, Melissa Yssel, MB ChB, FC Path(SA) Chem 139, and Wendy M. Zakowicz, BS 79 Purpose: To achieve clinical validation of cutoff values for newborn screening by tandem mass spectrometry through a worldwide collaborative effort. Methods: Cumulative percentiles of amino acids and acylcarnitines in dried blood spots of approximately 25-30 million normal newborns and 10,742 deidentified true positive cases are compared to assign clinical significance, which is achieved when the median of a disorder range is, and usually markedly outside, either the 99th or the 1st percentile of the normal population. The cutoff target ranges of analytes and ratios are then defined as the interval between selected percentiles of the two populations. When overlaps occur, adjustments are made to maximize sensitivity and specificity taking all available factors into consideration.

Purpose: To improve quality of newborn screening by tandem mass spectrometry with a novel approach made possible by the collaboration of 154 laboratories in 49 countries. Methods: A database of 767,464 results from 12,721 cases affected with 60 conditions was used to build multivariate pattern recognition software that generates tools integrating multiple clinically significant results into a single score. This score is determined by the overlap between normal and disease ranges, penetration within the disease range, differences between conditions, and weighted correction factors. Results: Ninety tools target either a single condition or the differential diagnosis between multiple conditions. Scores are expressed as the percentile rank among all cases with the same condition and are compared to interpretation guidelines. Retrospective evaluation of past cases suggests that these tools could have avoided at least half of 279 false-positive outcomes caused by carrier status for fatty-acid oxidation disorders and could have prevented 88% of known false-negative events. Conclusions: Application of this computational approach to raw data is independent from single analyte cutoff values. In Minnesota, the tools have been a major contributing factor to the sustained achievement of a false-positive rate below 0.1% and a positive predictive value above 60%

BACKGROUND AND PURPOSEGut microbiota is essential for the development of the gastrointestinal system, including the enteric nervous system (ENS). Perturbations of gut microbiota in early life have the potential to alter neurodevelopment leading to functional bowel disorders later in life. We examined the hypothesis that gut dysbiosis impairs the structural and functional integrity of the ENS, leading to gut dysmotility in juvenile mice. EXPERIMENTAL APPROACHTo induce gut dysbiosis, broad-spectrum antibiotics were administered by gavage to juvenile (3weeks old) male C57Bl/6 mice for 14 days. Bile acid composition in the intestinal lumen was analysed by liquid chromatography-mass spectrometry. Changes in intestinal motility were evaluated by stool frequency, transit of a fluorescent-labelled marker and isometric muscle responses of ileal full-thickness preparations to receptor and non-receptor-mediated stimuli. Alterations in ENS integrity were assessed by immunohistochemistry and Western blot analysis. KEY RESULTSAntibiotic treatment altered gastrointestinal transit, luminal bile acid metabolism and bowel architecture. Gut dysbiosis resulted in distorted glial network, loss of myenteric plexus neurons, altered cholinergic, tachykininergic and nitrergic neurotransmission associated with reduced number of nNOS neurons and different ileal distribution of the toll-like receptor TLR2. Functional defects were partly reversed by activation of TLR2 signalling. CONCLUSIONS AND IMPLICATIONSGut dysbiosis caused complex morpho-functional neuromuscular rearrangements, characterized by structural defects of the ENS and increased tachykininergic neurotransmission. Altogether, our findings support the beneficial role of enteric microbiota for ENS homeostasis instrumental in ensuring proper gut neuromuscular function during critical stages of development. Abbreviations

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Purposepancreatic adenocarcinoma is the fourth leading cause of cancer related deaths due to its aggressive behavior and poor clinical outcome. There is a considerable variability in the frequency of serum tumor markers in cancer' patients. We performed a metabolomics screening in patients diagnosed with pancreatic cancer.Experimental DesignTwo targeted metabolomic assays were conducted on 40 serum samples of patients diagnosed with pancreatic cancer and 40 healthy controls. Multivariate methods and classification trees were performed.Materials and MethodsSparse partial least squares discriminant analysis (SPLS-DA) was used to reduce the high dimensionality of a pancreatic cancer metabolomic dataset, differentiating between pancreatic cancer (PC) patients and healthy subjects. Using Random Forest analysis palmitic acid, 1,2-dioleoyl-sn-glycero-3-phospho-rac-glycerol, lanosterol, lignoceric acid, 1-monooleoyl-rac-glycerol, cholesterol 5α,6α epoxide, erucic acid and taurolithocholic acid (T-LCA), oleoyl-L-carnitine, oleanolic acid were identified among 206 metabolites as highly discriminating between disease states. Comparison between Receiver Operating Characteristic (ROC) curves for palmitic acid and CA 19-9 showed that the area under the ROC curve (AUC) of palmitic acid (AUC=1.000; 95% confidence interval) is significantly higher than CA 19-9 (AUC=0.963; 95% confidence interval: 0.896-1.000).ConclusionMass spectrometry-based metabolomic profiling of sera from pancreatic cancer patients and normal subjects showed significant alterations in the profiles of the metabolome of PC patients as compared to controls. These findings offer an information-rich matrix for discovering novel candidate biomarkers with diagnostic or prognostic potentials.