Evaluating the frequency of carbapenem and aminoglycoside resistance genes among clinical isolates of Acinetobacter baumannii from Ahvaz, south-west Iran.

Acinetobacter baumannii is one of the most important opportunistic challenging pathogens as a result of its ability to acquire resistance to broad range of antibiotics and cause a variety of severe nosocomial infections. We investigated the frequency of the aminoglycoside-modifying enzymes (AMEs) and oxacillinase genes among clinical isolates of A. baumannii collected from hospitalized patients in Imam Khomeini Hospital, Ahvaz city, Iran. This prospective cross-sectional study was performed on 80 clinical isolates of A. baumannii collected from patients referred to Imam Khomeini Hospital in Ahvaz, Iran. Initial identification of isolates as A. baumannii was performed using conventional bacteriologic tests, and final confirmation was carried out by PCR of bla OXA-51-like gene and multiplex PCR of gyrB locus. MICs of different classes of antibiotics against these strains was measured by using VITEK 2 system. After extraction of genomic DNA, two groups of multidrug-resistant A. baumannii genes including AME (aadA1, aadB, aphA6 and aacC1) and oxacillinases (bla OXA-23-like, bla OXA-24-like, bla OXA-51-like, bla OXA-58-like and bla OXA-143-like) were detected. According to antibiotic susceptibility testing, among 80 A. baumannii strains, 75 isolates (91.25%) were multidrug resistant. The results showed that colistin and tigecycline, with respective sensitivity rates of 97.5% (78/80) and 56.25% (45/80), had the highest effects. The presence of bla OXA-51-like and gyrB genes was confirmed in all strains. Furthermore, bla OXA-23-like and bla OXA-24-like genes were found in 68.75% (55/80) and 20% (16/80) of isolates respectively, while no isolate harbored the bla OXA-143-like gene. The frequency of genes encoding the AMEs including aadA1, aacC1, aphA6 and aadB were 11.25% (9/80), 16.25% (13/80), 22.5% (18/80) and 30% (24/80) respectively. Our findings indicate that the presence of the aadB and aphA6 is correlated with high resistance against amikacin and gentamicin. We found a very high resistance rate against most of the antimicrobial agents usually prescribed for severe infections caused by A. baumannii. Therefore, because of rapid emergence of resistance even for colistin or tigecycline, monotherapy should be avoided. These results show the importance of providing antibiotics correctly in intensive care units and following antibiotic stewardship protocols as the only effective strategies to attempt to control antibiotic resistance in healthcare settings.

The polymorphism of XRCC1 Arg399Gln (rs25487) and male infertility risk: a meta-analysis of 1,407 cases and 974 control studies.

X-ray repair cross-complementing group 1 (XRCC1) is a scaffold protein and a key element in DNA base excision repair process. Although, the role of XRCC1 polymorphisms in male infertility has been studied broadly, it is still a matter of debate. Hence, in order to shed light on the problem, we performed a meta-analysis to evaluate the overall effect of XRCC1 polymorphisms in male infertility risk. Databases, Web of Science, PubMed, Scopus, and Google Scholar were searched until September 15, 2018. Afterwards, the genotypes' distribution, genotyping methods, and ethnicity groups were extracted, and overall analyses were conducted. A total number of five researches on 1,407 subjects and 974 controls were found to meet our criteria in this meta-analysis. The XRCC1 Arg399Gln (rs25487) polymorphism was analyzed. This is the first meta-analysis to investigate the association of XRCC1 polymorphisms (codon 399) and male infertility risk. Our results indicated that the XRCC1 Arg399Gln polymorphism was not associated with male infertility risk in the total studied populations (Tab. 2, Fig. 3, Ref. 26). Keywords: meta-analysis; male infertility; polymorphism; XRCC1 Arg399Gln.

Cross-talk filtering in four dye fluorescence-based DNA sequencing.

We have addressed two important issues of nonlinear cross-talk and baseline adjustment in DNA data processing. An important aspect in the processing of the four-dye fluorescence-based data is the cross-talk filtering. Typically, a matrix M, which is a function of the fluorophores and the fluorescence detection system, is used in the multicomponent analysis. In this deconvolution process the matrix is applied directly to the raw signal, on a linear cross-talk assumption. This necessitates the signal to be aligned to the baseline before the filter is applied. The various techniques used for aligning the raw data have the negative effect of adding distortion to the signal. An algorithm for cross-talk removal is presented in this paper. The algorithm uses the intensity difference of the signal rather than the actual value itself, thus making the cross-talk removal possible before the base line adjustment. In addition, a supplementary filtering step is proposed in order to account for the nonlinear nature of the cross-talk. This second step is based on a matrix T that accounts for the correlation of each of the signals with the other three. The overall result is a more precise presentation of the DNA data and less information loss through filtering.

Mouse chromosome classification by radial basis function network with fast orthogonal search.

This paper provides the results of our study on automatic classification of mouse chromosomes. A radial basis function neural network was compared with a multi-layer perceptron and a probabilistic neural network. The networks were trained and tested with 3723 chromosomes presented to each network as 30-point banding profiles. The radial basis function classifier trained with the fast orthogonal search learning rule provided the best unconstrained classification error rate of 12.7% which was obtained with a training set of 2250 chromosomes.

Adaptive detection of small sinusoidal signals in non-Gaussian noise using an RBF neural network.

This paper addresses the application of locally optimum (LO) signal detection techniques to environments in which the noise density is not known a priori. For small signal levels, the LO detection rule is shown to involve a nonlinearity which depends on the noise density. The estimation of the noise density is a major part of the computational burden of LO detection rules. In this paper, adaptive estimation of the noise density is implemented using a radial basis function neural network. Unlike existing algorithms, the present technique places few assumptions on the properties of the noise, and performs well under a wide variety of circumstances. Experimental results are shown which illustrate the system performance as a variety of noise densities are encountered.

Classification of chromosomes using a probabilistic neural network.

This paper describes the application of a probabilistic neural network (PNN) to the classification of normal human chromosomes. The inputs to the network are 30 different features extracted from each chromosome in digitized images of metaphase spreads. The output is 1 of 24 different classes of chromosomes (the 22 autosomes plus the sex chromosomes X and Y). An updating procedure was implemented to take advantage of the fact that in a normal somatic cell only two chromosomes can be assigned to each class. The network has been tested using the Copenhagen, Edinburgh, and Philadelphia databases of digitized images of human chromosomes. The recognition rates achieved in this study are superior to those reported using either the maximum likelihood or back propagation neural network techniques.