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1.
China Journal of Chinese Materia Medica ; (24): 2697-2704, 2018.
Article in Chinese | WPRIM | ID: wpr-687397

ABSTRACT

With total flavonoid content and dry extract yield as the observation indexes, the optimal extraction conditions of Moringa oleifera leaves were determined by using single factor test and orthogonal test, and cyclophosphamide modeling method was used to establish immunosuppressed mice models, so as to investigate the effects of M. oleifera leaves extract on immune regulation in mice. The results showed that the optimal preparation conditions were as follows: extraction with 70% ethanol, material-liquid ratio 1:15, extraction temperature 80 °C, three times, 1.5 hours for each time. Under these conditions, the content of total flavonoids from M. oleifera leaves was 15.64 mg·g⁻¹, which can significantly enhance macrophage phagocytosis and immune organ index, promote the synthesis of serum immunoglobulin IgG and hemolysin, and decrease AST activity, with regulation effect on immune dysfunction.

2.
Chinese Journal of Medical Genetics ; (6): 612-615, 2013.
Article in Chinese | WPRIM | ID: wpr-254551

ABSTRACT

<p><b>OBJECTIVE</b>To analyze the clinical effect of fetal chromosomal reciprocal translocation in order to optimize procedures for prenatal diagnosis and clinical counseling.</p><p><b>METHODS</b>Conventional G-banding karyotype analysis was performed on 7901 amniotic fluid samples. For fetuses found to have carried a reciprocal translocation, karyotypes of their parents were checked. Fetuses with de novo translocations also underwent microarray analysis to exclude small deletions, and were subjected to prenatal ultrasound monitoring till birth and one year follow-up. Those with de novo translocations were followed till 3 years old.</p><p><b>RESULTS</b>A total of 24 fetal reciprocal translocations have been identified, which gave a detection rate of 0.30%. Analysis of parental karyotypes has found reciprocal translocations in 17 cases, including 9 maternal and 8 paternal cases. The remaining 4 were of de novo mutations, for which parental examination was refused in three cases. For fetuses with inherited translocations, prenatal ultrasound monitoring and follow-up results were all normal. For those with de novo translocations, although gene chip analysis has failed to detect copy number variations (CNVs), prenatal ultrasound and follow-up results had found three with abnormal outcome. These included 1 case with reciprocal translocation involving the X chromosome and an autosome.</p><p><b>CONCLUSION</b>For prenatally detected reciprocal chromosome translocations, parental origin should be traced. Gene chip analysis can help to exclude small deletions and duplications. However, ultrasound monitoring and follow-up after birth are equally important. Based on comprehensive analysis of the results of combined testing, accurate counseling can be provided.</p>


Subject(s)
Adult , Female , Humans , Male , Pregnancy , Young Adult , Amniotic Fluid , Cell Biology , Chromosome Banding , Fetal Diseases , Diagnosis , Genetics , Fetus , Cell Biology , Genetic Counseling , Prenatal Diagnosis , Translocation, Genetic
3.
Chinese Journal of Preventive Medicine ; (12): 246-251, 2012.
Article in Chinese | WPRIM | ID: wpr-292488

ABSTRACT

<p><b>OBJECTIVE</b>To explore the influence of landscape elements on the transmission of hemorrhagic fever with renal syndrome (HFRS) in Changsha.</p><p><b>METHODS</b>A total of 327 cases of HFRS diagnosed between year 2005 - 2009 were recruited in the study. Based on the demographic data, meteorological data and the data of second national land survey during the same period, a GIS landscape elements database of HFRS at the township scale of Changsha was established. Spatial-temporal cluster analysis methods were adopted to explore the influence of landscape elements on the spatial-temporal distribution of HFRS in Changsha during the year of 2005 - 2009.</p><p><b>RESULTS</b>The annual incidences of HFRS in Changsha between year 2005 - 2009 were 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000(87 cases), 0.75/100 000(47 cases) and 1.02/100 000(65 cases) respectively. The results of poisson regression model analysis of principal component showed that the incidence of HFRS was positively correlated with farmland area (M = 29.00 km2) and urban and rural area (M = 6.12 km2; incidence rate ratios (IRR) = 1.34, 95% CI: 1.27 - 1.41); but negatively correlated with forestland area (M = 39.00 km2; IRR = 0.67, 95% CI: 0.55 - 0.81) and garden plot area (M = 0.99 km2; IRR = 0.74, 95% CI: 0.63 - 0.86). A significant cluster of the spatial-temporal distribution of HFRS cases was found in the study. The primary cluster (28.9 N, 113.37 E, radius at 22.22 km, RR = 5.23, log likelihood ratio (LLR) = 51.61, P <0.01, 67 cases of HFRS and incidence at 4.4/100 000) was found between year 2006 and 2007; and the secondary cluster (28.2 N, 113.6 E, RR = 10.77, LLR = 16.01, P < 0.01, 11 cases of HFRS and the incidence at 10.6/100 000) was found between year 2008 and 2009.</p><p><b>CONCLUSION</b>The landscape elements were found to be closely related to the prevalence and transmission of HFRS.</p>


Subject(s)
Humans , China , Epidemiology , Climate , Geographic Information Systems , Hemorrhagic Fever with Renal Syndrome , Epidemiology , Regression Analysis , Space-Time Clustering
4.
Chinese Journal of Preventive Medicine ; (12): 430-435, 2012.
Article in Chinese | WPRIM | ID: wpr-292455

ABSTRACT

<p><b>OBJECTIVE</b>To analyze the periodicity of pandemic influenza A (H1N1) in Changsha in year 2009 and its correlation with sensitive climatic factors.</p><p><b>METHODS</b>The information of 5439 cases of influenza A (H1N1) and synchronous meteorological data during the period between May 22th and December 31st in year 2009 (223 days in total) in Changsha city were collected. The classification and regression tree (CART) was employed to screen the sensitive climatic factors on influenza A (H1N1); meanwhile, cross wavelet transform and wavelet coherence analysis were applied to assess and compare the periodicity of the pandemic disease and its association with the time-lag phase features of the sensitive climatic factors.</p><p><b>RESULTS</b>The results of CART indicated that the daily minimum temperature and daily absolute humidity were the sensitive climatic factors for the popularity of influenza A (H1N1) in Changsha. The peak of the incidence of influenza A (H1N1) was in the period between October and December (Median (M) = 44.00 cases per day), simultaneously the daily minimum temperature (M = 13°C) and daily absolute humidity (M = 6.69 g/m(3)) were relatively low. The results of wavelet analysis demonstrated that a period of 16 days was found in the epidemic threshold in Changsha, while the daily minimum temperature and daily absolute humidity were the relatively sensitive climatic factors. The number of daily reported patients was statistically relevant to the daily minimum temperature and daily absolute humidity. The frequency domain was mostly in the period of (16 ± 2) days. In the initial stage of the disease (from August 9th and September 8th), a 6-day lag was found between the incidence and the daily minimum temperature. In the peak period of the disease, the daily minimum temperature and daily absolute humidity were negatively relevant to the incidence of the disease.</p><p><b>CONCLUSION</b>In the pandemic period, the incidence of influenza A (H1N1) showed periodic features; and the sensitive climatic factors did have a "driving effect" on the incidence of influenza A (H1N1).</p>


Subject(s)
Humans , China , Epidemiology , Climate , Influenza A Virus, H1N1 Subtype , Influenza, Human , Epidemiology , Virology , Regression Analysis , Risk Factors , Seasons , Temperature
5.
Chinese Journal of Preventive Medicine ; (12): 881-885, 2011.
Article in Chinese | WPRIM | ID: wpr-266080

ABSTRACT

<p><b>OBJECTIVE</b>To realize the influence of climatic changes on the transmission of hemorrhagic fever with renal syndrome (HFRS), and to explore the adoption of climatic factors in warning HFRS.</p><p><b>METHODS</b>A total of 2171 cases of HFRS and the synchronous climatic data in Changsha from 2000 to 2009 were collected to a climate-based forecasting model for HFRS transmission. The Cochran-Armitage trend test was employed to explore the variation trend of the annual incidence of HFRS. Cross-correlations analysis was then adopted to assess the time-lag period between the climatic factors, including monthly average temperature, relative humidity, rainfall and Multivariate Elño-Southern Oscillation Index (MEI) and the monthly HFRS cases. Finally the time-series Poisson regression model was constructed to analyze the influence of different climatic factors on the HFRS transmission.</p><p><b>RESULTS</b>The annual incidence of HFRS in Changsha between 2000 - 2009 was 13.09/100 000 (755 cases), 9.92/100 000 (578 cases), 5.02/100 000 (294 cases), 2.55/100 000 (150 cases), 1.13/100 000 (67 cases), 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000 (87 cases), 0.75/100 000 (47 cases) and 1.02/100 000 (65 cases), respectively. The incidence showed a decline during these years (Z = -5.78, P < 0.01). The results of Poisson regression model indicated that the monthly average temperature (18.00°C, r = 0.26, P < 0.01, 1-month lag period; IRR = 1.02, 95%CI: 1.00 - 1.03, P < 0.01), relative humidity (75.50%, r = 0.62, P < 0.01, 3-month lag period; IRR = 1.03, 95%CI: 1.02 - 1.04, P < 0.01), rainfall (112.40 mm, r = 0.25, P < 0.01, 6-month lag period; IRR = 1.01, 95CI: 1.01 - 1.02, P = 0.02), and MEI (r = 0.31, P < 0.01, 3-month lag period; IRR = 0.77, 95CI: 0.67 - 0.88, P < 0.01) were closely associated with monthly HFRS cases (18.10 cases).</p><p><b>CONCLUSION</b>Climate factors significantly influence the incidence of HFRS. If the influence of variable-autocorrelation, seasonality, and long-term trend were controlled, the accuracy of forecasting by the time-series Poisson regression model in Changsha would be comparatively high, and we could forecast the incidence of HFRS in advance.</p>


Subject(s)
Humans , China , Epidemiology , Climate Change , Forecasting , Hemorrhagic Fever with Renal Syndrome , Epidemiology , Humidity , Incidence , Models, Theoretical , Seasons , Temperature
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