Objective The purpose of this paper was to evaluate the clinical value of double-contrast barium(DCB) combined with CT in the diagnosis of gastric carcinoma.Methods 112 patients with gastric carcinoma confirmed by surgery and pathology between 1990 and 1997 were included.69 patients took DCB of the upper gastric intestinal tract.43 patients were given CT scans,in whom 32 patients took DCB before CT.Results The accuracy of gastric carcinoma staging determined by DCB were 91.3%.The accordant rate of gross type of gastric carcinoma determined by DCB and the combined way were respectively 67.74% and 72.41%,superior to CT(47.22%,?

Objective To identify the species of Biomphalaria snails collected in Shenzhen reservoir,based on the mitochondrial 16S rDNA sequences.Methods The 16S rDNA fragments were amplified by PCR from the genome DNA of Biomphalaria snails,and inserted in plasmid pMD-18T for sequencing.The sequence of 16S rDNA fragment and its phylogenetic relationships with those of other species of Biomphalaria snails were analyzed with BLAST and MEGA4 software.Results The amplified 16S rDNA fragment of the Biomphalaria snails was about 466 bp in length.As aligned with the corresponding sequences of the related Biomphalaria species,the identity of nucleotides was 99％ with 1 isolate of Biomphaltria straminea (B.straminea),98％ with 3 isolates of B.kuhniana,95％ with 1 isolate of B.intermedia,and 94％ with 1 isolate of B.edisoni.Based on the 16S rDNA sequence,the results of phylogenetic analysis with neighbor-joining (NJ) and unweighted pair-group method with arithmetic means (UPGMA) indicated that the snails had close genetic relationships with the B.straminea isolate (Genbank accession NO.AY030213.1) Conclusion The Biomphalaria snails collected in Shenzhen reservoir could be classified as B.straminea based on the characteristics of 16S rDNA sequence.

Objective:To investigate the characteristics of death, tendency and the prediction of Shenzhen residents with adult hematological malignancies from 2017 to 2020.Methods:The surveillance data of hematological malignancies from 2017 to 2020 and the demographic data in Shenzhen were collected from Shenzhen death cause monitoring system and Shenzhen Center for Disease Control and Prevention, respectively. The data of the 7th national demographic data in 2020 were set as the standardized population data. Crude mortality rate (CMR), standardized mortality rate (SMR) and annual percentage change (APC) of mortality were calculated by using Joinpoint software. The grey model GM(1,1) was built to predict the mortality of adult hematological malignancies in Shenzhen between 2021 and 2025.Results:From 2017 to 2022, the male CMR of hematological malignancies was 1.15/100 000 to 1.85/100 000, and the SMR was 2.24/100 000 to 2.44/100 000; the female CMR of hematological malignancies was 0.81/100 000 to 1.75/100 000, and the SMR was 1.67/100 000 to 1.90/100 000. There were no statistically significant differences in the annual CMR and SMR between male and female hematological malignancies (all P > 0.05), and the annual change trend of CMR and SMR was not significant. The APC of male and female CMR was 27.28% and 12.70%, respectively (χ 2 = 0.01, P = 0.939); the APC of male and female SMR was 1.12% and 4.77%, respectively (χ 2 = 0.91, P = 0.318). The death causes of hematological malignancies were successively acute myeloid leukemia (AML), lymphoma, multiple myeloma, acute lymphoblastic leukemia (ALL), myelodysplastic syndrome (MDS) plus chronic myelomonocytic leukemia (CMML), chronic lymphoblastic leukemia (CLL) plus chronic myelogenous leukemia (CML). The CMR of patients with hematological malignancies aged 18-40 years was low, the CMR began to rise in patients above 40 years, especially the rapid increase at the age of 60 years, reaching the peak at the age of 80 years or above. The shortest median time of all kinds of hematological malignancies from the onset of disease to the death was found in AML group (8 months, range 0.1-168 months), the longest time was in CLL+CML group (24 months, range 0.1-300 months). Infection was the most direct cause of death, followed by single organ failure. GM(1,1) model had the better predictive effects and the total SMR would increase from 2021 to 2025 (4.52/100 000, 4.76/100 000, 5.01/100 000, 5.28/100 000 and 5.57/100 000, respectively). Conclusions:The incidence of hematological malignancies in Shenzhen residents over 40 years old is on the increase. The trend of adult hematological malignancies in Shenzhen will rise predicted by GM (1,1) grey model.

OBJECTIVETo study the potential association of DNA oxidation and DNA methylation, in vitro cultured cells were exposed to different doses of H2O2, 8-oxo-dG formation, cell DNA 5-mC contents were analyzed to explore the time- dose-response relationship of DNA oxidation and DNA methylation.

METHODSA549 cells were exposed to different doses of H2O2, 8-oxo-dG formation and cell genomic DNA 5-mC contents were analyzed by a high-performance liquid chromatography system and high performance capillary electrophoresis (HPCE), respectively.

RESULTSH2O2 induced the formation of 8-oxo-dG and 5-mC in different characteristics, it need at least 10 days for significant changes in the level of DNA methylation, whereas under the same conditions, changes in the level of DNA oxidation cast only 12 hours. H2O2 induced decreased levels of DNA methylation in A549 cells in a dose-dependent manner. In a certain range of time and dose, it showed a negative correlation between DNA oxidation and DNA methylation.

CONCLUSIONThe study suggests that oxidative DNA could lead to reduced levels of DNA methylation, DNA oxidation may affect the regulation of cellular methylation mechanisms, in the course of chemical mutagenesis, DNA oxidation may be an earlier important molecule event than DNA methylation.

Cell Line ; DNA ; chemistry ; DNA Damage ; DNA Methylation ; Deoxyguanosine ; analogs & derivatives ; chemistry ; Humans ; Hydrogen Peroxide ; toxicity ; Oxidative Stress

Objectives:This study aimed to evaluate the effect of the strategies on COVID-19 outbreak control in Shenzhen, and to clarify the feasibility of these strategies in metropolitans that have high population density and strong mobility.Methods:The epidemic feature of COVID-19 was described by different phases and was used to observe the effectiveness of intervention. Hierarchical spot map was drawn to clarify the distribution and transmission risk of infection sources at different time points. The Susceptible-Exposed-Infectious-Asymptomatic-Recovered model was established to estimate case numbers without intervention and compare with the actual number of cases to determine the effect of intervention. The positive rate of the nucleic acid test was used to reflect the risk of human exposure. A survey on COVID-19 related knowledge, attitude and behaviors were used to estimate the abilities of personal protection and emergency response.Results:The epidemic of COVID-19 in Shenzhen experienced the rising, plateau and decline stage. The case number increased rapidly at the beginning, with short duration of peak period. Although the epidemic curve showed human-to-human transmission, the "trailing" was not obvious. From the spot map, during the intervention period, the source of infection was widely distributed. More cases and higher transmission risk were observed in areas with higher population density. After the effective intervention measures, both infection sources and the risk of transmission decreased. After compared with the estimated case numbers without intervention, actual number proved the COVID-19 control strategies were effective. The positive rate of nucleic acid test for high risk populations decreased and no new cases reported since February 16. Shenzhen citizens had high knowledge, attitude and behavior level, and high protection ability and emergency response.Conclusions:Although the response initiated by the health administration department played a key role at the early stage of the epidemic, it was not enough to contain the outbreak of COVID-19. The first-level emergency response initiated by provincial and municipal government was effective and ensured the start of work resumption after the Spring Festival. Metropolitans like Shenzhen can also achieve the goals of strategies and measures for containment and mitigation of COVID-19.

Objective: To investigate the epidemiological characteristics of norovirus outbreaks in Shenzhen during 2005 to 2017 in order to provide reference for disease control and prevention. Methods: Monitoring data of norovirus outbreaks in Shenzhen from January 1, 2005 to December 31, 2017 were collected from Shenzhen Communicable Disease Information System and China Information System for Disease Control and Prevention. Descriptive epidemiological methods were used for data analysis. Results: From January 2005 to December 2017, 346 norovirus outbreaks (five or more cases in one community within one week) were reported in Shenzhen, of which 6.36% (22/346) were public health emergency events. Fewer outbreaks were reported during 2006 to 2013 and they were mainly caused by GⅡ.4 genotype, but the number increased sharply since 2014 with 57.80% (200/346) occurred in 2016—2017 and the epidemic genotype changed from GⅡ.4 to GⅡ.17 and GⅡ.2. The outbreaks peaked during November to March (76.88%, 266/346). There were 63.87% (221/346) reported in urban areas, 67.05% (232/346) in nurseries and 23.70% (82/346) in primary/middle schools. Among the 22 public health emergency events, 40.91% (10/22) were caused by person-to-person contacts, 40.91% (10/22) by foodborne transmission and 13.64% (3/22) by waterborne transmission. Moreover, 75.80% (238/314) of the outbreaks in nurseries and primary/middle schools were confined to one classroom and most were due to contact transmission. Conclusions Norovirus outbreaks increased obviously since 2014, which might be related to the changes of the predominant genotype from GⅡ.4 to GⅡ.17 and GⅡ.2. It is necessary to strengthen a comprehensive prevention and control in key units such as nurseries and primary/middle schools in winter and spring.