In our previous studies, DAZAP2 gene expression was down-regulated in untreated patients of multiple myeloma (MM). For better studying the structure and function of DAZAP2, a full-length cDNA was isolated from mononuclear cells of a normal human bone marrow, sequenced and deposited to Genbank (AY430097). This sequence has an identical ORF (open reading frame) as the NM_014764 from human testis and the D31767 from human cell line KG-1. Phylogenetic analysis and structure prediction reveal that DAZAP2 homologues are highly conserved throughout evolution and share a polyproline region and several potential SH2/SH3 binding sites. DAZAP2 occurs as a single-copy gene with a four-exon organization. We further noticed that the functional DAZAP2 gene is located on Chromosome 12 and its pseudogene gene is on Chromosome 2 with electronic location of human chromosome in Genbank, though no genetic abnormalities of MM have been reported on Chromosome 12. The ORF of human DAZAP2 encodes a 17-kDa protein, which is highly similar to mouse Prtb. The DAZAP2 protein is mainly localized in cytoplasm with a discrete pattern of punctuated distribution. DAZAP2 may associate with carcinogenesis of MM and participate in yet-to-be identified signaling pathways to regulate proliferation and differentiation of plasma cells.
Amino Acid Sequence ; Base Sequence ; Chromosomes, Human, Pair 12 ; genetics ; Chromosomes, Human, Pair 2 ; genetics ; Cytoplasm ; metabolism ; DNA Primers ; DNA, Complementary ; genetics ; Down-Regulation ; Gene Components ; Humans ; Likelihood Functions ; Models, Genetic ; Molecular Sequence Data ; Multiple Myeloma ; genetics ; metabolism ; Phylogeny ; Pseudogenes ; genetics ; RNA-Binding Proteins ; genetics ; metabolism ; Sequence Alignment ; Sequence Analysis, DNA

Objective To investigate the predictive value of preprocedural cystatin C level for contrast-in-duced acute kidney injury (CI-AKI) and poor long-term outcome after cardiac catheterization. Methods One thou-sand one hundred and fifty-four patients underwent cardiac catheterization were enrolled in Guangdong general hos-pital. The level of serum cystatin C was determined at 24 hours pre-operation. A 2-year follow up was performed for each patient. Preprocedural cystatin C level was compared between patients with or without CI-AKI. The cystatin C quartiles were compared between patients with incidence of CI-AKI and patients with adverse in-hospital outcomes. Analyses of the receiver operating characteristic curves (ROC) were performed to evaluate the predictive value and cutoff level of cystatin C level for CI-AKI. The log-rank test and Cox regression analyses were also performed to in-vestigate the correlation between cystatin C level and poor long-term outcomes. Results CI-AKI occurred in 42 patients (3.6%). The cystatin C level was significantly higher in the CI-AKI group than that in the non-CI-AKI gu-oup (1.76 ± 1.05 vs 1.20 ± 0.50 mg/L, P=0.001). Patients with higher cystatin C level also had higher risk of CI-AKI and adverse in-hospital outcomes. ROC and Youden index showed that 1.3 mg/L cystatin C of was a fair dis-criminator for CI-AKI, but not significantly different from the Mehran CI-AKI score (AUC, 0.75 vs 0.76, P =0.874). After adjusting for other known CI-AKI risk factors, cystatin C level over 1.3 mg/L remained significantly associated with CI-AKI. During the long-term follow-up , the patients with cystatin C level over 1.3 mg/L were at a higher risk of all-cause mortality and MACEs (P < 0.001). Concusions A preprocedural cystatin C level over 1.3 mg/L was a good predictor of CI-AKI and poor long-term outcomes after cardiac catheterization.

Objective To evaluate the prognostic values of common definition compared to traditional definition of contrast-induced nephropathy (CIN) in patients with normal serum creatinine (SCr). Methods Patients undergoing percutaneous coronary angiology or intervention with normal baseline SCr were enrolled prospectively. Those who were diagnosed as CIN according to common definition were divided into two groups based on the peak increase from baseline in the SCr concentration within 48 ~ 72 hours after the procedure: ≥ 44.2 μmol/L (CIN44.2 group, in common with traditional definition), ≥25% of baseline to < 44.2 μmol/L (CIN25%-44.2 group, interval between the two definitions). Hospital stay and long-term outcomes were compared among CIN44.2, CIN25%-44.2, and non-CIN groups. Results Of all 3,044 patients enrolled, 302 (9.9%) patients developed CIN according to common definition including CIN44.2 occurred in 56 (1.8%) patients and CIN25%-44.2 in 246 (8.1%) patients. Patients in CIN44.2 group indicated significant longer hospital stay and long-term outcomes compared with non-CIN group (P < 0.05). However, patients in CIN25%-44.2 group had similar in-hospital mortality and long-term cumulative risk of major clinical adverse events (MACE) and death with non-CIN group (all, P = 1.00). Multivariate Cox proportional hazard analyses also demonstrated that CIN25%-44.2 did not associate with long-term MACE (HR 1.16, P = 0.645) and death (HR 0.98, P = 0.964) after adjusting for potential confounding factors. Conclusions For patients with normal baseline SCr, common definition based on traditional definition of CIN is unreasonable and overestimates the incidence of CIN, whose extension of traditional denifition proves no significant clinical value.

Objective To investigate the effect of long?term exposure to environmental cadmium on eight mineral element's metabolic balance of human body. Methods To choose a high cadmium area polluted by smelting and mining north of Guangdong province and a cadmium?free area with a similar economic level, and living and eating habit of residents as a contrast from April 2011 to August 2012. Stratified random sampling and clustered sampling method were adopted to choose the non?occupationally cadmium?exposed respondents who have lived in local area for more than 15 years, older than 40 years, having local rice and vegetable as the main dietary source, with simple and relatively stable diet, and without diabetes, kidney disease, thyroid disease, liver disease or other history of chronic disease. This study included 298 respondents, of whom 155 were in cadmium exposure group and 143 in control group. Questionnaires was used to acquire their health status and their morning urine samples were collected. Electrolytically coupled plasma mass spectrometry (ICP?MS) was used to test the concentrations of sodium (Na), magnesium (Mg), phosphorus (P), potassium (K), calcium (Ca), copper (Cu), zinc (Zn) and iodine (I). The Mann?Whitney U test method was used to compare the differences of concentrations of urinary cadmium, Na, Mg, P, K, Ca, Cu, Zn, I, and the ratio of Na to K (Na/K), Ca to P (Ca/P) between exposed group and control group.χ2 test was used to compare the abnormal rate of urinary cadmium between exposed group and control group. Pearson correlation and multiple regression method were used to investigate the relationship between urinary cadmium levels, gender, age, smoking, passive smoking, and minerals. Results The urinary cadmium level P50 (P25-P75) in exposed group was 5.45 (2.62-10.68)μg/g·cr, which was higher than that of the control group, which was 1.69 (1.22-2.36)μg/g · cr (Z=-10.49, P<0.001). The abnormal rate of urinary cadmium was 51.6%(80/155), which was higher than that of the control group (2.8%(4/143)) (χ2=87.56,P<0.001). The urinary Ca, Cu, Zn, and I level P50 (P25-P75) of exposed group were 173.80 (114.40-251.70), 20.55 (14.95-28.44), 520.23 (390.25-647.15), and 246.94 (203.65-342.97)μg/g · cr, which were higher than those in control group (142.42 (96.87-179.11), 15.44 (12.26-20.98), 430.09 (309.85-568.78) and 213.85 (156.70-281.63) μg/g · cr, respectively) (Z values were-4.33,-5.04,-3.47 and-4.24, all P values<0.001). The urinary P, K level P50 (P25-P75) of exposed group were 582.50 (463.20-742.8), 890.10 (666.00-1 305.40) μg/g · cr, which were lower than control group (694.50 (546.20-851.17), 1 098.58 (904.53-1 479.18) μg/g · cr) (Z values were-3.36,-4.02, all P values <0.001). on Based the results of Pearson correlation analysis, urinary cadmium was positively correlated with urinary Ca, Cu, Zn, and I, and the correlation coefficients were 0.31, 0.61, 0.38, and 0.25, respectively(all P values<0.05). Based on the results of multiple regression analysis, urinary cadmium levels contributed most to the metabolic balance of urinary Ca, Cu, Zn and I. The standardized regression coefficients were 0.31, 0.59, 0.39, and 0.24, respectively (all P values<0.001). Conclusion Long?term environmental exposure to cadmium affected the metabolic balance of Ca, Cu, Zn and I in human body.

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 the effect of long?term exposure to environmental cadmium on eight mineral element's metabolic balance of human body. Methods To choose a high cadmium area polluted by smelting and mining north of Guangdong province and a cadmium?free area with a similar economic level, and living and eating habit of residents as a contrast from April 2011 to August 2012. Stratified random sampling and clustered sampling method were adopted to choose the non?occupationally cadmium?exposed respondents who have lived in local area for more than 15 years, older than 40 years, having local rice and vegetable as the main dietary source, with simple and relatively stable diet, and without diabetes, kidney disease, thyroid disease, liver disease or other history of chronic disease. This study included 298 respondents, of whom 155 were in cadmium exposure group and 143 in control group. Questionnaires was used to acquire their health status and their morning urine samples were collected. Electrolytically coupled plasma mass spectrometry (ICP?MS) was used to test the concentrations of sodium (Na), magnesium (Mg), phosphorus (P), potassium (K), calcium (Ca), copper (Cu), zinc (Zn) and iodine (I). The Mann?Whitney U test method was used to compare the differences of concentrations of urinary cadmium, Na, Mg, P, K, Ca, Cu, Zn, I, and the ratio of Na to K (Na/K), Ca to P (Ca/P) between exposed group and control group.χ2 test was used to compare the abnormal rate of urinary cadmium between exposed group and control group. Pearson correlation and multiple regression method were used to investigate the relationship between urinary cadmium levels, gender, age, smoking, passive smoking, and minerals. Results The urinary cadmium level P50 (P25-P75) in exposed group was 5.45 (2.62-10.68)μg/g·cr, which was higher than that of the control group, which was 1.69 (1.22-2.36)μg/g · cr (Z=-10.49, P<0.001). The abnormal rate of urinary cadmium was 51.6%(80/155), which was higher than that of the control group (2.8%(4/143)) (χ2=87.56,P<0.001). The urinary Ca, Cu, Zn, and I level P50 (P25-P75) of exposed group were 173.80 (114.40-251.70), 20.55 (14.95-28.44), 520.23 (390.25-647.15), and 246.94 (203.65-342.97)μg/g · cr, which were higher than those in control group (142.42 (96.87-179.11), 15.44 (12.26-20.98), 430.09 (309.85-568.78) and 213.85 (156.70-281.63) μg/g · cr, respectively) (Z values were-4.33,-5.04,-3.47 and-4.24, all P values<0.001). The urinary P, K level P50 (P25-P75) of exposed group were 582.50 (463.20-742.8), 890.10 (666.00-1 305.40) μg/g · cr, which were lower than control group (694.50 (546.20-851.17), 1 098.58 (904.53-1 479.18) μg/g · cr) (Z values were-3.36,-4.02, all P values <0.001). on Based the results of Pearson correlation analysis, urinary cadmium was positively correlated with urinary Ca, Cu, Zn, and I, and the correlation coefficients were 0.31, 0.61, 0.38, and 0.25, respectively(all P values<0.05). Based on the results of multiple regression analysis, urinary cadmium levels contributed most to the metabolic balance of urinary Ca, Cu, Zn and I. The standardized regression coefficients were 0.31, 0.59, 0.39, and 0.24, respectively (all P values<0.001). Conclusion Long?term environmental exposure to cadmium affected the metabolic balance of Ca, Cu, Zn and I in human body.

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.

To determine the value of radiomics in identifying lymph node (LN) metastasis in patients with rectal nonmucinous adenocarcinoma.
 Methods: Imaging data of 91 patients were retrospectively analyzed (61 in the training set and 30 in the test set). A total of 1 301 radiomics features were extracted from high-resolution T2-weighted images of the whole primary tumor. The least absolute shrinkage and selection operator (LASSO) logistic regression was performed to choose the optimal features and construct a radiomics classifier in the training set. Its discrimination performance was compared with that of morphological criteria by receiver operating characteristic (ROC) curve analysis, which was validated in the test set.
 Results: The radiomics classifier combined with five key features was significantly associated with LN metastasis, which distinguished LN metastasis with an area under curve (AUC) at 0.874 (95% CI 0.787 to 0.960) in the training set, and the performance was similar in the test set (AUC 0.878, 95% CI 0.727 to 1.000). The AUCs according to the morphological criteria in the training set and test set were 0.619 (95% CI 0.487 to 0.752) and 0.556 (95% CI 0.355 to 0.756), respectively. Discrimination of the radiomics classifier was superior to that of morphological criteria in both the two datasets (both P <0.05).
 Conclusion: The radiomics classifier provides individualized risk estimation for LN metastasis in rectal nonmucinous adenocarcinoma patients and it has the advantage over the morphological criteria.
Adenocarcinoma ; Humans ; Lymph Nodes ; Lymphatic Metastasis ; Rectal Neoplasms ; Retrospective Studies

Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.