Tooth extraction without discontinuation of oral antithrombotic treatment: A prospective study.

OBJECTIVE: To identify which variable, among those related to surgeries, to patients, or to antithrombotic treatments, could be considered as a bleeding indicator, and to analyze effectiveness of the local hemostatic protocols used, incidence of bleeding and healing index, depending on the number of extracted teeth, and patient antithrombotic treatment. METHODS: Patients who underwent tooth extractions without interruption or reduction of antithrombotic treatment were prospectively followed. The exact two-tailed Fisher test was used to investigate the relationship between presence/absence of bleeding and type of hemostatic material. The effect of variables on the probability of bleeding and healing index was assessed by means of a multivariate logistic regression. RESULTS: Two hundred and fifty-four procedures were analyzed. The incidence of bleeding was 15.75%. Severe bleeding occurred in only 6 patients (2.34%). The number of involved dental quadrants and pre-surgical antibiotic treatments were found to be positively related with bleeding. The use of vasoconstrictors during surgery resulted in a reduction of healing index scores. CONCLUSIONS: Tooth extractions in patients on antithrombotic treatment were found to be free from significant bleeding although the involvement of more than 1 quadrant in the same procedure should be avoided.

Changes of Conformation in Albumin with Temperature by Molecular Dynamics Simulations.

This work presents the analysis of the conformation of albumin in the temperature range of 300 K - 312 K , i.e., in the physiological range. Using molecular dynamics simulations, we calculate values of the backbone and dihedral angles for this molecule. We analyze the global dynamic properties of albumin treated as a chain. In this range of temperature, we study parameters of the molecule and the conformational entropy derived from two angles that reflect global dynamics in the conformational space. A thorough rationalization, based on the scaling theory, for the subdiffusion Flory-De Gennes type exponent of 0 . 4 unfolds in conjunction with picking up the most appreciable fluctuations of the corresponding statistical-test parameter. These fluctuations coincide adequately with entropy fluctuations, namely the oscillations out of thermodynamic equilibrium. Using Fisher's test, we investigate the conformational entropy over time and suggest its oscillatory properties in the corresponding time domain. Using the Kruscal-Wallis test, we also analyze differences between the root mean square displacement of a molecule at various temperatures. Here we show that its values in the range of 306 K - 309 K are different than in another temperature. Using the Kullback-Leibler theory, we investigate differences between the distribution of the root mean square displacement for each temperature and time window.

Genome-wide association study reveals the locus responsible for microtia in Valle del Belice sheep breed.

Microtia is a congenital deformity of the outer ear with phenotypes varying from a small auricle to total absence (anotia). The genetic basis is still poorly understood, and very few studies have been performed in sheep. Valle del Belice sheep is a breed showing microtia. The aim of this study was to identify the potential genomic regions involved in microtia in sheep. A total of 40 individuals, 20 with microtia and 20 normal, were genotyped with the Illumina OvineSNP50 BeadChip. The comparison among the results from a genome-wide association study, Fisher's exact test and FST analysis revealed a single strong association signal: rs419889303 on chromosome 1, located within intron 3 of the CLRN1 gene. Our study suggests for the first time that this novel candidate gene is responsible for microtia in sheep. Additional analysis based on the sequencing would help confirm our findings and allow for the proposal of a precise genetic basis for microtia in sheep.

Modeling of the Efficiency of the Centrifugal Conical Disk Dispenser of Bulk Materials.

Centrifugal disk dispensers are widely used in various tasks of dosing bulk, dispersed materials. The design of the disk depends on the physical and mechanical characteristics of the dosing medium. The work discusses the development of an analytical model of the movement of a material particle along a conical centrifugal disk depending on the kinematic characteristics of the dosing process and the characteristics of the dosing material, as well as experimental confirmation of the theoretical model, which is relevant for the calculation and design of working elements of this type. The obtained system of differential equations is solved using the Runge-Kutta numerical method. Experimental studies were carried out using the method of a planned factorial experiment. The experiment was conducted for three factors at three levels. The feedback criterion was the performance of a centrifugal conical disk dispenser for bulk materials. The disk cone angle was set at 10, 20, and 30°. The disk diameter was 130, 150, and 170 mm, the gap between the disk and the edge of the hopper neck was 6, 8, and 10 mm, and the rotational speed of the conical disk was 0.65, 1.02, and 1.39 rad/s. The dispensing rate of the dispenser ranged from 15 to 770 g/s, depending on the values of the experimental factors. For use in the regression equation of the natural values of the factors, a method of transforming the terms of the equation from coded values to natural ones is provided. The obtained experimental correlation dependencies were checked for reproducibility with Cochrane's test, and the adequacy of the model was checked using Fisher's test. The significance of the coefficients in the correlation equation was evaluated using the Student's t-test. The difference between the experimental data and the results of the theoretical modeling does not exceed 5%. The obtained system of differential equations makes it possible to model the radial velocity of the ascent of bulk material from the conical rotating disk depending on the rotation frequency, disk diameter, and the height of the annular gap between the discharge throat of the hopper and the conical disk. The analytical model enables the modeling of the productivity of the conical dispenser for bulk materials for arbitrary parameters of rotation frequency, disk diameter, and the size of the annular gap between the discharge throat of the hopper and the conical disk.

Gene differential co-expression analysis of male infertility patients based on statistical and machine learning methods.

Male infertility has always been one of the important factors affecting the infertility of couples of gestational age. The reasons that affect male infertility includes living habits, hereditary factors, etc. Identifying the genetic causes of male infertility can help us understand the biology of male infertility, as well as the diagnosis of genetic testing and the determination of clinical treatment options. While current research has made significant progress in the genes that cause sperm defects in men, genetic studies of sperm content defects are still lacking. This article is based on a dataset of gene expression data on the X chromosome in patients with azoospermia, mild and severe oligospermia. Due to the difference in the degree of disease between patients and the possible difference in genetic causes, common classical clustering methods such as k-means, hierarchical clustering, etc. cannot effectively identify samples (realize simultaneous clustering of samples and features). In this paper, we use machine learning and various statistical methods such as hypergeometric distribution, Gibbs sampling, Fisher test, etc. and genes the interaction network for cluster analysis of gene expression data of male infertility patients has certain advantages compared with existing methods. The cluster results were identified by differential co-expression analysis of gene expression data in male infertility patients, and the model recognition clusters were analyzed by multiple gene enrichment methods, showing different degrees of enrichment in various enzyme activities, cancer, virus-related, ATP and ADP production, and other pathways. At the same time, as this paper is an unsupervised analysis of genetic factors of male infertility patients, we constructed a simulated data set, in which the clustering results have been determined, which can be used to measure the effect of discriminant model recognition. Through comparison, it finds that the proposed model has a better identification effect.

Quantitative differences detected in the histology of galls induced by the same aphid species in different varieties of the same host.

Plant galls are abnormal growths caused by an inducer that determines their morphology and anatomy. We qualitatively and quantitatively compared the histological anatomy of five aphid species (Paracletus cimiciformis, Forda marginata, Forda formicaria, Baizongia pistaciae and Geoica wertheimae) that induce galls in Pistacia terebinthus shrubs growing in Israel. We also quantitatively compared these galls to those that the aphids create on the same host in Spain. Histological study was conducted following methods described previously by the authors. Quantitative differences among the galls were found in five of 12 common anatomical traits: gall thickness, stomatal number in the epidermis-air, size of vascular bundles, distance of phloem ducts from the lumen and number of intraphloematic schizogenous ducts. Other structures were particular to one or some species: number of cracks in the epidermis-lumen, a sclereid layer, trichomes and microcrystal inclusions. Fisher's tests of combined probabilities showed that the galls induced in Israel were statistically different from those in Spain. In particular, the number of intraphloematic schizogenous ducts was higher in the galls induced in P. terebinthus in Israel. Such differences were also found in other traits related to defence of the gall inhabitant. In conclusion, while the gall shape and size are determined mainly by the cecidogenic insect, it seems that the host plant also plays an important role in determining the number/size of quantitative traits, in this case mainly protective structures.

Statistical methods for the analysis of clinical trials data containing many zeros: An application in vaccine development.

In recent years, many vaccines have been developed for the prevention of a variety of diseases. Many of these vaccines, like the one for herpes zoster, are supposed to act in a multilevel way. Ideally, they completely prevent expression of the virus, but failing that they help to reduce the severity of the disease. A simple approach to analyze these data is the so-called burden-of-illness test. The method assigns a score, say W, equal to 0 for the uninfected and a post-infection outcome X > 0 for the infected individuals. One of the limitations of this test is the potential low power when the vaccine efficacy is close to 0. To overcome this limitation, we propose a Fisher adjusted test where we combine a statistic for infection with a statistic for post-infection outcome adjusted for selection bias. The advantages and disadvantages of different methods proposed in the literature are discussed. We compared the methods via simulations in herpes zoster, HIV, and malaria vaccine trial settings. In addition, we applied these methods to published data on HIV vaccine. The paper ends with some recommendations and conclusions.

Artificial Neural Networks approach to pharmacokinetic model selection in DCE-MRI studies.

PURPOSE: In pharmacokinetic analysis of Dynamic Contrast Enhanced MRI data, a descriptive physiological model should be selected properly out of a set of candidate models. Classical techniques suggested for this purpose suffer from issues like computation time and general fitting problems. This article proposes an approach based on Artificial Neural Networks (ANNs) for solving these problems. METHODS: A set of three physiologically and mathematically nested models generated from the Tofts model were assumed: Model I, II and III. These models cover three possible tissue types from normal to malignant. Using 21 experimental arterial input functions and 12 levels of noise, a set of 27,216 time traces were generated. ANN was validated and optimized by the k-fold cross validation technique. An experimental dataset of 20 patients with glioblastoma was applied to ANN and the results were compared to outputs of F-test using Dice index. RESULTS: Optimum neuronal architecture ([6:7:1]) and number of training epochs (50) of the ANN were determined. ANN correctly classified more than 99% of the dataset. Confusion matrices for both ANN and F-test results showed the superior performance of the ANN classifier. The average Dice index (over 20 patients) indicated a 75% similarity between model selection maps of ANN and F-test. CONCLUSIONS: ANN improves the model selection process by removing the need for time-consuming, problematic fitting algorithms; as well as the need for hypothesis testing.

Fractal analysis of dendrite morphology using modified box-counting method.

The box-counting dimension of a non-stellate neuron changes continuously with its rotation. During preprocessing for box-counting, non-stellate neurons should be arranged so that the major diameters of their dendrite fields are parallel. A non-stellate neuronal picture should have the smallest fractal dimension when the angle between the horizontal axis and its major diameter is about 45°. The box-counting method does not consider the position of a picture on the computer screen. Therefore a dispersion of the box dimension values of a neuronal sample is rather large and their mean value is with larger variance. Modified box-counting method partly diminishes these findings. To improve a dependence of neuronal rotation on the box-counting dimension of non-stellate neurons, prior to applying box-counting method, non-stellate neurons should be arranged so that the major diameters of their dendrite fields are parallel.