Chest computed tomography findings of the Omicron variants of SARS-CoV-2 with different cycle threshold values

BACKGROUND The Omicron variant of severe acute respiratory syndrome coronavirus 2(SARSCoV-2)mainly infects the upper respiratory tract.This study aimed to determine whether the probability of pulmonary infection and the cycle threshold(Ct)measured using the fluorescent polymerase chain reaction(PCR)method were related to pulmonary infections diagnosed via computed tomography(CT).AIM To analyze the chest CT signs of SARS-CoV-2 Omicron variant infections with different Ct values,as determined via PCR.METHODS The chest CT images and PCR Ct values of 331 patients with SARS-CoV-2Omicron variant infections were retrospectively collected and categorized into low(<25),medium(25.00-34.99),and high(≥35)Ct groups.The characteristics of chest CT images in each group were statistically analyzed.RESULTS The PCR Ct values ranged from 13.36 to 39.81,with 99 patients in the low,155 in the medium,and 77 in the high Ct groups.Six abnormal chest CT signs were detected,namely,focal infection,patchy consolidation shadows,patchy groundglass shadows,mixed consolidation ground-glass shadows,subpleural interstitial changes,and pleural changes.Focal infections were less frequent in the low Ct group than in the medium and high Ct groups;these infections were the most common sign in the medium and high Ct groups.Patchy consolidation shadows and pleural changes were more frequent in the low Ct group than in the other two groups.The number of patients with two or more signs was greater in the low Ct group than in the medium and high Ct groups.CONCLUSION The chest CT signs of patients with pulmonary infection caused by the Omicron variants of SARSCoV-2 varied depending on the Ct values.Identification of the characteristics of Omicron variant infection can help subsequent planning of clinical treatment.

Natural history and cycle threshold values analysis of COVID-19 in Xiamen City,China

Objective:This study elaborated the natural history parameters of Delta variant,explored the differences in detection cycle thresholds(Ct)among cases.Methods:Natural history parameters were calculated based on the different onset time and exposure time of the cases.Intergenerational relationships between generations of cases were calculated.Differences in Ct values of cases by gender,age,and mode of detection were analyzed statistically to assess the detoxification capacity of cases.Results:The median incubation period was 4 days;the detection time for cases decreased from 25 to 7 h as the outbreak continued.The average generation time(GT),time interval between transmission generations(TG)and serial interval(SI)were 3.6±2.6 days,1.67±2.11 days and 1.7±3.0 days.Among the Ct values,we found little differences in testing across companies,but there were some differences in the gender of detected genes.The Ct values continuous to decreased with age,but increased when the age was greater than 60.Conclusion:This epidemic was started from aggregation of factories.It is more reasonable to use SI to calculate the effective reproduction number and the time-varying reproduction number.And the analysis of Ct values can improve the positive detection rate and improve prevention and control measures.

Maintaining Consistency Based on Timely Updating Records List in Workflow Data

In order to settle the problem of workflow data consis-tency under the distributed environment, an invalidation strategy based-on timely updating record list is put forward. The strategy adopting the method of updating the records list and the recovery mechanism of updating message proves the classical invalidation strategy. When the request cycle of duplication is too long, the strategy uses the method of updating the records list to pause for sending updating message; when the long cycle duplication is requested again, it uses the recovery mechanism to resume the updating message. This strategy not only ensures the consistency of the workflow data, but also reduces the unnecessary network traffic. From theoretical comparison with those common strategies, the unnecessary network traffic of this strategy is fewer and more stable. The simulation results validate this conclusion.