Objective To search for the specific biomarkers associated with local lymphatic metastasis of colorectal cancer in serum.Methods The serum protein profile of colorectal cancer patients was determined by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS),and the peak values of proteins were identified with the matched software,and then clustered to construct the classification tree model.Seventy colorectal cancer patients with local lymphatic metastasis and 75 patients in matched age and gender without local lymphatic metastasis were assigned as a training set to construct the classification tree model,and 35 colorectal cancer patients with local lymphatic metastasis and 30 patients in matched age and gender without local lymphatic metastasis were assigned as test set to make the independent sample double-blind test.Results Forty-six distinct proteins were identified from the two groups,and the classification tree model formed by 5 proteins (M/Z:3104,3781,5867,7970 and 9290) could be used to identify the two groups with a sensitivity of 94.3% (66/70) and a specificity of 100.0% (75/75).The double-blind test challenged the model with a sensitivity of 91.4% (32/35),a specificity of 96.7% (29/30),and a positive predictive value of 97.0% (32/33),respectively.ConclusionThe constructed classification tree model may distinguish colorectal cancer patients with or without local lymphatic metastasis correctly,and show a great potential for preoperatively screening the colorectal cancer patients with or without local lymphatic metastasis.

OBJECTIVETo evaluate associations between carbon constituents of fine particulate matter (PM2.5) and atherogenic index of plasma (AIP).

METHODSWe collected subjects from two communities by a system sampling, and 112 people aged over 60 years old without cardiovascular disease were recruited. The levels of cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) of objects, and personal exposure to PM2.5 were measured on December, 2011. Total carbon (TC), organic carbon (OC) and elemental carbon (EC) of PM2.5 were detected and AIP was calculated according to its definition.

RESULTSThe value of AIP among the 112 subjects was 0.05 ± 0.26. Personal exposure concentration of PM2.5 and its carbon components (TC,OC and EC) were (164.75 ± 110.67), (53.86 ± 29.65), (44.93 ± 26.37) and (9.49 ± 5.75) µg/m(3), respectively. The Pearson analysis showed the linear relationship between TC,OC,EC and AIP, all significant positive correlations. The correlation coefficients were TC (r = 0.307, P < 0.05),OC (r = 0.287, P < 0.05) and EC (r = 0.252, P < 0.05), respectively. The multiple logistic regression analysis showed that when the AIP risk categories were selected as dependent variable and low risk group as reference group, the regression coefficient of TC,OC and EC was separately 1.03 (95%CI:1.01-1.05), 1.03 (95%CI:1.01-1.05), 1.12 (95%CI:1.02-1.22) in the high risk group; while there was no statistical significance of the regression coefficient and OR in the middle risk group.

CONCLUSIONThere was stable associations between the carbon constituents (TC,OC and EC) of fine Particulate Matter (PM2.5) and AIP. The findings suggested that carbon components of PM2.5 should be considered as risk factors of atherogenic.

Aged ; Air Pollutants ; analysis ; Air Pollution ; adverse effects ; Atherosclerosis ; diagnosis ; epidemiology ; Carbon ; analysis ; Cholesterol ; blood ; Environmental Exposure ; adverse effects ; Female ; Humans ; Male ; Middle Aged ; Particle Size ; Particulate Matter ; analysis ; Risk Assessment ; Triglycerides ; blood