Quantitative detection of atropine-delayed gastric emptying in the horse by the ¹³C-octanoic acid breath test

The <sup>13</sup>C-octanoic acid breath test has been correlated significantly to radioscintigraphy for measurement of gastric emptying indices in healthy horses. The objective of this study was to investigate the validity of the test for measurement of equine delayed gastric emptying, prior to its potential clinical application for this purpose. A model of atropine- induced gastroparesis was used. Gastric emptying rate was measured twice in 8 horses using concurrent radioscintigraphy and/or breath test after treatment i.v. with either atropine (0.035 mg/kg bwt) or saline in randomised order. Analysis of both data sets demonstrated that the atropine treatment had caused a significant delay in gastric emptying rate. Paired breath test data showed an atropine-induced delay in gastric half-emptying time t(1/2)), with no overlap in the 99% Cl range (P<0.001). Significant correlations were found between scintigraphy and <sup>13</sup>C-octanoic acid breath test for calculation of both t(1/2) (P<0.01) and lag phase duration (P<0.05) in the atropine-delayed emptying results. The mean (s.d.) bias in breath test t(1/2) when compared with scintigraphy was 1.78 (0.58) h. The results demonstrated that the <sup>13</sup>C-octanoic acid breath test was an effective diagnostic modality for the measurement of equine delayed gastric emptying. The technique offers advantages to existing methods for clinical investigation, as it is noninvasive, not radioactive, quantitative and requires minimal equipment or training to perform

From the discrete to the continuous - towards a cylindrically consistent dynamics

Discrete models usually represent approximations to continuum physics. Cylindrical consistency provides a framework in which discretizations mirror exactly the continuum limit. Being a standard tool for the kinematics of loop quantum gravity we propose a coarse graining procedure that aims at constructing a cylindrically consistent dynamics in the form of transition amplitudes and Hamilton's principal functions. The coarse graining procedure, which is motivated by tensor network renormalization methods, provides a systematic approximation scheme towards this end. A crucial role in this coarse graining scheme is played by embedding maps that allow the interpretation of discrete boundary data as continuum configurations. These embedding maps should be selected according to the dynamics of the system, as a choice of embedding maps will determine a truncation of the renormalization flow.Comment: 22 page

Validation of the ¹³C-octanoic acid breath test for measurement of equine gastric emptying rate of solids using radioscintigraphy

Reasons for performing study: Disordered gastric motility may be a significant factor in the pathogenesis of many equine conditions. Although tests for liquid phase emptying rate have been validated in the horse, there are no effective tests for solid phase emptying measurement that can be performed routinely in the field. Objectives: The objective of this study was the assessment of a novel stable isotope technique, the <sup>13</sup>C-octane acid breath test (<sup>13</sup> C-OABT), for the measurement of gastric emptying of solid ingesta, by direct comparison with the optimum method of gastric scintigraphy. Methods: To facilitate dual measurement of gastric emptying, a test meal was used containing baked egg yolk labelled with both <sup>13</sup>C-octanoic acid and (99m)technetium sulphur colloid. Simultaneous, serial lateral gastric scintigraphs and expiratory breath samples were obtained in 12 healthy horses after voluntary ingestion of the test meal. Analysis of breath (CO2)-C-13:(CO2)-C-12 ratio was performed by continuous flow isotope ratio mass spectrometry. Power regression was used to determine the gastric emptying coefficient, the gastric half-emptying time (t(1/2)) and duration of the lag phase (t(lag)). Results: Significant correlations (P < 0.001) were found between the 2 techniques for measurement of both t(1/2) and t(lag). In addition, scintigraphic left t(1/2) was correlated significantly to breath test gastric emptying coefficient (P < 0.001). Conclusions: It was concluded that the <sup>13</sup>C-octanoic acid breath test is a reliable diagnostic procedure to measure gastric emptying rate of solids in the horse. Potential relevance: Being safe, noninvasive and easy to perform, this test has potential value as; both sensitive diagnostic modality and humane research tool for motility studies

On direct measurement of the W production charge asymmetry at the LHC

The prospects for making a direct measurement of the W production charge asymmetry at the LHC are discussed. A modification to the method used at the Tevatron is proposed for measurements at the LHC. The expected sensitivity for such a measurement to parton distribution functions is compared to that for a measurement of the lepton charge asymmetry. The direct measurement approach is found to be less useful for placing constraints on parton distribution functions at the LHC than a measurement of the lepton charge asymmetry.Comment: 18 pages, 10 figures, v2: references and keywords updated v3: Additional paragraph discussing inclusion of W asymmetry in global fits adde

Using gamma+jets Production to Calibrate the Standard Model Z(nunu)+jets Background to New Physics Processes at the LHC

The irreducible background from Z(nunu)+jets, to beyond the Standard Model searches at the LHC, can be calibrated using gamma+jets data. The method utilises the fact that at high vector boson pT, the event kinematics are the same for the two processes and the cross sections differ mainly due to the boson-quark couplings. The method relies on a precise prediction from theory of the Z/gamma cross section ratio at high pT, which should be insensitive to effects from full event simulation. We study the Z/gamma ratio for final states involving 1, 2 and 3 hadronic jets, using both the leading-order parton shower Monte Carlo program Pythia8 and a leading-order matrix element program Gambos. This enables us both to understand the underlying parton dynamics in both processes, and to quantify the theoretical systematic uncertainties in the ratio predictions. Using a typical set of experimental cuts, we estimate the net theoretical uncertainty in the ratio to be of order 7%, when obtained from a Monte Carlo program using multiparton matrix-elements for the hard process. Uncertainties associated with full event simulation are found to be small. The results indicate that an overall accuracy of the method, excluding statistical errors, of order 10% should be possible.Comment: 22 pages, 14 figures; Accepted for publication by JHE

Multiple sequence alignment based on set covers

We introduce a new heuristic for the multiple alignment of a set of sequences. The heuristic is based on a set cover of the residue alphabet of the sequences, and also on the determination of a significant set of blocks comprising subsequences of the sequences to be aligned. These blocks are obtained with the aid of a new data structure, called a suffix-set tree, which is constructed from the input sequences with the guidance of the residue-alphabet set cover and generalizes the well-known suffix tree of the sequence set. We provide performance results on selected BAliBASE amino-acid sequences and compare them with those yielded by some prominent approaches

EEG-EMG-coherence in SDB patients with utilization of a support vector machine-algorithm [Poster Abstract]

Background We investigated whether the EEG-EMG-coherence allows a differentiation between patients with sleep-disordered breathing (SDB) without OSA and SDB-patients with mild, moderate or severe OSA. Methods Polysomnographic recordings of 102 patients with SDB (33 female; age: 53,± 12,4 years) were analyzed with the multitaper coherence method (MTM). Recordings contained 2 EEG-channels (C3 and C4) and a chin EMG-channel for one night. Four epochs (each 30 seconds, classified manually by AASM 2007 criteria) of each sleep stage were marked (1632 epochs in total), which were included in the classification analysis. The collected data sets were supplied to the support vector machine (SVM) algorithm to classify OSA severity. Twenty patients had a mild (RDI ≥10/h and < 15/h), 30 patients had a moderate (RDI ≥15/h and < 30/h) and 27 patients had a severe OSA (RDI ≥30/h). 25 patients had a RDI < 10/h. The AUC (area under the curve) value was calculated for each receiver operator curve (ROC) curve. Results EEG-EMG coherence was able to distinguish between the SDB-patients without OSA and SDB-patients with OSA in each of the 3 severity groups using an SVM algorithm. In mild OSA, the AUC was 0.616 (p = 0.024), in moderate OSA the AUC was 0.659 (p = 0.003), and in severe OSA the AUC was 0.823 (p < 0.001). Conclusions SDB patients with OSA can be differentiated from SDB patients without OSA on the basis of EEG-EMG coherence by using the Multitaper Coherence Method (MTM) and SVM algorithm

Sleep stage classification using spectral analyses and support vector machine algorithm on C3- and C4-EEG signals [Abstract]

Introduction Sleep stage classification currently relies largely on visual classification methods. We tested a new pipeline for automated offline classification based upon power spectrum at six different frequency bands. The pipeline allowed sleep stage classification and provided whole-night visualization of sleep stages. Materials and methods 102 subjects (69 male; 53.74 ± 12.4 years) underwent full-night polysomnography. The recording system included C3- and C4-EEG channels. All signals were measured at sampling rate of 200 Hz. Four epochs (30 seconds each) of each sleep stage (N1, N2, N3, REM, awake) were marked in the visually scored recordings of each one of the 102 patients. Scoring of sleep stages was performed according to AASM 2007-criteria. In total 408 epochs for each sleep stage were included in the sleep stage classification analyses. Recordings of all these epochs were fed into the pipeline to estimate the power spectrum at six different frequency bands, namely from very low frequency (VLF, 0.1-1 Hz) to gamma frequency (30-50 Hz). The power spectrum was measured with a method called multitaper method. In this method the spectrum is estimated by multiplying the data with K windows (i.e tapers).The estimated parameters were given as input to the support vector machine (SVM) algorithm to classify the five different sleep stages based on the mean power amplitude estimated from six different frequency bands. The SVM algorithm was trained with 51 subjects and the testing was done with the other 51 subjects. In order to avoid bias of the training dataset, a 10-fold cross validation was additionally done to check the performance of the SVM algorithm Results The estimated testing accuracy of prediction of the sleep stages was 84.1% for stage N1 using the mean power amplitude from the delta frequency band. Accuracy was 67.8% for stage N2 from the delta frequency band and 74.9% for stage N3 from the VLF. Accuracy was 79.7% for REM stage from the delta frequency band and 84,8% for the wake stage from the theta frequency band. Conclusions We were able to successfully classify the sleep stages using the mean power amplitude at six different frequency bands separately and achieved up to 85% accuracy using the electrophysiological EEG signals. The delta and theta frequency bands gave the best accuracy of classification among all sleep stages