Genotype and antibiotic resistance analyses of Campylobacter isolates from ceca and carcasses of slaughtered broiler flocks

To obtain genetic information about Campylobacter jejuni and Campylobacter coli from broilers and carcasses at slaughterhouses, we analyzed and compared 340 isolates that were collected in 2008 from the cecum right after slaughter or from the neck skin after processing. We performed rpoB sequence-based identification, multilocus sequence typing (MLST), and flaB sequence-based typing; we additionally analyzed mutations within the 23S rRNA and gyrA genes that confer resistance to macrolide and quinolone antibiotics, respectively. The rpoB-based identification resulted in a distribution of 72.0% C. jejuni and 28.0% C. coli. The MLST analysis revealed that there were 59 known sequence types (STs) and 6 newly defined STs. Most of the STs were grouped into 4 clonal complexes (CC) that are typical for poultry (CC21, CC45, CC257, and CC828), and these represented 61.8% of all of the investigated isolates. The analysis of 95 isolates from the cecum and from the corresponding carcass neck skin covered 44 different STs, and 54.7% of the pairs had matching genotypes. The data indicate that cross-contamination from various sources during slaughter may occur, although the majority of Campylobacter contamination on carcasses appeared to originate from the slaughtered flock itself. Mutations in the 23S rRNA gene were found in 3.1% of C. coli isolates, although no mutations were found in C. jejuni isolates. Mutations in the gyrA gene were observed in 18.9% of C. jejuni and 26.8% of C. coli isolates, which included two C. coli strains that carried mutations conferring resistance to both classes of antibiotics. A relationship between specific genotypes and antibiotic resistance/susceptibility was observed.

Uncovering the dynamics of cardiac systems using stochastic pacing and frequency domain analyses

Alternans of cardiac action potential duration (APD) is a well-known arrhythmogenic mechanism which results from dynamical instabilities. The propensity to alternans is classically investigated by examining APD restitution and by deriving APD restitution slopes as predictive markers. However, experiments have shown that such markers are not always accurate for the prediction of alternans. Using a mathematical ventricular cell model known to exhibit unstable dynamics of both membrane potential and Ca2+ cycling, we demonstrate that an accurate marker can be obtained by pacing at cycle lengths (CLs) varying randomly around a basic CL (BCL) and by evaluating the transfer function between the time series of CLs and APDs using an autoregressive-moving-average (ARMA) model. The first pole of this transfer function corresponds to the eigenvalue (λalt) of the dominant eigenmode of the cardiac system, which predicts that alternans occurs when λalt≤−1. For different BCLs, control values of λalt were obtained using eigenmode analysis and compared to the first pole of the transfer function estimated using ARMA model fitting in simulations of random pacing protocols. In all versions of the cell model, this pole provided an accurate estimation of λalt. Furthermore, during slow ramp decreases of BCL or simulated drug application, this approach predicted the onset of alternans by extrapolating the time course of the estimated λalt. In conclusion, stochastic pacing and ARMA model identification represents a novel approach to predict alternans without making any assumptions about its ionic mechanisms. It should therefore be applicable experimentally for any type of myocardial cell.

Proteome and radioimmunoassay analyses of pituitary hormones and proteins in response to feed restriction of dairy cows

The hypothalamic-pituitary system controls homeostasis during feed energy reduction. In order to examine which pituitary proteins and hormone variants are potentially associated with metabolic adaptation, pituitary glands from ad libitum and energy restrictively fed dairy cows were characterized using RIA and 2-DE followed by MALDI-TOF-MS. We found 64 different spots of regulatory hormones: growth hormone (44), preprolactin (16), luteinizing hormone (LH) (1), thyrotropin (1), proopiomelanocortin (1) and its cleavage product lipotropin (1), but none of these did significantly differ between feeding groups. Quantification of total pituitary LH and prolactin concentrations by RIA confirmed the results obtained by proteome analysis. Also, feed energy restriction provoked increasing non-esterified fatty acid, decreasing prolactin, but unaltered glucose, LH and growth hormone plasma concentrations. Energy restriction decreased the expression of glial fibrillary acidic protein, triosephosphate isomerase, purine-rich element-binding protein A and elongation factor Tu, whereas it increased expression of proline synthetase co-transcribed homolog, peroxiredoxin III, beta-tubulin and annexin A5 which is involved in the hormone secretion process. Our results indicate that in response to feed energy restriction the pituitary reservoir of all posttranslationally modified hormone forms remains constant. Changing plasma hormone concentrations are likely attributed to a regulated releasing process from the gland into the blood.

New methods can extend the use of minimal important difference units in meta-analyses of continuous outcome measures

For continuous outcomes measured using instruments with an established minimally important difference (MID), pooled estimates can be usefully reported in MID units. Approaches suggested thus far omit studies that used instruments without an established MID. We describe an approach that addresses this limitation.

P-Technique Factor Analyses of the Multiple Affect Adjective Checklist (MAACL)

The Multiple Affect Adjective Check List (MAACL) has been found to have five first-order factors representing Anxiety, Depression, Hostility, Positive Affect, and Sensation Seeking and two second-order factors representing Positive Affect and Sensation Seeking (PASS) and Dysphoria. The present study examines whether these first- and second-order conceptions of affect (based on R-technique factor analysis) can also account for patterns of intraindividual variability in affect (based on P-technique factor analysis) in eight elderly women. Although the hypothesized five-factor model of affect was not testable in all of the present P-technique datasets, the results were consistent with this interindividual model of affect. Moreover, evidence of second-order (PASS and Dysphoria) and third-order (generalized distress) factors was found in one data set. Sufficient convergence in findings between the present P-technique research and prior R-technique research suggests that the MAACL is robust in describing both inter- and intraindividual components of affect in elderly women.

Clinical, polysomnographic and genome-wide association analyses of narcolepsy with cataplexy: a European Narcolepsy Network study

The aim of this study was to describe the clinical and PSG characteristics of narcolepsy with cataplexy and their genetic predisposition by using the retrospective patient database of the European Narcolepsy Network (EU-NN). We have analysed retrospective data of 1099 patients with narcolepsy diagnosed according to International Classification of Sleep Disorders-2. Demographic and clinical characteristics, polysomnography and multiple sleep latency test data, hypocretin-1 levels, and genome-wide genotypes were available. We found a significantly lower age at sleepiness onset (men versus women: 23.74 ± 12.43 versus 21.49 ± 11.83, P = 0.003) and longer diagnostic delay in women (men versus women: 13.82 ± 13.79 versus 15.62 ± 14.94, P = 0.044). The mean diagnostic delay was 14.63 ± 14.31 years, and longer delay was associated with higher body mass index. The best predictors of short diagnostic delay were young age at diagnosis, cataplexy as the first symptom and higher frequency of cataplexy attacks. The mean multiple sleep latency negatively correlated with Epworth Sleepiness Scale (ESS) and with the number of sleep-onset rapid eye movement periods (SOREMPs), but none of the polysomnographic variables was associated with subjective or objective measures of sleepiness. Variant rs2859998 in UBXN2B gene showed a strong association (P = 1.28E-07) with the age at onset of excessive daytime sleepiness, and rs12425451 near the transcription factor TEAD4 (P = 1.97E-07) with the age at onset of cataplexy. Altogether, our results indicate that the diagnostic delay remains extremely long, age and gender substantially affect symptoms, and that a genetic predisposition affects the age at onset of symptoms.