SADD: STOCHASTIC ANALYSIS OF DESTRUCTIVELY MEASURED DATA - POSSIBILITIES TO INCLUDE BIOLOGICAL VARIATIONS IN STATISTICAL ANALYSIS

Three techniques are presented to include the structural variation always present in measured data in statistical analysis. The methods are investigated and compared using cross sectional data, generated based on an exponential model as if gathered by destructive measuring methods. All three methods are based on optimising objective functions based on the data and the biological shift model. These objective functions are calculated for each separate measuring point in time either according the specific density function belonging to the model applied, or after conversion into biological shift factors (also according to the model applied) according to a Gaussian distribution. The procedures used need to be improved, embedded in the existing statistical framework and all available statistical expertise and skills need to be combined into robust procedures capable of analysing everyday data

Scale space consistency of piecewise constant least squares estimators -- another look at the regressogram

We study the asymptotic behavior of piecewise constant least squares regression estimates, when the number of partitions of the estimate is penalized. We show that the estimator is consistent in the relevant metric if the signal is in $L^2([0,1])$, the space of c\`{a}dl\`{a}g functions equipped with the Skorokhod metric or $C([0,1])$ equipped with the supremum metric. Moreover, we consider the family of estimates under a varying smoothing parameter, also called scale space. We prove convergence of the empirical scale space towards its deterministic target.Comment: Published at http://dx.doi.org/10.1214/074921707000000274 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Techniques to assess biological variation in destructive data

Variation is present in all measured data, due to variation between individuals (biological variation) and variation induced by the measuring system (technical variation). Biological variation present in experimental data is not the result of a random process but strictly subject to deterministic rules as found on non-destructive data. The majority of data obtained in research are obtained by destructive techniques. The rules on behaviour and magnitude of variation should however, also apply to these cross sectional data. New techniques have been developed for analysing cross sectional data including the assessment of variation: 1) Probelation. In a set of cross-sectional data, the individual with the highest value at some point in time will resemble the individual with the highest value at previous or future times, and the second highest the second highest at previous times, and so on. One can assign an identification number based on the sorted order of the measured values per measuring point in time. This number can be used as a pseudo fruit number in indexed or mixed effects regression analysis, similar to the data analysis of longitudinal data; 2) Density assessment. For not too complex kinetic processes the density function can be deduced. Measuring a large number of individuals (on a single point in time) provides the possibility to assess directly the variation in the data; 3) Quantile regression. This technique also relies on ranking the data per measuring time. The probelation number is now converted into a probability, and the mean and standard deviation is estimated directly along with the kinetic parameter, using simple non-linear regression. Based on simulated data sets, all three techniques are demonstrated, and the results compared with the input values. Explained parts (R2 adj) obtained are generally well over 90%, provided that the technical variation is not excessively large

High-salinity growth conditions promote tat-independent secretion of tat substrates in Bacillus subtilis

The Gram-positive bacterium Bacillus subtilis contains two Tat translocases, which can facilitate transport of folded proteins across the plasma membrane. Previous research has shown that Tat-dependent protein secretion in B. subtilis is a highly selective process and that heterologous proteins, such as the green fluorescent protein (GFP), are poor Tat substrates in this organism. Nevertheless, when expressed in Escherichia coli, both B. subtilis Tat translocases facilitated exclusively Tat-dependent export of folded GFP when the twin-arginine (RR) signal peptides of the E. coli AmiA, DmsA, or MdoD proteins were attached. Therefore, the present studies were aimed at determining whether the same RR signal peptide-GFP precursors would also be exported Tat dependently in B. subtilis. In addition, we investigated the secretion of GFP fused to the full-length YwbN protein, a strict Tat substrate in B. subtilis. Several investigated GFP fusion proteins were indeed secreted in B. subtilis, but this secretion was shown to be completely Tat independent. At high-salinity growth conditions, the Tat-independent secretion of GFP as directed by the RR signal peptides from the E. coli AmiA, DmsA, or MdoD proteins was significantly enhanced, and this effect was strongest in strains lacking the TatAy-TatCy translocase. This implies that high environmental salinity has a negative influence on the avoidance of Tat-independent secretion of AmiA-GFP, DmsA-GFP, and MdoD-GFP. We conclude that as-yet-unidentified control mechanisms reject the investigated GFP fusion proteins for translocation by the B. subtilis Tat machinery and, at the same time, set limits to their Tat-independent secretion, presumably via the Sec pathway

Integrating omics datasets with the OmicsPLS package

Background: With the exponential growth in available biomedical data, there is a need for data integration methods that can extract information about relationships between the data sets. However, these data sets might have very different characteristics. For interpretable results, data-specific variation needs to be quantified. For this task, Two-way Orthogonal Partial Least Squares (O2PLS) has been proposed. To facilitate application and development of the methodology, free and open-source software is required. However, this is not the case with O2PLS. Results: We introduce OmicsPLS, an open-source implementation of the O2PLS method in R. It can handle both low- and high-dimensional datasets efficiently. Generic methods for inspecting and visualizing results are implemented. Both a standard and faster alternative cross-validation methods are available to determine the number of components. A simulation study shows good performance of OmicsPLS compared to alternatives, in terms of accuracy and CPU runtime. We demonstrate OmicsPLS by integrating genetic and glycomic data. Conclusions: We propose the OmicsPLS R package: a free and open-source implementation of O2PLS for statistical data integration. OmicsPLS is available at https://cran.r-project.org/package=OmicsPLSand can be installed in R via install.packages("OmicsPLS")

One frame and several new infinite families of Z-cyclic whist designs

AbstractIn 2001, Ge and Zhu published a frame construction which they utilized to construct a large class of Z-cyclic triplewhist designs. In this study the power and elegance of their methodology is illustrated in a rather dramatic fashion. Primarily due to the discovery of a single new frame it is possible to combine their techniques with the product theorems of Anderson, Finizio and Leonard along with a few new specific designs to obtain several new infinite classes of Z-cyclic whist designs. A sampling of the new results contained herein is as follows: (1) Z-cyclic Wh(33p+1), p a prime of the form 4t+1; (2) Z-cyclic Wh(32n+1s+1), for all n⩾1, s=5,13,17; (3) Z-cyclic Wh(32ns+1), for all n⩾1, s=35,55,91; (4) Z-cyclic Wh(32n+1s), for all n⩾1, and for all s for which there exist a Z-cyclic Wh(3s) and a homogeneous (s,4,1)-DM; and (5) Z-cyclic Wh(32ns) for all n⩾1, s=5,13. Many other results are also obtained. In particular, there exist Z-cyclic Wh(33v+1) where v is any number for which Ge and Zhu obtained Z-cyclic TWh(3v+1)

Human adult cardiac autonomic innervation : controversies in anatomical knowledge and relevance for cardiac neuromodulation

Background: Cardiac sympathetic blockade is a therapeutic approach for arrhythmias and heart failure and may be a beneficial effect of high thoracic epidural anesthesia. These treatments require detailed knowledge of the spatial location and distribution of cardiac autonomic nerves, however, there are controversies on this subject in humans. Objective: To provide a systematic overview of current knowledge on human anatomy of the cardiac autonomic nervous system. Results: In contrast to the often claimed assumption that human preganglionic sympathetic cardiac neurons originate mainly from thoracic spinal segments T1-T4 or T5, there is ample evidence indicating involvement of cervical spinal segment C8 and thoracic spinal segments below T5. Whether cervical ganglia besides the stellate ganglion play a role in transmission of cardiac sympathetic signals is unclear. Similarly, there is debate on the origin of cardiac nerves from different thoracic ganglia. Most human studies report thoracic cardiac nerves emerging from the first to fourth thoracic paravertebral ganglia; others report contributions from the fifth, sixth and even the seventh thoracic ganglia. There is no agreement on the precise composition of nerve plexuses at the cardiac level. After years of debate, it is generally accepted that the vagal nerve contributes to ventricular innervation. Vagal distribution appears higher in atria, whereas adrenergic fibers exceed the number of vagal fibers in the ventricles. Conclusion: Anatomy of the human cardiac autonomic nervous system is highly variable and likely extends beyond generally assumed boundaries. This information is relevant for thoracic epidural anesthesia and procedures targeting neuronal modulation of cardiac sympathetic innervation