Distribution of mRNA coding for 5-hydroxytryptamine receptor subtypes in the intestines of healthy dairy cows and dairy cows with cecal dilatation-dislocation

OBJECTIVE: To investigate the distribution of mRNA coding for 7 subtypes of 5-hydroxytryptamine receptors (5-HTRs) in the intestines of healthy dairy cows and dairy cows with cecal dilatation-dislocation (CDD). SAMPLE POPULATION: Full-thickness intestinal wall biopsy specimens were obtained from the ileum, cecum, proximal loop of the ascending colon, and external loop of the spiral colon (ELSC) of 15 cows with CDD (group 1) and 15 healthy dairy cows allocated to 2 control groups (specimens collected during routine laparotomy [group 2] or after cows were slaughtered [group 3]). PROCEDURE: Amounts of mRNA coding for 7 subtypes of 5-HTRs (5-HT1A, 5-HT1B, 5-HT1D, 5-HT1F, 5-HT2A, 5-HT2B, and 5-HT4) were measured by quantitative real-time reverse transcriptase-PCR assay. Results were expressed as the percentage of mRNA expression of a housekeeping gene. RESULTS: Expression of mRNA coding for 5-HTR1B, 5-HTR2B, and 5-HTR4 was significantly lower in cows with CDD than in healthy cows. For 5-HTR2B and 5-HTR4, significant differences between cows with CDD and control cows were most pronounced for the ELSC. Expression of mRNA for 5-HTR1D, 5-HTR1F, and 5-HTR2A was extremely low in all groups, and mRNA for 5-HTR1A was not detected. CONCLUSIONS AND CLINICAL RELEVANCE: Relative concentrations of mRNA coding for 5-HTR1B, 5-HT2B, and 5-HTR4 were significantly lower in the intestines of cows with CDD than in the intestines of healthy dairy cows, especially for 5-HT2B and 5-HTR4 in the ELSC. This supports the hypothesis that serotonergic mechanisms, primarily in the spiral colon, are implicated in the pathogenesis of CDD.

Asymptotics for Marginal Generalized Linear Models With Sparse Correlations

Marginal generalized linear models can be used for clustered and longitudinal data by fitting a model as if the data were independent and using an empirical estimator of parameter standard errors. We extend this approach to data where the number of observations correlated with a given one grows with sample size and show that parameter estimates are consistent and asymptotically Normal with a slower convergence rate than for independent data, and that an information sandwich variance estimator is consistent. We present two problems that motivated this work, the modelling of patterns of HIV genetic variation and the behavior of clustered data estimators when clusters are large.

From EEG dependency multichannel matching pursuit to sparse topographic EEG decomposition

In this work, we present a multichannel EEG decomposition model based on an adaptive topographic time-frequency approximation technique. It is an extension of the Matching Pursuit algorithm and called dependency multichannel matching pursuit (DMMP). It takes the physiologically explainable and statistically observable topographic dependencies between the channels into account, namely the spatial smoothness of neighboring electrodes that is implied by the electric leadfield. DMMP decomposes a multichannel signal as a weighted sum of atoms from a given dictionary where the single channels are represented from exactly the same subset of a complete dictionary. The decomposition is illustrated on topographical EEG data during different physiological conditions using a complete Gabor dictionary. Further the extension of the single-channel time-frequency distribution to a multichannel time-frequency distribution is given. This can be used for the visualization of the decomposition structure of multichannel EEG. A clustering procedure applied to the topographies, the vectors of the corresponding contribution of an atom to the signal in each channel produced by DMMP, leads to an extremely sparse topographic decomposition of the EEG.

Endothelium-specific replacement of the connexin43 coding region by a lacZ reporter gene

The murine gap junction protein connexin43 (Cx43) is expressed in blood vessels, with vastly different contribution by endothelial and smooth muscle cells. We have used the Cre recombinase under control of TIE2 transcriptional elements to inactivate a floxed Cx43 gene specifically in endothelial cells. Cre-mediated deletion led to replacement of the Cx43 coding region by a lacZ reporter gene. This allowed us to monitor the extent of deletion and to visualize the endothelial expression pattern of Cx43. We found widespread endothelial expression of the Cx43 gene during embryonic development, which became restricted largely to capillaries and small vessels in all adult organs examined. Mice lacking Cx43 in endothelium did not exhibit altered blood pressure, in contrast to mice deficient in Cx40. Our results show that lacZ activation after deletion of the target gene allows us to determine the extent of cell type-specific deletion after phenotypical investigation of the same animal.

Comparison of musical activities of cochlear implant users with different speech-coding strategies

Speech coding might have an impact on music perception of cochlear implant users. This questionnaire study compares the musical activities and perception of postlingually deafened cochlear implant users with three different coding strategies (CIS, ACE, SPEAK) using the Munich Music Questionnaire. Overall, the self-reported perception of music of CIS, SPEAK, and ACE users did not differ by very much.

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.

The end1 gene of Schizosaccharomyces pombe coding for a DNase is identical with the pnu1 gene coding for an RNase

The DNA nuclease activity encoded by the end1 gene, and its inactivation by mutation, was described in connection with the characterization of DNA topoisomerases in the fission yeast Schizosaccharomyces pombe (Uemura and Yanagida, 1984). Subsequently, end1 mutant strains were used for the preparation of cell extracts for the study of enzymes and intermediates involved in DNA metabolism. The molecular identification of the end1 gene and its identity with the pnu1 gene is presented. The end1-458 mutation alters glycine to glutamate in the conserved motif TGPYLP. The pnu1 gene codes for an RNase that is induced by nitrogen starvation (Nakashima et al., 2002b). Thus, the End1/Pnu1 protein, like related mitochondrial proteins in other organisms, is an example of a sugar-non-specific nuclease. The analysis of strains carrying a pnu1 deletion revealed no defects in meiotic recombination and spore viability.

Predictive-DCT Coding for 3D Mesh Sequences Compression

This paper proposes a new compression algorithm for dynamic 3d meshes. In such a sequence of meshes, neighboring vertices have a strong tendency to behave similarly and the degree of dependencies between their locations in two successive frames is very large which can be efficiently exploited using a combination of Predictive and DCT coders (PDCT). Our strategy gathers mesh vertices of similar motions into clusters, establish a local coordinate frame (LCF) for each cluster and encodes frame by frame and each cluster separately. The vertices of each cluster have small variation over a time relative to the LCF. Therefore, the location of each new vertex is well predicted from its location in the previous frame relative to the LCF of its cluster. The difference between the original and the predicted local coordinates are then transformed into frequency domain using DCT. The resulting DCT coefficients are quantized and compressed with entropy coding. The original sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders.

Impact of unlinked deaths and coding changes on mortality trends in the Swiss National Cohort

BACKGROUND Results of epidemiological studies linking census with mortality records may be affected by unlinked deaths and changes in cause of death classification. We examined these issues in the Swiss National Cohort (SNC). METHODS The SNC is a longitudinal study of the entire Swiss population, based on the 1990 (6.8 million persons) and 2000 (7.3 million persons) censuses. Among 1,053,393 deaths recorded 1991-2007 5.4% could not be linked using stringent probabilistic linkage. We included the unlinked deaths using pragmatic linkages and compared mortality rates for selected causes with official mortality rates. We also examined the impact of the 1995 change in cause of death coding from version 8 (with some additional rules) to version 10 of the International Classification of Diseases (ICD), using Poisson regression models with restricted cubic splines. Finally, we compared results from Cox models including and excluding unlinked deaths of the association of education, marital status, and nationality with selected causes of death. RESULTS SNC mortality rates underestimated all cause mortality by 9.6% (range 2.4%-17.9%) in the 85+ population. Underestimation was less pronounced in years nearer the censuses and in the 75-84 age group. After including 99.7% of unlinked deaths, annual all cause SNC mortality rates were reflecting official rates (relative difference between -1.4% and +1.8%). In the 85+ population the rates for prostate and breast cancer dropped, by 16% and 21% respectively, between 1994 and 1995 coincident with the change in cause of death coding policy. For suicide in males almost no change was observed. Hazard ratios were only negligibly affected by including the unlinked deaths. A sudden decrease in breast (21% less, 95% confidence interval: 12%-28%) and prostate (16% less, 95% confidence interval: 7%-23%) cancer mortality rates in the 85+ population coincided with the 1995 change in cause of death coding policy. CONCLUSIONS Unlinked deaths bias analyses of absolute mortality rates downwards but have little effect on relative mortality. To describe time trends of cause-specific mortality in the SNC, accounting for the unlinked deaths and for the possible effect of change in death certificate coding was necessary.