Parameters Statistics Research Articles

P185 FOLLOW–UP OF PATIENTS UNDERGOING POST–EXTRACTION LEADLESS PACEMAKER IMPLANTATION

Abstract Introduction The implantation of traditional stimulation devices involves numerous complications, in the short and long term, among which one of the most important is represented by infections. Most patients who experience this complication undergo a lead extraction procedure. In pacemaker–dependent patients, there is often the problem of having to perform an early reimplantation after extraction. This study aims to evaluate the outcome of Micra implantation in patients previously undergoing TLE, comparing them with patients who have a Micra as their first implant. Study materials and methods. From January 2017 to November 2022, 190 leadless pacemaker implant procedures were performed in our center. Of these patients 24 underwent an extraction procedure. To evaluate the technical performance of leadless pacemakers in post–extracted patients, a comparison was made between these and the "de novo" implanted leadless, so as to evaluate the effectiveness of the technical specifications. In particular, all the basic characteristics of the various patients, the data of the extraction and the implantation procedure were considered. Subsequently, the values ​​of the sensing, threshold, impedance and percentage of stimulation parameters collected in the follow–ups performed by the two groups of patients at 1 month after implantation, 6 months and every year were compared. Study results. An initial analysis of the follow–up of the aforementioned classes of patients from 2017 to today already provides us with some important data: in the patients who have implanted a leadless pacemaker following extraction, in no case has there been a recurrence of infection; the success of the Micra implant was 100%. Furthermore, the analysis of the electrical parameters statistics demonstrated the absolute effectiveness of the leadless device in both classes of patients compared, without highlighting major differences. Conclusions Leadless pacemaker implantation in post–extracted patients has proven to be an effective choice as an alternative to the implantation of a traditional pacemaker, to allow the reduction of the risk of infectious complications, while still guaranteeing optimal performance

DNA methylation microarrays identify epigenetically regulated lipid related genes in obese patients with hypercholesterolemia

BackgroundEpigenetics can contribute to lipid disorders in obesity. The DNA methylation pattern can be the cause or consequence of high blood lipids. The aim of the study was to investigate the DNA methylation profile in peripheral leukocytes associated with elevated LDL-cholesterol level in overweight and obese individuals.MethodsTo identify the differentially methylated genes, genome-wide DNA methylation microarray analysis was performed in leukocytes of obese individuals with high LDL-cholesterol (LDL-CH, ≥ 3.4 mmol/L) versus control obese individuals with LDL-CH, < 3.4 mmol/L. Biochemical tests such as serum glucose, total cholesterol, HDL cholesterol, triglycerides, insulin, leptin, adiponectin, FGF19, FGF21, GIP and total plasma fatty acids content have been determined. Oral glucose and lipid tolerance tests were also performed. Human DNA Methylation Microarray (from Agilent Technologies) containing 27,627 probes for CpG islands was used for screening of DNA methylation status in 10 selected samples. Unpaired t-test and Mann–Whitney U-test were used for biochemical and anthropometric parameters statistics. For microarrays analysis, fold of change was calculated comparing hypercholesterolemic vs control group. The q-value threshold was calculated using moderated Student’s t-test followed by Benjamini–Hochberg multiple test correction FDR.ResultsIn this preliminary study we identified 190 lipid related CpG loci differentially methylated in hypercholesterolemic versus control individuals. Analysis of DNA methylation profiles revealed several loci engaged in plasma lipoprotein formation and metabolism, cholesterol efflux and reverse transport, triglycerides degradation and fatty acids transport and β-oxidation. Hypermethylation of CpG loci located in promoters of genes regulating cholesterol metabolism: PCSK9, LRP1, ABCG1, ANGPTL4, SREBF1 and NR1H2 in hypercholesterolemic patients has been found. Novel epigenetically regulated CpG sites include ABCG4, ANGPTL4, AP2A2, AP2M1, AP2S1, CLTC, FGF19, FGF1R, HDLBP, LIPA, LMF1, LRP5, LSR, NR1H2 and ZDHHC8 genes.ConclusionsOur results indicate that obese individuals with hypercholesterolemia present specific DNA methylation profile in genes related to lipids transport and metabolism. Detailed knowledge of epigenetic regulation of genes, important for lipid disorders in obesity, underlies the possibility to influence target genes by changing diet and lifestyle, as DNA methylation is reversible and depends on environmental factors. These findings give rise for further studies on factors that targets methylation of revealed genes.

Outlier-insensitive Bayesian inference for linear inverse problems (OutIBI) with applications to space geodetic data

SUMMARYInverse problems play a central role in data analysis across the fields of science. Many techniques and algorithms provide parameter estimation including the best-fitting model and the parameters statistics. Here, we concern ourselves with the robustness of parameter estimation under constraints, with the focus on assimilation of noisy data with potential outliers, a situation all too familiar in Earth science, particularly in analysis of remote-sensing data. We assume a linear, or linearized, forward model relating the model parameters to multiple data sets with a priori unknown uncertainties that are left to be characterized. This is relevant for global navigation satellite system and synthetic aperture radar data that involve intricate processing for which uncertainty estimation is not available. The model is constrained by additional equalities and inequalities resulting from the physics of the problem, but the weights of equalities are unknown. We formulate the problem from a Bayesian perspective with non-informative priors. The posterior distribution of the model parameters, weights and outliers conditioned on the observations are then inferred via Gibbs sampling. We demonstrate the practical utility of the method based on a set of challenging inverse problems with both synthetic and real space-geodetic data associated with earthquakes and nuclear explosions. We provide the associated computer codes and expect the approach to be of practical interest for a wide range of applications.

Identification of potential carcinogenic and chemopreventive effects of prescription drugs: a protocol for a Norwegian registry-based study

IntroductionSurveillance of unintended effects of pharmaceuticals (pharmacovigilance or drug safety) is crucial, as knowledge of rare or late side effects is limited at the time of the introduction of new...

Hot Pixel Behavior as Pixel Size Reduces to 1 micron

Research has shown that in digital imaging sensors "Hot Pixels" defects accumulate as the camera ages over time. We have previously developed an empirical formula that projects hot pixel defects growth rates in terms of defect density (defects/year/mm2). We found that hot pixel densities grow via a power law, with the inverse of the pixel size raised to the power of about 3, and the ISO (gain) raised to the power of about 0.5. This paper experimentally explores the defect rates as pixels approach the 2 to 1 micron size. An analysis of the hot pixel parameters statistics shows that stuck high pixels that develop in the field are actually stuck hot pixels. In addition, this analysis indicates that as pixels shrink, not only does the defect rate increase, but it produces both a larger number of weak hot pixels at all ISOs, and a larger number of strong hot pixels at higher ISOs.

Stability Analysis of an Earth Slope Based on Taylor Series Method

Due to the complicated theory of reliability analysis method and the high requirement of parameters statistics and model calculation, most reliability analysis methods are not conductive to engineering application. In order to solve this problem, a simplified method, can be used in slope stability analysis. The technique is based on factor of safety method. The procedure of applying this method in slope stability analysis is studied. The methods of calculating parameters standard deviation are summarized. Engineering application shows that Taylor series method is feasible and practical in slope stability analysis and it provides a new method for slope reliability analysis.

Computer generation and quantitative morphometric analysis of virtual neurons.

An important goal in computational neuroanatomy is the complete and accurate simulation of neuronal morphology. We are developing computational tools to model three-dimensional dendritic structures based on sets of stochastic rules. This paper reports an extensive, quantitative anatomical characterization of simulated motoneurons and Purkinje cells. We used several local and global algorithms implemented in the L-Neuron and ArborVitae programs to generate sets of virtual neurons. Parameters statistics for all algorithms were measured from experimental data, thus providing a compact and consistent description of these morphological classes. We compared the emergent anatomical features of each group of virtual neurons with those of the experimental database in order to gain insights on the plausibility of the model assumptions, potential improvements to the algorithms, and non-trivial relations among morphological parameters. Algorithms mainly based on local constraints (e.g., branch diameter) were successful in reproducing many morphological properties of both motoneurons and Purkinje cells (e.g. total length, asymmetry, number of bifurcations). The addition of global constraints (e.g., trophic factors) improved the angle-dependent emergent characteristics (average Euclidean distance from the soma to the dendritic terminations, dendritic spread). Virtual neurons systematically displayed greater anatomical variability than real cells, suggesting the need for additional constraints in the models. For several emergent anatomical properties, a specific algorithm reproduced the experimental statistics better than the others did. However, relative performances were often reversed for different anatomical properties and/or morphological classes. Thus, combining the strengths of alternative generative models could lead to comprehensive algorithms for the complete and accurate simulation of dendritic morphology.

Ambulatory Low Back Load Exposure Estimation

An ambulatory monitor for physical low back load exposure should be non-interfering, unrestricted in application space or duration, practical in use and interpretation, sufficiently accurate and reliable, sensitive to load handling and load coping and offer both detailed load parameters statistics and global information on tasks and behavior. A method is introduced that tries to meet these demands applying 3 technological innovations: miniature inertial movement sensing, artificial neural network based automatic calibration of the dynamic surface EMG–moment relationship and miniature RF links for wireless video-synchronization (AMBER). The currently implemented ambulatory method assesses load exposure through absolute 3D trunk kinematics data, muscle activation patterns, net moment data at spinal level L5/S1, compressive forces in symmetric loading situations and synchronized video. Principles, validation and recent field applications of the method are presented.

Detection for a statistically known, time-varying dispersive channel

Detection for the statistically known channel (SKC) is aimed at obtaining good performance in situations where our statistical knowledge of a time-varying channel is good, and where other equalization/detection schemes are either too complex to implement, or their performance is limited due to the rapidity of channel fading, or where we are simply unable to perform channel estimation. By using a statistical characterization of the channel, we develop a new detector that performs maximum-likelihood sequence estimation (MLSE) (given the channel model) on blocks of N symbols. Both symbol-spaced and fractionally spaced samples are used, to obtain two different detectors, that are generalizations of those devised for optimal block schemes on nondispersive channels. The detector that uses fractionally spaced samples is shown to outperform the detector that uses symbol-spaced samples. The performance of both appears to approach that of the corresponding known channel (KC) detector as the block length increases. We also numerically evaluate the SKC detector performance under conditions where the channel parameters (statistics) are incorrectly estimated, and show that the fractionally spaced detector is fairly robust to modeling errors. Finally, we devise a sliding block algorithm, for use when transmitting more than N symbols.

ON EXTERNAL ANCILLARITY1

summaryStatistics distributed free of a certain parameter (called ancillary for the parameter) are of considerable use when sufficient estimation is not possible (Fisher (1925)). When the model involves, in addition to the parameters of interest, parameters not of direct interest (nuisance parameters) statistics which are distributed free of the latter may be of considerable use also. This requires a study of ancillary statistics which are not functions of the minimal sufficient statistic (MSS). In particular we study the general ancillary given in Williams (1982) and show that it has certain desirable properties including uniqueness under appropriate restrictions. Finally some non‐trivial applications are given.

On the noise operator approach to quantized dissipative systems

Invoking complex classical coordinates and momenta a consistent Hamiltonian theory suitable for the quantization of dissipative systems has been developed previously. In another paper this formalism has been illustrated on the basis of a simple order parameter equation by means of density operator techniques. This quite naturally calls for a comparison with quantum noise operator techniques. The present paper is an attempt to satisfy these demands. Extensive use will be made of operator ordering techniques and quasi-classical Fokker-Planck equations. As before, a certain incompleteness in the extractable information is clearly exhibited. It will be observed that the two techniques do not produce similar results in a general dynamical state as a consequence of dissipation. However, in the stationary state and within certain approximations both methods do lead to identical conclusions for the order parameters statistics. It will be argued that within the present context in general noise operator techniques are to be favoured.