pneumonia patients at an early stage. 86 patients with COVID-19 and non-severe pneumonia on admission were recruited as the training cohort at Renmin Hospital of Wuhan University from 2 to 20 January, 2020, and another 62 patients were prospectively enrolled as the validation cohort from 28 January to 9 February, 2020. COVID-19 was confirmed by real-time PCR. Disease severities of COVID-19 were defined as severe and non-severe pneumonia based on the criteria of American Thoracic Society guidelines for community-acquired pneumonia [2, 5]. The exclusion criteria included: 1) degrees of severity were not available on admission or during follow-up; 2) diagnosed with severe illness at the time of admission; 3) confirmed with COVID-19 and treated at other hospitals; 4) medication was administered within 15 days before admission; 5) received oxygen support during follow-up. Patients were divided into "progressed" or "non-progressed" groups, based on whether they progressed to severe illness or not during the 14-day follow-up period. Comorbidity included diabetes, hypertension, cardiovascular and cerebrovascular diseases, COPD, malignant tumour, chronic liver disease, chronic kidney disease, tuberculosis and immunodeficiency diseases, etc. Clinical characteristics and laboratory findings were extracted from electronic medical records. Radiological features were extracted from chest computed tomography (CT) imaging using a double-blind method [6]. To evaluate the lesion size accurately, a diagnosis system for COVID-19 based on artificial intelligence (AI) was employed to measure volume ratio of pneumonia automatically by analysing CT values [7, 8]. Logistic regression was used as the classifier to build the predictive model. The discriminative performance of the predictive model was quantified by the value of the area under the receiver operating characteristic curve (AUC) in the cross-validation of the training and validation datasets. Risk index calculated with the weight of each variable in the model was used to identify...
Salt stress is one of the most severe adverse environments in rice production; increasing salinization is seriously endangering rice production around the world. In this study, a rice backcross inbred line (BIL) population derived from the cross of 9311 and wild rice Oryza longistaminata was employed to identify the favorable genetic loci of O. longistaminata for salt tolerance. A total of 27 quantitative trait loci (QTLs) related to salt tolerance were identified in 140 rice BILs, and 17 QTLs formed seven QTL clusters on different chromosomes, of which 18 QTLs were derived from O. longistaminata, and a QTL for salt injury score (SIS), water content of seedlings (WCS) under salt treatment, and relative water content of seedlings (RWCS) was repeatedly detected and colocalized at the same site on chromosome 2, and a cytochrome P450 86B1 (MH02t0466900) was suggested as the potential candidate gene responsible for the salt tolerance based on sequence and expression analysis. These findings laid the foundation for further improving rice salt tolerance through molecular breeding in the future.
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