SARS-CoV-2 N protein-induced Dicer, XPO5, SRSF3, and hnRNPA3 downregulation causes pneumonia (preprint)

Age is a major risk factor for coronavirus disease (COVID-19)-associated severe pneumonia and mortality; however, the underlying mechanism remains unclear. Herein, we investigated whether age-related deregulation of RNAi components and RNA splicing factors affects COVID-19 severity. Decreased expression of RNAi components (Dicer and XPO5) and splicing factors (SRSF3 and hnRNPA3) correlated with increased severity of COVID-19 and SARS-CoV-2 nucleocapsid (N) protein-induced pneumonia. N protein induced autophagic degradation of Dicer, XPO5, SRSF3, and hnRNPA3, repressing miRNA biogenesis and RNA splicing and inducing DNA damage, proteotoxic stress, and pneumonia. Dicer, XPO5, SRSF3, and hnRNPA3 were downregulated with age in mouse lung tissues. Older mice experienced more severe N protein-induced pneumonia than younger mice. However, treatment with a poly(ADP-ribose) polymerase inhibitor (PJ34) or aromatase inhibitor (anastrozole) relieved N protein-induced pneumonia by restoring Dicer, XPO5, SRSF3, and hnRNPA3 expression. These findings will aid in developing improved treatments for SARS-CoV-2-associated pneumonia.

Visibility, wind speed, and dew point temperature are important factors in SARS-CoV-2 transmissibility.

The aim of this study is to provide evidence for the influencing factors of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus mutation by determining the impact of geographical and meteorological factors on SARS-CoV-2 transmission, and the different impacts of SARS-CoV-2 variant strains. From January 20 to March 10, 2020, we collected a number of daily confirmed new cases and meteorological factors in all cities and regions in China and Italy affected by the Alpha "variants of concern" (VOC). We also collected the daily confirmed cases of the Delta VOC infection in China and Italy from May 21 to November 30, 2021. The relationships between daily meteorological data and daily verified new cases of SARS-CoV-2 transmission were then investigated using a general additive model (GAM) with a log link function and Poisson family. The results revealed that latitude was substantially connected with daily confirmed new instances of the Alpha VOC, while there was no such correlation with Delta VOC transmission. When visibility is greater than 7 m, the propagation of the Alpha and Delta VOCs in Italy and China can be controlled. Furthermore, greater temperatures and increased wind speed reduce the transmission of the Alpha and Delta VOCs. In conclusion, geographical and meteorological factors play an important role in SARS-CoV-2 transmissibility and should be considered in virus mitigation strategies.

Artificial intelligence computed tomography helps evaluate the severity of COVID-19 patients: A retrospective study.

BACKGROUND: Computed tomography (CT) is a noninvasive imaging approach to assist the early diagnosis of pneumonia. However, coronavirus disease 2019 (COVID-19) shares similar imaging features with other types of pneumonia, which makes differential diagnosis problematic. Artificial intelligence (AI) has been proven successful in the medical imaging field, which has helped disease identification. However, whether AI can be used to identify the severity of COVID-19 is still underdetermined. METHODS: Data were extracted from 140 patients with confirmed COVID-19. The severity of COVID-19 patients (severe vs. non-severe) was defined at admission, according to American Thoracic Society (ATS) guidelines for community-acquired pneumonia (CAP). The AI-CT rating system constructed by Hangzhou YITU Healthcare Technology Co., Ltd. was used as the analysis tool to analyze chest CT images. RESULTS: A total of 117 diagnosed cases were enrolled, with 40 severe cases and 77 non-severe cases. Severe patients had more dyspnea symptoms on admission (12 vs. 3), higher acute physiology and chronic health evaluation (APACHE) II (9 vs. 4) and sequential organ failure assessment (SOFA) (3 vs. 1) scores, as well as higher CT semiquantitative rating scores (4 vs. 1) and AI-CT rating scores than non-severe patients (P<0.001). The AI-CT score was more predictive of the severity of COVID-19 (AUC=0.929), and ground-glass opacity (GGO) was more predictive of further intubation and mechanical ventilation (AUC=0.836). Furthermore, the CT semiquantitative score was linearly associated with the AI-CT rating system (Adj R 2=75.5%, P<0.001). CONCLUSIONS: AI technology could be used to evaluate disease severity in COVID-19 patients. Although it could not be considered an independent factor, there was no doubt that GGOs displayed more predictive value for further mechanical ventilation.

Efficacy and safety of Bufei Huoxue capsules in the management of convalescent patients with COVID-19 infection: A multicentre, double-blind, and randomised controlled trial.

BACKGROUND: As of September 17, 2021, coronavirus disease 2019 (COVID-19) has infected more than 226 million people in a worldwide pandemic, with conservative estimates suggesting that there are more than 204 million convalescent patients with COVID-19. Previous studies have indicated that patients in the recovery phase exhibit decreased function of multiple organs. In China, traditional Chinese medicine (TCM) treatment is recommended in the rehabilitation period of COVID-19; however, the safety and efficacy of such treatment remain to be confirmed. AIM OF STUDY: The present study aimed to evaluate the efficacy and safety of Bufei Huoxue (BFHX) in restoring the functional status and exercise tolerance of patients recovering from COVID-19. METHODS: A total of 131 patients in the rehabilitation period of COVID-19 infection were randomly divided into a Bufei Huoxue (BFHX) group (n = 66) and a placebo group (n = 65). BFHX or placebo was given orally three times a day (1.4 g/dose) for 90 days. The primary outcomes was to evaluate improvements in exercise tolerance and imaging manifestations on chest computed tomography (CT). RESULTS: After the exclusion of two patients who withdrew prior to receiving any medications, 129 patients were recruited, including 64 patients in the BFHX group and 65 patients in the placebo group. After 3 months of treatment, the BFHX group exhibited greater attenuation of pneumonia lesions on chest CT than the placebo group (P<0.05). Improvements in 6-min walk distance (6MWD) relative to baseline were also significantly better in the BFHX group than in the placebo group (P<0.01). Scores on the Fatigue Assessment Inventory (FAI) were lower in the BFHX group than in the placebo group (P<0.05). Although the rate of adverse events was higher in the BFHX group than in the placebo group (9.38% vs. 4.62%), the difference was not significant (P=0.3241). CONCLUSIONS: BFHX may exert strong rehabilitative effects on physiological activity in patients recovering from COVID-19, which may in turn attenuate symptoms of fatigue and improve exercise tolerance.

Bufei huoxue capsules in the management of convalescent COVID-19 infection: study protocol for a multicenter, double-blind, and randomized controlled trial.

Up to 30 May 2021, the cumulative number of patients diagnosed with corona virus disease-19 (COVID-19) globally has exceeded 170 million, with more than 152 million patients recovered from COVID-19. However, the long-term effect of the virus infection on the human body's function is unknown for convalescent patients. It was reported that about 63% of COVID-19 patients had observable lung damage on CT scans after being released from the hospital. Bufei Huoxue (BFHX) capsules, including three active ingredients of traditional Chinese herbal medicine, has been used clinically to prevent and treat pulmonary heart diseases with Qi deficiency and blood stasis syndrome. Some small-scale clinical trials have found that BFHX can improve lung ventilation function, reduce blood viscosity, and improve cardiopulmonary function. However, the efficacy and safety of BFHX in the treatment of the recovery phase of COVID-19 are unknown. This study is a multicenter, double-blinded, randomized, controlled trial. Subjects with convalescent COVID-19 were randomized (1:1) into either a BFHX or control group and observed for three months concomitant with receiving routine treatment. The primary efficacy indicators are the evaluation results and changes of the St. George's Respiratory Questionnaire score, Fatigue Assessment Inventory, and 6-min walk distance. Based on the intention-to-treat principle, all randomly assigned participants will be included in the statistical analysis. The last visit's outcomes will be used as the final outcomes for participants who prematurely withdraw from the trial. Per protocol set will pick up from the full analysis set for analysis. Efficacy analysis will be performed on the intention-to-treat datasets and per-protocol datasets. This study and its protocol were approved by the Ethics Committee of our University. Prior to participation, all subjects provided written informed consent. Results will be disseminated at medical conferences and in journal publications. We aimed to determine the efficacy and safety of BFHX for the treatment of the convalescent COVID-19 patients. Trial registration number: ChiCTR2000032573.

Natural Polymorphisms Are Present in the Furin Cleavage Site of the SARS-CoV-2 Spike Glycoprotein.

The furin cleavage site in the spike glycoprotein of the SARS-CoV-2 coronavirus is considered important for the virus to enter the host cells. By analyzing 45828 SARS-CoV-2 genome sequences, we identified 103 strains of SARS-CoV-2 with various DNA mutations including 18 unique non-synonymous point mutations, one deletion, and six gains of premature stop codon that may affect the furin cleavage site. Our results revealed that the furin cleavage site might not be required for SARS-CoV-2 to enter human cells in vivo. The identified mutants may represent a new subgroup of SARS-CoV-2 coronavirus with reduced tropism and transmissibility as potential live-attenuated vaccine candidates.

MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences.

With the continued spread of SARS-CoV-2 virus around the world, researchers often need to quickly identify novel mutations in newly sequenced SARS-CoV-2 genomes for studying the molecular evolution and epidemiology of the virus. We have developed a Python package, MicroGMT, which takes either raw sequence reads or assembled genome sequences as input and compares against database sequences to identify and characterize indels and point mutations. Although our default setting is optimized for SARS-CoV-2 virus, the package can be also applied to any other microbial genomes. The software is freely available at Github URL https://github.com/qunfengdong/MicroGMT.