Expansion of CD14(+)CD16(+) monocytes is related to acute leukemia.

OBJECTIVE: Aim to investigate the proportion of CD14(+)CD16(+) monocytes and understand the pathogenesis of this monocyte subset in acute leukemia. METHODS: Flow cytometry was utilized to study the phenotype expression of CD14(+)CD16(+) monocytes and CD3(+) T lymphocytes in peripheral blood derived from patients with acute leukemia. All the data were analyzed by SPSS 13.0 software. RESULTS: The proportion of CD14(+)CD16(+) monocytes including both intermediate and non-classical monocytes, increased significantly in patients with acute leukemia and changed negatively or positively according to the disease process. Meanwhile, the proportion of CD14(+)CD16(+) monocytes was inversely correlated with absolute number of CD4(+) T lymphocytes, ratio of CD4(+)/CD8(+) T cells, and positively correlated with the proportion of neutrophil granulocytes. CONCLUSIONS: The proportion of CD14(+)CD16(+) monocytes (especially the intermediate subpopulation) is related to the progression of acute leukemia, and the expansion of this monocyte subset could indicate the severity of the disease.

[Analysis of first flush effect of typical underlying surface runoff in Beijing urban city].

Rapid increase of the urban impervious underlying surfaces causes a great increase of urban runoff and the accumulation of pollutants on the roof and road surfaces brings many pollutants into the drainage system with the runoff, and it thus becomes a great threat to the urban water environment. To know the runoff pollution process and to build scientific basis for pollutant control, runoff processes from the roof and road surfaces were monitored and analyzed from 2004 to 2006, and the runoff EMC (Event Mean Concentration) was calculated. It was found that two types of runoff were seriously polluted by COD and TN. The COD and TN of roof runoff exceeded the fifth level of the surface water environmental quality standard (GB 3838-2002) by 3.64 and 4.80 times, respectively, and the COD and TN of road runoff exceeded by 3.73 and 1.07 times, respectively. M (V) curve was used to determine the relation between runoff volume and runoff pollution load. Various degrees of the first flush phenomenon were found for TSS, COD, TN and TP in roof runoff. But this phenomenon occurred only for TSS and TP of the road runoff, and on the whole it was not obvious. Properties of the underlying surfaces, rainfall intensity, and pollutant accumulation are all important factors affecting the roof and road runoff pollutant emission characteristics.

[Diurnal variation and evaluation of water quality in different seasons of Panxi River in Chongqing].

Based on the investigation of water quality of Panxi River in different seasons, 2010, we assessed the diurnal variation of water quality in different seasons and the characteristics of water quality changes within a day by using non-parametric test, analysis of variance and grey relationship analysis. The results showed that the differences were not significant for Zn and Cu (P > 0.05), but significant differences existed among the pH, EC, DO, COD, TP, TSS, BOD5, NO(3-)-N, TN, NH(4+)-N, Pb and Cd contents. It showed that the minimum DO concentration occurred in winter, and the maximum of BOD5, COD and TOC concentrations occurred in winter, and the maximum NO(3-)-N concentration occurred in summer and the minimum TN, NH(4+)-N and TP concentrations occurred in summer. The diurnal variation of dissolved heavy metals showed relatively larger fluctuations in different seasons. The diurnal variation of different water quality parameters presented distinct patterns: diurnal variation of organic pollutants and nutrients showed the peak at 12:00 to 16:00 and dissolved heavy metals peaked at 12:00. The results of grey relationship analysis for surface water indicated that the water quality in spring was in the II class at 06:00 and 08:00 and was inferior to theV class for the rest hours; and the water quality in summer was in the II class; and the water quality in autumn was inferior to the V class at 06:00 and 16:00 and was in the II class for the rest hours; and the water quality in winter was in the II class at 08:00 and was inferior to the V class for the rest hours.

[Diurnal variation and evaluation of water quality of Panxi River in spring].

Based on the investigation of water quality of Panxi River in spring, 2010, we assessed the diurnal variation of water quality in spring and the characteristics of water quality changes within a day by using non-parametric test, analysis of variance and grey relationship analysis. The results showed that the differences were not significant for t, DO, COD, Pb, Cd, Zn and Cu (P > 0.05) in upstream, midstream and downstream, but significant difference existed among the pH, EC, TP, TSS, BOD5, NO3(-) -N, TN and NH4(+) -N contents. The diurnal variation of different water quality parameters presented distinct patterns: TN, TP and EC increased wavelike with time in upstream, fluctuated less in middle and showed the "single-peak single-valley" pattern in downstream, with the peak at 12:00. The diurnal variation of COD showed that "single-peak" pattern and with the peak at 10:00 in upstream and midstream and peak at 12:00 in downstream. The concentrations of Pb, Cd, Zn and Cu were low and peak at 12:00 in midstream; The grey relationship analysis indicated that the water quality in upstream was inferior to the V class of surface water at 18:00 and 20:00 and were in the II class of surface water for the rest hours, and the water quality in midstream was inferior to the V class of surface water at 12:00 and were in the II class of surface water for the rest hours; and the water quality in downstream was inferior to the V class of surface water all time during investigation.

[Research on evaluation of water quality of Beijing urban stormwater runoff].

The natural rainwater and stormwater runoff samples from three underlying surfaces (rooftop, campus road and ring road) were sampled and analyzed from July to October, 2010 in Beijing. Eight rainfall events were collected totally and thirteen water quality parameters were measured in each event. Grey relationship analysis and principal component analysis were applied to assess composite water quality and identify the main pollution sources of stormwater runoff. The results show that the composite water quality of ring road runoff is mostly polluted, and then is rooftop runoff, campus road runoff and rainwater, respectively. The composite water quality of ring road runoff is inferior to V class of surface water, while rooftop runoff, campus road runoff and rainwater are in II class of surface water. The mean concentration of TN and NH4(+)-N in rainwater and runoff is 5.49-11.75 mg x L(-1) and 2.90-5.67 mg x L(-1), respectively, indicating that rainwater and runoff are polluted by nitrogen (N). Two potential pollution sources are identified in ring road runoff: (1) P, SS and organic pollutant are possibly related to debris which is from vehicle tyre and material of ring road; (2) N and dissolved metal have relations with automobile exhaust emissions and bulk deposition.

[Characterization and source apportionment of pollutants in urban roadway runoff in Chongqing].

By investigating surface runoff from urban roadway in Chongqing, we assessed the characteristics of surface runoff pollution and the effect of rainfall intensity and antecedent dry weather period on water quality. Using multivariate statistical analysis of data of runoff quality, potential pollutants discharged from urban roadway runoff were identified. The results show that the roadway runoff has high levels of COD, TP and TN, the EMC were 60.83-208.03 mg x L(-1), 0.47-1.01 mg x L(-1) and 2.07-5.00 mg x L(-1) respectively, being the main pollutants; The peaks of pollutant concentration are ahead of or synchronous with the peak of runoff volume; the peaks of pollutant concentrations are mostly occurred within 10 minutes of rainfall. The heavy metal concentrations fluctuate dentately during runoff proceeding. Two potential pollution sources to urban roadway runoff apportioned by using principal component analysis are: vehicle's traffic loss and atmospheric dry and wet deposition, and municipal wastes.