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Background@#/Aim: It is known that an imbalance in the intestinal f lora plays a crucial role in colorectal cancer (CRC), but the effect of food consumption patterns on the types of intestinal flora remains to be clarified. We aimed to analyze the associations between food intake and intestinal flora in healthy and CRC individuals. @*Methods@#Food intake data were recorded using the Food Frequency Questionnaire (FFQ). The composition and diversity of the intestinal flora detected by 16S rRNA gene sequencing, and the data were analyzed by R version 3.1.1 software. @*Results@#Higher intake of red meat or pickled foods, and lower intake of white meat, fruits, vegetables, beans, nuts were found in the CRC group compared with the healthy group. Higher levels of Fusobacteria and Proteobacteria, and lower levels of Firmicutes were observed in the CRC group. Partial correlation analysis revealed that the intake of fruits, beans, and nuts was negatively correlated with Proteobacteria and Fusobacteria, but pickled food was positively correlated with Fusobacteria (p < 0.05). Fish, beans, and nuts intake was negatively correlated with Escherichia (p = 0.01). Multiple regression analysis revealed that vegetable oil (odds ratio [OR], 0.26; 95% confidence interval [CI], 0.13 to 0.82), vegetables (OR, 0.26; 95% CI, 0.10 to 0.64), eggs (OR, 0.26; 95% CI, 0.10 to 0.69), pickled foods (OR, 21.02; 95% CI, 6.02 to 73.45), and red meat (OR, 4.23; 95% CI, 1.68 to 10.60) had an impact on CRC risk. @*Conclusions@#The species and abundance of intestinal flora varies between CRC and healthy individuals and may be affected by their food preference.
ABSTRACT
Background@#/Aim: It is known that an imbalance in the intestinal f lora plays a crucial role in colorectal cancer (CRC), but the effect of food consumption patterns on the types of intestinal flora remains to be clarified. We aimed to analyze the associations between food intake and intestinal flora in healthy and CRC individuals. @*Methods@#Food intake data were recorded using the Food Frequency Questionnaire (FFQ). The composition and diversity of the intestinal flora detected by 16S rRNA gene sequencing, and the data were analyzed by R version 3.1.1 software. @*Results@#Higher intake of red meat or pickled foods, and lower intake of white meat, fruits, vegetables, beans, nuts were found in the CRC group compared with the healthy group. Higher levels of Fusobacteria and Proteobacteria, and lower levels of Firmicutes were observed in the CRC group. Partial correlation analysis revealed that the intake of fruits, beans, and nuts was negatively correlated with Proteobacteria and Fusobacteria, but pickled food was positively correlated with Fusobacteria (p < 0.05). Fish, beans, and nuts intake was negatively correlated with Escherichia (p = 0.01). Multiple regression analysis revealed that vegetable oil (odds ratio [OR], 0.26; 95% confidence interval [CI], 0.13 to 0.82), vegetables (OR, 0.26; 95% CI, 0.10 to 0.64), eggs (OR, 0.26; 95% CI, 0.10 to 0.69), pickled foods (OR, 21.02; 95% CI, 6.02 to 73.45), and red meat (OR, 4.23; 95% CI, 1.68 to 10.60) had an impact on CRC risk. @*Conclusions@#The species and abundance of intestinal flora varies between CRC and healthy individuals and may be affected by their food preference.
ABSTRACT
OBJECTIVE To investigate the Ureaplasma urealyticum infection in patients with urogenital infections and the distribution of its serotypes and genotypes.METHODS The clinical samples were firstly screened with B-Merieux mycoplasma ID2 culture and identification kit,then the positive cultural samples were subtyped by PCR method.RESULTS The positive rate of U.urealyticum with cultural kit was 37.43%(670/1790).The 392 positive cultural samples were subtyped with PCR,the positive rate of U.parvum was 71.94% and the positive rate of U.urealyticum was 29.85%.The serotypes of 264 U.parvum positive samples were identified with PCR,there were 20 samples with serovar 1(7.58%),139 samples with serovar 3 or 14(52.65%),and 51 samples with serovar 6(19.32%).Ninety nine positive samples with U.urealyticum were genotyped,the results showed that the rate of genotype 3(serovar 7 or 11) was lower than genotypes 1 and 2.CONCLUSIONS PCR identification and subtyping of Ureaplasma in patients with urogenital infections showed that the major epidemic pathogen of Ureaplasma in east of Guangdong Province is U.urealyticum serovar 3 and serovar 6,and the distribution of different serotypes or genotypes of Ureaplasma in this area is specific.
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Objective To establish a quality control process for Sysmex UF 100 Urine analyzer. Methods L J control process of UF 100 Urine analyzer; x m Q C methods; Chemistry and UF 100 methods comparison; Microscope examination Results L J control process can reflect and monitor the instrument status and the reagent quality; The x m Q C method can indicate the influence factor which come from the samples; Chemistry and UF 100′s comparison can find their contradiction and the error causes;Microscopy can make up UF 100′s test blind spots Conclusions These methods can monitor the result′s quality practically and effectively It is benefit to improve the test quality of UF 100 analyzer
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Objective To study the clinical characteristics,diagnosis and differential diagnosis of myelodysplastic syndrome.Methods The clinical features,routine hematological tests and morphology of medullary cells were analyzed in 49 cases.Results Of 49 cases,there were 36.7% of RA,8.2% of RAS,20.4% of RAEB,30.6% of RAEBT and 4.0% of CMML,respectively ,which showed the positive pathosis hemogenesis ,and had a trend of transforming to leukemia.Conclusion MDS(especially RA)is difficult to diagnose,which should be diagnosed according to pathosis hemogensis.The detection of blasts in peripheral blood will help to differentiate RA and CAA,but more researches should be made on the differentiation of MDS/AML and AML-TMDS.