Ensemble Modeling Coupled with Six Element Concentrations in Human Blood for Cancer Diagnosis

2010 ◽  
Vol 143 (1) ◽  
pp. 143-152 ◽  
Author(s):  
Hui Chen ◽  
Chao Tan ◽  
Tong Wu
Epidemiology ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 112-119 ◽  
Author(s):  
Katie M. O’Brien ◽  
Alexandra J. White ◽  
Dale P. Sandler ◽  
Brian P. Jackson ◽  
Margaret R. Karagas ◽  
...  

Author(s):  
E M Tanvir ◽  
Karen M Whitfield ◽  
Jack C Ng ◽  
P Nicholas Shaw

Abstract Essential and nonessential element concentrations in human blood provide important information on the nutritional status of individuals and can assist in the screening or diagnosis of certain disorders and their association with other causative factors. A simple and sensitive method, suitable for use with small sample volumes, for quantification of multiple trace element concentrations in whole blood and plasma has been developed using inductively coupled plasma-mass spectrometry. Method validation was performed using standard reference materials of whole blood and serum using varying sample treatments with nitric acid, water and hydrogen peroxide. The method was applied to quantify the trace element concentrations in whole blood and plasma samples (0.1 mL) from 50 adult blood donors in Queensland. The whole blood sample (5 mL) was collected in Vacutainer tubes with K2EDTA as anticoagulant. The developed method was able to quantify, in blood and plasma samples over a wide range of concentrations, several essential elements: cobalt, copper, zinc, iron, manganese and selenium; the nutritionally probably essential elements vanadium and strontium; and nonessential elements including lead, cadmium, arsenic, caesium, barium, thallium and uranium. Significant differences (P < 0.0001) were observed between whole blood and plasma concentrations for 13 elements; 5 of the measured elements, cobalt (0.49 vs. 0.36 μg/L), copper (1.0 vs. 0.75 mg/L), strontium (28 vs. 16 μg/L), barium (1.5 vs. 0.64 μg/L) and thallium (0.06 vs. 0.03 μg/L), had higher mean concentrations in plasma than in blood. Whole blood concentrations of nine trace elements were significantly correlated (P < 0.0001) with plasma concentrations. The distribution of the trace elements between human blood and plasma varied considerably for the different elements. These results indicate that, using a small sample volume, this assay is suitable for the evaluation of nutritional status as well as in monitoring human toxic elemental exposures.


2002 ◽  
Vol 134 (1-3) ◽  
pp. 177-184 ◽  
Author(s):  
Ebba Bárány ◽  
Ingvar A. Bergdahl ◽  
Lars-Eric Bratteby ◽  
Thomas Lundh ◽  
Gösta Samuelson ◽  
...  

2019 ◽  
Vol 65 (6) ◽  
pp. 798-808 ◽  
Author(s):  
Yuchen Li ◽  
Jingjing Zhao ◽  
Shulin Yu ◽  
Zhen Wang ◽  
Xigan He ◽  
...  

Abstract BACKGROUND Extracellular vesicles (EVs) contain a rich cargo of different RNA species with specialized functions and clinical applications. However, the landscape and characteristics of extracellular vesicle long RNA (exLR) in human blood remain largely unknown. METHODS We presented an optimized strategy for exLR sequencing (exLR-seq) of human plasma. The sample cohort included 159 healthy individuals, 150 patients with cancer (5 cancer types), and 43 patients with other diseases. Bioinformatics approaches were used to analyze the distribution and features of exLRs. Support vector machine algorithm was performed to construct the diagnosis classifier, and diagnostic efficiency was evaluated by ROC analysis. RESULTS More than 10000 exLRs, including mRNA, circRNA, and lncRNA, were reliably detected in each exLR-seq sample from 1–2 mL of plasma. We observed that blood EVs contain a substantial fraction of intact mRNAs and a large number of assembling spliced junctions; circRNA was also enriched in blood EVs. Interestingly, blood exLRs reflected their tissue origins and the relative fractions of different immune cell types. Additionally, the exLR profile could distinguish patients with cancer from healthy individuals. We further showed that 8 exLRs can serve as biomarkers for hepatocellular carcinoma (HCC) diagnosis with high diagnostic efficiency in training [area under the curve (AUC) = 0.9527; 95% CI, 0.9170–0.9883], validation cohort (AUC = 0.9825; 95% CI, 0.9606–1), and testing cohort (AUC = 0.9627; 95% CI, 0.9263–0.9991). CONCLUSIONS In summary, this study revealed abundant exLRs in human plasma and identified diverse specific markers potentially useful for cancer diagnosis.


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