Multi-locus sequence type analysis of Shigellas pp. Isolates from Tehran, Iran

Background and Objectives: Strains of Shigella spp. can cause shigellosis, or bacillary dysentery. That is a public health problem worldwide. The aim of this study was to describe the population structure and genetic relatedness of multidrug resistant S. sonnei and S. flexneri isolated during a one year period from children with diarrhea in Tehran, Iran. Materials and Methods: A total of 70 Shigella spp. were detected during the study period. Twenty MDR isolates of Shigella spp. were randomly selected and used in this study. Bacterial identification was performed by conventional biochemical and serological and confirmed by molecular method. After antimicrobial susceptibility testing, we used Multilocus sequence typing (MLST) for subtyping isolates. Results: We found 14 Shigella sonnei and 6 Shigella flexneri isolates. Results of MLST showed five sequence types (ST) (145, 152, 241, 245, 1502) and BURST analysis revealed the largest number of single locus variant (SLV) and highest frequency (FREQ) for ST152. ST 152 with nine members was predicted as the founder by BURST. Frequency for ST 1502 and ST 245 was four isolates and the least frequency was seen for ST 241 and 145 with one and two members, respectively. ST 145 and ST 245 were described as singletons in BURST. All isolates with ST145 and ST245 were identified as Shigella flexneri. Conclusion: Annual Multi locus sequence typing of MDR Shigella would help us in better understanding of dominant species and comparing our results with the same studies in other countries especially our neighbor countries in source tracking purposes. © Tehran University of Medical Science. All rights reserved

Phenotypic and molecular characterization of plasmid mediated AmpC among clinical isolates of Klebsiella pneumoniae isolated from different hospitals in Tehran

Introduction: Klebsiella pneumoniae is one of the main opportunistic pathogens which can cause different types of infections. Production of beta-lactamases like AmpC and ESBL mostly lead to beta-lactam resistance in these Gram-Negative bacteria. The aim of this study was the detection of AmpC-producing K. pneumoniae in clinical isolates. Materials and Methods: Three hundred and three isolates of K. pneumoniae were identified. Double disc method including cefoxitin with cefepime and using boronic acid with cloxacillin were performed as two phenotypic methods for detection of AmpC. Amplification of AmpC gene was performed by PCR. Results: Eight and three isolates showed positive results in double disc method and by using boronic acid with cloxacillin, respectively. Five isolates had specific band for AmpC gene after electrophoresis. Conclusion: Our results were indicated the low prevalence of AmpC-producer-K. pnemoniae in Iran. On the other hand these two tested phenotypic methods showed low sensitivity for detection of AmpC. © 2015 Journal of Clinical and Diagnostic Research. All Rights Reserved

Effects of Stone-Wales Defect Position in Graphene Nanoribbon Field-Effect Transistor

In this paper, the current-voltage characteristics of a double-gated monolayer armchair graphene nanoribbon field-effect transistor (DG-AGNRFET) is investigated by introducing a Stone-Wales (SW) defect. After changing positions of the defect in width and length of the channel, it is found that the SW defect decreases off current and leads to the further reduction of the off current as the defect moves to the edge. However, this defect has not shown a notable impact on the on current. The results have confirmed the possibility of controlling the electron transport of the DG-AGNRFET by defect engineering can be useful to extend the applications of graphene nanoribbon-based devices. The device has been simulated based on the self-consistent solution of a 3D Poisson-Schrödinger equation using non-equilibrium Green's function (NEGF) formalism

Molecular epidemiology and drug susceptibility of Pseudomonas aeruginosa strains isolated from burn patients

Background: Pseudomonas aeruginosa is 1 of the major agents of nosocomial infections in burn centers. Our objectives were to determine the genetic diversity of P. aeruginosa isolated from burn patients. Methods: One hundred thirty-one P. aeruginosa isolates were collected from the burn center of Shahid Motahhari Hospital in Tehran. Phenotypic screening for drug susceptibility was performed by disk diffusion method according to Clinical Laboratory Standards Institute guidelines, and genetic diversity of all isolates was determined by the pulsed-field gel electrophoresis (PFGE) technique. Results: Antimicrobial susceptibility testing showed that the majority of P. aeruginosa strains were resistant to ceftizoxime (87) and aztreonam (80.2). Pulsed-field gel electrophoresis revealed 11 profiles in which environmental strains were included in PFGE1 and PFGE7 patterns. The major PFGE profile was PFGE1 containing 18 (42.9) MDR isolates and including an environmental MDR bacterium. Conclusions: Our findings highlighted that further attention needs to be focused on the disinfection of this burn unit

The occurrence of extended-spectrum β-lactamase producing Shigella spp. in Tehran, Iran

Background and Objectives: The emergence of extended-spectrum β-lactamase (ESBL)-producing Shigella spp. is of increasing clinical concern specially in children worldwide. The aim of this study was to investigate the occurrence of extended-spectrum β-lactamase producing Shigella spp. in Tehran, Iran. Materials and Methods: The study included all Shigella isolates recovered from pediatric patients aged less than 12 years admitted to a major pediatric hospital in Tehran, Iran, from 2008 to 2010. Bacterial identification, antimicrobial susceptibility testing, extended spectrum β-lactamases (ESBLs) screening and confirmatory tests were performed according to the standard guidelines. Conjugal transfer experiments and plasmid analysis were also carried out. Polymerase chain reaction and sequencing were used to identify the genetic determinants responsible for ESBL production. Results: Four out of 55 Shigella isolates, including three S. sonnei and one S. flexneri, showed an ESBL-positive phenotype. Plasmid transfer of the ESBL phenotype was successful for the S. flexneri isolate only. By PCR and sequencing, one S. sonnei isolate tested positive for the CMY-59 gene, while the other two S. sonnei and the S. flexneri isolates tested positive for the blaTEM-1 and blaCTX-M-15 genes. Conclusion: We found the prevalence of ESBL producing Shigella isolates was higher than detection rates observed in many other countries. Our finding raise concerns about the dissemination of ESBL among the strains of endemic S. sonnei throughout the country, because this species is now the most frequently isolated Shigella species in Iran and shigellosis by such strains in the community can pose a significant threat to patients and presents a challenge for disease management

Determination of characteristics of erythromycin resistant Streptococcus pneumoniae with preferred PCV usage in Iran

Amongst 100 Streptococcus pneumoniae isolated from clinical cases and nasopharynx of healthy individuals, 60 erythromycin resistant strains were isolated and characterized using MLST, PFGE, transposon analysis and Quellung reaction. Most of the S. pneumoniae erythromycin resistant (80) were found to be attributable to the ermB-edncoded ribosome methylase activity which differs from the dominant mechanism of macrolide resistance seen in North America. The most predominant transposons were; Tn 1545/6003(27), Tn6002 (22), Tn2009 (20), Tn2010 (17). Number of the clinical isolates carrying Tn2010 was more significant than the normal flora. The serotypes found were; 14 (33), 3 (22), 23F (15), 19F (15), 19A (7), 6A (3), 9V (3) and 6B (2). The most prevalent serotypes among the clinical (n = 28) and normal flora (n = 32) isolates were serotypes 14 (46) and 3 (31), respectively. The most prevalent vaccine serotypes amongst the clinical isolates and the healthy individuals were pneumococcal conjugate vaccines (PCV) 13 and PCV10, respectively. PFGE revealed 34 pulsotypes with 9 common and 25 single types. Significant number of the normal isolates belonged to CT5 and CT6. On the other hand, significant number of clinical isolates belonged to CT8 as compared to the normal flora isolates. MLST showed 2 dominant sequence types. ST3130 (23) and ST180 (22) were the most predominant sequence types in the clinical and normal isolates, respectively. There was no significant difference in other sequence types between clinical and normal flora isolates. Three polyclonal complexes including Sweden15A -25, Spain23F-1 and Spain9V-3 constituted 58 of the isolates. Our results suggest that the genetic diversity and transposon distribution were high among S. pneumoniae, particularly in the isolates containing erm(B) and double antibiotic resistant genes (erm/mef). The results presented here could influence the change in the current vaccination practices in Iran which currently calls for vaccination with PCV7 or PCV10. � 2016 Talebi et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Antibiotic susceptibility pattern and virulence genes in Enterococcus spp. Isolated from clinical samples of Milad hospital of Tehran, Iran

Background: Enterococcus spp. are part of the normal flora of humans and animals. The nosocomial pathogenicity of Enterococcus spp. has emerged in recent years and has caused great concern due to developing of resistance to many antimicrobial agents. Objectives: The current study aimed to determine the resistance pattern and the type of virulence genes in Enterococcus spp. isolated from Milad hospital of Tehran, Iran. Materials and Methods: The current observational study was conducted from Apr 2014 to Feb 2015 on a total of 149 Enterococcus species isolated from Milad hospital in Tehran, Iran. The antibiotic susceptibility pattern of the bacteria was determined by the disc diffusion method for eight antibiotics. Minimum inhibitory concentration (MIC) of vancomycin was also done using agar-dilution assay by clinical and laboratory standards institute (CLSI) recommendations. The sodA, esp, cyl, ace and gelE genes were detected by polymerase chain reaction (PCR) assay. Results: About 37.5, 73, 86.6, 35.8, 69, 60.8, 45 and 79 of the isolates were resistant to vancomycin, tetracycline, gentamicin, chloramphenicol, ciprofloxacin, penicillin, ampicillin and erythromycin, respectively. MIC on 38 of the isolates was � 256 μg/mL. Although, the prevalence of vancomycin-resistant Enterococcus (VRE) strains belonged to two species, E. faecium showed high resistance to a broad range of antibiotics. In total, 94 isolates were positive for esp, and 59, 48 and 3 isolates were positive for ace, cylA and gelE, Respectively. Conclusions: The results of the current study designate the important role of medical samples as reservoirs of resistance inducing elements. Early detection of VRE with their virulence trait will help to prevent the spread of vancomycin resistant Enterococcus species. Supervision for antibiotic usage in hospitals, especially for last option antibiotics, can prevent the spread of resistant isolates and losing all treatment options in the future. © 2016, Infectious Diseases and Tropical Medicine Research Center

Contribution of Case Reports to Brain Metastases Research: Systematic Review and Analysis of Pattern of Citation

Research activity related to different aspects of prevention, prediction, diagnosis and treatment of brain metastases has increased during recent years. One of the major databases (Scopus) contains 942 scientific articles that were published during the 5-year time period 2006–2010. Of these, 195 (21%) reported on single patient cases and 12 (1%) were reports of 2 cases. Little is known about their influence on advancement of the field or scientific merits. Do brain metastases case reports attract attention and provide stimuli for further research or do they go largely unrecognized? Different measures of impact, visibility and quality of published research are available, each with its own pros and cons. For the present evaluation, article citation rate was chosen. The median number of citations overall and stratified by year of publication was 0, except for the year 2006 when it was 2. As compared to other articles, case reports remained more often without citation (p<0.05 except for 2006 data). All case reports with 10 or more citations (n = 6) reported on newly introduced anticancer drugs, which commonly are prescribed to treat extracranial metastases, and the responses observed in single patients with brain metastases. Average annual numbers of citations were also calculated. The articles with most citations per year were the same six case reports mentioned above (the only ones that obtained more than 2.0 citations per year). Citations appeared to gradually increase during the first two years after publication but remained on a generally low or modest level. It cannot be excluded that case reports without citation provide interesting information to some clinicians or researchers. Apparently, case reports describing unexpected therapeutic success gain more attention, at least in terms of citation, than others

Mathematical properties of weighted impact factors based on measures of prestige of the citing journals

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-015-1741-0An abstract construction for general weighted impact factors is introduced. We show that the classical weighted impact factors are particular cases of our model, but it can also be used for defining new impact measuring tools for other sources of information as repositories of datasets providing the mathematical support for a new family of altmet- rics. Our aim is to show the main mathematical properties of this class of impact measuring tools, that hold as consequences of their mathematical structure and does not depend on the definition of any given index nowadays in use. In order to show the power of our approach in a well-known setting, we apply our construction to analyze the stability of the ordering induced in a list of journals by the 2-year impact factor (IF2). We study the change of this ordering when the criterium to define it is given by the numerical value of a new weighted impact factor, in which IF2 is used for defining the weights. We prove that, if we assume that the weight associated to a citing journal increases with its IF2, then the ordering given in the list by the new weighted impact factor coincides with the order defined by the IF2. We give a quantitative bound for the errors committed. We also show two examples of weighted impact factors defined by weights associated to the prestige of the citing journal for the fields of MATHEMATICS and MEDICINE, GENERAL AND INTERNAL, checking if they satisfy the increasing behavior mentioned above.Ferrer Sapena, A.; Sánchez Pérez, EA.; González, LM.; Peset Mancebo, MF.; Aleixandre Benavent, R. (2015). Mathematical properties of weighted impact factors based on measures of prestige of the citing journals. Scientometrics. 105(3):2089-2108. https://doi.org/10.1007/s11192-015-1741-0S208921081053Ahlgren, P., & Waltman, L. (2014). The correlation between citation-based and expert-based assessments of publication channels: SNIP and SJR vs. Norwegian quality assessments. Journal of Informetrics, 8, 985–996.Aleixandre Benavent, R., Valderrama Zurián, J. C., & González Alcaide, G. (2007). Scientific journals impact factor: Limitations and alternative indicators. El Profesional de la Información, 16(1), 4–11.Altmann, K. G., & Gorman, G. E. (1998). The usefulness of impact factor in serial selection: A rank and mean analysis using ecology journals. Library Acquisitions-Practise and Theory, 22, 147–159.Arnold, D. N., & Fowler, K. K. (2011). Nefarious numbers. Notices of the American Mathematical Society, 58(3), 434–437.Beliakov, G., & James, S. (2012). Using linear programming for weights identification of generalized bonferroni means in R. In: Proceedings of MDAI 2012 modeling decisions for artificial intelligence. Lecture Notes in Computer Science, Vol. 7647, pp. 35–44.Beliakov, G., & James, S. (2011). Citation-based journal ranks: The use of fuzzy measures. Fuzzy Sets and Systems, 167, 101–119.Buela-Casal, G. (2003). Evaluating quality of articles and scientific journals. Proposal of weighted impact factor and a quality index. Psicothema, 15(1), 23–25.Dorta-Gonzalez, P., & Dorta-Gonzalez, M. I. (2013). Comparing journals from different fields of science and social science through a JCR subject categories normalized impact factor. Scientometrics, 95(2), 645–672.Dorta-Gonzalez, P., Dorta-Gonzalez, M. I., Santos-Penate, D. R., & Suarez-Vega, R. (2014). Journal topic citation potential and between-field comparisons: The topic normalized impact factor. Journal of Informetrics, 8(2), 406–418.Egghe, L., & Rousseau, R. (2002). A general frame-work for relative impact indicators. Canadian Journal of Information and Library Science, 27(1), 29–48.Gagolewski, M., & Mesiar, R. (2014). Monotone measures and universal integrals in a uniform framework for the scientific impact assessment problem. Information Sciences, 263, 166–174.Garfield, E. (2006). The history and meaning of the journal impact factor. JAMA, 295(1), 90–93.Habibzadeh, F., & Yadollahie, M. (2008). Journal weighted impact factor: A proposal. Journal of Informetrics, 2(2), 164–172.Klement, E., Mesiar, R., & Pap, E. (2010). A universal integral as common frame for Choquet and Sugeno integral. IEEE Transaction on Fuzzy System, 18, 178–187.Leydesdorff, L., & Opthof, T. (2010). Scopus’s source normalized impact per paper (SNIP) versus a journal impact factor based on fractional counting of citations. Journal of the American Society for Information Science and Technology, 61, 2365–2369.Li, Y. R., Radicchi, F., Castellano, C., & Ruiz-Castillo, J. (2013). Quantitative evaluation of alternative field normalization procedures. Journal of Informetrics, 7(3), 746–755.Moed, H. F. (2010). Measuring contextual citation impact of scientific journals. Journal of Informetrics, 4, 265–277.NISO. (2014). Alternative metrics initiative phase 1. White paper. http://www.niso.org/apps/group-public/download.php/13809/Altmetrics-project-phase1-white-paperOwlia, P., Vasei, M., Goliaei, B., & Nassiri, I. (2011). Normalized impact factor (NIF): An adjusted method for calculating the citation rate of biomedical journals. Journal of Biomedical Informatics, 44(2), 216–220.Pinski, G., & Narin, F. (1976). Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing and Management, 12, 297–312.Pinto, A. C., & Andrade, J. B. (1999). Impact factor of scientific journals: What is the meaning of this parameter? Quimica Nova, 22, 448–453.Raghunathan, M. S., & Srinivas, V. (2001). Significance of impact factor with regard to mathematics journals. Current Science, 80(5), 605.Ruiz Castillo, J., & Waltman, L. (2015). Field-normalized citation impact indicators using algorithmically constructed classification systems of science. Journal of Informetrics, 9, 102–117.Saha, S., Saint, S., & Christakis, D. A. (2003). Impact factor: A valid measure of journal quality? Journal of the Medical Library Association, 91, 42–46.Torra, V., & Narukawa, Y. (2008). The h-index and the number of citations: Two fuzzy integrals. IEEE Transaction on Fuzzy System, 16, 795–797.Torres-Salinas, D., & Jimenez-Contreras, E. (2010). Introduction and comparative study of the new scientific journals citation indicators in journal citation reports and scopus. El Profesional de la Información, 19, 201–207.Waltman, L., & van Eck, N. J. (2008). Some comments on the journal weighted impact factor proposed by Habibzadeh and Yadollahie. Journal of Informetrics, 2(4), 369–372.Waltman, L., van Eck, N. J., van Leeuwen, T. N., & Visser, M. S. (2013). Some modifications to the SNIP journal impact indicator. Journal of Informetrics, 7, 272–285.Zitt, M. (2011). Behind citing-side normalization of citations: some properties of the journal impact factor. Scientometrics, 89, 329–344.Zitt, M., & Small, H. (2008). Modifying the journal impact factor by fractional citation weighting: The audience factor. Journal of the American Society for Information Science and Technology, 59, 1856–1860.Zyczkowski, K. (2010). Citation graph, weighted impact factors and performance indices. Scientometrics, 85(1), 301–315

Impact Factor: outdated artefact or stepping-stone to journal certification?

A review of Garfield's journal impact factor and its specific implementation as the Thomson Reuters Impact Factor reveals several weaknesses in this commonly-used indicator of journal standing. Key limitations include the mismatch between citing and cited documents, the deceptive display of three decimals that belies the real precision, and the absence of confidence intervals. These are minor issues that are easily amended and should be corrected, but more substantive improvements are needed. There are indications that the scientific community seeks and needs better certification of journal procedures to improve the quality of published science. Comprehensive certification of editorial and review procedures could help ensure adequate procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table