Rooting and Dating Large SARS-CoV-2 Trees by Modeling Evolutionary Rate as a Function of Time.

Almost all published rooting and dating studies on SARS-CoV-2 assumed that (1) evolutionary rate does not change over time although different lineages can have different evolutionary rates (uncorrelated relaxed clock), and (2) a zoonotic transmission occurred in Wuhan and the culprit was immediately captured, so that only the SARS-CoV-2 genomes obtained in 2019 and the first few months of 2020 (resulting from the first wave of the global expansion from Wuhan) are sufficient for dating the common ancestor. Empirical data contradict the first assumption. The second assumption is not warranted because mounting evidence suggests the presence of early SARS-CoV-2 lineages cocirculating with the Wuhan strains. Large trees with SARS-CoV-2 genomes beyond the first few months are needed to increase the likelihood of finding SARS-CoV-2 lineages that might have originated at the same time as (or even before) those early Wuhan strains. I extended a previously published rapid rooting method to model evolutionary rate as a linear function instead of a constant. This substantially improves the dating of the common ancestor of sampled SARS-CoV-2 genomes. Based on two large trees with 83,688 and 970,777 high-quality and full-length SARS-CoV-2 genomes that contain complete sample collection dates, the common ancestor was dated to 12 June 2019 and 7 July 2019 with the two trees, respectively. The two data sets would give dramatically different or even absurd estimates if the rate was treated as a constant. The large trees were also crucial for overcoming the high rate-heterogeneity among different viral lineages. The improved method was implemented in the software TRAD.

The pathological mechanism of the COVID-19 convalescence and its treatment with traditional Chinese medicine.

The severe acute respiratory syndrome coronavirus - 2 (SARS - CoV - 2) was reported to cause the Wuhan outbreak of the corona virus disease 2019(COVID-19). To date, the COVID-19 has infected more than 600 million people gloabally. As a growing number of patients recover from acute infections and are discharged from hospitals, the proportion of patients in the recovery period is gradually increasing. Many of these individuals have been reported to experience multiple symptoms during the convalescence, such as fatigue, dyspnea and pain which are designated as "long-COVID", "post-COVID syndrome" or "recovery sequelae. We searched for recent articles published in PubMed on COVID-19 convalescence and found that the pathogenesis of COVID-19 convalescence is not yet well recognized. It may be associated with incomplete recovery of immune system, parenchymal organ damage (liver or lung), coagulation abnormalities, "second hit" caused by viral infection, and Phenomenon of Cell Senescence-Associated Secretory Phenotype (SASP). Some drugs and psychological factors of patients also play a non-negligible role in it. We also found that the effect of traditional Chinese medicine (TCM) is effective in the treatment of the COVID-19 recovery phase, which can not only relieve the corresponding symptoms, but also improve the indicators and pulmonary fibrosis. Bufei Huoxue Capsule, as the only drug explicitly mentioned for COVID-19 recovery period, can exert strong rehabilitative effects on physiological activity in patients recovering from COVID-19. In addition, in previous studies, traditional Chinese medicine has been confirmed to have the ability to resist cytokine storms, as well as improve coagulation and myocardial damage, which makes it have potential therapeutic advantages in targeting the hyperimmune response, coagulation abnormalities and myocardial damage existing in the recovery period. In conclusion, the clinical symptoms of patients convalescing from COVID-19 are complex, and its pathogenesis has not been elucidated. traditional Chinese medicine, as a traditional treatment, its specific action and mechanism need to be confirmed by more studies, so that it can play a better role.