ABSTRACT
Giardia lamblia is a common enteric pathogen associated with diarrheal diseases. There are some reports of G. lamblia infection among different breeds of cattle in recent years worldwide. However, it is yet to know whether cattle in Jiangxi province, southeastern China is infected with G. lamblia. The objectives of the present study were to investigate the prevalence and examine the multilocus genotypes of G. lamblia in cattle in Jiangxi province. A total of 556 fecal samples were collected from 3 cattle breeds (dairy cattle, beef cattle, and buffalo) in Jiangxi province, and the prevalence and genotypes of G. lamblia were determined by the nested PCR amplification of the beta-giardin (bg) gene. A total of 52 samples (9.2%) were positive for G. lamblia. The highest prevalence of G. lamblia was detected in dairy cattle (20.0%), followed by that in beef cattle (6.4%), and meat buffalo (0.9%). Multilocus sequence typing of G. lamblia was performed based on sequences of the bg, triose phosphate isomerase and glutamate dehydrogenase loci, and 22, 42, and 52 samples were amplifiable, respectively, forming 15 MLGs. Moreover, one mixed G. lamblia infection (assemblages A and E) was found in the present study. Altogether, 6 novel assemblage E subtypes (E41*-E46*) were identified for the first time. These results not only provided baseline data for the control of G. lamblia infection in cattle in this southeastern province of China, but also enriched the molecular epidemiological data and genetic diversity of G. lamblia in cattle.
ABSTRACT
Giardia lamblia is a common enteric pathogen associated with diarrheal diseases. There are some reports of G. lamblia infection among different breeds of cattle in recent years worldwide. However, it is yet to know whether cattle in Jiangxi province, southeastern China is infected with G. lamblia. The objectives of the present study were to investigate the prevalence and examine the multilocus genotypes of G. lamblia in cattle in Jiangxi province. A total of 556 fecal samples were collected from 3 cattle breeds (dairy cattle, beef cattle, and buffalo) in Jiangxi province, and the prevalence and genotypes of G. lamblia were determined by the nested PCR amplification of the beta-giardin (bg) gene. A total of 52 samples (9.2%) were positive for G. lamblia. The highest prevalence of G. lamblia was detected in dairy cattle (20.0%), followed by that in beef cattle (6.4%), and meat buffalo (0.9%). Multilocus sequence typing of G. lamblia was performed based on sequences of the bg, triose phosphate isomerase and glutamate dehydrogenase loci, and 22, 42, and 52 samples were amplifiable, respectively, forming 15 MLGs. Moreover, one mixed G. lamblia infection (assemblages A and E) was found in the present study. Altogether, 6 novel assemblage E subtypes (E41*-E46*) were identified for the first time. These results not only provided baseline data for the control of G. lamblia infection in cattle in this southeastern province of China, but also enriched the molecular epidemiological data and genetic diversity of G. lamblia in cattle.
ABSTRACT
Objective: To forecast the visceral leishmaniasis cases using autoregress integrated moving average (ARIMA) and hybrid ARIMA-EGARCH model, which offers a scientific basis to control visceral leishmaniasis spread in Kashgar Prefecture of Xinjiang, China. Methods: The data used in this paper are monthly visceral leishmaniasis cases in the Kashgar Prefecture of Xinjiang from 2004 to 2016. The sample data between 2004 and 2015 were used for the estimation to choose the best model and the sample data in 2016 were used for the forecast. Time series of visceral leishmaniasis started on 1 January 2004 and ended on 31 December 2016, consisting of 1 790 observations reported in Kashgar Prefecture. Results: For Xinjiang, the total number of reported cases were 2 187, the male-to-female ratio of cases was 1:1.42. Patients aged between 0 and 10 years accounted for 82.72% of all reported cases and the largest percentage of visceral leishmaniasis cases was detected among scattered children who accounted for 68.82%. The monthly incidences fitted by ARIMA (2, 1, 2) (1, 1, 1)
ABSTRACT
Objective To quantitatively analyze the epidemic situation of tuberculosis(TB)by modeling the data of tuberculosis in prefectures of Xinjiang,and predict the new cases of tuberculosis in prefectures of Xinjiang.Methods A dynamic model was used to fit the data of TB in 14 prefectures in Xinjiang from 2005 to 2014,the results of the fitting were verified by tuberculosis data in 2015－2017,verified results were evaluated,estimated values and basic reproductive numbers (R0)of parameters in each region were obtained,data of new TB in 2018－2022 were predic-ted.Results The verification of TB data in 2015－2017 showed that the actual values fell within the 95% confidence interval of the predictive value curve,model was fit well.R0in Southern Kashgar was 1 1.38 (95%CI:1 1.33－11.50),R0in Urumqi City in Eastern Xinjiang and Ili Kazak Autonomous Prefecture in Northern Xinjiang were 5.46 (95% CI :5.28－5.50)and 2.22 (95% CI :2.18－2.28)respectively.The epidemic situation of TB in Southern Xinjiang was more serious than that in Northern and Eastern Xinjiang,epidemic situation of TB in Kash- gar Prefecture was most serious.The predicted results showed that the number of new TB from 2018 to 2022 will slowly grow in most prefectures.Conclusion The dynamical model of TB fits well and is feasible in this study,it can be used for prediction of new TB cases,intervention and management in Southern Xinjiang should be strength-ened to control the prevalence of TB.
ABSTRACT
Orange peel was used as lowcost adsorbent in binding of Methylene Blue.The effects of equilibrium time,pH,dye concentration have been studied.Carboxyl,amine and phosphonate functional groups were present in the orange peel.The equilibrium time was 1 hour,the maximum adsorption capacities of the orange peel was 370.3?31.0 mg/g at pH 10.The Langmuir and Freundlich isotherms were well fitted in this biosorption system.Results showed relatively higher rate constant and biosorption capacities.These adsorption performance indicate the orange peel as a potentially economical adsorbent for dye removal.