CTCs detected in a blood sample from a liver cancer patient.

<p>A total of 10 CTCs were detected in this sample; 3 single migratory biophenotypic epithelial/mesenchymal CTCs, 3 single migratory mesenchymal CTCs and a tumor microembolus containing 4 mesenchymal CTCs were observed (epithelial biomarkers are indicated by red fluorescence; mesenchymal biomarkers are indicated by green fluorescence).</p

The three blood samples containing CTM from liver, nasopharyngeal and breast cancers.

<p>The three blood samples containing CTM from liver, nasopharyngeal and breast cancers.</p

Table_1_Age-specific transmission dynamic of mumps: A long-term large-scale modeling study in Jilin Province, China.docx

ObjectivesDespite the adoption of a new childhood immunization program in China, the incidence of mumps remains high. This study aimed to describe the epidemiological characteristics of mumps in Jilin Province from 2005 to 2019 and to assess the transmissibility of mumps virus among the whole population and different subgroups by regions and age groups.MethodsThe Non-age-specific and age-specific Susceptible–Exposed–Pre-symptomatic–Infectious–Asymptomatic–Recovered (SEPIAR) models were fitted to actual mumps incidence data. The time-varying reproduction number (Rt) was used to evaluate and compare the transmissibility.ResultsFrom 2005 to 2019, a total of 57,424 cases of mumps were reported in Jilin Province. The incidence of mumps was the highest in people aged 5 to 9 years (77.37 per 100,000). The two SEPIAR models fitted the reported data well (P t) calculated by the two SEPIAR models were 1.096 (range: 1.911 × 10−5–2.192) and 1.074 (range: 0.033–2.114) respectively. The age-specific SEPIAR model was more representative of the actual epidemic of mumps in Jilin Province from 2005–2019.ConclusionsFor mumps control, it is recommended that mumps-containing vaccines (MuCV) coverage be increased nationwide in the 5–9 years age group, either by a mumps vaccine alone or by a combination of vaccines such as measles-mumps-rubella (MMR) vaccine. The coverage of vaccines in Jilin Province should be continuously expanded to establish solid immunity in the population. China needs to redefine the optimal time interval for MuCV immunization.</p

EpCAM, CK8/18/19, vimentin and twist expression in HepG2 tumor cells and leukocytes.

<p><b>A</b>: negative control, leukocytes stained for CD45 expression (bright blue fluorescence); <b>B</b>: HepG2 cells stained for EpCAM expression (red fluorescence); <b>C</b>: HepG2 cells stained for CK8 expression(red fluorescence); <b>D</b>: HepG2 cells stained for CK18 expression(red fluorescence); <b>E</b>: HepG2 cells stained for CK19 expression(red fluorescence); <b>F</b>: HepG2 cells stained for vimentin expression (green fluorescence); <b>G:</b> HepG2 cells stained for twist expression(green fluorescence); <b>H:</b> HepG2 cells stained for EpCAM, CK8/18/19, vimentin and twist expression (red/green fluorescence). The cells were analyzed using a 100x oil objective</p

Calibration curve obtained using the optimized CanPatrol CTC enrichment technique in the spiking experiment (n = 8) using HepG2 cells at different dilutions.

<p>Calibration curve obtained using the optimized CanPatrol CTC enrichment technique in the spiking experiment (n = 8) using HepG2 cells at different dilutions.</p

Information and clinical characteristics of the patients.

<p>Information and clinical characteristics of the patients.</p

Image_1_Comparison of epidemiological characteristics and transmissibility of different strains of COVID-19 based on the incidence data of all local outbreaks in China as of March 1, 2022.PNG

BackgroundThe epidemiological characteristics and transmissibility of Coronavirus Disease 2019 (COVID-19) may undergo changes due to the mutation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains. The purpose of this study is to compare the differences in the outbreaks of the different strains with regards to aspects such as epidemiological characteristics, transmissibility, and difficulties in prevention and control.MethodsCOVID-19 data from outbreaks of pre-Delta strains, the Delta variant and Omicron variant, were obtained from the Chinese Center for Disease Control and Prevention (CDC). Case data were collected from China's direct-reporting system, and the data concerning outbreaks were collected by on-site epidemiological investigators and collated by the authors of this paper. Indicators such as the effective reproduction number (Reff), time-dependent reproduction number (Rt), rate of decrease in transmissibility (RDT), and duration from the illness onset date to the diagnosed date (DID)/reported date (DIR) were used to compare differences in transmissibility between pre-Delta strains, Delta variants and Omicron variants. Non-parametric tests (namely the Kruskal-Wallis H and Mean-Whitney U tests) were used to compare differences in epidemiological characteristics and transmissibility between outbreaks of different strains. P ResultsMainland China has maintained a “dynamic zero-out strategy” since the first case was reported, and clusters of outbreaks have occurred intermittently. The strains causing outbreaks in mainland China have gone through three stages: the outbreak of pre-Delta strains, the outbreak of the Delta variant, and outbreaks involving the superposition of Delta and Omicron variant strains. Each outbreak of pre-Delta strains went through two stages: a rising stage and a falling stage, Each outbreak of the Delta variant and Omicron variant went through three stages: a rising stage, a platform stage and a falling stage. The maximum Reff value of Omicron variant outbreaks was highest (median: 6.7; ranged from 5.3 to 8.0) and the differences were statistically significant. The RDT value of outbreaks involving pre-Delta strains was smallest (median: 91.4%; [IQR]: 87.30–94.27%), and the differences were statistically significant. The DID and DIR for all strains was mostly in a range of 0–2 days, with more than 75%. The range of duration for outbreaks of pre-Delta strains was the largest (median: 20 days, ranging from 1 to 61 days), and the differences were statistically significant.ConclusionWith the evolution of the virus, the transmissibility of the variants has increased. The transmissibility of the Omicron variant is higher than that of both the pre-Delta strains and the Delta variant, and is more difficult to suppress. These findings provide us with get a more clear and precise picture of the transmissibility of the different variants in the real world, in accordance with the findings of previous studies. Reff is more suitable than Rt for assessing the transmissibility of the disease during an epidemic outbreak.</p

Image_2_Comparison of epidemiological characteristics and transmissibility of different strains of COVID-19 based on the incidence data of all local outbreaks in China as of March 1, 2022.PNG

BackgroundThe epidemiological characteristics and transmissibility of Coronavirus Disease 2019 (COVID-19) may undergo changes due to the mutation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains. The purpose of this study is to compare the differences in the outbreaks of the different strains with regards to aspects such as epidemiological characteristics, transmissibility, and difficulties in prevention and control.MethodsCOVID-19 data from outbreaks of pre-Delta strains, the Delta variant and Omicron variant, were obtained from the Chinese Center for Disease Control and Prevention (CDC). Case data were collected from China's direct-reporting system, and the data concerning outbreaks were collected by on-site epidemiological investigators and collated by the authors of this paper. Indicators such as the effective reproduction number (Reff), time-dependent reproduction number (Rt), rate of decrease in transmissibility (RDT), and duration from the illness onset date to the diagnosed date (DID)/reported date (DIR) were used to compare differences in transmissibility between pre-Delta strains, Delta variants and Omicron variants. Non-parametric tests (namely the Kruskal-Wallis H and Mean-Whitney U tests) were used to compare differences in epidemiological characteristics and transmissibility between outbreaks of different strains. P ResultsMainland China has maintained a “dynamic zero-out strategy” since the first case was reported, and clusters of outbreaks have occurred intermittently. The strains causing outbreaks in mainland China have gone through three stages: the outbreak of pre-Delta strains, the outbreak of the Delta variant, and outbreaks involving the superposition of Delta and Omicron variant strains. Each outbreak of pre-Delta strains went through two stages: a rising stage and a falling stage, Each outbreak of the Delta variant and Omicron variant went through three stages: a rising stage, a platform stage and a falling stage. The maximum Reff value of Omicron variant outbreaks was highest (median: 6.7; ranged from 5.3 to 8.0) and the differences were statistically significant. The RDT value of outbreaks involving pre-Delta strains was smallest (median: 91.4%; [IQR]: 87.30–94.27%), and the differences were statistically significant. The DID and DIR for all strains was mostly in a range of 0–2 days, with more than 75%. The range of duration for outbreaks of pre-Delta strains was the largest (median: 20 days, ranging from 1 to 61 days), and the differences were statistically significant.ConclusionWith the evolution of the virus, the transmissibility of the variants has increased. The transmissibility of the Omicron variant is higher than that of both the pre-Delta strains and the Delta variant, and is more difficult to suppress. These findings provide us with get a more clear and precise picture of the transmissibility of the different variants in the real world, in accordance with the findings of previous studies. Reff is more suitable than Rt for assessing the transmissibility of the disease during an epidemic outbreak.</p

Table_1_Comparison of epidemiological characteristics and transmissibility of different strains of COVID-19 based on the incidence data of all local outbreaks in China as of March 1, 2022.xlsx

BackgroundThe epidemiological characteristics and transmissibility of Coronavirus Disease 2019 (COVID-19) may undergo changes due to the mutation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains. The purpose of this study is to compare the differences in the outbreaks of the different strains with regards to aspects such as epidemiological characteristics, transmissibility, and difficulties in prevention and control.MethodsCOVID-19 data from outbreaks of pre-Delta strains, the Delta variant and Omicron variant, were obtained from the Chinese Center for Disease Control and Prevention (CDC). Case data were collected from China's direct-reporting system, and the data concerning outbreaks were collected by on-site epidemiological investigators and collated by the authors of this paper. Indicators such as the effective reproduction number (Reff), time-dependent reproduction number (Rt), rate of decrease in transmissibility (RDT), and duration from the illness onset date to the diagnosed date (DID)/reported date (DIR) were used to compare differences in transmissibility between pre-Delta strains, Delta variants and Omicron variants. Non-parametric tests (namely the Kruskal-Wallis H and Mean-Whitney U tests) were used to compare differences in epidemiological characteristics and transmissibility between outbreaks of different strains. P ResultsMainland China has maintained a “dynamic zero-out strategy” since the first case was reported, and clusters of outbreaks have occurred intermittently. The strains causing outbreaks in mainland China have gone through three stages: the outbreak of pre-Delta strains, the outbreak of the Delta variant, and outbreaks involving the superposition of Delta and Omicron variant strains. Each outbreak of pre-Delta strains went through two stages: a rising stage and a falling stage, Each outbreak of the Delta variant and Omicron variant went through three stages: a rising stage, a platform stage and a falling stage. The maximum Reff value of Omicron variant outbreaks was highest (median: 6.7; ranged from 5.3 to 8.0) and the differences were statistically significant. The RDT value of outbreaks involving pre-Delta strains was smallest (median: 91.4%; [IQR]: 87.30–94.27%), and the differences were statistically significant. The DID and DIR for all strains was mostly in a range of 0–2 days, with more than 75%. The range of duration for outbreaks of pre-Delta strains was the largest (median: 20 days, ranging from 1 to 61 days), and the differences were statistically significant.ConclusionWith the evolution of the virus, the transmissibility of the variants has increased. The transmissibility of the Omicron variant is higher than that of both the pre-Delta strains and the Delta variant, and is more difficult to suppress. These findings provide us with get a more clear and precise picture of the transmissibility of the different variants in the real world, in accordance with the findings of previous studies. Reff is more suitable than Rt for assessing the transmissibility of the disease during an epidemic outbreak.</p

Image_3_Comparison of epidemiological characteristics and transmissibility of different strains of COVID-19 based on the incidence data of all local outbreaks in China as of March 1, 2022.PNG

BackgroundThe epidemiological characteristics and transmissibility of Coronavirus Disease 2019 (COVID-19) may undergo changes due to the mutation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains. The purpose of this study is to compare the differences in the outbreaks of the different strains with regards to aspects such as epidemiological characteristics, transmissibility, and difficulties in prevention and control.MethodsCOVID-19 data from outbreaks of pre-Delta strains, the Delta variant and Omicron variant, were obtained from the Chinese Center for Disease Control and Prevention (CDC). Case data were collected from China's direct-reporting system, and the data concerning outbreaks were collected by on-site epidemiological investigators and collated by the authors of this paper. Indicators such as the effective reproduction number (Reff), time-dependent reproduction number (Rt), rate of decrease in transmissibility (RDT), and duration from the illness onset date to the diagnosed date (DID)/reported date (DIR) were used to compare differences in transmissibility between pre-Delta strains, Delta variants and Omicron variants. Non-parametric tests (namely the Kruskal-Wallis H and Mean-Whitney U tests) were used to compare differences in epidemiological characteristics and transmissibility between outbreaks of different strains. P ResultsMainland China has maintained a “dynamic zero-out strategy” since the first case was reported, and clusters of outbreaks have occurred intermittently. The strains causing outbreaks in mainland China have gone through three stages: the outbreak of pre-Delta strains, the outbreak of the Delta variant, and outbreaks involving the superposition of Delta and Omicron variant strains. Each outbreak of pre-Delta strains went through two stages: a rising stage and a falling stage, Each outbreak of the Delta variant and Omicron variant went through three stages: a rising stage, a platform stage and a falling stage. The maximum Reff value of Omicron variant outbreaks was highest (median: 6.7; ranged from 5.3 to 8.0) and the differences were statistically significant. The RDT value of outbreaks involving pre-Delta strains was smallest (median: 91.4%; [IQR]: 87.30–94.27%), and the differences were statistically significant. The DID and DIR for all strains was mostly in a range of 0–2 days, with more than 75%. The range of duration for outbreaks of pre-Delta strains was the largest (median: 20 days, ranging from 1 to 61 days), and the differences were statistically significant.ConclusionWith the evolution of the virus, the transmissibility of the variants has increased. The transmissibility of the Omicron variant is higher than that of both the pre-Delta strains and the Delta variant, and is more difficult to suppress. These findings provide us with get a more clear and precise picture of the transmissibility of the different variants in the real world, in accordance with the findings of previous studies. Reff is more suitable than Rt for assessing the transmissibility of the disease during an epidemic outbreak.</p