Distinguishing Petroleum (Crude Oil and Fuel) From Smoke Exposure within Populations Based on the Relative Blood Levels of Benzene, Toluene, Ethylbenzene, and Xylenes (BTEX), Styrene and 2,5-Dimethylfuran by Pattern Recognition Using Artificial Neural Networks.

Studies of exposure to petroleum (crude oil/fuel) often involve monitoring benzene, toluene, ethylbenzene, xylenes (BTEX), and styrene (BTEXS) because of their toxicity and gas-phase prevalence, where exposure is typically by inhalation. However, BTEXS levels in the general U.S. population are primarily from exposure to tobacco smoke, where smokers have blood levels on average up to eight times higher than nonsmokers. This work describes a method using partition theory and artificial neural network (ANN) pattern recognition to classify exposure source based on relative BTEXS and 2,5-dimethylfuran blood levels. A method using surrogate signatures to train the ANN was validated by comparing blood levels among cigarette smokers from the National Health and Nutrition Examination Survey (NHANES) with BTEXS and 2,5-dimethylfuran signatures derived from the smoke of machine-smoked cigarettes. Classification agreement for an ANN model trained with relative VOC levels was up to 99.8% for nonsmokers and 100.0% for smokers. As such, because there is limited blood level data on individuals exposed to crude oil/fuel, only surrogate signatures derived from crude oil and fuel were used for training the ANN. For the 2007-2008 NHANES data, the ANN model assigned 7 out of 1998 specimens (0.35%) and for the 2013-2014 NHANES data 12 out of 2906 specimens (0.41%) to the crude oil/fuel signature category.

Performance of succinylacetone assays and their associated proficiency testing outcomes.

BACKGROUND: Succinylacetone (SUAC) is the primary metabolic marker for hepatorenal tyrosinemia. MATERIALS AND METHODS: We used results reported for dried-blood-spot proficiency testing (PT) specimens and hepatorenal tyrosinemia patients' newborn screening (NBS) samples to demonstrate analytic biases in SUAC recoveries and differences in presumptive clinical classifications. RESULTS: SUAC recoveries from non-kit and NeoBase™ kit tandem mass spectrometry methods were markedly different. Kit users that set high cutoff values submitted discordant clinical assessments of "within normal limits" for PT specimens enriched with 10-15 µmol SUAC/L in blood. SUAC levels in tyrosinemia patients' NBS samples analyzed by NeoBase™ kit were lower than those in samples analyzed by non-kit methods. CONCLUSIONS: From 2009 to 2011, analytic biases in SUAC recoveries were consistent. Discordant clinical assessments of PT specimens were associated with high cutoff values for NeoBase™ kit results. Method-related differences in SUAC concentrations of tyrosinemia patients' samples were consistent with those of PT specimens.

The stability of markers in dried-blood spots for recommended newborn screening disorders in the United States.

OBJECTIVE: We aimed to measure separately the contributions of heat and humidity to changes in levels of 34 markers of inborn disorders in dried-blood-spot (DBS) samples. DESIGN AND METHODS: We stored paired sets of DBSs at 37°C for predetermined intervals in low-humidity and high-humidity environments. Marker levels of all samples in each complete sample set were measured in a single analytic run. RESULTS: During the 30 ± 5 day studies, galactose-1-phosphate uridyltransferase and biotinidase lost almost 65% of initial activities in low-humidity storage; most of the degradation in 27 other markers was attributable to adverse effects of high-humidity storage; seven markers in DBSs stored at high humidity lost more than 90% of initial levels by the end of the study and 4 of the 7 lost more than 50% of initial levels within the first week of storage. CONCLUSIONS: Minimizing both humidity and temperature in DBS transportation and storage environments is essential to maintaining sample integrity.