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To our knowledge, no study to date has examined alcohol and cigarette demand, via hypothetical purchase tasks, in a clinical sample of heavy drinking smokers. This study demonstrates that behavioral economic indices may be sensitive to cross-substance relationships and specifically that such relationships are asymmetrically stronger for smoking variables affecting alcohol demand, not the other way around.

Aflatoxins (AFs) are carcinogenic mycotoxins. A simple, quick, and accurate method for the micro-analysis of AFs in foodstuffs, especially spices, is needed.

A sophisticated pretreatment method that combines solid-phase dispersive extraction (SPDE) and solid-phase fluorescence derivatization using immunoaffinity (IA) gel as the solid phase was developed to analyze AFs in spices simply, quickly, and sensitively by liquid chromatography with fluorescence detection.

White and black pepper samples were extracted with a mixed solution of methanol/water (41) and then diluted with 7% aqueous solution of Triton-X. The solution was subjected to cleanup by SPDE using IA gel. find more Trifluoroacetic acid was added to the IA gel for on-site solid-phase fluorescence derivatization.

Chromatograms containing well-separated peaks and few interference peaks from contaminants were obtained. The method detection limit of AFs in white and black pepper was 0.15-0.29 ng/g. Repeatability and intermediate precision were <10% and <15%, respectively, and accuracy was 61.7-87.8%. In addition, inter-laboratory precision was <29% and mean recovery was 61.5-76.7%. A favorable z-score of |Z| ≦ 1 was obtained in seven laboratories, although one laboratory gave 2 < |Z| < 3.

The validity, reliability, practicality, and robustness of the developed method were verified.

By using SPDE and solid-phase fluorescence derivatization in combination for AF analysis, fluorescence derivatization during cleanup was realized, leading to simplification of the pretreatment operation.

By using SPDE and solid-phase fluorescence derivatization in combination for AF analysis, fluorescence derivatization during cleanup was realized, leading to simplification of the pretreatment operation.

Turmeric is widely used as an ingredient of food and medicinal products. There exists no validated method for multi-residue analysis of pesticides in turmeric.

This study was undertaken to develop a simple and robust method for the quantitative determination of multi-class pesticides in turmeric powder and rhizome by GC-MS/MS.

Initially, the samples were soaked in water for 30 min and homogenized to a fine paste. A portion of this paste (2 g) was extracted with acetonitrile (2 mL) and partitioned with hexane (2 mL) after adding 5 mL of 20% NaCl. link2 The cleanup step involved dispersive solid phase extraction with graphitized carbon black (GCB, 5 mg/mL). Its performance was evaluated against primary secondary amine (PSA) and C18 sorbents. link3 The cleaned extract was evaporated to dryness and reconstituted in ethyl acetate before GC-MS/MS analysis. The method was validated for a mixture of 208 multi-class pesticides at 10 ng/g and higher levels (i.e., 20 and 50 ng/g).

The findings, which demonstrated a satisfacme and powder matrices with satisfactory selectivity, sensitivity, accuracy, and precision.

The Solus One Salmonella immunoassay utilizes Salmonella specific selective media and automated liquid handling, for the rapid and specific detection of Salmonella species in select food types.

The candidate method was evaluated using 375 g test portions in an unpaired study design for a single matrix, instant non-fat dry milk (NFDM) powder.

The matrix was compared to the United States Food and Drug Administration/Bacteriological Analytical Manual (FDA/BAM) Chapter 5 Salmonella reference method. Eleven participants from 10 laboratories within academia and industry, located within the United States, Mexico, South Africa, Germany, and the United Kingdom, contributed data for the collaborative study. Three levels of contamination were evaluated for each matrix an uninoculated control level [0 colony forming units (CFU)/test portion], a low inoculum level (0.2-2 CFU/test portion) and a high inoculum level (2-5 CFU/test portion). Statistical analysis was conducted according to the Probability of Detection (POD) statistical model.

Results obtained for the low inoculum level test portions produced a dLPOD value with a 95% confidence interval between the candidate method confirmed (both alternative and conventional confirmation procedures) and the reference method of 0.07 (-0.02, 0.15).

The dLPOD results indicate equivalence between the candidate method and the reference method for the matrix evaluated and the method demonstrated acceptable inter-laboratory reproducibility as determined in the collaborative evaluation. False positive and false negative rates were determined for the matrix and produce values of <2%.

Based on the data generated, the method demonstrated acceptable inter-laboratory reproducibility data and statistical analysis.

Based on the data generated, the method demonstrated acceptable inter-laboratory reproducibility data and statistical analysis.

There are several statistical methods for detecting a difference of detection rates between alternative and reference qualitative microbiological assays in a single laboratory validation study with a paired design.

We compared performance of eight methods including McNemar's test, sign test, Wilcoxon signed-rank test, paired t-test, and the regression methods based on conditional logistic (CLOGIT), mixed effects complementary log-log (MCLOGLOG), mixed effects logistic (MLOGIT) models, and a linear mixed effects model (LMM).

We first compared the minimum detectable difference in the proportion of detections between the alternative and reference detection methods among these statistical methods for a varied number of test portions. We then compared power and type 1 error rates of these methods using simulated data.

The MCLOGLOG and MLOGIT models had the lowest minimum detectable difference, followed by the LMM and paired t-test. The MCLOGLOG and MLOGIT models had the highest average power but were anticonservative when correlation between the pairs of outcome values of the alternative and reference methods was high. The LMM and paired t-test had mostly the highest average power when the correlation was low and the second highest average power when the correlation was high. Type 1 error rates of these last two methods approached the nominal value of significance level when the number of test portions was moderately large (n > 20).

The LMM and paired t-test are better choices than other competing methods, and we provide an example using real data.

The LMM and paired t-test are better choices than other competing methods, and we provide an example using real data.

Niacin (NIA) is a water-soluble vitamin and the primary treatment of pellagra. No analytical method was found to assess NIA in complex mixtures with its official impurities.

Two validated, accurate, and selective chemometric models were developed to assay NIA in the presence of its four official impurities, including pyridine, a nephrotoxic and hepatotoxic substance. Additionally, the two selective chemometric models were compared by processing UV spectra in the range 220-305 nm and applying partial least squares regression (PLSR) and support vector regression (SVR) models.

A five levels five factors experimental design was chosen to exhibit a training set of 25 mixtures that had numerous variable percentages of tested substances. A test set consisting of 10 mixtures was designed to confirm the predictive power of the suggested models.

The presented results substantiate the strength of the developed multivariate calibration models to assay NIA specifically with high selectivity and accuracy (100.02 ± 1.312 and 100.04 ± 1.272 for PLSR and SVR models, respectively). The root mean square error of prediction for the validation set mixtures was applied as a main comparison tool and it was found to be 0.2016 and 0.1890 for PLSR and SVR models, respectively.

The results of the developed models and the reported HPLC method were statistically compared, where F-values and Student's t-tests did not show significant difference in regards to accuracy and precision. The SVR model proved to be more accurate than the PLSR model, producing a high generalization capacity, while PLSR was easy to implement and fast.

PixeeMo™ is a compact instrument that enables bacterial cell counting using microfluidic chips instead of counting of colonies on culture media. Chips containing electrodes, based on fluid, electric filtering and sorting technology (FES), allow the selection of bacterial cells from other components in the sample. In the United States (US), surface water or ground water affected by surface water must be treated to reduce the total microbial load to less than 500 CFU/mL. In Japan, drinking water regulations limit the total bacterial load to 100 CFU/mL.

To validate the PixeeMoTM aerobic bacteria method based on the Japanese regulation in the range of 30-300 CFU/mL in drinking water.

PixeeMoTM aerobic bacteria method was compared to the Standard Method for the Examination of Water and Wastewater (SMEWW) 9215B (2017) using naturally contaminated drinking water.

The maximum repeatability standard deviation of the PixeeMoTM method was 14.8%. The difference of mean log10 values between the PixeeMoTM and SMEWW 9215B methods ranged from -0.015 to 0.258. Similar results were obtained in the independent laboratory study.

The PixeeMoTM method is equivalent to that of the SMEWW 9215B methods. The product consistency and stability study demonstrated no significant difference within the expiration date. The robustness study confirmed that there was no effect within the expected range. The instrument variation study also demonstrated no significant difference among the data of three PixeeMoTM instruments.

Total counts of bacteria in drinking water can be determined accurately within 1 h with PixeeMoTM.

Total counts of bacteria in drinking water can be determined accurately within 1 h with PixeeMoTM.

Turmeric is a medicinal herb containing curcuminoids, used as quality markers in dietary supplements. In 2016, an AOAC First Action Official MethodSM was adopted for quantitation of curcuminoids and requires multi-laboratory reproducibility data for Final Action status.

To collect reproducibility data for the quantitation of curcuminoids in dietary supplements through the National Institutes of Health Office of Dietary Supplements/National Institute of Standards and Technology Quality Assurance Program (QAP).

Laboratories that participated in the QAP by following the Official Methods of AnalysisSM Method 2016.16, submitted data for ten turmeric products. The data were analyzed for mean, repeatability, and reproducibility standard deviations, repeatability, and reproducibility.

The initial data collection resulted in insufficient replicates (five) for each test sample to determine reproducibility, therefore laboratories were provided additional materials resulting in an incremental data approach. For homogenous products, reproducibility for curcumin ranged from 3.