Objective To investigate dynamic change of cadmium body burden and renal dysfunction among residents living in cadmium?polluted areas. Methods From April to July of 2011, the cadmium?polluted areas of northern Guangdong province in China was chosen as the study site. Based on the levels of cadmium pollution in soil and rice, the survey areas were divided into low exposed group (average concentration of cadmium was 0.15-0.40 mg/kg, 0.5-1.0 mg/kg in rice and soil, respectively) and high exposed group (average concentration of cadmium was >0.40 mg/kg, >1.0 mg/kg in rice and soil, respectively). Stratified random sampling and cluster sampling method of epidemiological investigations were carried out among 414 local residents who lived in cadmium exposure areas for more than 15 years, aged above 40, and without occupational cadmium exposure, including 168 and 246 residents in low and high exposed group, respectively. From March to June of 2014, 305 respondents of those who participated in 2011 were successfully traced, including 116 and 189 respondents in low and high exposed group, respectively. We used health questionnaires to acquire their health status. Home?harvested rice and vegetable samples were collected using quartering method for detection of cadmium level, including 190 rice samples, 161 vegetable samples in 2011 and 190 rice samples, 153 vegetable samples in 2014. Urine specimens of residents were collected for the detection of urinary cadmium and creatinine as well as renal dysfunction biomarkers, namely, N?acetyl?beta?D?glucosamidase (NAG) andβ2?microglobulin (β2?MG), respectively. In 2011 and 2014, Chi?square test was used to investigate the differences of abnormality of cadmium concentration in rice, vegetables and urinary cadmium,β2?MG,and NAG that were expressed as odds ratio (OR) and 95%confidence intervals (95%CI). Results In 2011 and 2014, cadmium concentration P50 (P25-P75) in rice was 0.43 (0.17-1.10) mg/kg,and 0.42 (0.20-1.14) mg/kg, respectively (Z=-0.77, P=0.440). In 2011 and 2014, cadmium concentrations P50 (P25-P75) in vegetables were 0.13 (0.07-0.34) mg/kg,and 0.25 (0.12-0.59) mg/kg, respectively, with abnormal rates of 38.5%(62/161) and 60.8%(93/153), respectively. In 2014, both average concentration and abnormal rate of cadmium in vegetables were higher than those in 2011 (Z=-4.69,P<0.001 andχ2=15.58, P<0.001). Concentrations of urinary cadmium P50 (P25-P75) in high exposed group were 7.90 (3.96-14.91)μg/g creatinine, 8.64 (4.56-17.60)μg/g creatinine in 2011 and 2014, respectively. Contrary to that in 2011, urinary cadmium of high exposed group was significantly increased in 2014 (Z=-2.80 ,P=0.005). In 2011 and 2014, concentrations of β2?MG, NAG P50 (P25-P75) were 0.15 (0.07-0.29)μg/g creatinine, 0.15 (0.07-0.45)μg/g creatinine,and 7.12 (5.05-10.65) U/g creatinine, 13.55 (9.1-19.84) U/g creatinine, respectively, with abnormal rates of 7.5% (23/305), 15.1% (46/305) ,8.2%(25/305) , and 33.8% (103/305), respectively. Compared with baseline in 2011, average concentrations ofβ2?MG, NAG significantly increased in 2014 (Z=-2.263,P=0.024 and Z=-12.52,P<0.001), and abnormal rates ofβ2?MG, NAG were also higher in 2014 (χ2=15.61,P<0.001 andχ2=64.72,P<0.001), with odds ratio (OR) of 2.00 (95%CI:1.23-3.24) and 4.12 (95%CI:2.87-5.92). Conclusion Environmental cadmium pollution of crops such as rice and vegetables in survey areas continued to remain high. Body burden of cadmium might kept at sustainably high levels and renal dysfunction was worsened after continuous, long?term cadmium exposure. Our results suggested that NAG might be more sensitive than β2?MG to serve as an indicator for an individual's future tubular function.

Objective To investigate dynamic change of cadmium body burden and renal dysfunction among residents living in cadmium?polluted areas. Methods From April to July of 2011, the cadmium?polluted areas of northern Guangdong province in China was chosen as the study site. Based on the levels of cadmium pollution in soil and rice, the survey areas were divided into low exposed group (average concentration of cadmium was 0.15-0.40 mg/kg, 0.5-1.0 mg/kg in rice and soil, respectively) and high exposed group (average concentration of cadmium was >0.40 mg/kg, >1.0 mg/kg in rice and soil, respectively). Stratified random sampling and cluster sampling method of epidemiological investigations were carried out among 414 local residents who lived in cadmium exposure areas for more than 15 years, aged above 40, and without occupational cadmium exposure, including 168 and 246 residents in low and high exposed group, respectively. From March to June of 2014, 305 respondents of those who participated in 2011 were successfully traced, including 116 and 189 respondents in low and high exposed group, respectively. We used health questionnaires to acquire their health status. Home?harvested rice and vegetable samples were collected using quartering method for detection of cadmium level, including 190 rice samples, 161 vegetable samples in 2011 and 190 rice samples, 153 vegetable samples in 2014. Urine specimens of residents were collected for the detection of urinary cadmium and creatinine as well as renal dysfunction biomarkers, namely, N?acetyl?beta?D?glucosamidase (NAG) andβ2?microglobulin (β2?MG), respectively. In 2011 and 2014, Chi?square test was used to investigate the differences of abnormality of cadmium concentration in rice, vegetables and urinary cadmium,β2?MG,and NAG that were expressed as odds ratio (OR) and 95%confidence intervals (95%CI). Results In 2011 and 2014, cadmium concentration P50 (P25-P75) in rice was 0.43 (0.17-1.10) mg/kg,and 0.42 (0.20-1.14) mg/kg, respectively (Z=-0.77, P=0.440). In 2011 and 2014, cadmium concentrations P50 (P25-P75) in vegetables were 0.13 (0.07-0.34) mg/kg,and 0.25 (0.12-0.59) mg/kg, respectively, with abnormal rates of 38.5%(62/161) and 60.8%(93/153), respectively. In 2014, both average concentration and abnormal rate of cadmium in vegetables were higher than those in 2011 (Z=-4.69,P<0.001 andχ2=15.58, P<0.001). Concentrations of urinary cadmium P50 (P25-P75) in high exposed group were 7.90 (3.96-14.91)μg/g creatinine, 8.64 (4.56-17.60)μg/g creatinine in 2011 and 2014, respectively. Contrary to that in 2011, urinary cadmium of high exposed group was significantly increased in 2014 (Z=-2.80 ,P=0.005). In 2011 and 2014, concentrations of β2?MG, NAG P50 (P25-P75) were 0.15 (0.07-0.29)μg/g creatinine, 0.15 (0.07-0.45)μg/g creatinine,and 7.12 (5.05-10.65) U/g creatinine, 13.55 (9.1-19.84) U/g creatinine, respectively, with abnormal rates of 7.5% (23/305), 15.1% (46/305) ,8.2%(25/305) , and 33.8% (103/305), respectively. Compared with baseline in 2011, average concentrations ofβ2?MG, NAG significantly increased in 2014 (Z=-2.263,P=0.024 and Z=-12.52,P<0.001), and abnormal rates ofβ2?MG, NAG were also higher in 2014 (χ2=15.61,P<0.001 andχ2=64.72,P<0.001), with odds ratio (OR) of 2.00 (95%CI:1.23-3.24) and 4.12 (95%CI:2.87-5.92). Conclusion Environmental cadmium pollution of crops such as rice and vegetables in survey areas continued to remain high. Body burden of cadmium might kept at sustainably high levels and renal dysfunction was worsened after continuous, long?term cadmium exposure. Our results suggested that NAG might be more sensitive than β2?MG to serve as an indicator for an individual's future tubular function.

AIM: To evaluate the bioequivalence of the test and reference formulations of mycophenolate mofetil capsule in Chinese healthy male subjects under fasting and fed conditions. METHODS: This was a 2-treatment, 2-sequence, 4-period, fully replicated crossover study that included 80 Chinese healthy male subjects (40 subjects in the fasting group and 40 subjects in the fed group, respectively). Subjects were assigned to receive a single oral administration of the test or reference formulation at a dose of 0.25 g in each period. The plasma concentration of mycophenolate mofetil (MMF) and metabolite mycophenolic acid (MPA) were analyhed by LC-MS/MS. The major pharmacokinetic parameters of MMF and MPA were calculated using non-compartmental analysis by WinNonlin 8.0. The statistical analysis was performed by SAS 9.4. Average bioequivalence (ABE) analysis was applied where it has been demonstrated that the within-subject standard deviation of the reference formulation (S